Using Neurofeedback to Improve ADHD Symptoms in School-Aged Children

The diagnosis and treatment of the behaviors associated with attention-deficit/hyperactivity disorder (ADHD) predominantly involves pharmacological interventions. Many children experience significant negative side effects (e.g., appetite suppression, insomnia, headaches, stomachaches, irritability, and impaired height) from the initial and continued use of stimulant medication. Consequently, many parents are motivated to consider alternative treatments for ADHD such as neurofeedback. This paper presents an archival review of the improvements in auditory and visual attention and response control after 40 sessions of artifact-corrected neurofeedback for 51 children ages 6 to 17 with ADHD. Initially, the majority of these clients were identified as having severe to extreme auditory and visual attention impairments. The IVA-2 CPT was administered prior to treatment and after 20 and 40 treatment sessions were completed. After 20 sessions of neurofeedback significant improvements of both auditory and visual attention and response control were found with small to large size effects. The clients continued to improve after an additional 20 sessions, with medium to large size effects after 40 sessions. At completion of treatment the mean of eight of the nine attention and response control scores fell within the “normal”

Welcome to NeuroRegulation Volume 5, Issue 4. We appreciate your joining us for this issue.
In 2013 the International Society for Neurofeedback and Research (ISNR) board felt it extremely important to have an open-access journal, one where the research, reviews, and commentary in our field is not locked behind subscription pay-walls, but openly available to researchers, students, clinicians, and the general public alike. Due to copyright and financial constraints it was necessary to establish a new journal, rather than change access to the society's original journal. As such, the board voted to cease publication of the Journal of Neurotherapy and to stand up a new, open-access journal, NeuroRegulation. One very unique aspect of this open-access format, in an era where many such journals charge authors upwards of thousands of dollars to publish, is the decision for ISNR to sponsor the journal so as to not charge authors or institutions any fees to publish. More so, as a service to the neuroscience community, currently, membership in ISNR is not necessary to publish at no charge in our journal. It is hoped our readers understand the importance of that board's decision several years ago and the significant ongoing contribution ISNR makes to our field.
As we come to the end of our fifth year of publication and move into our sixth year, we pause to acknowledge our growth and accomplishments. In addition to being indexed in Elsevier's Embase and Scopus databases during 2017 and 2018, respectively, our exposure and readership is growing greatly. In identifying the most viewed publications for each year, over the last 5 years, the article with the most views is the study on the effects of chocolate on the qEEG and blood pressure by Montopoli et al. (2015), with 13,560 views and counting. The next most viewed paper, with 8,540 views to date, was an evaluation of the impacts of digital addiction by Peper and Harvey (2018). Both of these papers were picked up and promoted by Science Daily, which brought an additional spotlight and recognition for NeuroRegulation. Our third most viewed article, with 8,529 views so far, is a study where neurofeedback (NF) is combined with heart rate variability (HRV) training by White et al. (2017). From our 2014 publications, Esmail and Linden's (2014) review of NF with Parkinson's Disease has been viewed 3,626 times to date, and from 2016 the study from La Marca and O'Connor (2016) with results of NF improving reading achievement with Attention-Deficit/ Hyperactivity Disorder (ADHD) students has so far had 3,223 views. In looking forward to our next 5 years and beyond we anticipate many additional exceptional scholarly contributions.
In the current issue Connie McReynolds, Lelah Villalpando, and Cynthia Britt present data for NF improvements in ADHD symptoms in school-aged children. Next, Laura Barry and Gregory Nooney present data for passive Infrared Hemoencephalography (pIR HEG) in athletic performance. Then, Kirtley Thornton provides insight and perspective on placebo effects as they may be inferred to NF. Finally, select abstracts for the proceedings of the 2018 ISNR annual conference are included in this issue.
NeuroRegulation thanks the authors in this issue, as well as those before them over the years, for their valuable contributions to the scientific literature for NF and learning.
We strive for high quality and interesting empirical topics. We encourage the members of ISNR and other biofeedback and neuroscience disciplines to consider publishing with us. It is important to stress that publication of case reports is always useful in furthering the advancement of an intervention for both clinical and normative functioning. We encourage researchers, clinicians, and students practicing NF to submit case studies! We thank you for reading NeuroRegulation!

Introduction
According to Visser, Zablotsky, Holbrook, Danielson, and Bitsko (2015), about 11% of children, or some 6.4 million school-aged children (i.e., > 1 in 10), in the United States have been diagnosed with Attention-Deficit/Hyperactivity Disorder (ADHD). In fact, the percentage of children diagnosed with this disorder increased 42% between the years 2003 to 2012 (Visser et al., 2015). Child-learning experts believe that many more teens and children are being diagnosed with an attention-deficit disorder than is merited (e.g., Grohol, 2013). Contributing factors to the increased diagnosis of ADHD will be discussed, coupled with a discussion on using neurofeedback as an alternative treatment method for ADHD.
The purpose of this archival study was to evaluate the clinical effectiveness of neurofeedback treatment for children who presented with a variety of attentional and behavioral symptoms including anxiety, panic attacks, learning, concentration difficulties, sleep disorders, depression, and memory concerns. It was hypothesized that the Integrated Visual and Auditory Continuous Performance Test -Version 2 (IVA-2 CPT) global measures of visual and auditory attention The two primary methods to diagnose ADHD are specified by either the American Psychiatric Association (APA) Diagnostic and Statistical Manual Fifth Edition (DSM-5;APA, 2013), or the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, in the form of the ICD-10, a global coding system developed by the World Health Organization (WHO) for classifying diseases and clinical procedures. Other factors that may increase ADHD diagnoses include medical conditions that mimic ADHD, along with the influence of both national-and state-based educational policies. Such policies support the eligibility of ADHD under the criteria of Other Health Impaired for special education services within the school systems. A brief review of the DSM-5 diagnostic criteria for childhood ADHD identifies three primary diagnostic classifications, which include the specifiers of inattention, hyperactivity/impulsivity, or both (see Table 1).
The criteria for the diagnosis of ADHD, Predominately Inattentive Presentation requires the child must be 17 years of age or younger and exhibit six or more of the symptoms (see Table 1.A.) for at least 6 months. In addition, these symptoms must be inconsistent with the child's developmental level, have a negative effect on the child's social and academic activities, and occur often. The criteria for the diagnosis of ADHD, Predominately Hyperactive-Impulsive Presentation indicates that six or more of the listed symptoms (see Table 1.B.) must be present for at least 6 months, must be inconsistent with the child's developmental level, must have a negative effect on the child's social and academic activities, and must occur often. The diagnosis of ADHD Combined Presentation (see Table 1.C.) is given when the child meets both sets of criteria.

Table 1 DSM-5 General Diagnostic Criteria.
A. Inattention 1. Fails to pay close attention to details 2. Has trouble sustaining attention 3. Does not seem to listen when spoken to directly 4. Fails to follow through on instructions and fails to finish schoolwork or chores 5. Has trouble getting organized 6. Avoids or dislikes doing things that require sustained focus/thinking 7. Loses things frequently 8. Easily distracted by other things 9. Forgets things B. Hyperactivity/Impulsivity 1. Fidgets with hands/feet or squirms in chair 2. Frequently leaves chair when seating is expected 3. Runs or climbs excessively 4. Trouble playing/engaging in activities quietly 5. Acts "on the go" and as if "driven by a motor" 6. Talks excessively 7. Often blurts out answers before questions are completed 8. Trouble waiting or taking turns 9. Interrupts or intrudes on what others are doing C. Inattentive and Hyperactive/Impulsive (Combined Presentation) Table 2 ICD-10 Diagnostic Criteria.
• A behavior disorder in which the essential features are signs of developmentally inappropriate inattention, impulsivity, and hyperactivity. • A behavior disorder originating in childhood in which the essential features are signs of developmentally inappropriate inattention, impulsivity, and hyperactivity. Although most individuals have symptoms of both inattention and hyperactivity-impulsivity, one or the other pattern may be predominant. The disorder is more frequent in males than females. Onset is in childhood. Symptoms often attenuate during late adolescence, although a minority experience the full complement of symptoms into mid-adulthood. • A disorder characterized by a marked pattern of inattention and/or hyperactivity-impulsivity that is inconsistent with developmental level and clearly interferes with functioning in at least two settings (e.g., home, school). At least some of the symptoms must be present before the age of 7 years.
Source: https://www.icd10data.com/ The ADHD diagnostic criteria identified by the ICD-10, which includes consideration of the behavioral characteristics for a diagnosis of ADHD in children, are itemized in Table 2. The ICD-10 classification system provides general diagnostic category types including ADHD that is either predominantly Inattention or Hyperactive, along with ADHD that is either Combined or Unspecified. In addition, to further categorize a child's behavior, the ICD-10 provides 15 supplementary codes (see Table 3) in a section titled Behavioral and Developmental Disorders.

Medical Symptoms Mimicking ADHD
In supporting the potential of misdiagnosing ADHD, Saul (2014) identified several medical symptoms that have the capacity to imitate ADHD symptoms due to complaint features that mimic the diagnostic criteria for ADHD. These health-related conditions include difficulties with vision, sleep disturbances, substance abuse, mood disorders (e.g., bipolar, depression), hearing problems, learning disabilities, sensoryprocessing disorders, giftedness, seizure disorder, obsessive-compulsive disorder, Tourette's syndrome, Asperger's syndrome (i.e., an Autism spectrum disorder), neurochemical distractibility/ impulsivity, schizophrenia, fetal alcohol syndrome, and Fragile X syndrome. Hinshaw and Scheffler (2014) identified factors associated with educational policies that have contributed to the number of school-aged children who are diagnosed with ADHD. They uncovered a relationship between the rates of ADHD diagnoses and the knowledge that many states changed how schools were budgeted in the 1990s. Specifically, operating funds for schools were distributed based on the number of students reaching set performance measures (e.g., graduation rates, achievement test scores). By the early 2000s, Hinshaw and Scheffler (2014) noted that federal dollars were subjected to the same type of budget management based mainly on student test performance. Together, both these actions at the state and federal levels were highly correlated with increases in the diagnosis of ADHD. Hinshaw and Scheffler (2014) concluded that the resulting increases in ADHD diagnoses in schoolaged children were caused by two parallel processes that motivated schools to accept children with ADHD as a means of increasing their student numbers. On the one hand, schools with high-performance standards attracted parents who wanted their children with ADHD to attend such schools for treatment purposes (Hinshaw & Scheffler, 2014). Conversely, schools in certain states were permitted to remove children who were diagnosed with ADHD from their performance metrics, which improved the overall achievement ranking of the district (Hinshaw & Scheffler, 2014). Thus, based on the heightened drive for academic achievement and stricter school accountability, the diagnosis of ADHD rose steeply, particularly, for the neediest children (Hinshaw & Scheffler, 2014).

Traditional Treatment Approach for ADHD
Once a child has a diagnosis of ADHD, the next step is generally to determine the type of treatment needed to improve the child's behavior. Treatment approaches to reduce the behavioral symptoms of ADHD in children generally fall into one of two categories, either behavior modification and/or medication.
The results of behavior modification and/or medication interventions have positive outcomes for some children (e.g., Fabiano et al., 2009) and not for others (e.g., Sonuga-Barke et al., 2013). Specifically, in a meta-analysis of non-medication treatment modalities, Sonuga-  did not find substantive positive treatment effects for behavioral interventions in addressing ADHD. However, Fabiano et al. (2009) uncovered support for behavioral interventions, although its long-term results were not evaluated. In a later meta-analysis, Daley et al. (2014) noted that behavioral interventions were associated with several positive benefits including bettering the empowerment of parents and reducing the conduct problems of children diagnosed with ADHD. However, positive outcomes in respect to a child's academic achievements and social skills resulting from behavioral interventions were not substantiated in this review.
For treatments based on the medication approach, several studies have identified concerns regarding the side effects of some of the typical prescriptiondrug regimens. Ellis (2016) discovered the possibility of bone loss (i.e., osteopenia) in children, who were taking methylphenidate (Ritalin), dexmethylphenidate (Focalin), dextroamphetamine (Dexedrine), atomoxetine (Strattera), and lisdexamfetamine (Vyvanse) medications. Nearly 25% of the children in the Ellis study displayed lower bone-mineral density in the femur, femoral neck, and lumbar spine when they were compared with children who had not taken any of these medications.
Ellis also reported additional medication side effects in children consisting of gastrointestinal problems such as decreased appetite and an upset stomach, which could possibly worsen nutrition as well as diminish normal calcium intake. In other research, Brazier (2015) reported that the use of methylphenidate (Ritalin, Concerta, Medikinet, Equasym) resulted in a 60% higher risk of sleep problems, along with an almost 300% greater risk of decreased appetite. Poulton et al. (2013) reported height suppression of between 1 to 1.5 inches associated with long-term use of ADHD medication. The MTA study (2004) found that physical growth (height and weight) was diminished in children following 14 months of intensive medication treatment. Additionally, in a long-term follow-up study, Swanson et al. (2017) also found evidence of height suppression in young adults following consistent use of medication from childhood to adulthood. Moreover, in a study of 41 students with ADHD, Steiner, Sheldrick, Gotthelf, and Perrin (2011) found that medication did not have long-lasting effects and that fewer than 50% of the children remained consistent with their prescribed dosage over a 6-month time frame. Swanson et al. (2017) also noted that consistent use of medication from childhood to adulthood occurred in less than 10% of ADHD cases and that long-term use was not associated with a reduction in symptom severity in adulthood.
ADHD medication is prescribed to reduce the symptoms of ADHD but does not correct the underlying causes of the behaviors. Remarkably, children are being prescribed medication at younger ages, even as early as preschool age (DSM-5;APA, 2013). Dunlop and Newman (2016) concluded that the use of stimulant medication in children diagnosed with ADHD may be too simple of an approach to treat the complex factors underlying an individual's unregulated behavioral and emotional difficulties.
An incongruity associated with ADHD pharmacological interventions is the existence of a subset of children for whom medications provide little or no improvement in their behavioral functioning (Gleason, 2013;Prasad et al., 2013). Partial cause for a noneffective result may come from rushing some medications to the market place before achieving sufficient scientific documentation (Swanson & Volkow, 2009). For example, Swanson and Volkow noted that Adderall was reapproved in 1996 as a treatment for ADHD even though there were no controlled randomized clinical trials of its effects on children with ADHD.
These authors further commented that despite initial indications of a longterm benefit over the first two treatment years, additional analyses after three treatment years were unable to document any long-term relative advantages of the ongoing treatment with stimulants. In addition, a systematic review and meta-analysis conducted by Prasad et al. (2013) of 43 studies involving a pooled-subject total of 2,110 children revealed that drug treatment benefited a child's school performance by at most only 15%, with only a maximum of 14% of children viewed as being more on-task. The limited benefits of stimulant medication were identified by Gleason (2013) as an important reason to intensify the field's research efforts to identify alternative therapies.
With respect to the long-term benefits of medication treatments in ameliorating the behavioral symptoms of ADHD, Riddle et al. (2013) discovered that nearly 90% of the 186 children investigated continued to struggle with ADHD symptoms after 6 years of drug treatment. That is, the long-term use of ADHD medications did not result in reduced symptoms in the children who had taken medications (Riddle et al., 2013). Instead, they were found to have symptoms as severe as children who were medication-free (Riddle et al., 2013). A question that arises from these medication limitations is: Why do ADHD symptoms seem to persist following traditional treatment approaches?
The Impact of Inattention "Limited processing capacity invariably implies a competition for attention…The term inattention usually implies that, at a given moment, the thing being attended to is either not what it was intended to be or not what adaptively it ought to be. If a single definition could be derived… it would refer…to the state of the individual through which learning takes place. It [attention] makes heavy demands upon the brain's processing capacity" (McCallum, 2015, p. 15-16).
Many theories of attention have been postulated over the decades, centuries, and millennia from Greek and Roman philosophers to modern day theorists. Attention has been linked to psychological processing, memory, learning, and perception (Norman, 1982).
Processing of information is generally held to be part of the function of attention and memory. In order to understand incoming information, it is necessary to process the information to extract meaning (Norman, 1982). In other words, one must be able to pay attention to be able to respond appropriately. Children who cannot pay attention are thereby unable to respond appropriately to their environmental cues. This inability to attend results in a plethora of difficulties for the child that generates behavioral reactions such as disorganization, lack of follow-through, not listening when spoken to directly, daydreaming, forgetting things, frequently losing things, being easily distracted, lack of focus, or even oppositional defiant disorder, which are common descriptors for children diagnosed with ADHD.

