Proceedings of the 2025 ISNR Annual Conference: Poster Presentations

Authors

  • International Society for Neuroregulation and Research (ISNR)

DOI:

https://doi.org/10.15540/nr.12.4.295

Keywords:

ISNR, neurofeedback, eeg biofeedback, conference abstracts

Abstract

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

References

Proceedings of the 2025 ISNR Annual Conference: Poster Presentations

---Review of Dipole Source Localization Using Electrophysiological Source Localization and Importance of Accurate Positioning of EEG Sensors

Dalal, S. S., Rampp, S., Willomitzer, F., & Ettl, S. (2014). Consequences of EEG electrode position error on ultimate beamformer source reconstruction performance. Frontiers in Neuroscience, 8, Article 42. https://doi.org/10.3389/fnins.2014.00042

Györfi, O., Ip, C.-T., Justesen, A. B., Gam-Jensen, M. L., Rømer, C., Fabricius, M., Pinborg, L. H., & Beniczky, S. (2022). Accuracy of high-density EEG electrode position measurement using an optical scanner compared with the photogrammetry method. Clinical neurophysiology Practice, 7, 135–138. https://doi.org/10.1016/j.cnp.2022.04.002

Kaneko, N., Yokoyama, M., Nakazawa, K., & Yokoyama, H. (2024). Accurate digitization of EEG electrode locations by electromagnetic tracking system: The proposed head rotation method and comparison against optical system. MethodsX, 12, Article 102766. https://doi.org/10.1016/j.mex.2024.102766

Khosla, D., Don, M., & Kwong, B. (1999). Spatial mislocalization of EEG electrodes—Effects on accuracy of dipole estimation. Clinical Neurophysiology, 110(2), 261–271. https://doi.org/10.1016/s0013-4694(98)00121-7

Shirazi, S. Y., & Huang, H. J. (2019). More reliable EEG electrode digitizing methods can reduce source estimation uncertainty, but current methods already accurately identify Brodmann areas. Frontiers In Neuroscience, 13, Article 1159. https://doi.org/10.3389/fnins.2019.01159

Singh, J., Ebersole, J. S., & Brinkmann, B. H. (2022). From theory to practical fundamentals of electroencephalographic source imaging in localizing the epileptogenic zone. Epilepsia, 63(10), 2476–2490. https://doi.org/10.1111/epi.17361

Taberna, G. A., Marino, M., Ganzetti, M., & Mantini, D. (2019). Spatial localization of EEG electrodes using 3D scanning. Journal of Neural Engineering, 16(2), Article 026020. https://doi.org/10.1088/1741-2552/aafdd1

Van Hoey, G., Vanrumste, B., D'Havé, M., Van de Walle, R., