Proceedings of the 2018 ISNR Annual Conference
DOI:
https://doi.org/10.15540/nr.5.4.150Keywords:
neurofeedback, neuromodulation, EEG, qEEG, neurotherapy, ISNRAbstract
Selected Abstracts of Conference Presentations at the 2018 International Society for Neurofeedback and Research (ISNR) 26th Annual Conference, Glendale, AZ, USA
References
-----Tuning the Traumatized Brain: LORETA Z-score Neurofeedback and Heart Rate Variability Biofeedback for Chronic PTSD
Foster, D. S., & Thatcher, R. W. (2015). Surface and LORETA neurofeedback in the treatment of post-traumatic stress disorder and mild traumatic brain injury. In R. W. Thatcher & D. S. Foster (Eds.), Z score neurofeedback: Clinical applications (pp. 59–92). San Diego, CA: Academic Press.
Gapen, M., van der Kolk, B. A., Hamlin, E., Hirshberg, L., Suvak, M., & Spinazzola, J. (2016). A pilot study of neurofeedback for chronic PTSD. Applied Psychophysiology and Biofeedback, 41(3), 251–261. http://dx.doi.org/10.1007/s10484-015-9326-5
Huang-Storms, L., Bodenhamer-Davis, E., Davis, R., & Dunn, J. (2006). QEEG-guided neurofeedback for children with histories of abuse and neglect: Neurodevelopmental rationale and pilot study. Journal of Neurotherapy, 10(4), 3–16. http://dx.doi.org/10.1300/J184v10n04_02
Kluetsch, R. C., Ros, T., Théberge, J., Frewen, P. A., Calhoun, V. D., Schmahl, C., … Lanius, R. A. (2014). Plastic modulation of PTSD resting-state networks and subjective wellbeing by EEG neurofeedback. Acta Psychiatrica Scandinavica, 130(2), 123–136. http://dx.doi.org/10.1111/acps.12229
Lanius, R. A., Frewen, P. A., Tursich, M., Jetly, R., & McKinnon, M. C. (2015). Restoring large-scale brain networks in PTSD and related disorders: A proposal for neuroscientifically-informed treatment interventions. European Journal of Psychotraumatology, 6(1). http://dx.doi.org/10.3402 /ejpt.v6.27313
Paret, C., Kluetsch, R., Ruf, M., Demirakca, T., Hoesterey, S., Ende, G., & Schmahl, C. (2014). Down-regulation of amygdala activation with real-time fMRI neurofeedback in a healthy female sample. Frontiers in Behavioral Neuroscience, 8, 299. http://dx.doi.org/10.3389/fnbeh.2014.00299
Peniston, E. G., & Kulkosky, P. J. (1991). Alpha-theta brainwave neurofeedback therapy for Vietnam veterans with combat-related post-traumatic stress disorder. Medical Psychotherapy, 4, 47–60.
Peniston, E. G., Marrinan, D. A., Deming, W. A., & Kulkosky, P. J. (1993). EEG alpha-theta brainwave synchronization in Vietnam theater veterans with combat-related post-traumatic stress disorder and alcohol abuse. Advances in Medical Psychotherapy, 6, 37–50.
Pop-Jordanova, N., & Zorcec, T. (2004). Child trauma, attachment and biofeedback mitigation. Prilozi / Makedonska Akademija Na Naukite I Umetnostite, Oddelenie Za Biološki I Medicinski Nauki = Contributions / Macedonian Academy of Sciences and Arts, Section of Biological and Medical Sciences, 25(1–2), 103–114.
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. http://dx.doi.org/10.3389/fnhum.2014.01008
Smith, W. D. (2008). The effect of neurofeedback training on PTSD symptoms of depression and attention problems among military veterans. Capella University. Retrieved from http://gradworks.umi.com/33/15/3315214.html
van der Kolk, B. A., Hodgdon, H., Gapen, M., Musicaro, R., Suvak, M. K., Hamlin, E., & Spinazzola, J. (2016). A randomized controlled study of neurofeedback for chronic PTSD. PLoS ONE, 11(12), e0166752. http://dx.doi.org/10.1371/journal.pone.0166752
-----Personalized EEG-Neurofeedback as a Treatment for 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 Neuroscience, 40(3), 180–189. http://dx.doi.org/10.1177/155005940904000311
Arns, M., Drinkenburg, W., & Kenemans, J. L. (2012). The effects of qEEG-informed neurofeedback in ADHD: An open-label pilot study. Applied Psychophysiology and Biofeedback, 37(3), 171–180. http://dx.doi.org/10.1007/s10484-012-9191-4
Johnstone, J., Gunkelman, J., & Lunt, J. (2005). Clinical database development: Characterization of EEG phenotypes. Clinical EEG and Neuroscience, 36(2), 99–107. http://dx.doi.org/10.1177/155005940503600209
-----The Nonlinear Brain: Investigating Neural Entrainment Using Missing Pulse Rhythms
Bauer, A.-K. R., Kreutz, G., & Herrmann, C. S. (2015). Individual musical tempo preference correlates with EEG beta rhythm. Psychophysiology, 52(4), 600–604. http://dx.doi.org/10.1111/psyp.12375
Large, E. W. (2010). Neurodynamics of music. In M. R. Jones, R. R. Fay, & A. N. Popper (Eds.), Springer Handbook of Auditory Research, Volume 36: Music perception (Vol. 36, pp. 201–231). Springer Science+Business Media, LLC. Retrieved from http://link.springer.com/10.1007/978-1-4419-6114-3_7
Large, E. W., Herrera, J. A., & Velasco, M. J. (2015). Neural networks for beat perception in musical rhythm. Frontiers in Systems Neuroscience, 9, 159. http://dx.doi.org/10.3389/fnsys.2015.00159
Repp, B. H. (2005a). Rate limits of on-beat and off-beat tapping with simple auditory rhythms: 2. The roles of different kinds of accent. Music Perception, 23(2), 165–188.