Negative Effects of Processing Problems
Male students, in particular, can demonstrate restless behaviors or disorganization, or take on the role of the class clown (Woliver & Ibrahim, 2012), which is often preferred by them rather than feeling rejected because they are unable to learn. For females, their problems may manifest in a different manner and, as a result of less "acting out" behaviors, are not identified as frequently as their male peers as being impaired. Female students may be passed along through school even when they are progressively falling behind in their academic work. In the end, female students may experience greater consequences than their male counterparts, as evidenced by an increased incidence of attempted suicide and other forms of self-injurious behaviors (Chronis-Tuscano et al., 2010;Hinshaw et al., 2012). Regardless of gender, both genders may experience a negative trajectory that has been recognized and documented for children struggling with behaviors associated with ADHD (Lee et al., 2008;Owens et al., 2009). Negative outcomes include a decreased likelihood of completing high school, a higher incidence of involvement with the criminal justice system, and diminished employment outcomes (Breslau, Miller, Chung, & Schweitzer, 2011;Hinshaw & Ellison, 2016;Pingault et al., 2011).
Children who are unable to follow through on instructions and requests even with repeated instructions or who cannot organize tasks typically experience greater levels of frustration. Increased levels of frustration often result in negative behaviors leading to behavioral dysregulation, acting-out behaviors, and a diminished sense of self.

Behavior Is a Form of Communication
Children are not always able to effectively verbally communicate the difficulties they are experiencing. One of the communication tools of a child is their behavior. When behaviors are seen as problematic, parents and teachers seek to reduce or eliminate the unwanted behavior. Although there is evidence that behavioral interventions have positive outcomes for some children (Evans, Owens, & Bunford, 2014) may be useful information that the child is communicating through these "problematic" behaviors that requires the understanding of parents and teachers-and may be the child's only means to receive the help that he or she needs.
By considering that problematic behaviors are a type of language to be decoded, a shift occurs in the perception of the observed "negative" behaviors. In considering that behavior is a form of communication, behaviors can provide information about what the child is struggling with in his or her life at home and at school. Shifting from attempting to reduce the negative behaviors using traditional medication or behavioral interventions to identifying the underlying cause of the behavioral symptoms creates an alternative approach to working with the child. Developing a greater understanding of the auditory and/or visual processing difficulties the child is experiencing provides a different context within which to apply a different intervention; namely, one that corrects the underlying auditory and visual processing difficulties. This shift has the potential to yield positive benefits for all involved-the child, the teacher, and the parents.

Auditory Processing Difficulties
Children who have auditory processing difficulties (APD) may engage in behaviors that mimic the behavioral symptoms of ADHD (Gyldenkaerne, Dillon, Sharma, & Purdy, 2014). APD is not about hearing loss, typically identified through audiological assessments, but rather concerns how the brain is processing auditory stimuli.
Distinguished from Central Auditory Processing Disorder (CAPD), Chermak and Musiek (1997) postulated that CAPD is an input disorder impeding selective and divided auditory attention, while ADHD is an output disorder causing sustained attention deficits across modalities. Tomlin, Dillon, Sharma, and Rance (2015) identified the need for better assessment measures to ferret out APD and cognitive limitations in children when attempting to determine causality of APD. Furthermore, Sharma, Purdy, and Kelly (2009) concluded that assessing central auditory processing, language and reading disorders did not provide a full explanation of auditory processing difficulties. Some identified symptoms of APD are noted in Table 4.
Children with APD may have difficulty learning when they are being taught in a noisy classroom environment (Behavioural Neurotherapy Clinic, 2016;Moore, Ferguson, Edmondson-Jones, Ratib & Riley, 2010) and may be unable to follow along in a conversation or remember what is said to them when asked to perform multi-stepped tasks. Instructions must be repeated multiple times and still the child does not follow through with the requested tasks in home and school environments. Because of APD, children may define themselves as less intelligent and lose confidence in themselves. Children with APD may engage in disruptive behaviors (Woliver & Ibrahim, 2012), and some may find it better to be labeled a "problem child" (Swingle, 2015, p. 106) than incapable or, even worse, as "slow."

Visual Processing Difficulties
Visual processing difficulties (VPD) are not about nearsightedness or farsightedness, but rather speak to how a child's brain processes visual information (Epstein, 2015). Children who have VPD may have difficulties remaining attentive to visual tasks. Farrar, Call, and Maples (2001) discovered that children diagnosed with ADHD have problems with visual memory and spatial orientation. Hagen, Moore, Wickham, and Maples (2008) found that children who have trouble with visual skills have difficulty with attention, which interferes with executive brain functioning and mimics ADHD symptoms. Children with VPD may be easily distracted by too much visual stimulation.
Some of the identified VPD symptoms include those noted in Table 5. Children who have VPD may demonstrate difficulty in remembering information that has been shown to them. They also may struggle with remembering letters and numbers, as if they have a short-or long-term memory problem (Epstein, 2015).

Identifying Auditory and Visual Processing Difficulties
The Integrated Visual and Auditory Continuous Performance Test -Version 2 (IVA-2; Sandford & Sandford, 2014) supports clinicians in their efforts to identify an individual's strengths and weaknesses in visual and auditory processing (Sandford & Sandford, 2014). Although the ability to discriminate between APD and ADHD has yet to be fully established in the treatment of ADHD, Gyldenkaerne et al. (2014) uncovered some degree of correlation between APD and ADHD measures. However, "even though deficits in both APD and maintained attention cooccur in more children than would be expected from chance alone, the two conditions are separate and largely independent conditions, even though they may have similar symptoms" (Gyldenkaerne et al., 2014, p. 676). Determining whether or not auditory and visual processing difficulties are a function of ADHD, or if ADHD has become a catchment category for auditory and visual processing difficulties, remains inconclusive.
Regardless of how auditory and visual processing difficulties are categorized, when a child cannot process what is being said to him or her regardless of the number of times the auditory and/or visual information is repeated, something is interfering with the child's ability to do so. Children generally want to succeed in school, and they want to have positive relationships with their parents, peers, and teachers. They want to have a better life and they want to do well. Yet many are unable to achieve these goals, despite their best efforts. Identifying and strengthening APD and VPD processes in children may lead to a reduction in problematic behaviors, yielding improvements both at home and at school. Based on our clinic work with children who have auditory and visual processing difficulties, often associated with an ADHD diagnosis, the results of this work are reported and discussed in the following sections. Table 6 lists some of the behavioral symptoms identified with the IVA-2 assessment in children who have auditory/visual attentional difficulties.

Participants
Neurofeedback treatment was provided for 51 children (n = 35 males, n = 16 females, ages 6 to 17) who completed a total of 40 half-hour sessions of neurofeedback treatment. The participants for this study were randomly drawn from an archival database of children who had previously received individualized neurofeedback training within a university-based clinic setting. Only those children who completed 40 neurofeedback treatment sessions and were identified by the IVA-2 comprehensive diagnostic algorithm to have manifested significant ADHD symptomatology were selected for this study.
Participants were brought in by a parent or guardian and informed consent was obtained prior to starting the treatment. Clinical neurofeedback services were provided to participants based on a sliding fee scale and since this was an archival study they were not compensated. This study was approved by the California State University San Bernardino Institutional Review Board.

Measurements
The IVA-2 CPT has been found to be a valid and reliable measure of both visual and auditory attention functioning for children and adults and provides global and primary measures of attentional functioning.
The normative sample, with approximately equal numbers of males and females, included 1,700 individuals ages 6 to 96 (Maddux, 2010). Furthermore, the IVA-2 provides both global and primary measures of attentional functioning that assess auditory and visual attention processing. All IVA-2 scale scores have a mean of 100 and a standard deviation of 15 (Sandford & Sandford, 2014 The Auditory Attention Quotient (AAQ) is a global measure of attention comprised of three primary visual and auditory scales: Vigilance, Speed, and Focus. Vigilance measures errors of omission, and Speed provides a measure of the response time in milliseconds to visual and auditory stimuli targets. Focus is a measure of the variability of response time to auditory test targets. The Visual Attention Quotient (VAQ) is based on the exact same scales as the AAQ but differs in that it assesses visual test responses to the same measures of attention. The FAQ is a global composite scale comprised of the AAQ and VAQ scales, which are used in equal weights (not an average) to determine the FAQ (Sandford & Sandford, 2014).
The Auditory Response Control Quotient (ARCQ) is a global measure comprised of three response control scales: Prudence, Consistency, and Stamina. Prudence measures impulsivity and response inhibition as evidenced by three different types of errors of commission. Consistency measures the general variability of response times ignoring outliers and is a measure of the ability to stay on task. Stamina compares the mean reaction times of correct responses between the first and last half of the IVA-2 test and is used to identify an individual's problems related to fatigue in mental processing speed over time. The Visual Response Control Quotient (VRCQ) has the exact same component scales as ARCQ but differs in that it specifically assesses visual test responses.
The FRCQ is a composite scale comprised of the ARCQ and VRCQ scales; it is the combined measure of the auditory and visual primary scales that assess impulsivity, consistency of response time and performance stamina during the test (Sandford & Sandford, 2014).
The Sustained Auditory Attention Quotient (SAAQ) provides a global measure of a person's ability to respond to auditory stimuli under low demand conditions accurately, quickly, and reliably, and it is combined with an assessment of the person's ability to sustain attention and be flexible under high demand conditions when auditory stimuli change frequently. It is comprised of the following primary scales: Acuity, Dependability, Elasticity, Reliability, Steadiness, and Swiftness. Acuity measures errors of omission under low demand conditions, Dependability reflects the variability of reaction times under low demand conditions, Elasticity reflects the ability to be flexible when faced with changing conditions, Reliability measures idiopathic errors of commission, Steadiness is a measure of accuracy under high demand conditions, and Swiftness measures response times under low demand conditions when the targets are rare. The Sustained Visual Attention Quotient (SVAQ) measures the exact same type of factors as SAAQ, but specifically for visual test responses. The Sustained Full Scale Attention Quotient (SFAQ) is the combined weighted global measure of the SAAQ and SVAQ global scales (Sandford & Sandford, 2014).

Test Procedures
Every participant was administered the IVA-2 CPT before beginning their first neurofeedback session. Testing was individually administered and scored in accordance with the specified test guidelines. Some individuals were not able to validly respond to either visual or auditory IVA-2 test stimuli due to their extreme deficits in attentional functioning. In these cases, their "invalid scores" for IVA-2 were scored as zero in accordance with the recommended test interpretive procedures (Sandford & Sandford, 2014). After the completion of both 20 and 40 neurofeedback sessions, the IVA-2 was readministered. Fifty-one participants completed 40 neurofeedback sessions. The IVA-2 data was analyzed comparing baseline test scores and the scores obtained after the 20th and 40th neurofeedback sessions were completed.

Neurofeedback Treatment Protocols
An individualized neurofeedback training plan was developed for each participant and modified as necessary. Treatment was provided on a one-to-one basis in a private room setting. Therapeutic goals focused on improving auditory and/or visual attentional functioning and reducing any identified behavioral-related symptoms of anxiety or fine motor hyperactivity. Training was completed using the SmartMind 3 artifact-corrected neurofeedback system with a two-channel EEG station (BrainTrain, Inc., North Chesterfield, Virginia) which continuously filters out both brief facial activity, as well as frequently occurring eye-blink and eye-movement artifacts in real time without interrupting the training program. As conducted in a McReynolds, Bell, and Lincourt (2017) study, neurofeedback exercises were provided in game-like format that utilized both visual and auditory reinforcement, as well as graphs and numerical scores to provide positive reinforcement. The first step in the training session was to collect participants' baseline EEG data to determine Z-score feedback goals for each participant. Based on each individual's performance, they were provided clinically relevant feedback and adjustments were made to the training protocol to optimize their performance. Sensors were attached and secured using 10-20 electrode paste and electrode rings after the site locations were prepared. Impedance was checked to meet the manufacturer's requirements prior to the beginning of training. All EEG data was automatically deartifacted and recorded by the SmartMind 3 software.

Results
The three main global scale scores that measured combined changes in auditory and visual general attention (FAQ), sustained attention (SFAQ), and response control (FRCQ) comprised the first step of evaluation. These three tests were correlated .54 and a Bonferroni correction was calculated taking into account the correlation using an alpha criterion of .05. The IVA-2 scores of these three scales were collected at baseline, and after 20 and 40 sessions were completed. This resulted in a determination that the p value test of significance criterion needed to be .03 for the nine paired t-tests that were completed. Given that it was expected based on past research studies that neurofeedback would result in positive changes in both auditory and visual attention, one-tail t-test values were used in assessing significance. Since the normative mean quotient score of the IVA-2 test is 100 and its standard deviation is 15, any change or difference of 8 or more quotient score points (i.e., greater than one half of a standard deviation) was considered to be of clinical significance. In order to evaluate whether neurofeedback training improves auditory and visual attention, paired sample t-tests were computed comparing the changes for the IVA-2 FAQ, SFAQ, and FRCQ global scale scores by comparing the scores between the baseline, after 20 sessions, after 40 sessions, and between 20 and 40 sessions. As indicated in Figure 1 (see Tables 7,8,9), children significantly increased their Global Combined Scale Scores for FRCQ.
SFAQ scores were found to be significantly higher after 20 sessions of treatment from a mean of 41 (Extremely Impaired) to 55 (Extremely Impaired), a 14-point increase, t(50) = −2.51, p < .01, Cohen's d = 0.34; SFAQ scores from 20 to 40 sessions of treatment significantly improved from a mean of 55 (Extremely Impaired) to 73 (Moderately Impaired), an 18-point increase, t(50) = −4.11, p < .001, Cohen's d = 0.48; overall, SFAQ scores between baseline and 40 sessions reflected a significant improvement from a mean of 41 (Extremely Impaired) to 73 (Moderately Impaired), a 32-point improvement, t(50) = −5.43, p < .001, Cohen's d = 0.85 (see Table 7 for baseline to 20, Table 8 for 20 to 40, and Table 9 for Baseline to 40).  In Figure 1, the continued improvement in global attention and response control from 20 to 40 sessions that was significant can be viewed across the FRCQ and SFAQ global measures. Scores on the FRCQ were found to be significantly higher after 20 sessions of treatment with a 14-point increase and significantly higher with an 18-point increase after 40 sessions. The SFAQ global scale scores were found to be significantly higher after 20 sessions of treatment with a 14-point increase and significantly higher with an 18-point increase after 40 sessions. The FAQ test scores significantly increased 17 points from baseline to 20 sessions; however, unlike the FRCQ and the SFAQ, the FAQ showed a 14-point change from 20 to 40 sessions.
The FAQ, SFAQ, and FRCQ are combined global scales based on each of their two respective auditory and visual global scales. General attention, sustained attention and response control global scale scores improved at 20 sessions with small to medium size effects, and all three global measures continued to significantly improve after an additional 20 sessions of training, resulting in neurofeedback treatment significantly improving attention and selfcontrol after additional training with large size effects (i.e., > 2 SDs). As indicated in Figure 2, ARCQ scores were found to be significantly higher after 20 sessions of treatment from a mean of 67 (Severely Impaired) to 89 (Slightly Impaired), a 22-point increase, t(50) = −4.5, p < .001, Cohen's d = 0.73; ARCQ scores from 20 to 40 sessions of treatment normalized from a mean of 89 (Slightly Impaired) to 94 (Average), a 5-point  In Figure 2, the continued improvement in auditory attention and auditory response control from 20 to 40 sessions that was significant can be viewed across all three global auditory measures. The ARCQ test scores significantly increased 22 points after 20 sessions and increased 5 points after 40 sessions, reflecting that significant change occurred from baseline to 20 sessions. Scores on the AAQ were found to be significantly higher from baseline to 20 sessions of treatment with a 12-point increase and a 7-point increase after 40 sessions, reflecting significant change occurred on the AAQ global scale at 20 sessions. The SAAQ global scale scores increased 7 points after 20 sessions of treatment and was significantly higher with a 14-point increase after 40 sessions, reflecting that significant change occurred following 40 sessions.
Auditory attention (AAQ) global scale (Vigilance, Focus, and Speed) were in the Severely Impaired range at baseline and normalized to the Mildly Impaired range at 40 sessions. ARCQ (Prudence, Consistency, and Stamina) scores were in the Severely Impaired range at baseline and normalized to the Average range following 40 sessions of treatment. SAAQ (Inattention) scores were in the Extremely Impaired range at baseline and were in the Mildly to Moderately Impaired range following 40 sessions of treatment.
As indicated in Figure 3, VRCQ scores were found to be significantly higher after 20 sessions of treatment from a mean of 54 (Extremely Impaired) to 72 (Moderately Impaired), an 18-point increase, t(50) = −3.20, p < .01, Cohen's d = 0.45; VRCQ scores from 20 to 40 sessions of treatment significantly improved from a mean of 72 (Moderately Impaired) to 81 (Mildly Impaired), a 9-point increase, t(50) = −2.11, p < .02, Cohen's d = 0.26; overall, VRCQ scores between baseline and 40 sessions reflected a significant improvement from a mean of 54 (Extremely Impaired) to 81 (Mildly Impaired), a 27-point improvement, t(50) = −4.35, p < .001, Cohen's d = 0.69.   In Figure 3, the continued improvement in auditory attention from 20 to 40 sessions that was significant can be viewed across all three global visual attention and response control measures. The VRCQ global scale scores increased 18 points from baseline to 20 sessions of treatment and increased 9 points after 40 sessions reflecting that significant change occurred after 20 and 40 sessions. Scores on the VAQ were found to be significantly higher from baseline to 20 sessions of treatment with a 17-point increase followed by a 13-point increase after 40 sessions reflecting significant change occurred on the visual global scales of attention after 20 and 40 sessions. The SVAQ test scores significantly increased 16 points after 20 sessions and increased 13 points after 40 sessions reflecting significant change occurred at 20 and 40 sessions.
Visual attention (VAQ) global scale (Vigilance, Focus, and Speed) were in the Extremely Impaired range at baseline and normalized to the Mildly Impaired range at 40 sessions. VRCQ (Prudence, Consistency, and Stamina) scores were in the Extremely Impaired range at baseline and normalized to the Mildly Impaired range following 40 sessions of treatment. SVAQ (Inattention) scores were in the Extremely Impaired at baseline and were in the Mildly to Moderately Impaired range following 40 sessions of treatment. Thus, these test results support the hypothesis that artifact-corrected neurofeedback training led to a significant improvement in global measures of both auditory and visual attention.

