Proceedings of the 2025 ISNR Annual Conference: Keynote and Plenary Presentations

Authors

  • International Society for Neuroregulation and Research (ISNR)

DOI:

https://doi.org/10.15540/nr.12.4.286

Keywords:

ISNR Annual Conference, Neurofeedback, EEG Biofeedback, qEEG

Abstract

Selected Abstracts of Conference Keynote and Plenary Presentations at the 2025 International Society for Neuroregulation and Research (ISNR) 33rd Annual Conference, Niagara Falls, New York, USA

References

References for Proceedings of the 2025 ISNR Annual Conference: Keynote and Plenary Presentations

---The Neuroscience of Deep Brain Reorienting (DBR): Healing of the Shock at the Core

Corrigan, F. M., & Christie-Sands, J. (2020). An innate brainstem self-other system involving orienting, affective responding, and polyvalent relational seeking: Some clinical implications for a “Deep Brain Reorienting” trauma psychotherapy approach. Medical Hypotheses, 136, Article 109502. https://doi.org/10.1016/j.mehy.2019.109502

Corrigan, F. M., Young, H., & Christie-Sands, J. (2025). Deep brain reorienting: understanding the neuroscience of trauma, attachment wounding, and DBR psychotherapy. Routledge, London.

Kearney, B. E., Corrigan, F. M., Frewen, P. A., Nevill, S., Harricharan, S., Andrews, K., Jetly, R., McKinnon, M. C., & Lanius, R. A. (2023). A randomized controlled trial of Deep Brain Reorienting: A neuroscientifically guided treatment for post-traumatic stress disorder. European Journal of Psychotraumatology, 14(2), Article 2240691. https://doi.org/10.1080/20008066.2023.2240691

---Endogenous Neuromodulation at Infra-Low Frequencies

Bazzana, F., Finzi, S., Di Fini, G., & Veglia, F. (2022). Infra-Low Frequency neurofeedback: A systematic mixed studies review. Frontiers in Human Neuroscience, 16, Article 920659. https://doi.org/10.3389/fnhum.2022.920659

Carlson, J., Ross, G. W., Tyrrell, C., Fiame, B., Nunokawa, C., Siriwardhana, C., & Schaper, K. (2025). Infra-low frequency neurofeedback impact on post-concussive symptoms of headache, insomnia and attention disorder: Results of a randomized control trial. Explore (New York, N.Y.), 21(2), Article 103137. https://doi.org/10.1016/j.explore.2025.103137

Dobrushina, O. R., Vlasova, R. M., Rumshiskaya, A. D., Litvinova, L. D., Mershina, E. A., Sinitsyn, V. E., & Pechenkova, E. V. (2020). Modulation of intrinsic brain connectivity by implicit electroencephalographic. Frontiers in Human Neuroscience, 14, Article 192. https://doi.org/10.3389/fnhum.2020.00192

Gerge, A. (2020). A multifaceted case-vignette integrating neurofeedback and EMDR in the treatment of complex PTSD. European Journal of Trauma & Dissociation, 4(3), Article 100157. https://doi.org/10.1016/j.ejtd.2020.100157

Grin-Yatsenko, V. A., Kara, O., Evdokimov, S. A., Gregory, M., Othmer, S., & Kropotov, J. D. (2020). Infra-low frequency neurofeedback modulates infra-slow oscillations of brain potentials: A controlled study. Journal of Biomedical Engineering Research, 4(104), 1–11. https://doi.org/10.17303/jber.2020.4.104

Grin-Yatsenko, V. A., Othmer, S., Ponomarev, V. A., Evdokimov, S., Konoplev, Y., & Kropotov, J. D. (2018). Infra-low frequency neurofeedback in depression: Three case studies. NeuroRegulation, 5(1), 30–42. https://doi.org/10.15540/nr.5.1.30