Repp, B. H. (2005b). Sensorimotor synchronization: A review of the tapping literature. Psychonomic Bulletin & Review, 12(6), 969–992. http://dx.doi.org/10.3758/BF03206433
Tal, I., Large, E. W., Rabinovitch, E., Wei, Y., Schroeder, C. E., Poeppel, D., & Golumbic, E. Z. (2017). Neural entrainment to the beat: The “missing-pulse” phenomenon. The Journal of Neuroscience, 37(26), 6331–6341. http://dx.doi.org/10.1523/JNEUROSCI.2500-16.2017
-----Noninvasive Cranial Nerve Stimulation for Human Cognitive Performance Enhancement
Berry, S. M., Broglio, K., Bunker, M., Jayewardene, A., Olin, B., & Rush, A. J. (2013). A patient‑level meta‑analysis of studies evaluating vagus nerve stimulation therapy for treatment‑resistant depression. Medical Devices: Evidence and Research, 6, 17–35. http://dx.doi.org/10.2147/MDER.S41017
DeGiorgio, C. M., Soss, J., Cook, I. A., Markovic, D., Gornbein, J., Murray, D., … Heck, C. N. (2013). Randomized controlled trial of trigeminal nerve stimulation for drug-resistant epilepsy. Neurology, 80(9), 786–791. http://dx.doi.org/10.1212/WNL.0b013e318285c11a
Sara, S. J. (2009). The locus coeruleus and noradrenergic modulation of cognition. Nature Reviews Neuroscience, 10(3), 211–223. http://dx.doi.org/10.1038/nrn2573
Tyler, W. J., Boasso, A. M., Mortimore, H. M., Silva, R. S., Charlesworth, J. D., Marlin, M. A., … Pal, S. K. (2015). Transdermal neuromodulation of noradrenergic activity suppresses psychophysiological and biochemical stress responses in humans. Scientific Reports, 5, 13865. http://dx.doi.org/10.1038/srep13865
-----The Effects of ALAY and High Beta Down-train Neurofeedback for Patients Who Comorbid with Major Depressive Disorder and Anxiety Symptoms
Bruder, G. E., Fong, R., Tenke, C. E., Leite, P., Towey, J. P., Stewart, J. E., ... Quitkin, F. M. (1997). Regional brain asymmetries in major depression with or without an anxiety disorder: A quantitative electroencephalographic study. Biological Psychiatry, 41(9), 939–948. http://dx.doi.org/10.1016/S0006-3223(96)00260-0
Grin-Yatsenko, V. A., Baas, I., Ponomarev, V. A., & Kropotov, J. D. (2009). EEG power spectra at early stages of depressive disorders. Journal of Clinical Neurophysiology, 26(6), 401–406. http://dx.doi.org/10.1097/WNP.0b013e3181c298fe
Mathersul, D., Williams, L. M., Hopkinson, P. J., & Kemp, A. H. (2008). Investigating models of affect: Relationships among EEG alpha asymmetry, depression, and anxiety. Emotion, 8(4), 560–572. http://dx.doi.org/10.1037/a0012811
Yamada, M., Kimura, M., Mori, T., & Endo, S. (1995). EEG power and coherence in presenile and senile depression. Characteristic findings related to differences between anxiety type and retardation type. Nihon Ika Daigaku Zasshi = Journal of Nippon Medical School, 62(2), 176–185. http://dx.doi.org/10.1272/jnms1923.62.176
-----Lateralized Readiness Potentials in Children with Autism Spectrum Disorder During Posner Cueing Task: An Event-related EEG Study
Dowell, L. R., Mahone, E. M., & Mostofsky, S. H. (2009). Association of postural knowledge and basic motor skill with dyspraxia in autism: Implication for abnormalities in disturbed connectivity and motor learning. Neuropsychology, 23(5), 563–570. http://dx.doi.org/10.1037/a0015640
Eimer, M. (1998). The lateralized readiness potential as an on-line measure of central response activation processes. Behavior Research Methods, Instruments, & Computers, 30(1), 146–156. http://dx.doi.org/10.3758/BF03209424
Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology, 32(1), 3–25. http://dx.doi.org/10.1080/00335558008248231
Weimer, A. K., Schatz, A. M., Lincoln, A., Ballantyne, A. O., & Trauner, D. A. (2001). “Motor” impairment in Asperger syndrome: Evidence for a deficit in propioception. Journal of Developmental & Behavioral Pediatrics, 22(2), 92–101. http://dx.doi.org/10.1097/00004703-200104000-00002
-----The Importance of Morphology and Montaging in EEG
Buzsáki, G. (2006). Rhythms of the brain. New York, NY: Oxford University Press.
Buzsáki, G., & Draguhn, A. (2004). Neuronal oscillations in cortical networks. Science, 304(5679), 1926–1929. http://dx.doi.org/10.1126/science.1099745
Sporns, O., Tononi, G., & Edelman, G. M. (2000a). Connectivity and complexity: The relationship between neuroanatomy and brain dynamics. Neural Networks, 13(8–9), 909–922. http://dx.doi.org/10.1016/S0893-6080(00)00053-8
Sporns, O., Tononi, G., & Edelman, G. M. (2000b). Theoretical neuroanatomy: Relating anatomical and functional connectivity in graphs and cortical connection matrices. Cerebral Cortex, 10(2), 127–141. http://dx.doi.org/10.1093/cercor/10.2.127
Stern, J. M. (2005). Atlas of EEG patterns (2nd ed.). Philadelphia, PA: Lippincott Williams & Wilkins.
-----The Impact of Using Effective Connectivity Measures (Granger Causality) in Guiding Neurofeedback
Coben, R., Middlebrooks, M., Lightstone, H. & Corbell, M. (in press). Four- channel multivariate coherence training: Development and evidence in support of a new form of neurofeedback. Frontiers in Neural Technology.