Discussion
Neurofeedback therapy, or EEG biofeedback, has been widely used for more than 40 years. During this time, it has gained recognition as an acceptable approach for treating conditions ranging from ADHD to anxiety, depression, sleep disorders, and learning disabilities (Hammond, 2011). For children identified as having impaired attention, once auditory and/or visual areas of weakness have been strengthened, many of the disruptive behavioral symptoms diminish (Ghaziri et al., 2013;Zhonggui, Shuhua, & Haiqing, 2005). This study specifically identified that artifactcorrected neurofeedback, which works by filtering out the contamination that continually results from naturally occurring EMG artifacts such as eye blinks, eye movements, and facial activity significantly improved both auditory and visual attention in impaired children.
As a group, these children initially presented as significantly impaired. After 40 half-hour treatment sessions, both their auditory and visual attention abilities improved and most IVA-2 scale score means were found to fall within the "normal" range (i.e., defined as a standard score of 77 or higher, 1.5 standard deviations; Sandford & Sandford, 2014) and all scales had effect sizes in the medium to large range demonstrating the clinical efficacy of this neurofeedback therapy. A standard score change of 8 points or more is clinically significant. With the additional 20 sessions, children gained 8+ points, and in some cases, a full SD of 15+ points. All scale score means improved from baseline to 20 sessions ranging from a 12-point to 24-point increase, except for SAAQ, which showed a 7-point increase.
The results of this archival study reveal that impaired children (N = 51) in this study needed 40 sessions to reach a normalized score. Improvements were noted across all global and standard scales, improvements were comprehensive and included both auditory and visual modalities. The improvements included response control (i.e., vigilance, consistency and stamina) in addition to both general attention (i.e., accuracy, consistency and speed) and sustained attention.
There were differences based on medium vs. large size effects for SVAQ versus SAAQ and ARCQ versus VRCQ. The SVAQ standard scales showed large effect size improvements (baseline to 40 sessions) and the SAAQ showed medium effect size improvements (baseline to 40 sessions). ARCQ showed large effect size improvements from the severely impaired range to only being slightly impaired (baseline to 40 sessions) and the VRCQ showed medium effect size improvements (baseline to 40 sessions). In respect to clinical improvement, greater changes were found on average for the visual attention scales (VAQ and SVAQ) in comparison to the auditory attention scales (AAQ and SAAQ) with these visual scale scores improving by .5 SD more than the auditory attention scales.
While this study utilized archival data and there was no control group to evaluate for possible test practice effects, the IVA-2 is an objective measure of attention which controls for practice effects in both its simplistic design (i.e., the test rule is to click if you see or hear the number one) and in its pretest instruction phase, which includes specific opportunities for individuals to practice the test before taking it. The reliability study in the test manual found that, on retesting, subjects did not significantly change by more than 3 to 4 points in either direction (Sandford & Sandford, 2014). Thus, any group increases in IVA-2 quotient scores greater than 3 to 4 points can be validly interpreted as a result of an active treatment and not due to practice effects. In this study, it was found that 40 half-hour neurofeedback sessions led specifically to the significant enhancement of auditory and visual attention as evidenced by the greater effect sizes observed and the significant increase in both auditory and visual attention scales from baseline to 20 sessions and from 20 to 40 sessions.
Thus, the hypothesis of this study that neurofeedback would significantly improve both auditory and visual attention was confirmed, and effect sizes were large for the enhancement on the three comprehensive IVA-2 global measures of general attention, sustained attention and response control (FRCQ, FAQ, and SFAQ, respectively). The findings of this archival study support that neurofeedback offers the potential as an alternative, nonpharmacological treatment approach that is clinically efficacious without any significant side effects. Lubar (1995) found that the benefits of neurofeedback can potentially be long lasting. In a 10-year follow-up study, Lubar reported that about 80% of clients treated with neurofeedback substantially improved their symptoms of ADD and ADHD, and that the changes were maintained. Cannon and Lubar (2011) later reported that neurofeedback training may generate a global integration effect that progresses on a continuum yielding ongoing improvements in the areas of working memory, higher order executive functioning, affective processing, attention, and cognition. In general, neurofeedback is becoming more widely accepted by many health care professionals and warrants institutional and governmental support for new research specifically with children who have ADHD symptomatology based on the results of this study and numerous others.
This research finding further substantiates the value and benefit of utilizing this new artifact corrected type of neurofeedback in the treatment of children with symptoms of ADHD and warrants further research as a neurofeedback intervention. In this study, initially children (N = 51) were found to be experiencing significant levels of attention impairment. After receiving neurofeedback treatment without any supportive counseling or coaching, all of them improved across the nine global and standard score measures of auditory and visual processing. Thus, the benefits of artifact corrected type neurofeedback demonstrated potential to help children improve their attentional functioning, which is consistent with the findings of La Marca et al. (2018) and consistent with the findings of improved attentional functioning of .
In interpreting the results of this study, certain limitations were considered. A primary drawback was its archival nature. Follow-up evaluations at 6 months and 1 year to determine the long-term effects of neurofeedback treatment are also components recommended for consideration for future studies in this field.
While this archival research was not designed to evaluate learning effects, the evaluation and demonstration of individuals' learned control of brainwave activity is an important issue which needs to be addressed in future research. Thus, research specifically designed to measure learning effects respective to the targeted EEG frequencies trained is recommended.
However, in order to evaluate learning effects this type of study would require that all participants in the study receive training that used the same standardized treatment protocol for each person. Any clinical modifications to meet a person's specific needs would not be permitted.
Based on 8 years of work with children using EEG biofeedback, children in our clinic have reported they are "able to pay attention even when they don't want to…" and that they are able to "choose whether to focus on what their friends are saying in the classroom or to listen to the teacher." Children in our clinic have gone from earning poor grades to passing grades, some excelling to the level of being on the honor roll for the first time in their academic lives. Based on child and parent self-report, the resulting enhanced attentional auditory and visual processing has led to improvements in academic work, decreased behavioral interventions, and improved family dynamics.

Future Directions
School systems use levels of interventions to support school-aged children's behavior, social, emotional, and academic readiness. Traditional forms of schoolbased interventions consist of approaches (i.e., Positive Behavioral Interventions and Supports; PBIS) to promote and improve social, emotional, and academic outcomes for all students. Behavioral interventions (i.e., Applied Behavioral Analysis; ABA) implement classical forms of conditioning to alter behaviors or introduce an alternative appropriate behavior.
Additional forms of support targeting specific areas of student social and emotional development are provided by mental health providers within the school setting through individual or group therapy. The goals of these interventions are to enhance the skills and competencies of school-aged children to be successful in school. Each of these interventions involves using visual or auditory instructions designed to enhance learning. The consistent limitation of each of these traditional school-based interventions is that children must be able to process the intervention information. As discussed earlier, if a child is unable to process auditory or visual information even the best planned interventions may fail.
In the future, coupling neurofeedback interventions with school-based support may provide a more effective and individualized form of intervention. Furthermore, neurofeedback intervention in schools may provide educators with additional tools and knowledge to individualize student support. La Marca and O'Connor (2016) found that by using neurofeedback children were able to improve their reading comprehension and demonstrated more focused attention in the classroom.
Using the IVA-2 as an initial assessment tool will provide school interventionists with specific information on the student's auditory and visual processing strengths and weaknesses. With more specific information gleaned from the IVA-2, interventions can be developed targeting specific areas of weakness and used to modify the learning environment while the student is participating in a neurofeedback training program. In addition, the neurofeedback assessment and treatment process would serve as an intervention providing additional documentation in determining whether or not there is a need for a special education assessment.
Development of a pilot project in the school setting is necessary to support students by identifying auditory and visual processing difficulties. Offering individualized neurofeedback training in the school setting would generate useful information regarding alternative interventions that may reduce referrals to Special Education. In other words, if neurofeedback and the IVA-2 assessment can identify children who have auditory and visual processing difficulties and effectively reduce these impairments, school districts may find a reduction in the need for Special Education services for this group of children. A reduction in the use of Special Education services would benefit the school district as well as benefiting the children if they are not in actual need of these specialized services.
Neurofeedback provides the opportunity for students to retrain their self-regulation abilities associated with social-emotional wellness (Huang-Storms, Bodenhamer-Davis, Davis, & Dunn, 2007), a process that is not typically accomplished with pharmaceutical interventions. Current estimates of annual out-ofpocket costs associated with traditional ADHD treatment approaches (i.e., medication and therapist visits) averaged $2,125 per child in 2012 (Doshi et al., 2012), which is approximately equal to 20 hours of neurofeedback training. When coupled with the average annual cost to society of $5,007 per child (Robb et al., 2011), the financial cost to schools, to families, and to society suggest that alternative treatments for ADHD are necessary to help reduce the large financial impact of ADHD (Doshi et al., 2012). The use of neurofeedback is a viable alternative that addresses the underlying associated problems of auditory and visual processing at the core of many of the symptoms of ADHD. Given the ongoing annual costs of traditional approaches to ADHD, neurofeedback becomes a viable and costreducing nonpharmaceutical alternative; even more so given the potential for long-term, ongoing benefits gained following neurofeedback treatment (Cannon & Lubar, 2011;Lubar, 1995).
The enhancement of social-emotional well-being has the capacity to improve a student's academic performance (Durlak, Weissberg, Dymnicki, Taylor, & Schellinger, 2011;La Marca & O'Connor, 2016). Additionally, by including neurofeedback as a form of support for school-aged children educators would have access to an alternative intervention. As a nonpharmacological intervention, neurofeedback provides a mechanism that teaches children how to function better by training their brain. Therefore, neurofeedback as a form of intervention in the school systems should be considered in future research directions.

Conclusion
The results of this study supported the hypothesis that neurofeedback would significantly improve both auditory and visual attention of children with symptoms of ADHD. The children's improvement in their auditory and visual attention scores revealed they achieved clinically significant improvements after 40 half-hour treatment sessions. Artifact corrected neurofeedback proved to be a clinically efficacious intervention that helps normalize the significant attentional impairments symptomatic of ADHD in children ages 6 to 17.  (7), 441-451. Ghaziri, J., Tucholka, A., Larue, V., Blanchette-Sylvestre, M.,

Description of IVA-2 Global and Standard Composite Scores
The IVA-2 provides nine global composite quotient scores to help gain an in-depth understanding of the variety of ways ADHD-type problems may manifest (Sandford & Sandford, 2014 Reflects the average reaction time for all correct responses throughout the test and helps to identify attention-processing problems related to slow discriminatory mental processing

Response Control Primary Scales
Prudence Measure of impulsivity and response inhibition as evidenced by three different types of errors of commission

Consistency
Measures the general reliability and variability of response times and is used to help measure the ability to stay on task

Stamina
Compares the mean reaction times of correct responses during the first 100 trials to the last 100 trials; this score is used to identify problems related to sustaining attention and effort over time The human brain is only 2% of one's body mass (Wang et al., 2014). The study of the brain is difficult for many reasons. One main reason is that we cannot manipulate someone's brain. The brain is so intriguing, and everyone thinks very differently, but we cannot cut open a healthy human to conduct research. That leaves all of the research up to people who have had a head trauma, stroke, mood disorders, headaches, and neurodegenerative disorders (Wang et al., 2014). From laboratory studies, researchers have found that almost all of the brain's processes are sensitive to temperature (Wang et al., 2014). To study the brain of brain-injured participants we need to be aware of the brain temperature to keep them safe and effective for the trial (Wang et al., 2014). If researchers fail to do so, the functional activity and energy efficiency of the brain will go down remarkably for the participant (Wang et al., 2014).

Biofeedback
Wouldn't it be useful to have instant feedback regarding aches and pains that go on in our brains without having to cut open one's head? Dr. Antoine Remond discovered that electroencephalography (EEG) helped to identify those with attention-deficit disorder (ADD) or people with minimal brain dysfunction (Siever, 2008).
Hershel Toomim's research led him to develop instruments to measure brain temperature and galvanic skin response (now known as electrodermal response; Siever, 2008 Biofeedback is a procedure that provides a person feedback over a bodily function that allows that individual to develop more control over that function to treat the medical problem (Siever, 2008). Toomim, however, found a further connection between cerebral blood flow and EEG (Siever, 2008), which led him to build the first ever blood oxygenation biofeedback device, which he named nIR hemoencephalography (HEG; Siever, 2008).

EEG Biofeedback
EEG biofeedback (hereafter referred to as neurofeedback or NF) training specifically looks at brain waves and how a participant receives instant results (Hammond, 2007). This type of training is very specific to the temporal, occipital, and parietal regions of the brain. Depending on where the electrodes are placed determines which skill the training is focusing on: balance, concentration, anxiety, etc. (Hammond, 2007). A study looked at performance enhancement in golfers using EEG profiles (Arns, Kleinnijenhuis, Fallahpour, & Breteler, 2008). They specifically looked at the central-temporal parietal areas and found that if the left-temporal alpha increased, the athlete's performance decreased, but if the righttemporal alpha increased, the athlete's performance increased (Arns et al., 2008). The results showed that each athlete performed differently even though they were completing the same task (Arns et al., 2008).
Another study looked at performance in dancers by using EEG slow wave heart rate coherence training (Thompson, Steffert, Ros, Leach, & Gruzelier, 2008). Results showed that EEG slow wave training increased confidence, well-being, energy, respiratory control, and pitch (Thompson et al., 2008). Thompson and colleagues (2008) found the same results in singers and musicians. EEG slow wave training is great for relaxation therapy, but EEG fast wave training involves more visuomotor activities (Thompson et al., 2008). Another study conducted by Vernon in NF training found that, if experimenters made one hemisphere more active, then the other hemisphere becomes dominant (2005). By reducing the verbalizations in the left-temporal lobe, it increases the visual-spatial process in the righttemporal lobe, which raises the question: can shifting more positivity or negativity on a specific lobe improve performance (Vernon, 2005)? Vernon (2005) looked at pre-elite archers and found that the use of NF does enhance performance.

Hemoencephalography (HEG)
There are two approaches to HEG which is another form of biofeedback training but pertains more to the activation of the prefrontal cortex and its functions. Toomim et al. (2004) developed near infrared spectrophotometry (nIR HEG) and Carmen (2004) developed passive infrared hemoencephalography (pIR HEG).
One of Toomim's studies used "top down" training, which allows for the brain to shift from the damaged areas and activate different areas for problem solving. They used a spectrophotometer to access blood flow in the prefrontal cortex (Toomim et al., 2004). Toomim and colleagues (2004) specifically looked at attention, impulsivity, reaction time, and reaction time variability. Results showed that after nIR HEG training there was an increase in blood flow in the brain corresponding to the training sites (Toomim, 2004). The study was limited to specific brain dysfunctions due to the area of the brain researchers wanted to explore (Toomim, 2004).
Headaches and migraines have also been studied and treated with HEG. A migraine is a lingering persistent pain causing the individual to suffer (Walker & Lyle, 2016). In the United States 18% of women and 6% of men receive migraines daily (Stokes & Lappin, 2010). Each person's migraine can be different, but they are a frequent phenomenon that can be studied and treated. There is no cure for migraines but one common form of treatment for migraines is peripheral skin temperature biofeedback, blood volume pulse, and electromyography feedback (Stokes & Lappin, 2010). In a previous study conducted by Stokes and Lappin (2010) Another study conducted by Carmen utilized pIR HEG. Carmen (2004) had participants pick out a movie of their choice and wear a headset monitor to measure waste heat caused by increased blood flow to the prefrontal cortex. Once the participant got emotionally involved in the movie, their limbic system was activated and their prefrontal cortex went partially off-line. The headset monitor device picked up the decreased heat in the prefrontal cortex due to the reduced blood flow, and the computer paused the movie. The participant was then instructed to focus and relax at the same time. By doing so, the participant's limbic activation was reduced and the prefrontal cortex activation was increased which also increased the blood flow in that area and, once it reached a preset level, the movie began to play again. As the participants were able to handle longer pause times without getting fatigued, their brain learned to spontaneously strengthen the functioning of the prefrontal cortex and inhibit the limbic system more efficiently. This resulted in improvements in migraine headache frequency and intensity (Carmen, 2004). Results showed that this was a very useful and longlasting way to treat migraines, but it would take at least six sessions to really get the training to stick (Carmen, 2004).
Athletes often get headaches due to the stress of their sport. There has been quite a bit of research conducted on athletes and concussions. A study conducted by Keightley and colleagues (2014) studied young children with concussions and their working memory. Working memory is tied into the prefrontal cortex because information only stays in our working memory for a few seconds. The prefrontal cortex deals with impulse decisions and personality. To be successful, athletes must be able to react quickly and efficiently to rapidly changing stimuli while maintaining a relaxed focus. Since pIR HEG is designed to improve prefrontal cortex efficiency, we became interested in whether this treatment would result in performance improvement for athletes.

