Proceedings of the 2017 ISNR Conference: Keynotes, Invited, and Student Award Presentations

  • International Society for Neurofeedback and Research (ISNR)


Selected Abstracts of Conference Presentations at the 2017 International Society for Neurofeedback and Research (ISNR) 25th Annual Conference, Mashantucket, CT, USA


-----Functional Neuroimaging as a Window into Human Brain Function: Applications to Better Understand and Optimize Neuromodulatory Therapies

Harris, R. E., Napadow, V., Huggins, J. P., Pauer, L., Kim, J., Hampson, J., … Clauw, D. J. (2013). Pregabalin rectifies aberrant brain chemistry, connectivity, and functional response in chronic pain patients. Anesthesiology, 119(6), 1453–1464.

Kim, J., Loggia, M. L., Cahalan, C. M., Harris, R. E., Beissner, F., Garcia, R. G., … Napadow, V. (2015). The somatosensory link in fibromyalgia: Functional connectivity of the primary somatosensory cortex is altered by sustained pain and is associated with clinical/autonomic dysfunction. Arthritis & Rheumatology, 67(5), 1395–1405.

Kim, J., Loggia, M. L., Edwards, R. R., Wasan, A. D., Gollub, R. L., & Napadow, V. (2013). Sustained deep-tissue pain alters functional brain connectivity. Pain, 154(8), 1343–1351.

Loggia, M. L., Kim, J., Gollub, R. L., Vangel, M. G., Kirsch, I., Kong, J., … Napadow, V. (2013). Default mode network connectivity encodes clinical pain: An arterial spin labeling study. Pain, 154(1), 24–33.

Napadow, V., & Harris, R. E. (2014). What has functional connectivity and chemical neuroimaging in fibromyalgia taught us about the mechanisms and management of “centralized” pain? Arthritis Research & Therapy, 16(4), 425.

Napadow, V., Kim, J., Clauw, D. J., & Harris, R. E. (2012). Brief report: Decreased intrinsic brain connectivity is associated with reduced clinical pain in fibromyalgia. Arthritis & Rheumatology, 64(7), 2398–2403.

Napadow, V., LaCount, L., Park, K., As-Sanie, S., Clauw, D. J., & Harris, R. E. (2010). Intrinsic brain connectivity in fibromyalgia is associated with chronic pain intensity. Arthritis & Rheumatology, 62(8), 2545–2555.

-----Impact of Childhood Maltreatment on Brain Development and the Critical Importance of Distinguishing Between Maltreated and Non-Maltreated Diagnostic Subtypes

Teicher, M. H., & Samson, J. A. (2013). Childhood maltreatment and psychopathology: A case for ecophenotypic variants as clinically and neurobiologically distinct subtypes. The American Journal of Psychiatry, 170(10), 1114–1133.

Teicher, M. H., & Samson, J. A. (2016). Annual Research Review: Enduring neurobiological effects of childhood abuse and neglect. The Journal of Child Psychology and Psychiatry, 57(3), 241–266.

Teicher, M. H., Samson, J. A., Anderson, C. M., & Ohashi, K. (2016). The effects of childhood maltreatment on brain structure, function and connectivity. Nature Reviews Neuroscience, 17, 652–666.

-----The Evolution of Quantitative EEG: A Perfect Storm

Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The Brain's Default Network: Anatomy, Function, and Relevance to Disease. Annals of the New York Academy of Sciences, 1124, 1¬–38. /annals.1440.011

Dohrmann, A.-L., Stengler, K., Jahn, I., & Olbrich, S. (2017). EEG-arousal regulation as predictor of treatment response in patients suffering from obsessive compulsive disorder. Clin Neuropsychol, 128(10), 1906–1914. /j.clinph.2017.07.406

Hanley, D., Prichep, L. S., Bazarian, J., Huff, J. S., Naunheim, R., Garrett, J., … Hack, D. C. (2017). Emergency Department Triage of Traumatic Head Injury Using Brain Electrical Activity Biomarkers: A Multisite Prospective Observational Validation Trial. Academic Emergency Medicine, 24(5), 617–627.