Coben, R., Mohammad-Rezazadeh, I., & Cannon, R. L. (2014). Using quantitative and analytic EEG methods in the understanding of connectivity in autism spectrum disorders: A theory of mixed over-and under-connectivity. Frontiers in Human Neuroscience, 8, 45. http://dx.doi.org/10.3389/fnhum.2014.00045
Friston, K., Moran, R., & Seth, A. K. (2013). Analysing connectivity with Granger causality and dynamic causal modelling. Current Opinion in Neurobiology, 23(2), 172–178. http://dx.doi.org/10.1016/j.conb.2012.11.010
Kuś, R., Kamiński, M., & Blinowska, K. J. (2004). Determination of EEG activity propagation: Pair-wise versus multichannel estimate. IEEE Transactions on Biomedical Engineering, 51(9), 1501–1510. http://dx.doi.org/10.1109/TBME.2004.827929
-----Trends in Scientific Research Reflect and Predict the Clinical Relevance of (EEG) Biomarkers
Arns, M., Conners, C. K., & Kraemer, H. C. (2013). A decade of EEG theta/beta research in ADHD: A meta-analysis. Journal of Attentional Disorders, 17(5), 374–383. http://dx.doi.org/10.1177/1087054712460087
Pavlenko, V. B., Chernyi, S. V., & Goubkina, D. G. (2009). EEG correlates of anxiety and emotional stability in adult healthy subjects. Neurophysiology, 41(5), 337–345. http://dx.doi.org/10.1007/s11062-010-9111-2
Perlis, M. L., Merica, H., Smith, M. T., & Giles, D. E. (2001). Beta EEG activity and insomnia. Sleep Medicine Reviews, 5(5), 363–374. http://dx.doi.org/10.1053/smrv.2001.0151
-----Understanding the Mysterious 40 Hz Brain System for Attention, Learning, and Feeling Good
Cowan, J., & Albers, S. (2017). Manual for the Peak Brain Happiness Trainer. Goshen, KY: Peak Achievement Training.
Cowan, J. D., & Starman, J. D. (2011). Understanding and activating your brain’s pleasure systems. Retrieved from http://www.peakachievement.com/UABC.pdf
Knutson, B., Fong, G. W., Bennett, S. M., Adams, C. M., & Hommer, D. (2003). A region of mesial prefrontal cortex tracks monetarily rewarding outcomes: Characterization with rapid event-related fMRI. NeuroImage, 18(2), 263–272. http://dx.doi.org/10.1016/S1053-8119(02)00057-5
Llinás, R., Ribary, U., Contreras, D., & Pedroarena, C. (1998). The neuronal basis for consciousness. Philosophical Transactions of the Royal Society of London, Series B, Biological Sciences, 353(1377), 1841–1849. http://dx.doi.org/10.1098/rstb.1998.0336
Rubik, B. (2011). Neurofeedback-enhanced gamma brainwaves from the prefrontal cortical region of meditators and non-meditators and associated subjective experiences. Journal of Alternative and Complementary Medicine, 17(2), 109–115. http://dx.doi.org/10.1089/acm.2009.0191
Sokhadze, E. (2012). Peak performance training 7sing prefrontal EEG biofeedback. Biofeedback, 40(1), 7–15. http://dx.doi.org /10.5298/1081-5937-39.3.4
Sokhadze, E., & Daniels, R. (2016). Effects of prefrontal 40 Hz-centered EEG band neurofeedback on emotional state and cognitive functions in adolescents. Adolescent Psychiatry, 6(4), 116-129.
Sokhadze, E., Stewart, C., El-Baz, A., Ramaswamy, R., Hollifield, M., & Tasman, A. (2009). Induced EEG gamma oscillations in response to drug- and stress-related cues in cocaine addicts and patients with dual diagnosis. Journal of Neurotherapy, 13(4), 270–271.
Wang, Y., Sokhadze, E. M., El-Baz, A. S., Li, X., Sears, L., Casanova, M. F., & Tasman, A. (2016). Relative power of specific EEG bands and their ratios during neurofeedback training in children with autism spectrum disorder. Frontiers in Human Neuroscience, 9, 723. http://dx.doi.org/10.3389/fnhum.2015.00723
-----Gender Differences in Quantitative EEG Volumetric Analysis Shortly After Sport Concussion Injury in High School Athletes
Cantu, R. C. (2010). The role of concussion history and gender in recovery from soccer-related concussion. Yearbook of Sports Medicine, 2010, 29–30. http://dx.doi.org/10.1016/s0162-0908(10)79666-5
Hamson-Utley, J. J., Schulte, S., Fowler, L., Glodowski, C., Scharmann, S., Podlog, L., … Ashley, A. (2013, July). Concussion-related neuroproteins: A comparison of gender differences in extreme sports. Poster presented at the 122nd Annual Conference of the American Psychological Association, Honolulu, HI. http://dx.doi.org/10.1037/e620352013-001
Ims, P. D., & Kerasidis, H. (2018, April). Re-training the injured brain: A case series in sLORETA neurofeedback as an acute concussion intervention in youth. Poster session presented at the 49th Annual Association for Applied Psychophysiology and Biofeedback Conference, Orlando, FL.
Kerasidis, H., & Ims, P. D. (2017, July). sLORETA quantitative EEG analysis demonstrates persistent EEG changes beyond clinical recovery from sport concussion in high school athletes: A volumetric study. Poster session presented at 4th Annual American Academy of Neurology Sports Concussion Conference, Jacksonville, FL.