Sports Enhancement
NF has been proven to improve sports performance by maximizing optimal brain function (Ross, 2015). Specifically, NF can improve an athlete's attention, focus, and emotional control, slow cognitive decline, improve sleep, and help to restore brain function after a traumatic injury (Ross, 2015). NF in general has made sports psychology very cutting edge and up to date. With more advanced technology we can target individual sports and explore specific effects on the individual athlete (Hammond, 2007).
Athletes must master the skills of stepping back and analyzing multiple sources of input in a short period of time and of having enough focus and concentration to act quickly and definitively. These skills primarily involve prefrontal cortex brain activities. In this study we focused on pIR HEG as developed by Jeffrey Carmen (2004), which targets the prefrontal cortex and its variety of functions, such as impulse control, organization of emotional reactions, personality, prioritizing, competing, and complex planning (McKinley, O'Loughlin, Pennefather-O'Brien, & Harris, 2015). Since pIR HEG improves prefrontal cortex efficiency, we are hypothesizing that this treatment will result in an improvement in these athletes functioning in their particular sport.

Method Participants
Participants included one male undergraduate student athlete from each of the following teams: basketball, volleyball, and baseball at Briar Cliff University (n = 3). The average age of participants was 21 years old. The study was approved by the Internal Review Board (IRB) of Briar Cliff University where the first author was a student in the Psychology department.

Setting
The training took place in the second author's office. The remaining pieces of the experiment took place in practice (gym, field, or course, depending on the sport) and at different locations based on competition.

Materials
Materials included an ordinary deck of cards, a DVD movie (of the participant's choice), the EZPIR system (Jeff Carmen; Manlius, NY), and an infrared camera.
The EZPIR system has two major components: the headset with a heat sensor connected to a computer through a hardware encoder and BioEra software (Proatech LLC, www.proatech.com). The camera utilized was the Seek Compact Pro made by Seek Thermal. This instrument was designed to connect to an iPhone and utilizes the internal computer power of the iPhone in order to process the images, thus producing a false color image that distinguishes between different levels of heat. The pIR HEG headband heat sensor picks up waste heat which is distributed through the forehead and thus indirectly measures increased blood flow to the prefrontal cortex.

Procedure
The experimenter recruited participants by asking permission from the coach and asking the athletes to participate in the study. The researcher told the athletes that the study would be measuring their athletic performance while they completed pIR HEG training.
Each participant signed the informed consent form before training began. Individually each participant completed training once a week. Training included sorting a deck of cards, by suit and then numerical order, while being timed. The participant was instructed to complete the task as fast as possible.
The researcher explained how sorting, impulse control, and speed correlated to the prefrontal cortex.
Then the researcher took a picture of the subject's face with special attention to the forehead utilizing the Seek Compact Pro. The researcher then explained what the picture meant; the darker (cooler) parts could mean fatigue or slight depression and the lighter (warmer) parts are how engaged your prefrontal cortex is at that moment. The goal was that by the end of the training the whole prefrontal cortex would be warm and evenly distributed across the forehead.
Next, the participant was instructed to choose a movie that they could become emotionally invested in. After the movie was selected the participant was guided to put on a headband with the heat sensor.
The researcher helped to place the detector just above the eyebrows but not too far in the hairline and ensured that no hair was underneath the sensor on the forehead. The participant was then instructed to watch the movie and wait for further instruction. The computer software is programmed to pause the movie when the subject becomes emotionally activated, causing a less active prefrontal cortex blood flow. Once the movie paused, a bar graph would appear on the left side of the screen. After the bar appeared on the screen the participant was instructed to relax their body and concentrate on the bar graph. If the bar did not move up or continuously went down, the researcher instructed the participant to relax and concentrate specifically on the neck and shoulder muscles while continuing to focus on the bar graph. When the subject was successful in this endeavor, there would be increased blood flow in the prefrontal cortex; the sensor would pick up the increased waste heat; and the bar on the graph would rise. Once the bar reached the yellow line at the top of the graph, the movie would resume, which was a tangible reward for the subject. If at any point the participant felt tired or exhausted, they were instructed to tell the researcher immediately. After approximately 30 minutes of watching the movie, the researcher took another picture using the Seek Compact Pro. Then the researcher explained what the picture meant to the participant. The participant then scheduled another meeting for training.

Data Analysis
A multiple-baseline design was used to show the effects of treatment of performance in athletes. Due to the fact there were a variety of sports in this study, we could not begin each treatment at the same time.
To demonstrate a treatment effect, we collected data during practice and not solely at competition. We collected three practice baseline points and one game point (depending on the team's games schedule) before starting treatment. Data was then collected once a week in practice, treatment, and then games in between treatment.

Baseball
The results for the baseball player's stats were broken down into balls and strikes over a series of 20 pitches. During baseline he averaged 13 strikes and 7 balls in practice, as seen in Figure 1. He did not pitch in any games during baseline. Once treatment began, he averaged 14 strikes and 6 balls in practice and 15 strikes and 5 balls in games. Figure 1 shows the rise a steady trend of the practice strikes decreasing and the practice balls increasing. His card-sorting time did decrease steadily throughout treatment indicating a significant trend. Figure 2 shows the before and after of the infrared images.

Volleyball
The results for the volleyball player's stats were broken down by passing rating, which is an average of all the passes he completed based on a 3-point rating scale. During baseline he averaged a 1.7 passing rate in practice and a 2.7 passing rate in a game, shown in Figure 3. Once treatment began, he averaged a 1.8 passing rate in practice and a 2.4 passing rate in a game. Figure 3 shows the consistency his passing became throughout treatment.
His card-sorting time did steadily decrease causing a significant trend, meaning he steadily did improve throughout treatment; reasons will be discussed further in the Discussion. Figure 4 shows the before and after of the infrared images.

Basketball
The results for the basketball player's stats were broken down by average free throws shot. During baseline he made 75.5% of shots in practice and 0% during the game, shown in Figure 5. The average percentage of shots made once treatment began was also 75% and average game percentage remained at 0. There was no change in percentage of shots made during games until two games posttreatment. His card-sorting time did decrease throughout treatment but not consistently enough to make a trend. Consequently, due to the lack of change in his statistics, treatment was not shown to be beneficial to this athlete in his game play. Figure 6 shows the before and after of the infrared images.

Social Validity
All three participants reported treatment had positively affected the way they see their game. The basketball player reported more concentration on how he shot the ball. The baseball player exclusively reported seeing an improvement in pitching strikes instead of balls. The volleyball player described an improved ability to "see the whole picture" during games and recalled a positive change in one specific game. All three did recall the mechanics of their sport improved. Along with their game play the baseball and volleyball player were able to concentrate on things outside of their game; e.g., homework, being more attentive in class, or demonstrating more initiative. Also, both the volleyball and baseball player reported to have had consistent migraines since grade school. Since beginning treatment, they have not had a migraine.

Discussion
In the current study we hypothesized that pIR HEG treatment will result in an improvement in these athletes' functioning in their particular sport. Our hypothesis was not fully supported. Participants were all chosen based on their playing time consistency, which allowed us to continuously collect data.
Unfortunately, there is a lot of variability within a sport that did not allow us to generalize the sport overall. We did a nonconcurrent multiple baseline due to initial start date of the sport. Fortunately, we were able to have at least points of baseline before beginning treatment.
Secondly, we saw positive decreasing trends in the card-sorting task with the volleyball and baseball player. Both participants reported having consistent migraines since grade school and have reported they have decreased the frequency of them since beginning treatment. Additionally, they both reported to have carried the positive effects of this treatment into their everyday lives.
Unfortunately, there were quite a few limitations involved in this study and we are unable to generalize the results. There were consistent environment changes (e.g., weather, stress, gyms, etc.) that we could not control. Also, the length of study was a huge limitation. With the length of the semester and the initial starting times of each sport, we were forced to limit the study to 5 weeks. If the study would have been at least 8 weeks or longer we might have seen a stronger result. In addition, the measurement and interpretation of the infrared images was problematic (see Figures 2, 4, and 6). We needed a measurement that made it valid and reliable. The relatively inexpensive infrared camera used was capable of creating a false color spectrum, but it had limitations in being able to provide consistent images that could be compared.
We would recommend that future studies be conducted with longer periods of time, a larger number of subjects, and increased number of pIR HEG sessions, ideally at least 10 to 12 weekly sessions. We would also recommend that a more expensive, sensitive infrared camera be used that would provide for a more reliable comparison of images.
If future studies would focus on just one sport, it would make it more likely that some generalization of that specific sport could be drawn. For example, a study could conduct treatment on several different basketball players playing different positions. Since each position has unique challenges and different stress levels, the results could more readily generalize to the sport of basketball.
Due to the diverse functionality of the prefrontal cortex of the brain, we believe that there are many creative ways in which further studies of pIR HEG's effects on sports enhancement would be useful and would encourage others to design such studies.

Definitions of Placebo and Effects
The common thread of varying definitions is that a placebo has (a) a positive effect on the patient's perception and self-report; and (b) does not have any physical beneficial effects on the illness for which it is prescribed.
Thibault and Raz (2017) conclude that "EEG-nf works, but it likely relies heavily on placebo phenomena" (p. 683). They further argue that "mental health professionals stand to benefit from studying the ubiquitous placebo influences that likely drive these treatment outcomes" (p. 679). "EEG-nf studies largely neglect investigating treatment mechanisms that rely on participant motivation, belief in the treatment administered, interacting with a practitioner, level of positive feedback, and sense of control of their brain signal" (p. 684). This paper will investigate the logic and evidence regarding the potential placebo effect in the neurotherapy (NT) situation.
In order to demonstrate a placebo effect, a research project must meet the following criteria document: (a) the expectation of the subject or study characteristics which encourage such an expectation; (b) the concomitant biological correlates (neurochemical, EEG, fMRI, DTI correlates of the expectation); and (c) the lack of a relationship between the biological correlates of the placebo and the biological correlates of the illness in question. To document that the effect is a real, substantive effect, (d) the results must distinguish between the effects of the intervention which have no measurable physical effect on the problem in question (a placebo) and those interventions which have a direct measurable physical effect on the problem.
It is clear that there is a real physiological effect from a placebo. The mechanism is not the pill or the treatment but rather the subject's perception that there is a value (positive/negative) in the pill or treatment. It is this belief that creates a change in the physiology of the brain and thus underlies the perceived changes in symptoms. It is the goal of this paper to understand the relationship between the perception of change and the underlying electrophysiology and biochemistry of that change.
We will address what is known/unknown about this relationship. If NT is a placebo response, then it is necessary to document the physiology of placebo response and its relationship to reported changes obtained with NT.
There is some inherent ambiguity built into the question of whether NT is a placebo in the traditional sense. It should be noted that the placebo argument originated in drug research addressing physical conditions, thus a physical intervention (pill, etc.) addressing a physical condition. NT is not a pill addressing a physical condition but an operant conditioning method to change the EEG signal which is related to behavior (such as attention). In both situations, however, the concern is whether the subject's subjective response is influencing the results which are tied to the relevant behavior issue (attention, etc.) and how much. In the case of attention-deficit disorder (ADD), if the "illness" is excessive theta activity and deficient beta and a placebo or NT changes the theta and beta values and relevant behavior, then the question is: Has a "cure" occurred? It is not assumed that the theta/beta issues are the sole physical issue in the attentiondeficit/hyperactivity disorder (ADHD) subject.
This paper will examine research on the physical/physiological effects related to the placebo response (endorphins, dopamine, EEG signal) and determine if it is credible to account for the NT effects as a placebo. Hróbjartsson and Gøtzsche (2010) reviewed the literature on placebos for 60 clinical conditions and concluded that there was a placebo effect in the clinical conditions of pain, nausea, asthma, and phobia but no effect in smoking, dementia, depression, obesity, hypertension, insomnia, and anxiety. Thus, only 7% of the conditions studied had a documented placebo effect. The perception of pain condition appears to be most responsive to the placebo effect (approximately 30 to 60 percent of people report a positive effect; Cherry, 2018).

Placebos work on patient's perceptions
In addition, not all subjects respond to the placebo effect. Beecher (1955) reviewed 26 studies and found on average 32% of the patients responded to placebo. In addition, it appears that some subjects are not responsive to the placebo effect due to genetics. "Predisposition to respond to placebo treatment may be in part a stable heritable trait" (Hall, Loscalzo, & Kaptchuk, 2015, p. 20). Rossi (1986) concluded that "placebo is about 55-60% as effective as active medications irrespective of the potency of these active medications." Rossi also mentions that "in a study of morphine, there was a 50% pain reduction in 75% of the patients treated.
The placebo group had a 50% pain reduction in 36% of the patients" (WRF, n.d.) Kaptchuk et al. (2010) studied two groups of irritable bowel syndrome (IBS) patients. One group did not receive any treatment, while the other group was provided with pills labeled placebo and were told they were "fake, inert drugs" and that the "placebo pills, something like sugar pills, have been shown in rigorous clinical testing to produce significant mindbody self-healing processes'' (Kaptchuk et al., 2010). The group receiving the fake placebo drugs reported twice as much symptom relief as the no treatment group and comparable to the best real medicine for IBS. According to Feinberg (2013), Kaptchuk's interest is "not if, but how, placebo effects work," as Kaptchuk argues that "sham treatment won't shrink tumors or cure viruses" (p. 36).
Wechsler, Kelley, and Kaptchuk (2011) studied 40 asthma patients with four different interventions. They found that only the real treatment showed results. However, there was no difference between the patient's subjective response to the real versus sham treatments. The patient's subjective response was not consistent with the objective measures. Thus, the placebo does not cure the problem but does result in a patient's perception of change.
The argument that NT is solely a placebo effect for all of the participants who have been involved in the treatment must be understood in the context that the placebo effect has only been documented in 7% of the conditions, by 32% of the patients, is determined, in part, by genetics and is about half as effective as morphine (in terms of patient response rates). Thus, the "ubiquitous placebo influences" are not found everywhere.

Placebo's Physical Effects on the Body and Brain
The placebo's physical effects on activity in brain structures has been documented in Parkinson disease (Benedetti et al., 2004 (Furmark et al., 2008;Petrovic et al., 2005). The anxiety and depression results are in contradiction to the Hróbjartsson and Gøtzsche Cochrane review. The hypothesis resulting from these studies suggest a prefrontal control mechanism that effects activity and neurotransmitters. A full understanding of the structural, functional, biochemical, and electrophysiological effects is required.
"Researchers have found that placebo treatmentsinterventions with no active drug ingredients-can stimulate real physiological responses, from changes in heart rate and blood pressure to chemical activity in the brain, in cases involving pain, depression, anxiety, fatigue, and even some symptoms of Parkinson's" (Feinberg, 2013). Levine, Gordon, Jones, and Fields (1978) first reported that blocking the release of endorphins (chemically) by opioid antagonist naloxone would stop the placebo effect. Endorphins are the brain's natural pain relievers and are similar to morphine and opiates. Benedetti et al. (2004) concluded that "there is ample evidence that expectancy-based placebo effects are mediated by endogenous opioids." Levine et al. (1978) noted that naloxone blocks the brain's ability to soak up endorphins. Volavka, James, Reker, and Cho (1979) showed that "naloxone elicited a significant slowing of the average alpha frequency" (p. 1267). This slowing effect would most likely be manifested in the lowering of the peak frequency of alpha. Thus, the alpha frequency appears to be involved in the placebo/endorphin response. The interrelationships between different measures of the alpha frequency (magnivolts, relative power, peak frequency) pose a complex problem, which is beyond the scope of this paper. Lipman et al. (1990) reported that, in chronic pain subjects, the placebo responders had higher concentrations of endorphins in the cerebrospinal fluid than the placebo non-responders. Wager, Scott, and Zubieta (2007) concluded that placebo effects involve opioid activation in opioid receptor rich regions including "periaqueductal gray and nearby dorsal raphe and nucleus cuneiformis, amygdala, orbitofrontal cortex, insula, rostral anterior cingulate, and lateral prefrontal cortex" (p. 11056). Thus, the placebo effects involve a similar activity or results suggest that endogenous opioid release in core affective "brain regions is an integral part of the mechanism whereby expectancies regulate affective and nociceptive circuits" (p. 11056).