Grin-Yatsenko, V. A., Ponomarev, V. A., & Kropotov, J. D. (2023). The changes of the infra-slow EEG fluctuations of the brain potentials under influence of infra-low frequency neurofeedback. Journal of Evolutionary Biochemistry and Physiology, 59, 831–840. https://doi.org/10.1134/S002209302303016X

Kirk, H. W., & Dahl, M. G. (2022). Infra low frequency neurofeedback training for trauma recovery: A case report. Frontiers in Human Neuroscience, 16, Article 905823. https://doi.org/10.3389/fnhum.2022.905823

Schmidt, C., Laugesen, H. (2023). Infra-low frequency neurofeedback training in Dravet Syndrome: A case study. Epilepsy & Behavior Reports, 22, Article 100606 https://doi.org/10.1016/j.ebr.2023.100606

Spreyermann, R. (2022). Infra-low frequency neurofeedback for PTSD: A therapist’s perspective. Frontiers in Human Neuroscience, 16, Article 893830. https://doi.org/10.3389/fnhum.2022.893830

---A Multidisciplinary Approach to Neurodevelopmental Delay

Aldharman, S. S., Al-Jabr, K. H., Alharbi, Y. S., Alnajar, N. K., Alkhanani, J. J., Alghamdi, A., Abdellatif, R. A., Allouzi, A., Almallah, A. M., & Jamil, S. F. (2023). Implications of early diagnosis and intervention in the management of neurodevelopmental delay (NDD) in children: A systematic review and meta-analysis. Cureus, 15(5), Article e38745. https://doi.org/10.7759/cureus.38745

Arns, M. (2012). EEG-based personalized medicine in ADHD: Individual alpha peak frequency as an endophenotype associated with nonresponse. Journal of Neurotherapy, 16(2), 123–141. https://doi.org/10.1080/10874208.2012.677664

Bailey, T. (2014). Diagnosing and treating developmental disorders with qEEG and neurotherapy. In D. S. Cantor & J. R. Evans (Eds.), Clinical neurotherapy (pp. 321–355). https://doi.org/10.1016/b978-0-12-396988-0.00013-1

Cantor, D. S., & Chabot, R. (2009b). QEEG studies in the assessment and treatment of childhood disorders. Clinical EEG and Neuroscience, 40(2), 113–121. https://doi.org/10.1177/155005940904000209

Filippi, C. G., Uluğ, A. M., Deck, M. D. F., Zimmerman, R. D., & Heier, L. A. (2002, May 1). Developmental delay in children: Assessment with proton MR spectroscopy. American Journal of Neuroradiology, 23(5), 882–888.

Johnstone, J., Gunkelman, J., & Lunt, J. (2005). Clinical database development: Characterization of EEG phenotypes. Clinical EEG and Neuroscience, 36(2), 99–107. https://doi.org/10.1177/155005940503600209

Martello, J. M. (2023). Persistent primitive reflex and developmental delay in the school-aged child. The Journal for Nurse Practitioners, 19(10), Article 104767. https://doi.org/10.1016/j.nurpra.2023.104767

Melillo, R., Leisman, G., Mualem, R., Ornai, A., & Carmeli, E. (2020). Persistent childhood primitive reflex reduction effects on cognitive, sensorimotor, and academic performance in ADHD. Frontiers in Public Health, 8, Article 431835. https://doi.org/10.3389/fpubh.2020.431835

---Virtual Neurofeedback: Implementation and Examination of Effectiveness

Economides, M., Lehrer, P., Ranta, K., Nazander, A., Hilgert, O., Raevanuori, A., Gevirtz, R., Khazan, I., & Forman-Hoffman, V. L. (2020). Feasibility and efficacy of the addition of heart rate variability biofeedback to a remote digital health intervention for depression. Applied Psychophysiology and Biofeedback, 45(2), 75–86. https://doi.org/10.1007/s10484-020-09458-z

Philippe, T. J., Sikder, N., Jackson, A., Koblanski, M. E., Liow, E., Pilarinos, A., & Vasarhelyi, K. (2022). Digital health interventions for delivery of mental health care: Systematic and comprehensive meta-review. JMIR Mental Health, 9(5), Article e35159. https://doi.org/10.2196/35159