Jelic, V., Johansson, S.-E., Almkvist, O., Shigeta, M., Julin, P., Nordberg, A., … Wahlund, L.-O. (2000). Quantitative electroencephalography in mild cognitive impairment: Longitudinal changes and possible prediction of Alzheimer's disease. Neurobiology of Aging, 21(4), 533–540.

John, E. R., Ahn, H., Prichep, L. S., Trepetin, M., Brown, D., & Kaye, H. (1980). Developmental equations for the electroencephalogram. Science, 210(4475), 1255–1258.

Pascual-Marqui, R. D., Esslen, M., Kochi, K., & Lehman, D. (2002). Functional imaging with low resolution brain electromagnetic tomography (LORETA): A review. Methods & Findings in Experimental & Clinical Pharmacology, 24C, 91–95. /LORETA-ReviewPaper03.pdf

Prichep, L. S., John, E. R., Ferris, S. H., Rausch, L., Fang, Z., Cancro, R., … Reisberg, B. (2006). Prediction of longitudinal cognitive decline in normal elderly with subjective complaints using electrophysiological imaging. Neurobiology of Aging, 27(3), 471–481. /j.neurobiolaging.2005.07.021

Prichep, L. S., Shah, J., Merkin, H., et al. (in press, 2017). Identification of Chronic Pain Matrix Using Quantitative EEG Source Localization. Clinical EEG and Neuroscience.

-----Early Detection and Treatment of Attention Deficits in Preterm Infants

Gomes, H., Molholm, S., Christodoulou, C., Ritter, W., & Cowan, N. (2000). The development of auditory attention in children. Frontiers in Bioscience, 5, 108–120.

Gutiérrez-Hernández, C. C., Harmony, T., Avecilla-Ramírez, G. N., Barrón-Quiroz, I., Guillén-Gasca, V., Trejo-Bautista, G., & Bautista-Olvera, M. M. (2017). Infant Scale of Selective Attention: A Proposal to Assess Cognitive Abilities. Evaluar, 17(1), 94–106. Retrieved from /index.php/revaluar/article/download/17077/16708

Polich, J. (2007). Updating P300: An integrative theory of P3a and P3b. Clinical Neurophysiology, 118(10), 2128–2148.

Reynolds, G. D., & Romano, A. C. (2016). The development of attention systems and working memory in infancy. Frontiers in Systems Neuroscience, 10, 15. /fnsys.2016.00015

-----Functional Neuromarkers for Psychiatry and Neurology: Defining Brain Dysfunctions and Constructing Protocols of Neuromodulation

Kropotov, J. D. (2016). Functional neuromarkers for psychiatry: Applications for diagnosis and treatment. Amsterdam, Netherlands: Academic Press, Elsevier.

-----Is A/T Neurofeedback Training (NFT) a Successful Treatment Method for Women with Moderate to Severe Trait Anxiety: A Clinical Trial and Methodological Considerations

Aliño, M., Gadea, M., & Espert, R. (2016). A critical view of neurofeedback experimental designs: Sham and control as necessary conditions. International Journal of Neurology and Neurotherapy, 3(1), 041.

Alkoby, O., Abu-Rmileh, A., Shriki, O., & Todder, D. (2017). Can we predict who will respond to neurofeedback? A review of the inefficacy problem and existing predictors for successful EEG neurofeedback learning. Neuroscience. /10.1016/j.neuroscience.2016.12.050

Bates, D., Maechler, M., & Bolker, B. (2013). lme4: Linear mixed-effects models using S4 classes. R package version 0.999999-0. 2012. Retrieved from

Baxter, A. J., Scott, K. M., Vos, T., & Whiteford, H. A. (2013). Global prevalence of anxiety disorders: A systematic review and meta-regression. Psychological Medicine, 43(5), 897–910.

Éismont, E. V., Lutsyuk, N. V., & Pavlenko, V. B. (2011). Moderation of increased anxiety in children and teenagers with the use of neurotherapy: estimation of efficacy. Neurophysiology, 43(1), 53–61.