Endorphins
However, it has also been reported that the placebo effect can occur without the involvement of opioids and naloxone can only partially inhibit the placebo analgesia effect in some situations (Amanzio & Benedetti, 1999;Gracely, Dubner, Wolskee, & Deeter, 1983;Grevert, Albert, & Goldstein, 1983).
The relationship between endorphins and the EEG has not been studied directly. However, there is indirect evidence that the endorphins increase the level of alpha magnitudes. Mimasa et al. (1996) "found that the larger the changes in beta-endorphin following exercise, the higher the appearance rate of the alpha wave in EEG. There was a positive and significant correlation (r = .563, p < .05) between the increase in alpha wave component and that of the plasma beta-endorphin." It is unclear whether the increase was a magnitude or relative power increase. Thornton (2016) reported a positive correlation (r = .66, p < .05) between magnitude and relative power measures of alpha. However, Crabbe and Dishman (2004) were able to document that exercise results in increased alpha magnitudes. Pfefferbaum et al. (1979) found that "beta-endorphin and morphine produced similar increases in alpha power within 5 to 15 minutes after injection." Peniston and Kulkosky (1989) compared a nonalcoholic control group, a traditionally treated alcoholic control group, and alcoholics receiving brainwave training (BWT). The BWT group showed significant increases in percentages of EEG record in alpha and theta rhythms (the focus of the intervention), increased alpha rhythm amplitudes, and improved outcome compared to the other two groups.
However, the alcoholics receiving abstinence, group psychotherapy, or antidepressants showed a significant elevation in serum beta-endorphin levels at the conclusion of the experiment. "This neuropeptide is an index of stress and a stimulant of caloric (e.g., ethanol) intake" (Peniston & Kulkosky, 1989, p.271). "Beta-endorphins play a role in certain behavioral patterns (stress, alcoholism), in obesity, diabetes, and psychiatric diseases" (Peniston & Kulkosky, 1989). Dalayeun, Norès, and Bergal (1993) application of brainwave treatment, a relaxation therapy, appears to counteract the increase in circulating beta-endorphin levels seen in the control group of alcoholics. This partially explained result stands in contrast to the expected increases in alpha associated with increases in endorphin levels.
It appears that the placebo effect involves endorphins and alpha magnitudes, relative power and peak frequency. Thus, when a subject believes an intervention is going to be successful, the endorphins increase and the magnitudes of alpha increase, as well as probably other frequencies. It remains unclear whether the increase in alpha magnitudes is a result of the placebo effect or NT. Even an increase in the alpha and theta magnitudes during a session or treatment period is not an argument against a placebo effect as the argument could be made that the placebo's effect increases during the session gains or as more sessions are employed.

Dopamine
De la Fuente-Fernández et al. (2001) found that placebo-induced expectation of motor improvement activates endogenous dopamine in the striatum of Parkinsonian patients.
Additional studies have pointed to dopamine involvement in the placebo response in pain conditions (Scott et al., 2008;Zubieta et al., 2005;Zubieta & Stohler, 2009). Hall et al. (2012) stated that "Catechol-Omethyltransferase (COMT), an important enzyme in dopamine catabolism, plays a key role in processes associated with the placebo effect such as reward, pain, memory, and learning." As "COMT activity decreased, theoretically making more dopamine available in the prefrontal cortex, placebo responses increased in a linear fashion…associated with a positive outcome only in groups given a placebo (and not in the waitlist control group) is of particular importance, as it indicates that it is a predictor of the placebo effect, not just improvement in general" (Hall et al., 2012).
Dopamine has been shown to be part of the ADHD condition. An increase in psychostimulants should result in increases in dopamine levels and increases in EEG arousal frequencies (alpha and beta) and decreases in lower frequencies (delta and theta). "Methylphenidate: Ritalin produces a decrease in delta and theta, with a more pronounced posterior alpha increase and an increase in low beta, with effects delayed up to 6 hours, compared to the rapid effects of the amphetamines" (Gunkleman, 2009, p. 4). "Medication resulted in normalization of theta power, but, after medication, increased relative beta was also apparent in the female ADHD group" (Clarke, Barry, McCarthy, Selikowitz, & Johnstone, 2007). This result was also obtained in adults Bresnahan, Barry, Clarke, and Johnstone (2006), who reported that following medication, there was a "significant reduction in slow wave activity in the ADHD adult group to levels similar to those in the control group." However, these findings have not been without contrary evidence. Lubar, Swartwood, Swartwood, and Timmermann (1996) failed to show increases in qEEG indicators of cortical arousal with methylphenidate. Other researchers (Barkley, 1998;Ernst et al., 1994;Matochik et al., 1994) have failed to demonstrate the neurophysiological effects of Ritalin at the cortical level.
There is solid research in the efficacy of operant conditioning (Staddon & Cerutti, 2003). The research has documented that NT can increase beta magnitudes and decrease theta magnitudes as well as increase alpha (Lubar et al., 1996;Sherlin, Arns, Lubar, & Sokhadze, 2010). The effect can be maintained up to 2 years (Gani, Birbaumer, & Strehl, 2008;Leins et al., 2007) and is maintained after cessation of medication (Monastra, Monastra, & George, 2002). Endorphins and dopamine have short-term effects. Foley et al. (1979) reported the half-life of beta-endorphin was 37 to 93 minutes. "The half-life of dopamine effect is 2 min" (ADHB, 2018). It is conceptually challenging to understand how it is possible that the placebo effect could be manifested 2 years later.
In conclusion, activation of an endorphin response appears tied to the alpha frequency, while dopamine's effects are predominantly in the beta frequency. NT and medications appear to break apart the naturally positive relationships between the magnitudes of the theta, alpha, and beta frequencies.

Neurotherapy and Structural/Functional Changes on fMRI, MRI, and DTI
Lévesque, Beauregard, and Mensour (2006)  group on the two cognitive and two questionnaire variables. In addition, a repeat fMRI scan was conducted while they (EXP and CON) performed a Counting Stroop task. The initial evaluation indicated significant increases in both groups in the left superior parietal location (Brodmann area 7). Postintervention fMRI scan revealed that the EXP group had increased activation of BA 24b-c and 32, which involve the anterior cingulate cortex, known to be involved in attentional issues (Bush et al., 1999). The CON group "did not receive an attentional training lasting the same time duration than the NT received by EXP subjects," which the authors suggested needs to be further evaluated (Lévesque et al., (2006). Thus, the NT intervention showed positive behavioral attentional and relevant fMRI results, with some qualifications regarding the CON group intervention.
In this study, the posttreatment Counting Stroop task requested the subjects to indicate the number of words presented (neutral condition) and then provided with an interference condition, during which the words one, two, three, and four were presented. The analysis compared the interference condition to the neutral condition. For both the EXP and CON groups, there was a significant locus of activation in the left superior parietal lobule (BA 7; fMRI) at both time periods. For the EXP group, at time 2, there were significant activations in the right BA 32 and left the caudate nucleus. Banich et al. (2000) reported that the anterior cingulate cortex is employed in selecting an appropriate response and allocate attentional resources. BA 32 is located in the anterior cingulate cortex. The caudate nucleus is involved in the inhibitory control of action (Nestler, Hyman, & Malenka, (2009 For the EXP group, there were significant increases in fractional anisotropy (FA) in the right and left CB, right anterior corona radiata and SCC as was as left SLF and ILF. "These WM pathways are known to be associated with sustained attention" (Ghaziri et al., 2013, p. 269).
This result satisfies criteria (d) mentioned at the beginning of this paper which states "must distinguish between the effects of the intervention which have no measurable physical effect on the problem in question (a placebo) and those interventions have a direct measurable physical effect on the problem." In this case, the EXP group had a direct measurable physical effect on the problem of attention, as the affected "WM pathways are known to be associated with sustained attention." Thus, the intervention must be viewed not as a placebo but a valid, relevant intervention on the "cause" of the problem-WM pathways.
The visual attention performance correlated with the FA measures in the left SLF and left ALIC (left anterior limb of the internal capsule). In the sham and CON conditions, there were no significant FA increases at posttesting.
For the EXP group, the GMV measures showed increases in Brodmann areas 9, 20, 19, 6, 47, 22 and 7 while the sham group showed increases in BA 10, 6, and 18. Thus, the EXP group activated BA areas 9, 19, 20, 22, and 47 that the sham group did not. The sham group received training "for approximately 20 hours, participants in the SHAM group had to undergo a perceptual-cognitive 'training', consisting of staring at the computer screen and staying focused with respect to the animation displayed on that screen. The members of this group also received hours of personal coaching to pay attention visually" (Ghaziri et al., 2013, p. 269). This coaching, perhaps, explains their improvement on the visual attention IVA. Thus, the sham group did not result in increased communication patterns (increases in FA values) but did result in increased GMV in frontal areas (BA areas 10 and 6) while the EXP group increased frontal GMV in BA 9 and 47. The study was the "first empirical demonstration that NT can lead to microstructural changes in white and gray matter" (Ghaziri et al.,Vol. 5 2013). This study had the sham group engaged in training which addressed the problem in the Lévesque et al. (2006) study with the control group.
The lack of significant FA increases in the sham condition presents a serious challenge to the NT as placebo argument. This result indicates that the NT intervention is resulting in a substantive change in the physical functioning (FA) of the brain while the sham intervention does not. This is evident in both the communication measure (FA) and different GMV increases, reflecting that the NT approach is fundamentally changing. The presence of a sham condition argues definitively against a placebo effect.  and Gevensleben, Holl, Albrecht, Vogel, et al. (2009) studied 94 ADHD children with a randomization approach involving multicenters and a sham condition (a computerized attention skills training). The NT intervention involved decreasing theta (4-8 Hz) and increasing beta (13-20 Hz). The post-qEEG data showed reduced theta power, demonstrating efficacy and specificity. Gevensleben et al. (2010) conducted a 6-month follow-up on the 2009 study and found that the improvements in the NT group were comparable to the effects at the end of the training period (effect size of .71), employing parent rating scales. Thus, the maintenance of effect at the 6-month time period is problematic for a placebo explanation in addition to the reduction of theta magnitudes which is not concurrent with a reduction in beta magnitudes, the naturally occurring pattern.

Clinical Conditions
We will examine the different clinical conditions to determine if the NT effects can justifiably be called a placebo effect.

ADD
The ADD condition has been the subject of many investigations with modern medical imaging technology. Initial research focused on the theta/beta values. Eyes-closed, resting EEG data indicated that higher relative power of theta and reduced relative power of alpha and beta, as well as elevated theta/alpha and theta/beta ratios being associated with ADD/ADHD (Barry, Clarke, & Johnstone, 2003).
NT approaches (combined theta/beta training with the training of slow cortical potentials, SCPs) obtained a reduction of theta activity (Gevensleben et al., 2010). Improvements on the EEG measures was associated with improvements on an ADHD rating scale. Similarly, Monastra et al. (2002) reported a decrease of the theta/beta quotient in a group of children with ADHD with an initially enhanced theta/beta quotient.
The clinical value of the theta/beta ratio resides in its high correlation (r = .99) and age-related changes in the ADHD behavioral symptomatology (Snyder & Hall, 2006).
More recently, the research has focused on deficits in white matter tracts (Hamilton et al., 2008;Konrad et al., 2012;Niogi, Mukherjee, Ghajar, & McCandliss, 2010;Pavuluri et al., 2009;Qiu et al., 2011). Niogi, Mukherjee, Ghajar, and McCandliss (2010) conducted a DTI study (healthy participants) and showed a positive correlation between FA values in the anterior limb of the internal capsule and performance on a sustained attention task. Kong et al. (2006) has reported DTI research on ADHD which reported significantly lower FA values in the left hemisphere involving the frontoparietal networks (SLF, ILF, and CB), or are implicated in interhemispheric processing within parietal areas ( SCC). Van Ewijk, Heslenfeld, Zwiers, Buitelaar, and Oosterlaan (2012) conducted a meta review of the DTI area and ADHD and concluded that "alterations in white matter integrity were found in widespread areas, most consistently in right anterior corona radiata, right forceps minor, bilateral internal capsule, and left cerebellum." Thus, the ADHD pattern is one of elevated theta, reduced beta activity, and decreased FA values. The decreased FA values would imply lowered coherence and phase values. Treatment approaches have indicated the ability of NT to decrease theta and increase beta levels. Specific interventions on coherence and phase values in the ADHD subject has not been published to the best of the author's knowledge.
If the placebo effect of alpha magnitude increase was occurring during the NT intervention, one would expect an increase in theta and beta1 magnitudes and thus no significant change in the theta/beta ratios.
Yet the research Monastra et al., 2002)  report decreases in theta magnitudes and changes in theta/beta ratios which employ magnitude values. Peniston and Kulkosky (1989) studied alcoholics receiving BWT and showed a gradual increase in alpha and theta brain "rhythms" across the 15 experimental sessions. It is assumed that rhythms means amplitudes. The reason for the intervention was the previous research which hypothesized a decreased alpha level in alcoholics (Gabrielli et al., 1982). Saletu, Anderer, Saletu-Zyhlarz, Arnold, and Pascual-Marqui (2002) documented with qEEG and LORETA mapping studies of detoxified alcoholdependent patients, as compared with normal controls, higher values of absolute and relative beta power, and lower values in alpha and delta/theta power for the alcohol patients. Sokhadze, Cannon, and Trudeau (2008) reviewed the research on substance use disorders and biofeedback and concluded that "alpha theta training-either alone for alcoholism or in combination with beta training for stimulant and mixed substance abuse and combined with residential treatment programs, is probably efficacious…. Based on the guidelines jointly established by the Association for Applied Psychophysiology and Biofeedback (AAPB) and the International Society for Neurofeedback and Research (ISNR)" (p. 1). The NT intervention used most frequently was the rewarding of alpha (8-13 Hz) and theta (4-8 Hz) in eyes-closed condition. The Scott, Kaiser, Othmer, and Sideroff (2005) modification involved initially rewarding C3-FPZ and C4-PZ SMR (12-15 Hz) and beta (15-18 Hz) while inhibiting theta (2-7 Hz) and high beta (22-30 Hz), and then followed up with the Peniston protocol (reward alpha and theta). Abstinence was obtained for 77% of the EXP subjects and 44% for the controls at 1 year after intervention. The controls were involved in the Minnesota Model 12-steporiented program as well as additional time in treatment which equaled the EXP time in treatment.

Drug abuse
There remains the possibility of a placebo effect with endorphins and dopamine affecting the alpha and beta frequencies. However, the endorphins and dopamine would be increasing alpha and beta. The authors did not report the changes in the frequencies. However, the results were better than most rehabilitation programs and the 1-year time reassessment is a long time to expect a placebo effect to last.

Depression
There are numerous studies that report decreases in depression on the Minnesota Multiphasic Personality Inventory (MMPI) and other measures following NT, typically involving alpha/theta protocols Grin-Yatsenko et al., 2018;Hammond, 2005;Raymond, Varney, Parkinson, & Gruzelier, 2005;. Scott et al. (2005) reported improvements on the MMPI which included the experimental group's changes and exhibited a significant improvement compared with the changes in the control subjects on the Hypochondriasis, Depression, Conversion Hysteria, Schizophrenia, and Social Introversion scales.
As with the other clinical conditions, the possible placebo effect of increased endorphins or dopamine related to increases in alpha and beta remains a possibility. Contrary to that possibility,  reported on changes in selfperception of positive emotional state following 12 sessions of NT involving increasing the prefrontal relative power of 35-45 Hz EEG band at Fpz (middle of forehead). The NT training resulted in a significant linear increase of the relative power of the 35-45 Hz gamma measure and increase in self-report of happiness scores. Follow-up at 3.9 months showed maintenance of gains in happiness measure as well as MicroCog and IVA+Plus neurocognitive tests. The foundation for the research was raised in three previous publications (Cowan, & Albers, 2009;Cowan & Sokhadze, 2010. In addition, there is no research that the author is aware of which ties increases in the gamma frequency to a placebo effect.

Anxiety
Walker (2009) studied 19 PTSD patients with alpha/theta NT and obtained significant reductions in anxiety, while the control group (N = 4) did not show any reductions in anxiety. A decline in alpha activity has been reported in anxiety disorders using the qEEG (Buchsbaum et al., 1985;Heller, Nitschke, Etienne, & Miller, 1997).
The qEEG abnormalities in 100 anxious patients were reported by Gurnee (2003). He described six qEEG subtypes-high beta, high alpha, low alpha, cingulate dysfunction, high mean frequency beta, and high mean frequency alpha.
Interventions directed towards these problems were generally effective in reducing anxiety. The placebo effect (alpha increase) could be employed to account for some of these improvements. However, the explanation of a sole alpha placebo effect across these diverse EEG conditions faces the same problem previously discussed of alpha increases related to general magnitude increases across the different frequencies.
Cognitive -Memory Thornton and Carmody (2013) reported on significant improvements in cognitive function in a group of 79 participants, including normal individuals, traumatic brain-injured, and specific learning disabilities (children, adult). Table 1 presents the results of the 2013 article as well as two previous articles (Thornton & Carmody, 2005.

