A Neurovisceral Approach to Autism: Targeting Self-Regulation and Core Symptoms Using Neurofeedback and Biofeedback

Authors

  • Matthew S. Goodman Alliant International University, San Diego
  • Nicolette Castro
  • Mary Sloan
  • Rita Sharma
  • Michael Widdowson
  • Eduardo Herrera
  • Jaime A Pineda University of California, San Diego

DOI:

https://doi.org/10.15540/nr.5.1.9

Keywords:

autism, neurofeedback, biofeedback, heart rate variability, mu rhythms, mirror neuron system, neurovisceral integration

Abstract

Mu Rhythm Synchrony Neurofeedback (MRS-NFB) has shown promise in improving electrophysiological and behavioral deficits in autism spectrum disorder (ASD).  Heart rate variability biofeedback (HRV-BFB), a method for improving self-regulation of the autonomic nervous system (ANS), has yet to be tested as a clinical intervention for ASD.  This study evaluated the impact of HRV-BFB on symptoms of ASD; and whether a combined HRV-BFB + MRS-NFB intervention would be more efficacious than HRV-BFB alone.  Fifteen children with a verified diagnosis of ASD completed the study. Participants were assigned to either an HRV-BFB group (Group 1) or a combined HRV-BFB + MRS-NFB group (Group 2).  All children underwent pre- and postassessments of electroencephalography (EEG), heart rate variability (HRV), and parent-reported behaviors.  No significant between-groups differences were observed on any parent-reported behaviors.  Group 1 showed significant pre–post improvements in emotion regulation and social behavior, while Group 2 showed significant pre–post improvements in emotional lability and autistic behaviors.  Group 2 also showed significant improvements in RMSSD and lnHF (vagal tone) indices of HRV over time, while Group 1 displayed no significant changes in HRV over time.  Group 1 showed an increase in mu suppression posttraining, and Group 2 showed a reduction in mu suppression posttraining.  The results suggest that HRV-BFB, alone or in combination with MRS-NFB, may improve behavioral features of autism.  A combined approach may be more efficacious in enhancing HRV, while the implications of each approach on mu suppression are mixed.  Neurovisceral approaches that teach self-regulation offer a novel treatment avenue for ASD.

References

Adolphs, R., Sears, L., & Piven, J. (2001). Abnormal processing of social information from faces in autism. Journal of Cognitive Neuroscience, 13(2), 232–240. http://dx.doi.org/10.1162/089892901564289

American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders (5th ed.). Washington, DC: Author.

Bal, E., Harden, E., Lamb, D., Van Hecke, A. V., Denver, J. W., & Porges, S. W. (2010). Emotion recognition in children with autism spectrum disorders: Relations to eye gaze and autonomic state. Journal of Autism and Developmental Disorders, 40(3), 358–370. http://dx.doi.org/10.1007/s10803-009-0884-3

Bass, M. M., Duchowny, C. A., & Llabre, M. M. (2009). The effect of therapeutic horseback riding on social functioning in children with autism. Journal of Autism and Developmental Disorders, 39(9), 1261–1267. http://dx.doi.org/10.1007/s10803-009-0734-3

Belmonte, M. K., Cook, E. H., Anderson, G. M., Rubenstein, J. L. R., Greenough, W. T., Beckel-Mitchener, A., … Tierney, E. (2004). Autism as a disorder of neural information processing: Directions for research and targets for therapy. Molecular Psychiatry, 9(7), 646–663. http://dx.doi.org/10.1038/sj.mp.4001499

Benarroch, E. E. (1993). The central autonomic network: Functional organization, dysfunction, and perspective. Mayo Clinic Proceedings, 68(10), 988–1001. http://dx.doi.org/10.1016/S0025-6196(12)62272-1

Bernier, R., Aaronson, B., & McPartland, J. (2013). The role of imitation in the observed heterogeneity in EEG mu rhythm in autism and typical development. Brain and Cognition, 82(1), 69–75. http://dx.doi.org/10.1016/j.bandc.2013.02.008

Biswal, B., Yetkin, F. Z., Haughton, V. M., & Hyde, J. S. (1995). Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magnetic Resonance in Medicine, 34(4), 537–541. http://dx.doi.org/10.1002/mrm.1910340409

Braadbaart, L., Williams, J. H., & Waiter, G. D. (2013). Do mirror neuron areas mediate mu rhythm suppression during imitation and action observation? International Journal of Psychophysiology, 89(1), 99–105. http://dx.doi.org/10.1016/j.ijpsycho.2013.05.019