Sarkheil, P., Chechko, N., Veselinović, T., Marx, G., & Neuner, I. (2021). Telepsychiatry: The remote care that unifies. The European Journal of Psychiatry, 35(1), 64–65. https://doi.org/10.1016/j.ejpsy.2020.08.004

Schaefer, M., Iskander, J., Tams, S., & Butz, C. (2021). Offering biofeedback assisted relaxation training in a virtual world: Considerations and future directions. Clinical Practice in Pediatric Psychology, 9(4), 405–411. https://doi.org/10.1037/cpp0000391

Thompson, L., & Thompson, M. (1998). Neurofeedback combined with training in metacognitive strategies: Effectiveness in students with ADD. Applied Psychophysiology and Biofeedback, 23(4), 243–263. https://doi.org/10.1023/a:1022213731956

Thompson, L., Thompson, M., & Reid, A. (2010). Neurofeedback outcomes in clients with Asperger's syndrome. Applied Psychophysiology and Biofeedback, 35(1), 63–81. https://doi.org/10.1007/s10484-009-9120-3

---The Stress Phenotyping Framework: A Multidisciplinary Biobehavioral Approach for Assessing and Therapeutically Targeting Maladaptive Stress Physiology

Fisher, J. (2019). Sensorimotor psychotherapy in the treatment of trauma. Practice Innovations, 4(3), 156–165. https://doi.org/10.1037/pri0000096

Gilgoff, R., Mengelkoch, S., Elbers, J., Kotz, K., Radin, A., Pasumarthi, I., Murthy, R., Sindher, S., Burke Harris, N., & Slavich, G. M. (2024). The stress phenotyping framework: A multidisciplinary biobehavioral approach for assessing and therapeutically targeting maladaptive stress physiology. Stress, 27(1), Article 2327333. https://doi.org/10.1080/10253890.2024.2327333

Gilgoff, R., Schwartz, T., Owen, M., Bhushan, D., & Burke Harris, N. (2022). Opportunities to treat toxic stress. Pediatrics, 151(1), Article e2021055591. https://doi.org/10.1542/peds.2021-055591

Kearney, B. E., & Lanius, R. A. (2022). The brain-body disconnect: A somatic sensory basis for trauma-related disorders. Frontiers in Neuroscience, 16, Article 1015749. https://doi.org/10.3389/fnins.2022.1015749

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), Article 27313. https://doi.org/10.3402/ejpt.v6.27313

Teicher, M. H., & Samson, J. A. (2016). Annual research review: Enduring neurobiological effects of childhood abuse and neglect. Journal of Child Psychology and Psychiatry, and Allied Disciplines, 57(3), 241–266. https://doi.org/10.1111/jcpp.12507

---Clinical Impact of Infra-Low Frequency Neurofeedback on Combat Veterans With Concussion

Agimi, Y., Hai, T., Gano, A., Stuessi, K., Gold, J., Kaufman, R., & McKinney, G. (2024). Clinical trajectories of comorbidity associated with military-sustained mild traumatic brain injury: Pre- and post-injury. The Journal of Head Trauma Rehabilitation, 39(6), E564–E575. https://doi.org/10.1097/HTR.0000000000000934

Arina, G. A., Dobrushina, O. R., Shvetsova, E. T., Osina, E. D., Meshkov, G. A., Aziatskaya, G. A., Trofimova, A. K., Efremova, I. N., Martunov, S. E., & Nikolaeva, V. V. (2022). Infra-low frequency neurofeedback in tension-type headache: A cross-over sham-controlled study. Frontiers in Human Neuroscience, 16, Article 891323. https://doi.org/10.3389/fnhum.2022.891323

Carlson, J., & Ross, G. W. (2021). Neurofeedback impact on chronic headache, sleep, and attention disorders experienced by veterans with mild traumatic brain injury: A pilot study. Applied Psychophysiology & Biofeedback, 49(1), 2–9. https://doi.org/10.5298/1081-5937-49.01.01