Ferreira, A., Celeste, W. C., Cheein, F. A., Bastos-Filho, T. F., Sarcinelli-Filho, M., & Carelli, R. (2008). Human-machine interfaces based on EMG and EEG applied to robotic systems. Journal of NeuroEngineering and Rehabilitation, 5, 10.

Gidron, Y. (2013). State Anxiety. In M. D. Gellman & J. R. Turner (Eds.), Encyclopedia of Behavioral Medicine (p. 1877). New York, NY: Springer. http://dx.doi.org10.1007/978-1-4419-1005-9

Kohn, P. M., Kantor, L., DeCicco, T. L., & Beck, A. T. (2008). The Beck Anxiety Inventory-Trait (BAI): A measure of dispositional anxiety not contaminated by dispositional depression. Journal of Personality Assessment, 90(5), 499–506. /10.1080/00223890802248844

Marzbani, H., Marateb, H. R., & Mansourian, M. (2016). Neurofeedback: A comprehensive review on system design, methodology and clinical applications. Basic and Clinical Neuroscience, 7(2), 143–158. /J.BCN.03070208

Mennella, R., Patron, E., & Palomba, D. (2017). Frontal alpha asymmetry neurofeedback for the reduction of negative affect and anxiety. Behaviour Research and Therapy, 92, 32–40.

Mirman, D. (2014). Growth curve analysis and visualization using R (p. 168). Boca Raton, FL: CRC Press.

Mirman, D., Dixon, J. A., & Magnuson, J. S. (2008). Statistical and computational models of the visual world paradigm: Growth curves and individual differences. Journal of Memory and Language, 59(4), 475–494. /j.jml.2007.11.006

Monastra, V. J., Lynn, S., Linden, M., Lubar, J. F., Gruzelier, J., & LaVaque, T. J. (2005). Electroencephalographic biofeedback in the treatment of Attention-Deficit/Hyperactivity Disorder. Applied Psychophysiology and Biofeedback, 30(2), 95–114.

Moore, N. C. (2000). A review of EEG biofeedback treatment of anxiety disorders. Clinical Electroencephalography, 31(1), 1–6.

Moore, T. J., & Mattison, D. R. (2017). Adult utilization of psychiatric drugs and differences by sex, age, and race. JAMA Internal Medicine, 177(2), 274–275.

Paluch, K., Jurewicz, K., Rogala, J., Krauz, R., Szczypińska, M., Mikicin, M., ... & Kublik, E. (2017). Beware: Recruitment of Muscle Activity by the EEG-Neurofeedback Trainings of High Frequencies. Frontiers in Human Neuroscience, 11, 119.

Phneah, S. W., & Nisar, H. (2017). EEG-based alpha neurofeedback training for mood enhancement. Australasian Physical & Engineering Sciences in Medicine, 40(2), 325–336.

Plotkin, W. B., & Rice, K. M. (1981). Biofeedback as a placebo: Anxiety reduction facilitated by training in either suppression or enhancement of alpha brainwaves. Journal of Counseling and Clinical Psychology, 49(4), 590–596. /10.1037/0022-006X.49.4.590

Raymond, J., Varney, C., Parkinson, L. A., & Gruzelier, J. H. (2005). The effects of alpha/theta neurofeedback on personality and mood. Cognitive Brain Research, 23(2), 287–292.

Rice, K. M., Blanchard, E. B., & Purcell, M. (1993). Biofeedback treatment of generalized anxiety disorder: Preliminary results. Biofeedback and Self-Regulation, 18(2), 93–105.

Rogala, J., Jurewicz, K., Paluch, K., Kublik, E., Cetnarski, R., & Wróbel, A. (2016). The Do's and Don'ts of Neurofeedback Training: A Review of the Controlled Studies Using Healthy Adults. Frontiers in Human Neuroscience, 10, 301.