Brock, J., Brown, C. C., Boucher, J., & Rippon, G. (2002). The temporal binding deficit hypothesis of autism. Development and Psychopathology, 14(2), 209–224. http://dx.doi.org/10.1017/S0954579402002018

Casciaro, F., Laterza, V., Conte, S., Pieralice, M., Federici, A., Todarello, O., … Conte, E. (2013). Alpha-rhythm stimulation using brain entrainment enhances heart rate variability in subjects with reduced HRV. World Journal of Neuroscience, 3(4), 213–220. http://dx.doi.org/10.4236/wjns.2013.34028

Coben, R., Linden, M., & Myers, T. E. (2010). Neurofeedback for autistic spectrum disorder: A review of the literature. Applied Psychophysiology and Biofeedback, 35(1), 83–105. http://dx.doi.org/10.1007/s10484-009-9117-y

Coben, R., & Padolsky, I. (2007). Assessment-guided neurofeedback for autistic spectrum disorder. Journal of Neurotherapy, 11(1), 5–23. http://dx.doi.org/10.1300/J184v11n01_02

Cochin, S., Barthelemy, C., Roux, S., & Martineau, J. (1999). Observation and execution of movement: Similarities demonstrated by quantified electroencephalography. European Journal of Neuroscience, 11(5), 1839–1842. http://dx.doi.org/10.1046/j.1460-9568.1999.00598.x

Constantino, J. N. (2012). Social Responsiveness Scale, Second Edition (SRS-2). Los Angeles, CA: Western Psychological Services.

Constantino, J. N., Davis, S. A., Todd, R. D., Schindler, M. K., Gross, M. M., Brophy, S. L., … Reich, W. (2003). Validation of a brief quantitative measure of autistic traits: Comparison of the Social Responsiveness Scale with the Autism Diagnostic Interview-Revised. Journal of Autism and Developmental Disorders, 33(4), 427–433. http://dx.doi.org/10.1023/A:1025014929212

Delorme, A., & Makeig, S. (2004). EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1), 9–21. http://dx.doi.org/10.1016/j.jneumeth.2003.10.009

Di Martino, A., Ross, K., Uddin, L. Q., Sklar, A. B., Castellanos, F. X., & Milham, M. P. (2009). Functional brain correlates of social and nonsocial processes in autism spectrum disorders: An activation likelihood estimation meta-analysis. Biological Psychiatry, 65(1), 63–74. http://dx.doi.org/10.1016/j.biopsych.2008.09.022

di Pellegrino, G., Fadiga, L., Fogassi, L., Gallese, V., & Rizzolatti, G. (1992). Understanding motor events: A neurophysiological study. Experimental Brain Research, 91(1), 176–180. http://dx.doi.org/10.1007/BF00230027

Enticott, P. G., Kennedy, H. A., Rinehart, N. J., Bradshaw, J. L., Tonge, B. J., Daskalakis, Z. J., & Fitzgerald, P. B. (2013). Interpersonal motor resonance in autism spectrum disorder: Evidence against a global “mirror system” deficit. Frontiers in Human Neuroscience, 7, 218. http://dx.doi.org/10.3389/fnhum.2013.00218

Fishman, I., Keown, C. L., Lincoln, A. J., Pineda, J. A, & Müller, R.-A. (2014). Atypical cross talk between mentalizing and mirror neuron networks in autism spectrum disorder. JAMA Psychiatry, 71(7), 751–760. http://dx.doi.org/10.1001/jamapsychiatry.2014.83

Friedrich, E. V. C., Sivanathan, A., Lim, T., Suttie, N., Louchart, S., Pillen, S., & Pineda, J. A. (2015). An effective neurofeedback intervention to improve social interactions in children with autism spectrum disorder. Journal of Autism and Developmental Disorders, 45(12), 4084–4100. http://dx.doi.org/10.1007/s10803-015-2523-5

Gallese, V., Fadiga, L., Fogassi, L., & Rizzolatti, G. (1996). Action recognition in the premotor cortex. Brain, 119(2), 593–609.