Connectivity Measures
• Spectral Correlation Coefficient (SCC): spectral morphology comparison correlation between two channels using the formula (∑│X││Y│) 2 / (∑│X│ 2 ∑│Y│ 2 ) expressed in percent, where X and Y represent the Fourier series of the two channels and ∑ represents the summation within a band's frequency range.
• Phase: peak amplitude phase difference between two channels using the formula 100(1-│θ1-θ2│/π). A value of 100 percent represents zero degrees out of phase and a value of zero percent represents 180 degrees out of phase.
An analysis of the changes in the relative power values of the different frequencies showed that the relative power of beta2 (32-64 Hz) was the only frequency that showed significant improvements when analyzed using confidence intervals. The relative power of beta2 was a main focus of the interventions. Thus, a placebo's effect on the relative power value of beta2 seems unlikely, given the previous discussion, as the placebo response is focused on the alpha and lower beta frequencies.
The correlation between % improvement in relative power of beta2 was most evident in the TBI group (+.46) and adult specific learning disability (+.77) in the auditory memory condition.
The conclusion for the coherence values was that "the average raw value of the Spectral Correlation Coefficient (SCC) change for alpha was 6.1 points (2.09 SD), for SCC beta1 (13-32 Hz) 6.53 points (1.81 SD), and for beta2 (32-64 Hz) 7.5 points (1.77 SD)." Thus, the NT interventions were able to obtain significant increases in the relative power of beta2 and coherence values from alpha to beta2, across all subjects.
As previously noted, the placebo's effect is in the alpha or beta frequency and not the gamma frequency. In addition, alpha values are generally negatively related to the gamma frequency values (Thornton, 2016). Thus, it appears implausible that the placebo effect could account for these changes as there is no evidence to support the effect of placebos on relative power of beta2 (32-64 Hz) or any changes in the coherence and phase values of the beta1 of beta2 frequencies, which are critical to successful cognitive functioning (Thornton, 2016

Discussion / Conclusions
Thibault and Raz (2017) make the argument that "placebo effects dominate EEG-nf outcomes. Whereas most neurofeedback experts acquiesce to this insight" (p. 684). The support for this statement resides in following quotes from experts: It would be naïve to believe that neurofeedback offers an adequate and sufficient treatment for any disorder (Joel Lubar, personal communication, 2016).…"It would be foolish to conclude that a foundation of knowledge has been realized enabling textbooks to be written [on EEG-nf]" (Gruzelier, 2014, p. 178).…Niels Birbaumer proposed that the cumulative evidence in favor of EEG-nf is preliminary and we stand to benefit from more controlled evidence to confirm that genuine feedback is a necessary component to achieve positive treatment outcomes (personal communication, 2016). (p.

688)
These direct quotes do not mention placebo effects, so it is difficult to discern how the authors came to that conclusion. Thibault and Raz (2017) further state that "in light of the comparable benefits of veritable-versus-sham feedback, conflicts of interest, and a weak theoretical underpinning, advocating for EEG-nf poses a conundrum…Sparse evidence supports the idea that humans can reliably modulate EEG-nf signals" (p. 684). This conclusion is in stark contrast to the Thornton and Carmody (2013) and Thornton (2006) research study of cognitive changes, which consistently documented the ability of the approach to change the EEG signals along a number of measures and across different subjects.
A "weak theoretical underpinning" is a grossly inaccurate way to characterize operant conditioning, a concept Skinner proposed in 1938(Skinner, 1938. The research cited in this article does show the effectiveness of NT over sham treatment, thus providing research support for its effectiveness which effectively addresses criticisms. In addition, the NT as a placebo argument has considerable problems as: 1) It claims "ubiquitous placebo influences" of NT (Thibault & Raz, 2017). This statement is not consistent with research on placebo effects, which show only 7% overall effectiveness across different clinical conditions, only 32% of patients respond to placebos, a genetic predisposition, and a lower percentage of patient responsiveness than an effective drug (for pain).
2) The biochemical effect of the endorphins and dopamine levels of a placebo are not sufficient to explain the short-term and longterm effects, given their half-lives. However, this criticism requires qualification as some patients show the placebo effect long after the half-lives of the endorphins and dopamine have passed. A possible answer is that the patient is continuing to produce these neurotransmitters by continuing to affect the alpha frequency. If this is the case, then we are still left with the problem of the cause. Is the continuing alpha activity the result of a placebo effect or effective operant conditioning? Since both the biofeedback typical program addresses alpha and the biochemical effect appears to be in the alpha frequency, it appears that the data presently available is unable to directly address that question.
3) The relationship of the biochemical effects on the alpha and beta frequencies appear to possibly explain the NT results. However, the gamma responsivity is inconsistent with the biochemical hypothesis as there is no evidence of a biochemical effect on this frequency.

4)
Occam's razor states that among competing hypotheses, the one with the fewest assumptions should be selected. NT as a placebo has considerable problems in its explanation of the research findings. It is simpler to assume and more consistent with the literature that operant conditioning is the effective operant rather than some inconsistent and intermittent placebo effect.
5) This article has presented empirical evidence that humans can have an effect on the EEG signal. The relationship between the qEEG variables and cognitive performance is a complex one. It is difficult to assert that the placebo's effect is on all/most of the variables that relate to performance. If we reward a qEEG variable that has an empirical relationship to performance (memory) and the variable and memory performance improve, it is logical to conclude that the intervention is not a placebo. To assert that a placebo knows what qEEG variable relates to performance and increases the values of those specific variables (among the 2,000+ available) is a difficult position to defend.
In conclusion, the effect of a placebo or subject's expectation can be linked to biochemical and electrophysiological activity. However, the relationship is a complex one and the ability of a placebo to explain all the effects is not credible, given the evidence reviewed. The alternate explanation that operant conditioning is causing the changes in the EEG signals is a more plausible and simpler one.

References
Amanzio, M., & Benedetti, F. (1999). Neuropharmacological dissection of placebo analgesia: Expectation-activated opioid systems versus conditioning-activated specific subsystems. The most common type of addiction treatment in the United States today is based on the Minnesota Model. This style of treatment relies on 12 Steps principles and was developed over 60 years ago. Despite a tremendous amount of research and new evidence-based practices, very few treatment centers incorporate innovations like neurofeedback.
In this session, we will look at and review several cases studies from the Atlanta Healing Center that illustrate important advances in treatment of the chronic brain disease of addiction. We will focus on the importance of making the proper diagnosis; medication-assisted recovery; evaluating cooccurring psychiatric, cognitive, and pain conditions; assessing the hormonal and nutritional status of patients; and providing treatment modalities like neurofeedback. Education of the family and patient is important and connecting with recovery support is essential for the patient to have the best possible outcome in the management of this potentially lifethreatening disease.

Melissa Day
School of Psychology, University of Queensland, St. Lucia, Queensland, Australia Chronic low back pain (CLBP) is a pervasive, costly, and highly disabling condition. Research has shown that CLBP is inadequately managed solely by biomedical approaches alone. Thus, current guidelines put forth by the Centers for Disease Control and Prevention in the U.S. recommend nonpharmacological therapy as the first line approach to chronic pain management. In this context, there is evidence that Cognitive Therapy (CT) and mindfulness meditation (MM) programs are beneficial for a range of CLBP-related outcomes. Although not previously tested for CLBP management, evidence in other pain populations suggests that Mindfulnessbased Cognitive Therapy (MBCT)-which seamlessly integrates CT and MM techniques-might also be particularly well suited for improving pain, mood, and function.
An expanding body of research is investigating the potential neuromodulatory function of these psychosocial pain treatments.
Although scarce research has examined brain state-related changes in the context of CT and MBCT for pain, within MM, several studies in pain samples have used electroencephalogram (EEG) at pre-and posttreatment to test the possible role of brain activity changes in association with improved pain-related outcomes. Results found MM was associated with power increases primarily in the alpha band, and this increase in alpha was suggested to play a key role in the effects of MM on pain. It is not known, however, if this potential neuromodulatory pathway is unique to MM as delivered as an isolated technique, or if it might also play a role in other similarly efficacious treatments, such as CT and MBCT.
In this session I will present data from a recently completed randomized controlled trial comparing MM versus CT versus MBCT within a CLBP sample. Treatment consisted of eight weekly, 2-hour groupdelivered sessions. EEG brain state data was obtained at pre-and posttreatment, as was selfreported pain-related outcome measures of pain interference, pain intensity, physical function, and depression. I will present (1) the treatment-related changes in the self-reported outcomes, (2) an analysis of change in brain activity across the three treatments, and (3) how potential changes in brain state are associated with changes in the self-reported outcomes.

Marc Lewis
University of Toronto, Toronto, Ontario, Canada Over the past 20 to 30 years, medical authorities have come to define and explain addiction as a brain disease. However, the domination of the disease model skews the science of addiction, diverts attention from key social-psychological factors, and results in potentially harmful trends in policy and clinical practice. In this talk I review the distortions and omissions of the classic brain disease model and point to problems in the treatment philosophy derived from it. I then outline an alternative model of addiction based on principles of learning and development. This model views addiction as an entrenched habit for regulating emotional needs, learned through the repeated pursuit of highly motivating but short-lived rewards.
Developmental-learning models of addiction help explain individual differences in vulnerability (and recovery) based on early emotional difficulties and current psychological and social resources.

Dirk DeRidder
Dunedin School of Medicine, University of Otago, Dunedin, New Zealand Although chronic pain is one of the most important medical problems facing society, there has been limited progress in the development of novel therapies for this condition. The key to more successful pain treatment is to understand the mechanisms that generate and maintain chronic pain. Anatomically there exist at least two ascending pain input pathways and one descending pain inhibitory pathway.
One input pathway encodes the painfulness, whereas the other pathway encodes the suffering or emotional pain associated with the painful stimulus. The pain inhibitory pathway probably encodes the percentage of the time the pain is dominantly present during the day. The anatomical pathways can be visualized using functional MRI meta-analyses, and LORETA EEG further shows that chronic pain is an imbalance between the ascending and descending pain inhibitory pathways. This is indeed confirmed both by activity, functional and effective connectivity EEG analyses.
Nonpharmacological treatment for chronic pain using spinal cord stimulation normalizes this imbalance, supporting the concept that pain is truly a balance disorder between pain input and pain suppression in the brain, and causally related to this imbalance. Pain thus is not merely the result of more pain input via the spinal cord or brainstem.
This imbalance mechanism, also known as thalamocortical dysrhythmia, might be universal in view of the pathophysiological analogy between pain, tinnitus, Parkinson's disease, and major depression. Furthermore, thalamocortical dysrhythmia and reward deficiency syndrome (obesity, addiction, ADHD, and personality disorders) may be two sides of the same coin as suggested by EEG source analyzed conjunction analyses between thalamocortical dysrhythmia and reward deficiency syndromes. As such, this new conceptualization of pain, Parkinson, tinnitus, depression, addiction, ADHD, OCD, and personality disorders as imbalances in the brain paves the way for neuromodulation techniques such as transcranial electrical stimulation and infraslow neurofeedback to normalize this imbalance.

Inna Khazan
Harvard Medical School, Boston, Massachusetts, USA Bio and neurofeedback are powerful treatment modalities shown to be effective at alleviating numerous psychophysiological conditions. Biofeedback provides a way to work with challenging conditions in cases for which other interventions have been unsuccessful, such as chronic pain, anxiety, headaches, and trauma.
At the same time, bio/neurofeedback treatment itself can stall, leaving the client and the therapist feeling frustrated and unsure of how to proceed. These challenges include situations when the client is highly anxious about his or her physiological symptoms, feels pressure to "do things right," becomes easily overwhelmed with emotional stimuli, or is simply too distracted to attend to the computer screen for more than a few minutes at a time. Oftentimes, these challenges are due to the clients' unhelpful efforts to control the fundamentally uncontrollable aspects of their internal experience.
Mindfulness-based approach to bio/neurofeedback can help people experience change through mindful, nonjudgmental awareness and acceptance, providing the therapist and the client a way to work with what gets in the way of biofeedback success. In this talk participants will learn how to apply mindfulnessbased skills to their biofeedback practice in order to help their clients reap the benefits of biofeedback without getting stuck in unproductive attempts to control their internal experience.

Mark Trullinger
NeuroThrive LLC, Parkville, Maryland, USA ISNR, in partnership with AAPB and BCIA, have taken significant strides in the past few years toward pushing for insurance reimbursement. This presentation will provide a macro-level progress report on the CPT coding workgroup trying to modernize our codes, petitions for inclusion as a recognized organization for AMA activities for CPT coding and Relative Value Unit (RVU) determinations, and national-level efforts for insurance reimbursement.  (Lanius, Frewen, Tursich, Jetly, & McKinnon, 2015). A systematic review of the literature revealed ten studies (n = 213) that examined neurofeedback as a method for altering these neural patterns and alleviating PTSD symptoms (Foster & Thatcher, 2015;Gapen et al., 2016;Paret et al., 2014;Peniston & Kulkosky, 1991;Peniston, Marrinan, Deming, & Kulkosky, 1993;Pop-Jordanova & Zorcec, 2004;Smith, 2008;van der Kolk et al., 2016). These studies demonstrated mostly medium to large improvements following a variety of NF training modalities. Low-resolution electromagnetic tomography analysis (LORETA) zscore neurofeedback (LZNF) is a newer modality that is believed to produce more targeted and efficient outcomes than traditional modalities; however, it has not been adequately examined for the treatment of PTSD. This study is the first to examine the effectiveness of this modality using a controlled, experimental design.

STUDENT AWARD PRESENTATIONS -PLENARY SESSIONS
Method. The purpose of this research study was to examine the effects of LZNF training, as compared to heart rate variability biofeedback (HRVB) training, on PTSD symptoms, autonomic regulation, and brainwave activation patterns in adults with chronic PTSD. Twenty-four participants were alternately assigned to receive 15 sessions of either LZNF (n = 12) or HRVB (n = 12) training. HRVB was chosen as an active control condition due to the ability to closely match many conditions to the LZNF group (i.e., time with trainer, resting state, body-computer interface, similar audio/visual feedback, etc.) while providing an ethical alternative for this sensitive population. Psychophysiological measurements (i.e., 19-channel EEG and HRV) were recorded before, during, and after a single session of training as well as before and after 15 training sessions. Psychosocial questionnaires were completed during the pre-and postintervention assessments.
Results. The data for this study is still being analyzed and thus results are not yet available; however, visual examination of the data and symptom reports suggest the results will be positive. The full results will be analyzed and ready to present before this ISNR conference. Paired and independent samples t-tests and Cohen's d effect sizes are being utilized to examine both within-and between-group changes after 1 and 15 sessions. Pre-post changes will be analyzed for mean LORETA current source density (CSD) z-scores of three neural networks (i.e., DMN, SN, and CEN); HRV metrics (i.e., standard deviation of NN intervals, root mean square of the successive difference, low-frequency power); and total scores on the PTSD Checklist for DMS-V and Beck Anxiety Inventory. I have hypothesized that LZNF will produce greater changes in LORETA CSD z-scores and PTSD symptoms, while HRVB will produce greater changes in HRV metrics.
Conclusion. This study is expected to provide important, preliminary data regarding the effectiveness of both LZNF and HRVB training on Several neurophysiological subtypes based on electroencephalographic (EEG) biomarkers have been identified in attention-deficit/hyperactivity disorder (ADHD; Johnstone, Gunkelman, & Lunt, 2005). However, most studies investigating the efficacy of neurofeedback (NFB) as a treatment for ADHD use uniform treatment protocols that are not taking into account individual EEG biomarkers (Arns, de Ridder, Strehl, Breteler, & Coenen, 2009). A recent pilot study suggests that personalizing NFB protocols to individual EEG biomarkers of ADHD might lead to increased specificity and efficacy of treatment (Arns, Drinkenburg, & Kenemans, 2012). Hence, the objective of this presentation is to investigate the effects of personalized EEG-NFB as a treatment for ADHD. It will provide an overview of personalized EEG-NFB protocols for ADHD and introduce results from a pilot project that aimed to integrate a neurofeedback clinic as part of the services offering of the Office for Students with Disabilities in a Canadian college. A hundred and eight college students with a diagnosis of ADHD received free personalized EEG-NFB twice a week over a period of 4 months. Half of the participants was randomly assigned to the experimental condition. The other half was put on a waiting list to serve as a control group and received treatment later. Restingstate EEG signals were recorded to evaluate overall brain activity pre-and posttraining, and to determine individual EEG-biomarkers for selection of personalized treatment protocol. ADHD behavioral symptoms were assessed pre-and posttraining using the Conners' Adult ADHD Rating Scale (CAARS-S:L), the Integrated Visual and Auditory Continuous Performance Test (IVA-2) and assessment of executive functions.