Carlson, J., Ross, G. W., Tyrrell, C., Fiame, B., Nunokawa, C., Siriwardhana, C., and Schaper, K. (2025). Infra-low frequency neurofeedback impact on post-concussive symptoms of headache, insomnia and attention disorder: Results of a randomized control trial. Explore, 21(2), Article 103137, https://doi.org/10.1016/j.explore.2025.103137

Dobrushina, O., Arina, G., Osina, E., & Aziatskaya, G. (2017). Clinical and psychological confirmation of stabilizing effect of neurofeedback in migraine. European Psychiatry, 41(S1), S253–S253. https://doi.org/10.1016/j.eurpsy.2017.02.045

Grin-Yatsenko, V. A., & Kropotov, J. (2020). Effect of infra-low frequency (ILF) neurofeedback on the functional state of the brain in healthy and depressed individuals. In H. W. Kirk (Ed.), Restoring the brain (2nd ed.). Routledge.

Grin-Yatsenko, V. A., Othmer, S., Ponomarev, V., Evdokimov, S., Konoplev, Y., & Kropotov, J. (2018). Infra-low frequency neurofeedback in depression: Three case studies. NeuroRegulation, 5(1), 30–42. https://doi.org/10.15540/nr.5.1.30

Kirk, H. W., & Dahl, M. G. (2022). Infra low frequency neurofeedback training for trauma recovery: A case report. Frontiers in Human Neuroscience, 16, Article 905823. https://doi.org/10.3389/fnhum.2022.905823

Legarda, S. B., Lahti, C. E., McDermott, D., & Michas-Martin, A. (2022). Use of novel concussion protocol with infralow frequency neuromodulation demonstrates significant treatment response in patients with persistent postconcussion symptoms, a retrospective study. Frontiers in Human Neuroscience, 16, Article 894758. https://doi.org/10.3389/fnhum.2022.894758

McMahon, D. (2020). Neurofeedback in an integrative medical practice. In H. W. Kirk, Restoring the brain (2nd ed., pp. 112–133). Routledge.

Shapero, E. J., & Prager, J. P. (2020). ILF neurofeedback and alpha-theta training in a multidisciplinary chronic pain program. In H. W. Kirk (Ed.), Restoring the brain (2nd ed., chapter 11). Routlege. https://doi.org/10.4324/9780429275760

---Using Machine Learning to Enhance the EEG Screening Review by Prescreening the EEG

Cavallo, F., Brubaker, H., & Brown, T. (2021). Utilizing individual z-scores to measure efficacy of the World’s first augmented reality glasses for autism: A single case study. Journal of Social Sciences Research, 54–71.

Collura, T., Cantor, D., Chartier, D., Crago, R., Hartzoge, A., Hurd, M., Kerson, C., Lubar, J., Nash, J., Prichep, L. S., Surmeli, T., Thompson, T., Tracy, M., & Turner, R. (2025) International QEEG certification board guideline minimum technical requirements for performing clinical quantitative electroencephalography. Clinical EEG Neuroscience, 56(5), 391–399. https://doi.org/10.1177/15500594241308654

Collura, T., & Tarrant, J. (2020). Principles and statistics of individualized live and static z-scores. NeuroRegulation, 7(1), 45–56. https://doi.org/10.15540/nr.7.1.45

Keizer, A. W. (2021). Standardization and personalized medicine using quantitative EEG in clinical settings. Clinical EEG Neuroscience, 52(2), 82–89. https://doi.org/10.1177/1550059419874945

Livint Popa, L., Dragos, H., Pantelemon, C., Verisezan-Rosu, O., & Strilciuc, S. (2020). The role of quantitative EEG in the diagnosis of neuropsychiatric disorders. Journal of Medicine and Life, 13(1), 8–15. https://doi.org/10.25122/jml-2019-0085