Geier, D. A., Kern, J. K., & Geier, M. R. (2013). A comparison of the Autism Treatment Evaluation Checklist (ATEC) and the Childhood Autism Rating Scale (CARS) for the quantitative evaluation of autism. Journal of Mental Health Research in Intellectual Disabilities, 6(4), 255–267. http://dx.doi.org/10.1080/19315864.2012.681340

Hamilton, A. F. d. C. (2013). Reflecting on the mirror neuron system in autism: A systematic review of current theories. Developmental Cognitive Neuroscience, 3, 91–105. http://dx.doi.org/10.1016/j.dcn.2012.09.008

Hill, E. L. (2004). Executive dysfunction in autism. Trends in Cognitive Sciences, 8(1), 26–32. http://dx.doi.org/10.1016/j.tics.2003.11.003

Iacoboni, M. (2009). Imitation, empathy, and mirror neurons. Annual Review of Psychology, 60, 653–670. http://dx.doi.org/10.1146/annurev.psych.60.110707.163604

Kana, R. K., Keller, T. A, Minshew, N. J., & Just, M. A. (2007). Inhibitory control in high-functioning autism: Decreased activation and underconnectivity in inhibition networks. Biological Psychiatry, 62(3), 198–206. http://dx.doi.org/10.1016/j.biopsych.2006.08.004

Kennedy, D. P., Redcay, E., & Courchesne, E. (2006). Failing to deactivate: Resting functional abnormalities in autism. Proceedings of the National Academy of Sciences of the United States of America, 103(21), 8275–8280. http://dx.doi.org/10.1073/pnas.0600674103

Kouijzer, M. E. J., van Schie, H. T., de Moor, J. M. H., Gerrits, B. J. L., & Buitelaar, J. K. (2010). Neurofeedback treatment in autism. Preliminary findings in behavioral, cognitive, and neurophysiological functioning. Research in Autism Spectrum Disorders, 4(3), 386–399. http://dx.doi.org/10.1016/j.rasd.2009.10.007

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. http://dx.doi.org/10.1023/A:1009554825745

Lehrer, P., Vaschillo, E., Lu, S.-E., Eckberg, D., Vaschillo, B., Scardella, A., & Habib, R. (2006). Heart rate variability biofeedback: Effects of age on heart rate variability, baroreflex gain, and asthma. Chest, 129(2), 278–284. http://dx.doi.org/10.1378/chest.129.2.278

Lin, G., Xiang, Q., Fu, X., Wang, S., Wang, S., Chen, S., … Wang, T. (2012). Heart rate variability biofeedback decreases blood pressure in prehypertensive subjects by improving autonomic function and baroreflex. The Journal of Alternative and Complementary Medicine, 18(2), 143–152. http://dx.doi.org/10.1089/acm.2010.0607

Lord, C., Rutter, M., DiLavore, P. C., Risi, S., Gotham, K., & Bishop, S. (2012). Autism Diagnostic Observation Schedule-2nd Edition (ADOS-2). Torrance, CA: Western Psychological Services. https://www.wpspublish.com/store/p/2648/autism-diagnostic-observation-schedule-second-edition-ados-2

Lord, C., Rutter, M., & Le Couteur, A. (1994). Autism diagnostic interview-revised: A revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. Journal of Autism and Developmental Disorders, 24(5), 659–685. http://dx.doi.org/10.1007/BF02172145

Magiati, I., Moss, J., Yates, R., Charman, T., & Howlin, P. (2011). Is the Autism Evaluation Checklist (ATEC) a useful tool for monitoring progress in children with autism spectrum disorders? Journal of Intellectual Disability Research, 55(3), 302–312. http://dx.doi.org/10.1111/j.1365-2788.2010.01359.x

Mazefsky, C. A., Herrington, J., Siegel, M., Scarpa, A., Maddox, B. B., Scahill, L., & White, S. W. (2013). The role of emotion regulation in autism spectrum disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 52(7), 679–688. http://dx.doi.org/10.1016/j.jaac.2013.05.006

McCraty, R., & Shaffer, F. (2015). Heart rate variability: New perspectives on physiological mechanisms, assessment of self-regulatory capacity, and health risk. Global Advances in Health and Medicine, 4(1), 45–61. http://dx.doi.org/10.7453/gahmj.2014.073

McCrimmon, A. W., & Smith, A. D. (2013). Review of the Wechsler Abbreviated Scale of Intelligence, Second Edition (WASI-II). Journal of Psychoeducational Assessment, 31(3), 337–341. http://dx.doi.org/10.1177/0734282912467756

Menon, V., & Uddin, L. Q. (2010). Saliency, switching, attention and control: A network model of insula function. Brain Structure and Function, 214(5–6), 655-677. http://dx.doi.org/10.1007/s00429-010-0262-0