Miyashita, T. L., Diakogeorgiou, E., & VanderVegt, C. (2016). Gender differences in concussion reporting among high school athletes. Sports Health, 8(4), 359–363. http://dx.doi.org/10.1177/1941738116651856
Mollayeva, T., El-Khechen-Richandi, G., & Colantonio, A. (2018). Sex & gender considerations in concussion research. Concussion, 3(1). http://dx.doi.org/10.2217/cnc-2017-0015
Tanveer, S., Zecavati, N., Delasobera, E. B., & Oyegbile, T. O. (2017). Gender differences in concussion and postinjury cognitive rindings in an older and younger pediatric population. Pediatric Neurology, 70, 44–49. http://dx.doi.org /10.1016/j.pediatrneurol.2017.02.001
-----Social, Spiritual, Psychological, and Physiological Predictors of Well-being of Military Veterans: A Pilot Study of a Viable, Holistic, and Predictive Model of Well-being
Avey, J. B. (2014). The left side of psychological capital: New evidence on the antecedents of PsyCap. Journal of Leadership & Organizational Studies, 21(2), 141–149. http://dx.doi.org/10.1177/1548051813515516
Del Brutto, O. H., Mera, R. M., Del Brutto, V. J., Maestre, G. E., Gardener, H., Zambrano, M., & Wright, C. B. (2015). Influence of depression, anxiety and stress on cognitive performance in community-dwelling older adults living in rural Ecuador: Results of the Atahualpa Project. Geriatrics & Gerontology International, 15(4), 508–514. http://dx.doi.org/10.1111/ggi.12305
Faraji, M., & Begzadeh, S. (2017). The relationship between organizational commitment and spiritual intelligence with job performance in physical education staff in east Azerbaijan province. International Journal of Management, Accounting & Economics, 4(5), 565–577.
Fatisson, J., Oswald, V., & Lalonde, F. (2016). Influence diagram of physiological and environmental factors affecting heart rate variability: An extended literature overview. Heart International, 11(1), e32–e40. http://dx.doi.org/10.5301/heartint.5000232
Howell, R. T., Kern, M. L., & Lyubomirsky, S. (2007). Health benefits: Meta-analytically determining the impact of well-being on objective health outcomes. Health Psychology Review, 1(1), 83–136. http://dx.doi.org/10.1080/17437190701492486
Kent, P., Hawthorne, G., Kjaer, P., Manniche, C., & Albert, H. (2015). A Danish version of the Friendship Scale: Translation and validation of a brief measure of social isolation. Social Indicators Research, 120(1), 181–195. http://dx.doi.org/10.1007/s11205-014-0576-z
King, D. B., & DeCicco, T. L. (2009). A viable model and self-report measure of spiritual intelligence. The International Journal of Transpersonal Studies, 28(1), 68–85.
Lathan, C., Spira, J. L., Bleiberg, J., Vice, J., & Tsao, J. W. (2013). Defense Automated Neurobehavioral Assessment (DANA)—Psychometric properties of a new field-deployable neurocognitive assessment tool. Military Medicine, 178(4), 365–371. http://dx.doi.org/10.7205/MILMED-D-12-00438
Lorenz, T., Beer, C., Pütz, J., & Heinitz, K. (2016). Measuring psychological capital: Construction and validation of the Compound PsyCap Scale (CPC-12). PloS ONE, 11(4), 1–17. http://dx.doi.org/10.1371/journal.pone.0152892
Luthans, F., Youssef, C. M., Sweetman, D. S., & Harms, P. D. (2013). Meeting the Leadership Challenge of Employee Well-Being Through Relationship PsyCap and Health PsyCap. Journal of Leadership & Organizational Studies, 20(1), 118–133. http://dx.doi.org/10.1177/1548051812465893
Thatcher, R. W., North, D. M., Biver, C. J. & Zhou, L. (2017). Brain Function Index. Retrieved from http://www.appliedneuroscience.com/Brain_Function_Index.pdf
-----Altered States NeuroMeditation: Current Approaches, Preliminary Findings, and Future Applications
Carhart-Harris, R. L., Erritzoe, D., Williams, T., Stone, J. M., Reed, L. J., Colasanti, A., … Nutt, D. J., (2012). Neural correlates of the psychedelic state as determined by fMRI studies with psilocybin. Proceedings of the National Academy of Sciences (PNAS), 109(6), 2138–2143. http://dx.doi.org/10.1073/pnas.1119598109
Crane, R. (2007). Infinite potential: A neurofeedback pioneer looks back and ahead. In T. H. M. Press (Ed.), Handbook of neurofeedback: Dynamics and clinical applications: Haworth series in neurotherapy (pp. 3–21). Binghamton, NY: CYC Press.
Tarrant, J. (2017). Neuromeditation: An introduction and overview. In T. F. Collura & J. A. Frederick (Eds.), Clinician’s companion to QEEG and neurofeedback (annotated and with an introduction by J. Kiffer). New York, NY: Taylor & Francis.
Trudeau, D. L. (2016). Experiences with alpha theta: Its origins in studies of meditation. In A. Martins-Mourao, & C. Kerson (Eds.), Alpha-theta training in the 21st century: A handbook for clinicians and researchers (pp. 36-64). Murfreesboro, TN: Foundation for Neurofeedback and Neuromodulation Research (FNNR).
-----Cognitive and Psychophysiological Test Operations as Assessment Tool for Neurofeedback Clinicians: A Pilot Study on Its Preliminary Normative Data and Validity
Brauer-Boone, K., Pontón, M. O., Gorsuch, R. L., González, J. J., & Miller, B. L. (1998). Factor analysis of tour measures of prefrontal lobe functioning. Archives of Clinical Neuropsychology, 13, 585–595.
De la Torre, G. G. (2002). El modelo funcional de atención en neuropsicología. Revista de Psicología General y Aplicada, 55(1), 113–121.
Fan, J., McCandliss, B. D., Fossella, J., Flombaum, J. I., & Posner, M. I. (2005). The activation of attentional networks. NeuroImage, 26(2), 471–479. http://dx.doi.org/10.1016/j.neuroimage.2005.02.004
Fan, J., McCandliss, B. D., Sommer, T., Raz, M., & Posner, M. I. (2002). Testing the efficiency and independence of attentional networks. Journal of Cognitive Neuroscience, 14(3), 340–347. http://dx.doi.org/10.1162/089892902317361886
Pineda, D. A., Merchán, V., Rosselli, M., & Ardila, A. (2000). Estructura factorial de la función ejecutiva en estudiantes universitarios jóvenes = Factor structure of the executive function in young university students. Revista de Neurología, 31(12), 1112–1118.