Mahajan, R., & Morshed, B. I. (2014). Unsupervised eye blink artifact denoising of EEG data with modified multiscale sample entropy, kurtosis, and wavelet-ICA. IEEE Journal of Biomedical and Health Informatics, 19(1), 158–165. https://doi.org/10.1109/JBHI.2014.2333010

Mateos, D. M., Guevara Erra, R., Wennberg, R., & Perez-Velazquez, J. L. (2018). Measures of entropy and complexity in altered states of consciousness. Cognitive Neurodynamics, 12(1), 73–84. https://doi.org/10.1007/s11571-017-9459-8

Piloto, C. (2022). Machine learning vs artificial intelligence: What’s the difference? | MIT Professional Education. MIT Professional Education. https://professionalprograms.mit.edu/blog/technology/machine-learning-vs-artificial-intelligence/

Rejer, I., & Górski, P. (2015) Benefits of ICA in the case of a few channel EEG. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), (pp. 7434–7437). Milan, Italy. https://doi.org/10.1109/EMBC.2015.7320110

Wallace, B., & Collura, T. F. (1993). Imaging ability and visual processing of EEG waveforms. Bulletin of Psychometric Society, 31, 4–6. https://doi.org/10.3758/BF03334123

---Individualized Z-Scores for Assessment and Training

Collura, T. F. (1990). Real-time filtering for the estimation of steadystate visual evoked potentials. IEEE Transactions on Biomedical Engineering, 37(6), 650–652. https://doi.org/10.1109/10.55670

Collura, T. F. (2014). Technical foundations of neurofeedback. Routledge.

Collura, T. F. (2014, Spring). Specifying and developing references for live z-score neurofeedback. NeuroConnections, 9(1), 26–39. Retrieved from https://docs.wixstatic.com/ugd/cba323_b824c922625941808b2d633bc63f3df7.pdf

Collura, T. F., Thatcher, R. W., Smith, M. L., Lambos, W. A., & Stark, C. R. (2009). EEG biofeedback training using live z-scores and a normative database. In J. R. Evans, T. H. Budzynski, H. K. Budzynski., & A. Arbanal (Eds.), Introduction to quantitative EEG and neurofeedback: Advanced theory and applications (2nd ed., pp. 103–142). Elsevier.

Host-Mandel, A., & Handel, P. (2000). Effects of sampling and quantization on single-tone frequency estimation. IEEE Transactions on Signal Processing, 48(3), 650–662. https://doi.org/10.1109/78.824661

Kerson, C., deBeus, R., Lightstone, H., Arnold, L. E., Barterian, J., Pan, X., & Monastra, V. J. (2020). EEG theta/beta ratio calculations differ between various EEG neurofeedback and assessment software packages: Clinical interpretation. Clinical EEG and Neuroscience, 51(2), 114–120. https://doi.org/10.1177/1550059419888320

Messick, S. (1998). Test validity: A matter of consequence. Social Indicators Research, 45(1–3), 35–44. https://doi.org/10.1023/A:1006964925094

Siever, D., & Collura, T. (2017). Audio-visual entrainment: Physiological mechanisms and clinical outcomes. In J. R. Evans & R. P. Turner (Eds.), Rhythmic stimulation in neuromodulation (pp. 51–95). Elsevier.

Social Science Statistics (2019). T test calculator for 2 dependent means. https://www.socscistatistics.com/tests/ttestdependent/default.aspx

Thatcher, R. W. (2008, April). Z-score EEG biofeedback: Conceptual foundations. NeuroConnections, 9–11. Retrieved from https://docs.wixstatic.com/ugd/cba323_426c6449511f48968c49c4ee94fa0c7e.pdf

---Applying Progressive Return to Activity for Concussions to Neurotherapies

Bailie, J. M., Remigio-Baker, R. A., Cole, W. R., McCulloch, K. L., Ettenhofer, M. L., West, T., Ahrens, A., Sargent, P., Cecchini, A., Malik, S., Mullins, L., Stuessi, K., Qashu, F. M., & Gregory, E. (2019). Use of the progressive return to activity guidelines may expedite symptom resolution after concussion for active duty military. The American Journal of Sports Medicine, 47(14), 3505–3513. https://doi.org/10.1177/0363546519883259