Personalized EEG-Neurofeedback as a Treatment for ADHD
A significant change was observed in subjects trained in EEG-NFB, both in brain activation patterns and at the behavioral level. More specifically, normalization of targeted resting brain waves was observed in the experimental group. Results from this pilot project demonstrate the feasibility of personalizing NFB protocols to individual EEG biomarkers of ADHD and the efficacy of NFB as a treatment for ADHD. On a broader level, this presentation will allow for a better understanding of the impact of neurofeedback training on neural and behavioral correlates of ADHD.  (Bauer, Kreutz, & Herrmann, 2015;Repp, 2005aRepp, , 2005b. However, responses at the stimulus frequency do not allow one to distinguish whether synchrony occurs as a response to a common input or as the result of an emergent population oscillation that entrains at a particular frequency. It is possible to create a rhythm with no spectral energy at the pulse frequency by manipulating the number of events that occur anti-phase (180°) versus in-phase (0°) with the basic rhythmic cycle. Dynamical analysis predicts neural oscillation will emerge at such a "missing" pulse frequency (Large, 2010). Previous studies have shown that subjects tap along to complex rhythms at the missing pulse frequency (Large, Herrera, & Velasco, 2015)-a finding that supports the prediction, and responses at missing pulse frequencies have been seen in auditory brain areas using magnetoencephalography (MEG; Tal et al., 2017).
Aims. This study aimed to investigate whether the sensorimotor system, as measured by 32-channel cortical EEG, would entrain to a complex rhythm at the pulse frequency even when the complex rhythm contained no spectral power at that frequency.
Methods. The experiment utilized four different rhythms of varying complexity (one simple, two complex, and one random rhythm) created from 100 ms tones with a 200 Hz fundamental frequency (F0). Offline the EEG was decomposed into the corticalsteady state response (SS-EP) and the subcortical frequency following response (FFR). Fast Fourier Transform (FFT) of the Hilbert envelope showed energy at the repetition frequency (2 Hz) for the simple rhythm, but no spectral energy at the missing pulse frequency (2 Hz) for the complex rhythms. EEG responses to these stimuli were examined for evidence of neural oscillations and power modulations at the missing pulse frequency predicted by dynamical analysis.

Results.
We report evidence of responses in the EEG to the pulse frequency of missing pulse rhythms. We also note a differing topography of power at the pulse frequency across the scalp for the complex rhythms versus the simple and random rhythms.
Conclusions. These data support the theory that rhythmic synchrony occurs as the result of an emergent population oscillation that entrains at this particular frequency. Additional analyses examined whether the FFR to the F0 is modulated by whether the stimuli are perceived as being on-beats or offbeats in the rhythmic context.  (Berry et al., 2013;DeGiorgio et al., 2013;Tyler et al., 2015). These stimulation sites are all believed to innervate the locus coeruleus-norepinephrine system (Berry et al., 2013). Taking into account the extensive role norepinephrine plays in various executive functions, these stimulation techniques should be able to affect executive functioning in healthy subjects as well (Sara, 2009). As such, our protocol seeks to elucidate the neuromodulatory effects of noninvasive cranial nerve stimulation on attention.
A passive auditory oddball task was selected to measure attention. Subjects were instructed to listen to a series of 100 ms tones followed by 500 ms of silence. For each 600 ms trial, there was an 82% chance the tone would be at 750 Hz and an 18% chance it would be at 1,500 Hz. Tones were presented until 150 tones at 1,500 Hz were presented. Subjects were not required to physically or consciously respond to either type of tone. This task was created entirely with custom MATLAB (Natick, MA) software.
CNS, TNS, and VNS were all delivered using a custom, current-controlled stimulator connected to 2.5 cm round Axelgaard PALS electrodes (Fallbrook, CA). Stimulation trains were delivered for 10 min between oddball tasks. Each train was symmetrically biphasic, charge-balanced, and cathodic-first. Subjects were randomly assigned to receive either CNS, TNS, or VNS at 30, 300, or 3,000 Hz with pulse durations of 50, 350, and 50 μs, respectively. After all testing, subjects completed a subjective report stimulation to describe the stimulation experience.

Electroencephalography
(EEG), electrocardiography, galvanic skin response, respiratory rate, and hand temperature were all utilized to assess the physiological responses to stimulation.
Data collection is ongoing. EEG data will be averaged across subjects for each stimulation location and parameter set and presented as voltage traces and spectrograms to examine effects in both time and frequency domains. Physiological data will be averaged similarly to EEG data.
Subjects' subjective experiences will also be reported.

Background and Description.
Previous studies indicated that Frontal Alpha Asymmetry (FAA) and parietal hyperactivity among patients who comorbid with Major Depressive Disorder (MDD; Bruder et al., 1997;Mathersul, Williams, Hopkinson, & Kemp, 2008) and high-level anxiety symptoms. The purpose of this study was to examine the effects of alpha asymmetry (ALAY) and high beta down-train (BETA) neurofeedback protocols on emotional symptoms and electroencephalogram (EEG) among patients with MDD and anxiety symptoms.  Quebec, Canada). The goal of the ALAY group was to increase the A1 score, while the BETA group was to decrease high beta at P3 and P4.
Conclusion. This study indicated that both ALAY and BETA neurofeedback protocols significantly decreased the symptoms of depression and anxiety among the patients who comorbid with MDD and high-level anxiety. Moreover, there was a significant decrease in high beta activity at posterior region (P3) which was found in high beta down-train neurofeedback protocol.
Background. Autism spectrum disorder (ASD) is a developmental disorder characterized by social communication deficits, and engagement in restricted, stereotyped behaviors. An estimated 80% of individuals with ASD also display dyspraxia (Weimer, Schatz, Lincoln, Ballantyne, & Trauner, 2001;Dowell, Mahone, & Mostofsky, 2009), a condition involving difficulties in motor coordination and sequencing, as well as speech production. However, it is unclear how the processing, preparation, and execution phases of motor movement are affected by dyspraxia in ASD. We examined EEG activity and behavioral indices in children diagnosed with ASD during performance of a visuo-motor spatial attention task.

Methods.
Participants included 30 children diagnosed with ASD (15.6 ± 3.8 years old, 8 girls), and an age-matched control group of 30 typicallydeveloping children (TD; 15.7 ± 3.9 years old, 7 girls). Subjects performed a modified Posner's attentional cueing task (Posner, 1980). In each trial, subjects were initially presented a visual "cue" stimulus on left or right side of the screen. After a 1-s delay, a "target" stimulus appeared on the same (congruent, 80%) or opposite (incongruent, 20%) side from the cue, and subjects used a left-or right-handed button press to indicate the position of the target. In half of the trials, a more complex diagonal stimulus presentation was used. EEG data was collected for analysis of several event-related potentials (ERPs), including the lateralized readiness potential (LRP), a measurement of asymmetric brain activity that reflects preparation of contralateral limb movement (Eimer, 1998).

Discussion and Conclusions.
Shorter RTs to congruent trials in ASD and TD suggest that both groups exhibited an attentional bias toward the cued side. However, ASD group had higher RTs and lower accuracy regardless of trial condition, indicating poorer performance compared to TD. EEG analysis demonstrated that ASD group exhibited differences in the early ERPs and LRP, indicating differences at the early cognitive phase of stimulus processing and movement preparation rather that at the late motor execution phase. A more in-depth understanding of abnormalities in LRP and other ERPs during motor task performance could shed light on the underlying neuropathology of dyspraxia in autism and could potentially serve as a useful biomarker for early diagnosis.

Tiffany Thompson
NeuroField Neurotherapy, Santa Barbara, California, USA Reading the raw EEG is an artform that is essential knowledge-base of any practitioner using EEG to assess and diagnose their patients' conditions. Spindles, triangular shapes, sinusoidal, monomorphic, and archiform waveforms are just a few telling morphological signs that are imperative in understanding what is really going on. Does the waveform wax and wane? Does it travel in spindles or bursts? Does it appear only a few times in the record? What if it is rhythmic? These temporal dynamics are also imperative in a proper assessment of the person. When looking at the raw waveform, you will learn more than what any qEEG, alone, can tell you.
Through exploring the more insidious forms of artifact (i.e., electricity, channel noise, mixed metals, etc.) to detecting less commonly seen morphological forms in the EEG (i.e., lambda, mu, OIRDA, beta spindles, etc.), this lecture will guide the clinician through some of the more advanced ways of interpreting EEG so that the qEEG does not mislead one into misdiagnosis.
We are privileged to have many analysis and diagnostic tools to help us dissect, spatially and temporally analyze, condense, and summate the EEG into neat and tidy diagrams, but we fail our patients and our profession if we miss the devils in the details.
Finally, montages are necessary to understand the many ways in which we can assess and view the EEG. There is no best montage for all purposes. While linked ears can provide a global view, it is prone to contamination if there is a strong temporal finding or if there is contamination otherwise in the ear electrodes.
Average and weighted average montages (such as the Laplacian and Hjorth montages), will highlight any local phenomena, and will uncover any significant temporal component, but will fail us to see global information. Bipolar montages are excellent for displaying phase

Robert Coben, Anne Stevens
Integrated Neuroscience Services, Fayetteville, Arkansas, USA Over the past several years, we have seen advancements in the ways we assess coherence and connectivity that provide great insights into brain functioning (Coben, Mohammad-Rezazadeh, & Cannon, 2014). This understanding has led to approaching coherence in a multivariate fashion that enhances its accuracy (Kuś, Kamińshi, & Blinowska, 2004). Multivariate autoregressive statistical tools have become critical to this endeavor. Such techniques enable us to measure effective connectivity in a source localized fashion such that we can image reciprocal causality and influence. This accuracy in depicting neural networks gets us closer to the real signals in the brain. This led to an enhancement in how we do neurofeedback training which now uses four sensors and trains coherence in a multivariate fashion (Coben, Middlebrooks, Lightstone, & Corbell, 2018).
We have adopted a theory that states the more accurate our assessment of connectivity and the source of the activity then the more effective our attempts at neurofeedback may be. In this pilot study we evaluated the effects of basing our neurofeedback (multivariate coherence training) protocols on coherence measures as compared to multivariate autoregressive effective connectivity that uses sources to estimate reciprocal causality (see Friston, Moran, & Seth, 2013). We sampled 45 subjects with various presenting complaints and divided up into three groups. All subjects had their neurofeedback protocols developed based on qEEG methods. Group 1 was based on ICA and effective connectivity Granger causality, and groups 2 and 3 were based on correlational coherence measures. We used two separate comparison groups, one served as a withingroup and the other a between-group comparison.
All subjects underwent between 12 and 15 neurofeedback sessions followed by another assessment period. Dependent measures included EEG comparisons of power and graph theory metrics of effective connectivity. Clinical comparisons were also made based on rating of progress to measure their symptoms change over this period of time. Preliminary data analysis has shown that all groups show changes and gains from their neurofeedback training, but that the group that had their protocols based on effective connectivity measures showed greater clinical and EEG changes. The implications of these findings will be presented. specific psychological disorders. The most wellknown link is that of excess theta/beta ratio in relation with ADHD (e.g., Arns, Conners, & Kraemer, 2013).

Trends in Scientific Research Reflect and Predict the Clinical Relevance of (EEG) Biomarkers
Recent approval of the FDA for an ADHD diagnostic test based on excess theta/beta ratio illustrates that this "EEG biomarker" is both meaningful and reliable. Other markers for psychopathology include "alpha asymmetry" for depression (Thibodeau, Jorgensen, & Kim, 2006) and excess beta power for anxiety and insomnia Perlis, Merica, Smith & Giles, 2001). However, a modern qEEG report will contain many different and detailed analyses of an individual EEG. Moreover, the number of analyses that can be performed on EEG data has been increasing rapidly. Interpreting the clinical relevance of these analyses for the treatment of an individual patient depends on the scientific studies demonstrating links between these measures and the symptoms of the patient.
In the current presentation, the trends in qEEG research will be discussed and an attempt will be made to assess the relevance of different qEEG analyses for clinical purposes using a systematic analysis of the scientific literature.
The main approach is to analyze the number of papers published on a particular search term (reflecting a certain EEG biomarker) per year. A secondary approach is to analyze the number of citations per year to seminal papers which describe a new EEG biomarker.
Finally, comparisons with scientific literature in different fields may provide useful analogies. For example, the interpretation of an individual blood test for cancer relies on scientific research on the association between certain biomarkers (e.g., certain proteins) and the presence of a tumor. How did scientific research on these "tumor markers" evolve and eventually lead up to the use of tumor markers in clinical testing today, and what can this tell us about the current state-of-the-art and future clinical relevance of different EEG analyses?
One hypothesis is that papers which demonstrate a promising new biomarker will show a continuous increase in citations per year when the biomarker can be replicated and when it is useful as a diagnostic tool in clinical practice. In contrast, when such a study cannot be replicated it may show an initial increase of citations, but the number of citations per year will inevitably go down after this initial increase. In the latter case, it can be concluded that the biomarker is not useful in clinical practice. Analyzing trends in the scientific literature to predict clinical relevance of potential EEG biomarkers is novel and relevant approach which may have important implications for the scientific and clinical field of qEEG and neurofeedback.
Evidence from a wide variety of studies and authors supports a new synthesis of understanding regarding the 40 Hz brain scanning system and its role in attention, understanding, learning, and creating positive feelings as a reward for the effort. It is a basic foundation for the individual's survival, promoting their effective responses to new discoveries and situations. We have therefore named this brain system Neureka! (short for Neural Eureka!). This understanding builds upon Llinas' discovery of the "Event Binding Rhythm" (Llinas, Ribary, Contreras, & Pedroarena,1998), which scans the cortical layers from front to back 40 times a second and reports back to its origin, the centrally located nuclei in the thalamus, all of which we will review here.
These nuclei synthesize all this information and send out modified 40 Hz scanning rhythms which look for additional information to add to the understanding of a particular new event. This looping information exchange continues until the event is evaluated and a response is created. Salient events are stored in short-term memory, particularly in the prefrontal cortex (PFC). Short-term memory is then converted to longer term memory, particularly if dopamine, norepinephrine, and/or other neuromodulators are released. There is evidence that both of these neuromodulators are released in the PFC, particularly near FPz. Dopamine also creates a variety of positive feelings when it is released there.
We will review several lines of evidence about the Neureka! brain system from fMRI and other scans (Knutson, Fong, Bennett, Adams, & Hommer, 2003), and complement them with our EEG studies based on the Neureka! measurement, which selectively clarifies this particular 40 Hz rhythm and separates it from the other 40 Hz activity passing through more peripheral parts of the thalamus.
These studies show that neurofeedback training of Neureka! enhances memory and happiness (for at least four months) and decreases depressed feelings. It also improves memory and attention measurements . Previous studies (Cowan & Albers, 2011;Cowan & Starman, 2017;Rubik, 2011) demonstrate clear relationships between increases in Neureka! amplitude and love, happiness, satisfaction, gratitude, and appreciation. We will review studies where neurofeedback training using the Neureka! measure (Sokhadze, 2012) was used to improve behavioral symptoms in children with autism . Furthermore, the 40 Hz rhythm was used to distinguish the emotional reaction to drug and stress cues of substance abusers from those with comorbid PTSD .

Introduction.
We have previously reported changes in sLORETA quantitative analysis shortly after acute sport-related concussion injury in high school athletes, which persist after clinical recovery (Kerasidis & Ims, 2017). We have also reported the effects of neurofeedback on these changes during the acute recovery period (Ims & Kerasidis, 2018). Studies have identified gender differences in the incidence, severity, and recovery time from sport concussion injury, all increased in females (Cantu, 2010;Hamson-Utley et al., 2013;Miyashita, Diakogeorgiou, & VanderVegt, 2016;Mollayeva, El-Khechen-Richandi, & Colantonio, 2018;Tanveer, Zecavati, Delasobera, & Oyegbile, 2017). The objective of this investigation is to explore gender differences in volumetric qEEG analysis after sport concussion injury in high school athletes.

Methods. Standard electroencephalograms (EEGs)
were analyzed in 40 high school athletes (20 males) shortly after concussion injury using sLORETA imaging compared to a normative database (NYU/BrainDx). Peak Z-score variation (PZV), and percentage of volume of grey matter activity that fell outside Z = −2.5 to 2.5 (PIGMV for increased activity, PRGMV for reduced) were calculated for each of five EEG frequency bands. These domains are interconnected and work together via situational, dispositional, and intentional variables to produce well-being, or the lack thereof (Howell, Kern, & Lyubomirsky, 2007). To test the viability and utility of this model, a stepwise multiple regression analysis was conducted on archival data of 117 military veterans. Based on the literature of, and the shared nomological network between, well-being (e.g., Howell et al., 2007), PsyCap (e.g., Avey, 2014;Lorenz, Beer, Pütz, & Heinitz, 2016), social isolation or connectedness (e.g., Kent, Hawthorne, Kjaer, Manniche, & Albert, 2015), spiritual intelligence (e.g., Faraji, & Begzadeh, 2017), psychological and cognitive performance (e.g., Del Brutto et al., 2015;Lathan, Spira, Bleiberg, Vice, & Tsao, 2013), as well as heart rate variability (HRV; e.g., Fatisson ). Moreover, such findings would support a viable model of well-being, which military leaders can use to baseline and monitor its members.