Nauta, M. H., Scholing, A., Rapee, R. M., Abbott, M., Spence, S. H., & Waters, A. (2004). A parent-report measure of children’s anxiety: Psychometric properties and comparison with child-report in a clinic and normal sample. Behaviour Research and Therapy, 42(7), 813–839. http://dx.doi.org/10.1016/S0005-7967(03)00200-6

Oberman, L. M., Hubbard, E. M., McCleery, J. P., Altschuler, E. L., Ramachandran, V. S., & Pineda, J. A. (2005). EEG evidence for mirror neuron dysfunction in autism spectrum disorders. Cognitive Brain Research, 24(2), 190–198. http://dx.doi.org/10.1016/j.cogbrainres.2005.01.014

Oberman, L. M., Ramachandran, V. S., & Pineda, J. A. (2008). Modulation of mu suppression in children with autism spectrum disorders in response to familiar or unfamiliar stimuli: The mirror neuron hypothesis. Neuropsychologia, 46(5), 1558¬–1565. http://dx.doi.org/10.1016/j.neuropsychologia.2008.01.010

Patriquin, M. A., Lorenzi, J., & Scarpa, A. (2013). Relationship between respiratory sinus arrhythmia, heart period, and caregiver-reported language and cognitive delays in children with autism spectrum disorders. Applied Psychophysiology and Biofeedback, 38(3), 203–207. http://dx.doi.org/10.1007/s10484-013-9225-6

Patriquin, M. A., Scarpa, A., Friedman, B. H., & Porges, S. W. (2013). Respiratory sinus arrhythmia: A marker for positive social functioning and receptive language skills in children with autism spectrum disorders. Developmental Psychobiology, 55(2), 101–112. http://dx.doi.org/10.1002/dev.21002

Pineda, J. A. (2005). The functional significance of mu rhythms: Translating “seeing” and “hearing” into “doing.” Brain Research Reviews, 50(1), 57–68. http://dx.doi.org/10.1016/j.brainresrev.2005.04.005

Pineda, J. A. (2008). Sensorimotor cortex as a critical component of an 'extended' mirror neuron system: Does it solve the development, correspondence, and control problems in mirroring? Behavioral and Brain Functions, 4, 47. http://dx.doi.org/10.1186/1744-9081-4-47

Pineda, J. A., Allison, B. Z., & Vankov, A. (2000). The effects of self-movement, observation, and imagination on μ rhythms and readiness potentials (RP’s): Toward a brain-computer interface (BCI). IEEE Transactions on Rehabilitation Engineering, 8(2), 219–222. Retrieved from http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=847822

Pineda, J. A., Brang, D., Hecht, E., Edwards, L., Carey, S., Bacon, M., … Rork, A. (2008). Positive behavioral and electrophysiological changes following neurofeedback training in children with autism. Research in Autism Spectrum Disorders, 2(3), 557–581. http://dx.doi.org/10.1016/j.rasd.2007.12.003

Pineda, J. A., Carrasco, K., Datko, M., Pillen, S., & Schalles, M. (2014). Neurofeedback training produces normalization in behavioural and electrophysiological measures of high-functioning autism. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1644), 20130183. http://dx.doi.org/10.1098/rstb.2013.0183

Pineda, J. A., Friedrich, E. V. C., & LaMarca, K. (2014). Neurorehabilitation of social dysfunctions: A model-based neurofeedback approach for low and high-functioning autism. Frontiers in Neuroengineering, 7, 29–34. http://dx.doi.org/10.3389/fneng.2014.00029

Porges, S. W. (2001). The polyvagal theory: Phylogenetic substrates of a social nervous system. International Journal of Psyhophysiology, 42(2), 123–146. http://dx.doi.org/10.1016/S0167-8760(01)00162-3

Porges, S. W. (2003). The polyvagal theory: Phylogenetic contributions to social behavior. Physiology & Behavior, 79(3), 503–513. http://dx.doi.org/10.1016/S0031-9384(03)00156-2

Porges, S. W. (2007). The polyvagal perspective. Biological Psychology, 74(2), 116–143. http://dx.doi.org/10.1016/j.biopsycho.2006.06.009

Rimland, B., & Edelson, S. M. (1999). Autism Treatment Evaluation Checklist (ATEC). San Diego, CA: Autism Research Institute.