Posner, M. I., & Dehaene, S. (1994). Attentional networks. Trends in Neurosciences, 17(2), 75–79.
Spikman, J., Kiers, H. A. L., Deelman, B. G., & van Zomeren, A. H. (2001). Construct validity of concepts of attention in healthy controls and patients with CHI. Brain and Cognition, 47(3), 446–460. http://dx.doi.org/10.1006/brcg.2001.1320
-----Training Blood Flow: nHEG Utilization for Specific qEEG Phenotypes in ASD
Chabot, R. J., Coben, R., Hirshberg, L. & Cantor, D. S. (2015). QEEG and VARETA based Neurophysiological Indices of Brain Dysfunction in Attention Deficit and Autistic Spectrum Disorder. Austin Journal of Autism & Related Disabilities, 1(2), 1007.
Dias, A. M., Van Deusen, A. M., Oda, E., & Bonfim, M. R. (2012) Clinical efficacy of a new automated hemoencephalographic neurofeedback protocol. Spanish Journal of Psychology, 15(3), 930–941.
Edelson, S. B., & Cantor, D. S. (1998). Autism: Xenobiotic influence. Toxicology and Industrial Health, 14(6), 799–811. http://dx.doi.org/10.1177%2F074823379801400603
Kouijzer, M. E. J., van Schie, H. T., Gerrits, B. J. L., Buitelaar, J. K., & de Moor, J. M. H. (2013). Is EEG-biofeedback an Effective Treatment in Autism
Spectrum Disorders? A Randomized Controlled Trial. Applied Psychophysiology and Biofeedback, 38(1), 17–28. http://dx.doi.org/10.1007/s10484-012-9204-3
Wilcox, J., Tsuang, M. T., Ledger, E., Algeo, J., & Schnurr, T. (2002). Brain perfusion in autism varies with age. Neuropsychobiology. 46, 13–16. http://dx.doi.org/10.1159/000063570
-----Applied Innovation in Clinical Practice — Let's Go Beyond Neurofeedback
Busscher, B., Spinhoven, P., van Gerwen, L. J., & de Geus, E. J. C. (2013). Anxiety sensitivity moderates the relationship of changes in physiological arousal with flight anxiety during in vivo exposure therapy. Behaviour Research and Therapy, 51(2), 98–105. http://dx.doi.org/10.1016/j.brat.2012.10.009
Ehrlich, I., Humeau, Y., Grenier, F., Ciocchi, S., Herry, C., & Lüthi, A. (2009). Amygdala inhibitory circuits and the control of fear memory. Neuron, 62(6), 757–771. http://dx.doi.org/10.1016/j.neuron.2009.05.026
Feusner, J. D., Madsen, S., Moody, T. D., Bohon, C., Hembacher, E., Bookheimer, S. Y., & Bystritsky, A. (2012). Effects of cranial electrotherapy stimulation on resting state brain activity. Brain and Behavior, 2(3), 211–220. http://dx.doi.org/10.1002/brb3.45
Harper, M. L., Rasolkhani-Kalhorn, T., & Drozd, J. F. (2009). On the neural basis of EMDR therapy: Insights from qEEG studies. Traumatology, 15(2), 81–95. http://dx.doi.org/10.1177/1534765609338498
Lande, R. G., & Gragnani, C. (2013). Efficacy of cranial electric stimulation for the treatment of insomnia: A randomized pilot study. Complementary Therapies in Medicine, 21(1), 8–13. http://dx.doi.org/10.1016/j.ctim.2012.11.007
Pavlenko, V. B., Chernyi, S. V., & Goubkina, D. G. (2009). EEG correlates of anxiety and emotional stability in adult healthy subjects. Neurophysiology, 41(5), 337–345. http://dx.doi.org/10.1007/s11062-010-9111-2
Serin, A., Hageman, N. S., & Kade, E. (2018). The therapeutic effect of bilateral alternating stimulation tactile form technology on the stress response. Journal of Biotechnology and Biomedical Science, 1(2), 42–47. http://dx.doi.org /10.14302/issn.2576-6694.jbbs-18-1887
-----Multivariate Coherence Training for Developmental Trauma
Armes, C. A., & Coben, R. (2017, September). Impact of developmental trauma on brain function and connectivity. Presented at the International Society of Neurofeedback and Research 25th Annual Conference, Foxwoods, CT.
Cook, A., Spinazzola, J., Ford, J., Lanktree, C., Blaustein, M., Cloitre, M., … van der Kolk, B. (2005). Complex trauma in children and adolescents. Psychiatric Annals, 35(5), 390–398.