Jeff Tarrant
NeuroMeditation Institute LLC, Corvallis, Oregon, USA Using neurofeedback and other technologies to achieve altered states of consciousness has its roots in the early development of the field of neurofeedback.
In fact, some of the initial neurofeedback protocols were designed to replicate many of the effects commonly experienced during a meditative state (Crane, 2007;Trudeau, 2016). Having observed that the practice of meditation often led to an increase in alpha power or increased theta activity crossing over alpha, these two approaches became the foundation of Deep States NeuroMeditation protocols, essentially attempting to facilitate elements of an altered state (Tarrant, 2017).
This work and these protocols are powerful and have been associated with impressive results with difficult clinical populations including alcoholics and those suffering with PTSD. Recent explorations into the study of consciousness has led to some new approaches and protocols for assisting clients into achieving altered states for the purposes of psychological and emotional healing. This presentation will present a new and novel approach to achieving altered states with neurofeedback by replicating brain-based research on psychedelic therapies. Current research with psilocybin, LSD, DMT, and other psychedelics have all shown tremendous potential in treating a wide range of mental health disorders. It is believed that these impacts are due, at least in part, to the way they alter perception and the dysfunctional creation of a self-identity (Carhart-Harris et al., 2012). Based on this emerging field, certain brain patterns and brain regions have revealed themselves as important in these transformative experiences. By targeting these brain patterns through neurofeedback, in conjunction with additional strategies, we may be on the cusp of a brand-new approach to the use of neurofeedback. In this presentation, we will share preliminary research showing how these altered states can be facilitated using neurofeedback. We will explore approaches, indications and contraindications as well as a variety of adjunctive aids, including vibroacoustics, evocative music, and visual entrainment. Neurofeedback is a paradigm in which individuals are trained to modulate their electroencephalogram (EEG) by providing them feedback about the targeted EEG component to treat symptoms and disorders associated to the neuronal condition. Neurofeedback shows effects on both the alleviation of symptoms and also changes in cognitive performance as an appreciated side effect or as bringing up the desired/expected ability like improved continuous attention, focus, and impulse control. For example, training the alpha band frequency has been associated with improved attentional control and working memory. Investigating attentional control is typically done with tasks such as the Stroop task, in which a color word is shown in a font color that is different (incongruent) than what the word represents and the participant is asked to name only the font color. Tests have shown that there is often a remarkable decrease in response time (delay) and an increase of accuracy from pre-to postneurofeedback sessions. In general, the Stroop test could be used to mark objectively success of neurofeedback over time. The problem is that that clinicians complain about the time which is spent to administer the Stroop test, which makes it interesting for research but not for clinical praxis.

Cognitive and Psychophysiological Test Operations as Assessment Tool for Neurofeedback Clinicians: A Pilot Study on Its Preliminary Normative Data and Validity
The purpose of this study was to obtain normative data of a battery of informatized tests from the software Cognitive and Psychophysiological Test Operations (CAPITO) and its comparation with classical neuropsychological tests in order to assure construct validity with the goal to create a test which is suitable for use by primary care medical staff, psychologists, and neuropsychologists, since it can be administered in just 10 minutes.
We administered a battery of informatized tests (Stroop, simple reaction time, sustained attention, shifting attention) to 120 subjects who are cognitively normal and range in age from 18 to 65 years, of whom 26 randomly selected subjects also scored in classical tests in order to check battery validity (confidence level of 90%, sampling margin of error 15%). In the case of subjects receiving both modalities (informatized and classical testing) the order of application was balanced, in order to avoid application order bias. Statistics of each test scores were calculated and comparisons between informatized and classical tests were conducted. The spectrum of autistic disorders is among the most heterogeneous, both in regard to electrophysiology and to metabolism. Specific to brain electrophysiology, research points to multiple noted outlying quantitative EEG features; consistent with the heterogeneity of the symptoms of this disorder. That variation of noted phenomenon has led to various EEG neurofeedback training strategies over the past two decades. Many of these strategies have undergone clinical research and, while encouraging, have presented similarly heterogeneous outcomes. It is still an active discussion with regard to which symptom features of ASD are specific to which neurofeedback protocols. Furthermore, protocols that address frontal pole delta or frontotemporal and temporal beta in low-functioning patients are challenging as these features are often confounded by muscle artifact and eye movement during training. In this presentation, we propose an alternative neurofeedback training protocol that can be used to improve particularly the frontal and temporal region dysfunctions that play a role in regulating attention and response control, and that is nearly impervious to the contamination of eye movement or muscle tension. One of the systemic dysregularities noted in the ASD population is a variety of metabolic imbalances which we argue can be presented as diffuse, low absolute power measures spanning two or more frequency bands in the qEEG. The specific physiological mechanism for this phenotypic pattern is not yet well understood but one rationale is that as a result of underlying metabolic dysregulation, oxygen perfusion is reduced resulting in reduced cell energy and subsequent low power.
With this supposition, the authors have been using a nHEG (Toomim) training protocol since 2011. We have selected from 50 of the qualifying clinical nHEG training cases run in 2016 and 2017. The multicase study reveals significant improvement in the qEEG features from baseline to subsequent evaluations following approximately 10 hours of treatment. These results are compared to a protocol of neurofeedback therapy that trains to increase absolute power by rewarding EEG absolute power parameters alone.

Multivariate Coherence Training for Developmental Trauma
Robert Coben 1 , Clark Thompson 2 , Anne Stevens 1 1 Integrated Neuroscience Services, Fayetteville, Arkansas, USA 2 BaySide NeuroRehab Services, Portland, Maine, USA Developmental trauma is a major public health concern that has generated increased interest from researchers over the past few decades. The Adverse Childhood Experiences (ACE) study revealed correlational relationships between traumatic childhood experiences and an array of outcomes after several years, which included depression, substance abuse, domestic violence, suicide attempts, and various medical conditions (Felitti et al., 1998). Common domains of impairment observed by children exposed to developmental trauma are multifaceted, consisting of self-concept, attachment, behavioral regulation, affect regulation, dissociation, and biology (Cook et al., 2017). Neuroimaging studies of this population have revealed structural changes in the brain, such as reduced development of the hippocampus, amygdala, corpus callosum, and left neocortex (Teicher et al., 2003). Overall, there are a paucity of neurofeedback studies on developmental trauma. A small handful of projects have focused on power training (van der , some of which have been qEEG based .
We are conducting a study on participants with a history of developmental trauma who underwent neurofeedback training.
We hypothesize that subjects who undergo neurofeedback training will show significantly decreased levels of mood and trauma-related symptoms compared to controls. Based on the findings of Armes and Coben (2017), we hypothesize that changes in connectivity will be related to success in neurofeedback and reduction of symptoms. Our study consists of 40 participants who were randomly assigned to a four-channel multivariate coherence training group or a control group who received an alternative treatment with no neurofeedback training.
Dependent variables included the Beck Depression Inventory-II, Beck Anxiety Inventory, Trauma Symptom Inventory-II, as well as power and graph theory connectivity metrics based on qEEG findings. These measures were all administered at time 1 and time 2 with an intervening period of neurofeedback training. Preliminary findings show enhancements in coherence metrics are associated with decreased depression, anxiety, and trauma-related symptoms. ISF electroencephalographic (EEG) biofeedback focuses on the low energy signals produced by the brain. This includes frequencies of less than 0.1 Hz (Smith, Collura, Ferrera, & de Vries, 2014).

The Effect of Infraslow Frequency Neurofeedback on Quantitative Electroencephalogram and Autonomic Nervous System Function in Adults with Anxiety and Related Diseases
Evidence suggests that these slow oscillations play a role in synchronizing faster activity and modulates cortical excitability (Bazhenov & Timofeev, 2006).
The origins of these slow oscillations are not yet well understood but studies have indicated the involvement of the thalamus and other subcortical structures (Lörincz, Geall, Bao, Crunelli, & Hughes, 2009). The ANS is an important role player in maintaining sympatheticparasympathetic and cardiovascular homeostasis. It includes vagal cholinergic and sympathetic noradrenergic nerves that supply the heart and sympathetic noradrenergic nerves that enmesh arterioles. Therefore, clinicians and researchers have long sought valid, noninvasive, quantitative means to identify patho-physiologically relevant abnormalities of these systems (Goldstein, Bentho, Park, & Sharabi, 2011). Heart Rate Variability (HRV) is one of the most well-known means of measurement. There is increasing research pointing to the clinical application of HRV in training and exercise due to its apparent result in strengthening sympathetic-parasympathetic balance (Peper, Harvey, Lin, Tylova, & Moss, 2007). Achieving an increased HRV while doing ISF training should be a good indicator of firstly reaching clients Optimum Frequency (OF) and secondly achieving a sympathetic-parasympathetic balance (Camp, Remus, Kalburgi, Porterfield, & Johnson, 2012;Collura, 2014). This study hypothesizes that ISF training has a measurable physiological effect on an individual by measuring certain autonomic functions; namely, HRV, muscle tension, skin temperature, skin conductance, heart rate, respiration rate, and blood pressure. Also, to demonstrate how ISF training impacts the resting state EEG.
Methods. Thirty adults between the ages of 18 and 55 with primarily anxiety will receive a quantitative electroencephalogram (qEEG) to get a baseline before training. The participants will then receive ISF neurofeedback training for 10 sessions while continuous monitoring of ANS changes will be done to determine if there are measurable changes. After 10 sessions we will repeat a qEEG to determine what changes occurred. The same process will be completed for a control group. The control group will receive one-channel power training where Theta and Hibeta activity will be inhibited at 3-7 Hz and 22-30 Hz respectively and Lobeta 12-15 Hz activity enhanced at the C4 location on the head. Anticipated results. Preliminary results and a pilot study conducted show significant changes that have been observed in participants trained in ISF neurofeedback, both in the activation patterns when looking at the qEEG and the autonomic functions that were measured. No significant changes have been seen thus far in the control group.
Conclusion. The study will possibly demonstrate that autonomic functions are affected by ISF neurofeedback training and that changes occur in the resting state EEG of participants trained.  Davidson, 1998). Asymmetry scores (A1) were calculated from log-transformed of alpha power (8-12 Hz), log (F4) − log (F3). Some studies based on theoretical of FAA and applied alpha asymmetry neurofeedback (ALAY) showed some improvement in the depressive symptoms. However, the changes of electroencephalography (EEG) parameters were inconsistent (Baehr, Rosenfeld, & Baehr, 2001;Choi et al., 2011;. This study hypothesized the differences on EEG patterns between participants with FAA (A1−) and without FAA (A1+) among the healthy controls and patients with MDD; as well as the effect of ALAY neurofeedback on A1 score between the A1(−) group or the A1(+) group among patients with MDD.

The Frontal Alpha Asymmetry and Neurofeedback in Patients with Major Depressive Disorder
Method. Study 1: The participants were composed of 127 patients with MDD (72 in the A1+ group; 55 in the A1− group) and 129 healthy controls (87 in the A1+ group; 42 in the A1− group). Beck Depression Inventory-II was administered, and a 19-channel EEG cap with BrainAvatar (BrainMaster, Bedford, Ohio) has collected EEG raw signals at F3 and F4 and transformed to absolute alpha power (8-12 Hz), and then calculated alpha asymmetry score (A1). Study 2: A total of 48 patients with MDD were assigned to the ALAY neurofeedback groups (A1+, n = 11; A1−, n = 13) and the control groups (A1+, n = 10; A1−, n = 12) based on their A1 score at pretest. The ALAY neurofeedback groups received 60 min, twice a week for 10 consecutive sessions of neurofeedback that was assisted by BioGraphy Infiniti 6.0 (Thought Technology, Quebec, Canada).
The goal of neurofeedback was to increase A1 score with the visual and the auditory feedback. The control group received the normal treatment as usual. All of the participants underwent pretest and posttest measurement which included the performance on psychological questionnaires and EEG, which included the F3 alpha, F4 alpha, and A1 score.
Results. For EEG patterns, there was higher alpha power in the left prefrontal lobe (F3) in the A1(−) group compared to A1(+) group in the healthy controls; as well as lower alpha power in the right prefrontal lobe (F4) in the A1(−) group compared to A1(+) group in patients with MDD. Regarding the effect of ALAY neurofeedback, the ALAY A1(−) group significantly increased the A1 score at posttest than the pretest. However, ALAY A1(+) group did not show significant improvements, as well as two MDD controls (A1+ and A1−). Both neurofeedback groups (ALAY A1− and ALAY A1+) significantly decreased the depression total score and cognitive depression, and ALAY A1(−) also decreased the anxiety score.

Conclusion.
The high alpha power in the left prefrontal lobe in the healthy controls, and low alpha power in the right prefrontal lobe in the MDD group, were found in participants who had FAA. The neurofeedback therefore was beneficial for patients with FAA in decreasing depressive symptoms and increasing the A1 score. Background. For decades EEG neurofeedback has been the only method of self-regulation of brain activity in mental disorders. Current developments in fMRI technology made possible neuroimaging neurofeedback targeted to a well-defined cerebral area. Implementations of the technology aimed to enhance subjects' control of the activity of brain structures involved in emotion regulation were successful both in healthy volunteers (Johnston et al., 2011) and in patients with major depression (Hamilton et al., 2016;Linden et al., 2012;Young et al., 2017).
Objectives. The aim of our study was to examine effects of the real-time fMRI neurofeedback as a treatment arm for mild to severe depression. Alphaasymmetry neurofeedback and cognitive-behavioral therapy (CBT) served as control treatment arms.
Methods. Thirty subjects (10 males, 20 females, aged 20-50, mean age of 33) were recruited and randomly assigned to experimental or one of two control groups. Participants of experimental group received eight weekly sessions of fMRI neurofeedback targeted bilaterally to the area within medial prefrontal cortex. During each session blocks of enhancing and suppressing the response of the target area were alternating. Subjects continuously received visual feedback reflecting percent of signal change within the region of interest (ROI). The source signal was recorded using Philips Ingenia 3T MR scanner with an EPI sequence, TR = 1000 ms. Temporal dynamics of the signal from ROI was captured from the IViewBOLD graphs and presented on the screen as a yellow circle, the diameter and brightness of which depended on the signal values. Offline fMRI analysis was performed using SPM 12 software. Concurrent EEG was recorded with a 32channel MR-compatible BrainAmp system, corrected for MR, cardiac, and ocular artifacts and processed in Vol. 5 (4) Results. Preliminary EEG recordings comparing the stress condition to the TouchPoints condition exhibited significantly reduced activity in frontal Theta, specifically in 5 Hz at Fp2 and F4 sites and reduced activity in Beta 1 at 12-14 Hz in the frontal channel locations (Fp1, Fp2, Fp3, Fz, F4). Significant right frontal decreases are shown in Beta 2 at 16-18 Hz, Beta 3 bands at 19 Hz and 23 Hz, and Gamma 1 at 30-35 Hz with activity decreasing along the midline also in Beta 3 at 19 Hz and 23 Hz and in Gamma 1 at 30 Hz.
Conclusion. The significant reduction in beta activity provides preliminary evidence that BLAST technology may have a therapeutic effect on reducing subcortical activity associated with anxiety and stress. Our results are consistent with previous studies  suggesting beta wave activity is correlated with increased levels of anxiety. This preliminary data implicates the potential efficacy of BLAST as a mediator of SNS arousal and stress through beta-activity reduction in both clinical and nonclinical samples. Follow-up research is required utilizing a comparison control group with a larger sample to assess for qEEG differences in brain activity.
Results. Children with ASD did not differ from typical children in reaction time (RT), but they committed more errors (12.9% vs. 2.2 %, F = 14.9, p < .001) and did not show normative posterror RT slowing (F = 27.6, p < .001). The error-related negativity was lower in ASD (F = 8.5, p = .004). The early ERPs (P100 and N100) to nontarget stimuli were of higher amplitude and delayed in the ASD group (ps < 0.05). The late ERPs (P3a and P3b) to nontarget stimuli were prolonged in ASD without amplitude differences, though P3a was delayed as well to targets in the ASD (458 vs. 426 ms, F = 4.9, p = .03).

Conclusions.
Results are in concordance with our prior studies where children with ASD showed excessive reactivity to task-irrelevant stimuli at the early sensory stage processing of information leading to delayed cognitive ERP to targets resulting in error monitoring and correction deficits. It was important to replicate these findings when ERPs were analyzed only at the midline frontal and parietal areas as it may have practical implications. It creates opportunity for our group to start development of a custom-made experimental control and EEG acquisition system with limited number of channels (e.g., Fz, Pz) for ERP analysis in oddball test with illusory figures that can be used for functional diagnostic and as outcome of neurofeedback or neuromodulation interventions.