Losoi, H., Silverberg, N. D., Wäljas, M., Turunen, S., Rosti-Otajärvi, E., Helminen, M., Luoto, T. M., Julkunen, J., Öhman, J., & Iverson, G. L. (2016). Recovery from mild traumatic brain injury in previously healthy adults. Journal of Neurotrauma, 33(8), 766–776. https://doi.org/10.1089/neu.2015.4070

Patricios, J. S., Schneider, K. J., Dvorak, J., Ahmed, O. H., Blauwet, C., Cantu, R. C., Davis, G. A., Echemendia, R. J., Makdissi, M., McNamee, M., Broglio, S., Emery, C. A., Feddermann-Demont, N., Fuller, G. W., Giza, C. C., Guskiewicz, K. M., Hainline, B., Iverson, G. L., Kutcher, J. S., … Meeuwisse, W. (2023). Consensus statement on concussion in sport: The 6th International Conference on Concussion in Sport-Amsterdam, October 2022. British Journal of Sports Medicine, 57(11), 695–711. https://doi.org/10.1136/bjsports-2023-106898

---Psychopathology: Through the Triple Network Lens

Das, A., & Menon, V. (2024). Electrophysiological dynamics of salience, default mode, and frontoparietal networks during episodic memory formation and recall: A multi-experiment iEEG replication. bioRxiv. https://doi.org/10.1101/2024.02.28.582593

De Ridder, D., Smith, M. L., & Adhia, D. (2023). Autonomic nervous system and the triple network: An evolutionary perspective with clinical implications. In D. R. Chartier, M. B. Dellinger, J. R. Evans, & H. K. Budzynski (Eds.), Introduction to quantitative EEG and neurofeedback (3rd ed., pp. 63–77). Academic Press.

De Ridder, D., Vanneste, S., Smith, M., & Adhia, D. (2022). Pain and the triple network model. Frontiers in Neurology, 13, Article 757241. https://doi.org/10.3389/fneur.2022.757241

Hutchinson-Wong, N., Glue, P., Adhia, D., & de Ridder, D. (2025). How does depressive cognition develop? A state-dependent network model of predictive processing. Psychological Review, 132(2), 442–469. https://doi.org/10.1037/rev0000512

Menon, B. (2019). Towards a new model of — The triple network, psychopathology and the structure of the mind. Medical Hypotheses, 133, Article 109385. https://doi.org/10.1016/j.mehy.2019.109385

Menon, V. (2011). Large-scale brain networks and psychopathology: A unifying triple network model. Trends in Cognitive Sciences, 15(10), 483–506. https://doi.org/10.1016/j.tics.2011.08.003

Sha, Z., Wager, T. D., Mechelli, A., & He, Y. (2019). Common dysfunction of large-scale neurocognitive networks across psychiatric disorders. Biological Psychiatry, 85(5), 379–388. https://doi.org/10.1016/j.biopsych.2018.11.011

Zhang, W., Kaldewaij, R., Hashemi, M. M., Koch, S. B. J., Smit, A., van Ast, V. A., Beckmann, C. F. Klumpers, F., & Roelofs, K. (2022). Acute-stress-induced change in salience network coupling prospectively predicts post-trauma symptom development. Translational Psychiatry, 12(1), Article 63. https://doi.org/10.1038/s41398-022-01798-0

Zhu, X., Suarez-Jimenez, B., Lazarov, A., Such, S., Marohasy, C., Small, S. S., Wager, T. D., Lindquist, M. A., Lissek, S., & Neria, Y. (2022). Sequential fear generalization and network connectivity in trauma exposed humans with and without psychopathology. Communications Biology, 5(1), Article 1275. https://doi.org/10.1038/s42003-022-04228-5

Downloads

Published

2025-12-19

Issue

Section

Proceedings