Felitti, V. J., Anda, R. F., Nordenberg, D., Williamson, D. F., Spitz, A. M., Edwards, V., ... Marks, J. S. (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The Adverse Childhood Experiences (ACE) Study. American Journal of Preventive Medicine, 14(4), 245–258. http://dx.doi.org/10.1016/S0749-3797(98)00017-8
Huang-Storms, L., Bodenhamer-Davis, E., Davis, R., & Dunn, J. (2006). QEEG-guided neurofeedback for children with histories of abuse and neglect: Neurodevelopmental rationale and pilot study. Journal of Neurotherapy, 10(4), 3–16. http://dx.doi.org/10.1300/J184v10n04_02
Teicher, M. H., Andersen, S. L., Polcari, A., Anderson, C. M., Navalta, C. P., & Kim, D. M. (2003). The neurobiological consequences of early stress and childhood maltreatment. Neuroscience & Biobehavioral Reviews, 27(1), 33–44. http://dx.doi.org/10.1016/S0149-7634(03)00007-1
van der Kolk, B. A., Hodgdon, H., Gapen, M., Musicaro, R., Suvak, M. K., Hamlin, E., & Spinazzola, J. (2016). A randomized controlled study of neurofeedback for chronic PTSD. PLoS ONE 11(12), e0166752. http://dx.doi.org/10.1371/journal.pone.0166752
-----The Effect of Infraslow Frequency Neurofeedback on Quantitative Electroencephalogram and Autonomic Nervous System Function in Adults with Anxiety and Related Diseases
Bazhenov, M., & Timofeev, I. (2006). Thalamocortical oscilations. Scholarpedia, 1(6), 1319. http://dx.doi.org/10.4249/scholarpedia.1319
Camp, R. M., Remus, J. L., Kalburgi, S. N., Porterfield, V. M., & Johnson, J. D. (2012). Fear conditioning can contribute to behavioral changes observed in a repeated stress model. Behavioural Brain Research, 233(2), 536–544. http://dx.doi.org/10.1016/j.bbr.2012.05.040
Collura, T. F. (2014). Technical foundations of neurofeedback. New York, NY: Routlege/Taylor & Francis.
Goldstein, D. S., Bentho, O., Park, M. Y., & Sharabi, Y. (2011). Low-frequency power of heart rate variability is not a measure of cardiac sympathetic tone but may be a measure of modulation of cardiac autonomic outflows by baroreflexes. Experimental Physiology, 96(12), 1255–1261. http://dx.doi.org/10.1113/expphysiol.2010.056259
Hallman, D., & Lyskov, E. (2012). Autonomic regulation in musculoskeletal pain. Retrieved on July 15, 2017, from Intech Open Science: https://www.intechopen.com/books/pain-in-perspective/autonomic-regulation-in-musculosceletal-pain
Lőrincz, M., Geall, F., Bao, Y., Crunelli, V., & Hughes, S. W. (2009). ATP-dependent infra-slow (< 0.1 Hz) oscillations in thalamic networks. PLoS One, 4(2), e4447. http://dx.doi.org/10.1371/journal.pone.0004447
Peper E, Harvey, R., Lin, I., Tylova, H., & Moss, D. (2007). Is there more to blood volume pulse than heart rate variability, respiratory sinus arrhythmia, and cardiorespiratory synchrony? Biofeedback, 35(2), 54–61.
Smith, M. L., Collura, T. F., Ferrera, J., & de Vries, J. (2014). Infra-slow fluctuation training in clinical practice: A technical history. NeuroRegulation, 1(2), 187–207. http://dx.doi.org/10.15540/nr.1.2.187
-----The Human Compassion Circuit
Buhle, J. T., Silvers, J. A., Wager, T. D., Lopez, R., Onyemekwu, C., Kober, H., … Ochsner, K. N. (2014). Cognitive reappraisal of emotion: A meta-analysis of human neuroimaging studies. Cerebral Cortex, 24(11), 2981–2990. http://dx.doi.org/10.1093/cercor/bht154
de Waal, F. (2009). The age of empathy. New York, NY: Three Rivers Press.
Fehse, K., Silveira, S., Elvers, K., & Blautzik, J. (2015). Compassion, guilt and innocence: An fMRI study of responses to victims who are responsible for their fate. Social Neuroscience, 10(3), 243–252. http://dx.doi.org/10.1080/17470919.2014.980587
Gallese, V., Keysers, C., & Rizzolatti, G. (2004). A unifying view of the basis of social cognition. Trends in Cognitive Sciences, 8(9), 396–403. http://dx.doi.org/10.1016/j.tics.2004.07.002
Goetz, J. L., Keltner, D., & Simon-Thomas, E. (2010). Compassion: An evolutionary analysis and empirical review. Psychological Bulletin, 136(3), 351–374. http://dx.doi.org/10.1037/a0018807
Kédia, G., Berthoz, S., Wessa, M., Hilton, D., & Martinot, J.-L. (2008). An agent harms a victim: A functional magnetic resonance imaging study on specific moral emotions. Journal of Cognitive Neuroscience, 20(10), 1788–1798. http://dx.doi.org/10.1162/jocn.2008.20070
Lindquist, K. A., Wager, T. D., Kober, H., Bliss-Moreau, E., & Barrett, L. F. (2012). The brain basis of emotion: A meta-analytic review. Behavioral and Brain Sciences, 35(3), 121–143. http://dx.doi.org/10.1017/S0140525X11000446
Lutz, A., Greischar, L. L., Rawlings, N. B., Ricard, M., & Davidson, R. J. (2004). Long-term meditators self-induce high-amplitude gamma synchrony during mental practice. Proceedings of the National Academy of Sciences, 101(46), 16369–16373. http://dx.doi.org/10.1073/pnas.0407401101
Ochsner, K. N., Ray, R. D., Cooper, J. C., Robertson, E. R., Chopra, S. Gabrieli, J. D. E, & Gross, J. J. (2004). For better or for worse: Neural systems supporting the cognitive down- and up-regulation of negative emotion. NeuroImage, 23(2), 483–499. http://dx.doi.org/10.1016/j.neuroimage.2004.06.030
Ochsner, K. N., Ray, R. R., Hughes, B., McRae, K., Cooper, J. C., Weber, J., … Gross, J. J. (2009). Bottom-up and top-down processes in emotion generation: Common and distinct neural mechanisms. Psychological Science, 20(11), 1322–1331. http://dx.doi.org/10.1111/j.1467-9280.2009.02459.x
Phan, K. L., Wager, T., Taylor, S. F., & Liberzon, I. (2002). Functional neuroanatomy of emotion: A meta-analysis of emotion activation studies in PET and fMRI. NeuroImage, 16(2), 331–348. http://dx.doi.org/10.1006/nimg.2002.1087
Porges, S. W. (2003). The Polyvagal Theory: Phylogenetic contributions to social behavior. Physiology and Behavior, 79, 503–513. http://dx.doi.org/10.1016/S0031-9384(03)00156-2
