A Neurovisceral Approach to Autism: Targeting Self-Regulation and Core Symptoms Using Neurofeedback and Biofeedback
DOI:
https://doi.org/10.15540/nr.5.1.9Keywords:
autism, neurofeedback, biofeedback, heart rate variability, mu rhythms, mirror neuron system, neurovisceral integrationAbstract
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
Downloads
Published
Issue
Section
License
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC-BY) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).