Ros, T., Baars, B. J., Lanius, R. A., & Vuilleumier, P. (2014). Tuning pathological brain oscillations with neurofeedback: A systems neuroscience framework. Frontiers in Human Neuroscience, 8, 1008. /fnhum.2014.01008

Sargunaraj, D., Kumaraiah, V., Mishra, H. & Kumar, K. A. (1987). A comparison of the efficacy of electromyograph and alpha biofeedback therapy in anxiety neurosis. NIMHANS Journal, 5, 103–107.

Sarkar, P., Rathee, S. P., & Neera, N. (1999). Comparative efficacy of pharmacotherapy and bio-feed back among cases of generalised anxiety disorder. Journal of Projective Psychology & Mental Health, 6(1), 69¬–77.

Simkin, D. R., Thatcher, R.W., & Lubar, J. F. (2014). Quantitative EEG and neurofeedback in children and adolescents: Anxiety disorders, depressive disorders, comorbid addiction and attention-deficit/hyperactivity disorder, and brain injury. Child & Adolescent Psychiatric Clinics of North America, 23(3), 427–464.

Snapinn, S. M., & Jiang, Q. (2007). Responder analyses and the assessment of a clinically relevant treatment effect. Trials, 8(1), 31.

Soutar, R. G., & Longo, R. E. (2011). Doing neurofeedback: An introduction. ISNR Research Foundation.

Spielberger, C. D., Gorsuch, R. L., Lushene, R., Vagg, P. R., & Jacobs, G. A. (1983). Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press.

Strehl, U. (2013). Lerntheoretische Grundlagen und Überlegungen zum Neurofeedback. In U. Strehl (Ed.), Neurofeedback (pp. 13–30). Stuttgart, Germany: Kohlhammer.

Strehl, U. (2014). What learning theories can teach us in designing neurofeedback treatments. Frontiers in Human Neuroscience, 8, 894. /fnhum.2014.00894

Studer, P., Kratz, O., Gevensleben, H., Rothenberger, A., Moll, G. H., Hautzinger, M., & Heinrich, H. (2014). Slow cortical potential and theta/beta neurofeedback training in adults: Effects on attentional processes and motor system excitability. Frontiers in Human Neuroscience, 8, 555.

Thatcher, R. W., & Lubar, J. F. (2008). History of the scientific standards of QEEG normative databases. In T. Budzinsky, H. Budzinsky, J. Evans, & A. Abarbanel (Eds.), Introduction to QEEG and neurofeedback: Advanced theory and applications. San Diego, CA: Academic Press.

Uryniak, T., Chan, I. S. F., Fedorov, V. V., Jiang, Q., Oppenheimer, L., Snapinn, S. M., ... & Zhang, J. (2012). Responder analyses—A PhRMA position paper. Statistics in Biopharmaceutical Research, 3(3), 476–487. /10.1198/sbr.2011.10070

Vanathy, S., Sharma, P. S. V. N., & Kumar, K. B. (1998). The efficacy of alpha and theta neurofeedback training in treatment of generalized anxiety disorder. Indian Journal of Clinical Psychology, 25(2), 136–143.

Wang, S., Zhao, Y., Chen, S., Lin, G., Sun, P., & Wang, T. (2013). EEG biofeedback improves attentional bias in high trait anxiety individuals. BMC Neuroscience, 14(1), 115.

Watson, C. G., & Herder, J. (1980). Effectiveness of alpha biofeedback therapy: Negative results. Journal of Clinical Psychology, 36(2), 508–513. /jclp.6120360221

White, E. K., Groeneveld, K. M., Tittle, R. K., Bolhuis, N. A., Martin, R. E., Royer, T. G., & Fotuhi, M. (2017). Combined neurofeedback and heart rate variability training for individuals with symptoms of anxiety and depression: A retrospective study. NeuroRegulation, 4(1), 37–55.

Wyckoff, S., & Birbaumer, N. (2014). Neurofeedback. In D. J. A. Dozois (Ed.), The Wiley Handbook of Cognitive Behavioral Therapy, Part One (13, pp. 273–310). Princeton, NJ: Wiley & Sons Press. /9781118528563.wbcbt13

Zuberer, A., Brandeis, D., & Drechsler, R. (2015). Are treatment effects of neurofeedback training in children with ADHD related to the successful regulation of brain activity? A review on the learning of regulation of brain activity and a contribution to the discussion on specificity. Frontiers in Human Neuroscience, 9, 135.