Premack, D., & Woodruff, G. (1978). Does the chimpanzee have a theory of mind? Behavioral and Brain Sciences, 1(4), 515–526. http://dx.doi.org/10.1017/S0140525X00076512
Singer, T. (2006). The neuronal basis and ontogeny of empathy and mind reading: Review of literature and implications for future research. Neuroscience and Behavioral Reviews, 30(6), 855–863. http://dx.doi.org/10.1016/j.neubiorev.2006.06.011
Singer, T., Critchley, H. D., & Preuschoff, K. (2009). A common role of insula in feelings, empathy and uncertainty. Trends in Cognitive Sciences, 13(8), 334–340. http://dx.doi.org/10.1016/j.tics.2009.05.001
-----Neurofeedback: An Effective Treatment for Symptoms of Posttraumatic Stress Disorder in Veterans
McReynolds, C. J., Bell, J., & Lincourt, T. M. (2017). Neurofeedback: A noninvasive treatment for symptoms of posttraumatic stress disorder in veterans. NeuroRegulation, 4(3–4), 114–124. http://dx.doi.org/10.15540/nr.4.3-4.114
-----The Frontal Alpha Asymmetry and Neurofeedback in Patients with Major Depressive Disorder
Baehr, E., Rosenfeld, J. P., & Baehr, R. (2001). Clinical use of an alpha asymmetry neurofeedback protocol in the treatment of mood disorders: Follow-up study one to five years post therapy. Journal of Neurotherapy, 4(4), 11–18. http://dx.doi.org/10.1300/J184v04n04_03
Cheon, E.-J., Koo, B.-H., & Choi, J.-H. (2016). The efficacy of neurofeedback in patients with major depressive disorder: An open labeled prospective study. Applied Psychophysiology and Biofeedback, 41(1), 103–110. http://dx.doi.org/10.1007/s10484-015-9315-8
Choi, S. W., Chi, S. E., Chung, S. Y., Kim, J. W., Ahn, C. Y., & Kim, H. T. (2011). Is alpha wave neurofeedback effective with randomized clinical trials in depression? A pilot study. Neuropsychobiology, 63(1), 43–51. http://dx.doi.org/10.1159/000322290
Davidson, R. J. (1998). Anterior electrophysiological asymmetries, emotion, and depression: Conceptual and methodological conundrums. Psychophysiology, 35(5), 607–614.
Wang, S.-Y., Lin, I.-M., Peper, E., Chen, Y.-T., Tang, T.-C., Yeh, Y.-C., ... Chu, C.-C. (2016). The efficacy of neurofeedback among patients with major depressive disorder: Preliminary study. NeuroRegulation, 3(3), 127–134. http://dx.doi.org /10.15540/nr.3.3.127
-----A Real-time fMRI Neurofeedback for Mild to Severe Depression Compared to Frontal Alpha-asymmetry Neurofeedback and Cognitive–Behavioral Therapy
Hamilton, J. P., Glover, G. H., Bagarinao, E., Chang, C., Mackey, S., Sacchet, M. D., & Gotlib, I. H. (2016). Effects of salience-network-node neurofeedback training on affective biases in major depressive disorder. Psychiatry Research, 249, 91–96. http://dx.doi.org/10.1016/j.pscychresns.2016.01.016
Johnston, S., Linden, D. E. J., Healy, D., Goebel, R., Habes, I., & Boehm, S. G. (2011). Upregulation of emotion areas through neurofeedback with a focus on positive mood. Cognitive Affective, & Behavioral Neuroscience, 11(1), 44–51. http://dx.doi.org/10.3758/s13415-010-0010-1
Linden, D. E. J., Habes, I., Johnston, S. J., Linden, S., Tatineni, R., Subramanian, L., … Goebel, R. (2012). Real-time self-regulation of emotion networks in patients with depression. PLoS One, 7(6), 38115. http://dx.doi.org/10.1371/journal.pone.0038115
Young, K. D., Siegle, G. J., Zotev, V., Phillips, R., Misaki, M., Yuan, H., … Bodurka, J. (2017). Randomized clinical trial of real-time fMRI amygdala neurofeedback for major depressive disorder: Effects on symptoms and autobiographical memory recall. The American Journal of Psychiatry, 174(8), 748–755. http://dx.doi.org/10.1176/appi.ajp.2017.16060637
-----Preliminary Evidence for Stress-Reducing Effects of Bilateral Alternating Stimulation Tactile (BLAST) Following Significant Quantitative Electroencephalography (qEEG) Reduction in Beta Wave Activity
Busscher, B., Spinhoven, P., van Gerwen, L. J., & de Geus, E. J. C. (2013). Anxiety sensitivity moderates the relationship of changes in physiological arousal with flight anxiety during in vivo exposure therapy. Behaviour Research and Therapy, 51(2), 98–105. http://dx.doi.org/10.1016/j.brat.2012.10.009
Ehrlich, I., Humeau, Y., Grenier, F., Ciocchi, S., Herry, C., & Lüthi, A. (2009). Amygdala inhibitory circuits and the control of fear memory. Neuron, 62(6), 757¬–771. http://dx.doi.org/10.1016/j.neuron.2009.05.026
Harper, M. L., Rasolkhani-Kalhorn, T., & Drozd, J. F. (2009). On the neural basis of EMDR therapy: Insights from qEEG studies. Traumatology, 15(2), 81–95. http://dx.doi.org/10.1177/1534765609338498
Pavlenko, V. B., Chernyi, S. V., & Goubkina, D. G. (2009). EEG correlates of anxiety and emotional stability in adult healthy subjects. Neurophysiology, 41(5), 337–345. http://dx.doi.org/10.1007/s11062-010-9111-2
Serin, A., Hageman, N. S., & Kade, E. (2018). The therapeutic effect of bilateral alternating stimulation tactile form technology on the stress response. Journal of Biotechnology and Biomedical Science, 1(2), 42¬–47. http://dx.doi.org/10.14302/issn.2576-6694.jbbs-18-1887
-----Event-related Potential Study of Illusory Figure Processing Deficits in Children with Autism Spectrum Disorder
Baruth, J. M., Casanova, M., Sears, L., & Sokhadze, E. (2010). Early-stage visual processing abnormalities in high-functioning autism spectrum disorder (ASD). Translational Neuroscience, 1(2), 177–187. http://dx.doi.org/10.2478/v10134-010-0024-9
Bomba, M. D., & Pang, E. W. (2004). Cortical auditory evoked potentials in autism: A review. International Journal of Psychophysiology, 53(3), 161–169. http://dx.doi.org/10.1016/j.ijpsycho.2004.04.001
Cui, T., Wang, P. P., Liu, S., & Zhang, X. (2017). P300 amplitude and latency in autism spectrum disorder: A meta-analysis. European Child & Adolescent Psychiatry, 26(2),177–190. http://dx.doi.org/10.1007/s00787-016-0880-z
Kanizsa, G. (1976). Subjective contours. Scientific American, 234(4), 48–52.