Sabbagh, M. A. (2004). Understanding orbitofrontal contributions to theory-of-mind reasoning: Implications for autism. Brain and Cognition, 55(1), 209–219. http://dx.doi.org/10.1016/j.bandc.2003.04.002

Schultz, R. T., Grelotti, D. J., Klin, A., Kleinman, J., Van der Gaag, C., Marois, R., & Skudlarski, P. (2003). The role of the fusiform face area in social cognition: Implications for the pathobiology of autism. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 358(1430), 415–427. http://dx.doi.org/10.1098/rstb.2002.1208

Shields, A., & Cicchetti, D. (1997). Emotion regulation among school-age children: The development and validation of a new criterion Q-sort scale. Developmental Psychology, 33(6), 906–916. http://dx.doi.org/10.1037/0012-1649.33.6.906

Shih, P., Shen, M., Öttl, B., Keehn, B., Gaffrey, M. S., & Müller, R. A. (2010). Atypical network connectivity for imitation in autism spectrum disorder. Neuropsychologia, 48(10), 2931–2939. http://dx.doi.org/10.1016/j.neuropsychologia.2010.05.035

Siepmann, M., Aykac, V., Unterdörfer, J., Petrowski, K., & Mueck-Weymann, M. (2008). A pilot study on the effects of heart rate variability biofeedback in patients with depression and in healthy subjects. Applied Psychophysiology and Biofeedback, 33(4), 195–201. http://dx.doi.org/10.1007/s10484-008-9064-z

Spence, S. H. (1998). A measure of anxiety symptoms among children. Behaviour Research and Therapy, 36(5), 545–566. http://dx.doi.org/10.1016/S0005-7967(98)00034-5

Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. (1996). Heart rate variability standards of measurement, physiological interpretation, and clinical use. Circulation, 93, 1043–1065. http://dx.doi.org/10.1161/01.CIR.93.5.1043

Thayer, J. F., & Brosschot, J. F. (2005). Psychosomatics and psychopathology: Looking up and down from the brain. Psychoneuroendocrinology, 30(10), 1050–1058. http://dx.doi.org/10.1016/j.psyneuen.2005.04.014

Thayer, J. F., Hansen, A. L., Saus-Rose, E., & Johnsen, B. H. (2009). Heart rate variability, prefrontal neural function, and cognitive performance: the neurovisceral integration perspective on self-regulation, adaptation, and health. Annals of Behavioral Medicine, 37(2), 141–153. http://dx.doi.org/10.1007/s12160-009-9101-z

Thayer, J. F., & Lane, R. D. (2000). A model of neurovisceral integration in emotion regulation and dysregulation. Journal of Affective Disorders, 61(3), 201–216. http://dx.doi.org/10.1016/S0165-0327(00)00338-4

Uddin, L. Q., & Menon, V. (2009). The anterior insula in autism: Under-connected and under-examined. Neuroscience & Biobehavioral Reviews, 33(8), 1198–1203. http://dx.doi.org/10.1016/j.neubiorev.2009.06.002

Umetani, K., Singer, D. H., McCraty, R., & Atkinson, M. (1998). Twenty-four hour time domain heart rate variability and heart rate: Relations to age and gender over nine decades. Journal of the American College of Cardiology, 31(3), 593–601.

Van Hecke, A. V., Lebow, J., Bal, E., Lamb, D., Harden, E., Kramer, A., … Porges, S. W. (2009). Electroencephalogram and heart rate regulation to familiar and unfamiliar people in children with autism spectrum disorders. Child Development, 80(4), 1118–1133. http://dx.doi.org/10.1111/j.1467-8624.2009.01320.x

Vissers, M. E., Cohen, M. X., & Geurts, H. M. (2012). Brain connectivity and high functioning autism: A promising path of research that needs refined models, methodological convergence, and stronger behavioral links. Neuroscience & Biobehavioral Reviews, 36(1), 604–625. http://dx.doi.org/10.1016/j.neubiorev.2011.09.003

White, S. W., Oswald, D., Ollendick, T., & Scahill, L. (2009). Anxiety in children and adolescents with autism spectrum disorders. Clinical Psychology Review, 29(3), 216–229. http://dx.doi.org/10.1016/j.cpr.2009.01.003

Williams, J. H. G., Waiter, G. D., Gilchrist, A., Perrett, D. I., Murray, A. D., & Whiten, A. (2006). Neural mechanisms of imitation and “mirror neuron” functioning in autistic spectrum disorder. Neuropsychologia, 44(4), 610–621. http://dx.doi.org/10.1016/j.neuropsychologia.2005.06.010

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2018-03-30

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