-----The Effect of Slow Breathing Training on Electroencephalogram

Lehrer, P. M., Vaschillo, E., & Vaschillo, B. (2000). Resonant frequency biofeedback training to increase cardiac variability: Rationale and manual for training. Applied Psychophysiology and Biofeedback, 25(3), 177–191. /A:1009554825745

Prinsloo, G. E., Rauch, H. G. L., Karpul, D., & Derman, W. E. (2013). The effect of a single session of short duration heart rate variability biofeedback on EEG: A pilot study. Applied Psychophysiology and Biofeedback, 38(1), 45–56.

-----The Effects of Personalized EEG-Neurofeedback in College Students with ADHD

Arns, M., de Ridder, S., Strehl, U., Breteler, M., & Coenen, A. (2009). Efficacy of neurofeedback treatment in ADHD: The effects on inattention, impulsivity and hyperactivity: A meta-analysis. Clinical EEG and Neuroscience, 40(3), 180–189.

Arns, M., Drinkenburg, W., & Leon Kenemans, J. (2012). The effects of qEEG-informed neurofeedback in ADHD: An open-label pilot study. Applied Psychophysiology and Biofeedback, 37(3), 171–180.

Johnstone, J., Gunkelman, J., & Lunt, J. (2005). Clinical database development: Characterization of EEG phenotypes. Clinical EEG and Neuroscience, 36(2), 99–107.

-----The Differences Between Frontal Alpha Asymmetry Among Healthy Participants and Patients with Major Depressive Disorder

Baehr, E., Rosenfeld, J. P., & Baehr, R. (1997). The clinical use of an alpha asymmetry protocol in the neurofeedback treatment of depression: Two case studies. Journal of Neurotherapy, 2(3), 10–23.

Thibodeau, R., Jorgensen, R. S., & Kim, S. (2006). Depression, anxiety, and resting frontal EEG asymmetry: A meta-analytic review. Journal of Abnormal Psychology, 115(4), 715–729.

-----Neurostructural Predictors of Cognitive Behavioral Therapy (CBT) for Obsessive-Compulsive Disorder: Implications for the Integration of Neurofeedback Training and CBT

Butler, A. C., Chapman, J. E., Forman, E. M., & Beck, A. T. (2006). The empirical status of cognitive-behavioral therapy: A review of meta-analyses. Clinical Psychology Review, 26(1), 17¬–31.

Hammond, D. C. (2003). QEEG-guided neurofeedback in the treatment of obsessive compulsive disorder. Journal of Neurotherapy, 7(2), 25–52. /J184v07n02_03

Menzies, L., Chamberlain, S. R., Laird, A. R., Thelen, S. M., Sahakian, B. J., & Bullmore, E. T. (2008). Integrating evidence from neuroimaging and neuropsychological studies of obsessive-compulsive disorder: The orbitofronto-striatal model revisited. • Neuroscience & Biobehavioral Reviews, 32(3), 525–549. /j.neubiorev.2007.09.005

Mito, H., Matsuura, N., Mukai, K., Yanagisawa, Y., Nakajima, A., Motoyama, M., ... & Matsunaga, H. (2014). The impacts of elevated autism spectrum disorder traits on clinical and psychosocial features and long-term treatment outcome in adult patients with obsessive-compulsive disorder. Comprehensive Psychiatry, 55(7), 1526–1533.

Mohlman, J., & Gorman, J. M. (2005). The role of executive functioning in CBT: A pilot study with anxious older adults. Behaviour Research and Therapy, 43(4), 447–465.

Murray, K., Jassi, A., Mataix-Cols, D., Barrow, F., & Krebs, G. (2015). Outcomes of cognitive behaviour therapy for obsessive–compulsive disorder in young people with and without autism spectrum disorders: A case controlled study. Psychiatry Research, 228(1), 8–13.