Kemner, C., van der Gaag, R. J., Verbaten, M., & van Engeland, H. (1999). ERP differences among subtypes of pervasive developmental disorders. Biological Psychiatry, 46(6), 781–789. http://dx.doi.org/10.1016/S0006-3223(99)00003-7
Sokhadze, E., Baruth, J., El-Baz, A., Horrell, T., Sokhadze, G., Carroll, T., … Casanova, M. F. (2010). Impaired error monitoring and correction function in autism. Journal of Neurotherapy, 14(2), 79–95. http://dx.doi.org/10.1080/10874201003771561
Sokhadze, E. M., Baruth, J. M., Sears, L., Sokhadze, G. E., El-Baz, A. S., Williams, E. L., … Casanova, M. F. (2012). Event-related potential study of attention regulation during illusory figure categorization task in ADHD, autism spectrum disorder, and typical children. Journal of Neurotherapy, 16(1), 12–31. http://dx.doi.org/10.1080/10874208.2012.650119
Sokhadze, E., Baruth, J., Tasman, A., Sears, L., Mathai, G., El-Baz, A. & Casanova, M. F. (2009). Event-related potential study of novelty processing abnormalities in autism. Applied Psychophysiology and Biofeedback, 34(1), 37–51. https://doi.org/10.1007/s10484-009-9074-5
Townsend, J., Westerfield, M., Leaver, E., Makeig, S., Jung, T.-P., Pierce, K., & Courchesne, E. (2001). Event-related brain response abnormalities in autism: Evidence for impaired cerebello-frontal spatial attention networks. Cognitive Brain Research, 11(1), 127–145. http://dx.doi.org/10.1016/S0926-6410(00)00072-0
-----Effects rTMS-based Neuromodulation Dosage on Event-related Potentials and Evoked and Induced Gamma Oscillations in Children with Autism Spectrum Disorder
Casanova, M. F., Buxhoeveden, D., & Gomez, J. (2003). Disruption in the inhibitory architecture of the cell minicolumn: Implications for autism. The Neuroscientist, 9(6), 496–507. http://dx.doi.org/10.1177/1073858403253552
Rubenstein, J. L. R., & Merzenich, M. M. (2003). Model of autism: Increased ratio of excitation/inhibition in key neural systems. Genes, Brain and Behavior, 2(5), 255–267. http://dx.doi.org/10.1034/j.1601-183X.2003.00037.x
Sokhadze, E., Baruth, J., Tasman, A., Mansoor, M., Ramaswamy, R., Sears, L., … Casanova, M. F. (2010). Low-frequency repetitive transcranial magnetic stimulation (rTMS) affects event-related potential measures of novelty processing in autism. Applied Psychophysiology and Biofeedback, 35(2), 147–161. http://dx.doi.org/10.1007/s10484-009-9121-2
Sokhadze, E. M., El-Baz, A., Baruth, J., Mathai, G., Sears, L., & Casanova, M. F. (2009). Effects of low-frequency repetitive transcranial magnetic stimulation (rTMS) on gamma frequency oscillations and event-related potentials during processing of illusory figures in autism. Journal of Autism and Developmental Disorders, 39(4), 619–634. http://dx.doi.org/10.1007/s10803-008-0662-7
Sokhadze, E. M., El-Baz, A. S., Tasman, A., Sears, L. L., Wang, Y., Lamina, E. V., & Casanova, M. F. (2014). Neuromodulation integrating rTMS and neurofeedback for the treatment of autism spectrum disorder: An exploratory study. Applied Psychophysiology and Biofeedback, 39(3–4), 237–257. http://dx.doi.org/10.1007/s10484-014-9264-7
Uzunova, G., Pallanti, S., & Hollander, E. (2016). Excitatory/inhibitory imbalance in autism spectrum disorders: Implications for interventions and therapeutics. The World Journal Biological Psychiatry, 17(3), 174–186. http://dx.doi.org/10.3109/15622975.2015.1085597
-----Using Neurofeedback to Lower Anxiety Symptoms: A Follow-up Study
Dreis, S. M., Gouger, A. M., Perez, E. G., Russo, G. M., Fitzsimmons, M. A., & Jones, M. S. (2015). Using neurofeedback to lower anxiety symptoms using individualized qEEG protocols: A pilot study. NeuroRegulation, 2(3), 137–148. http://dx.doi.org/10.15540/nr.2.3.137
Lu, Y., Wang, C., Su, L., Ma, Z., Li, S., & Fan, Y. (2017). Effects of neurofeedback on panic disorder patients’ anxiety. NeuroQuantology, 15(3). http://dx.doi.org/10.14704/nq.2017.15.3.1083
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. http://dx.doi.org/10.1016/j.brat.2017.02.002
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).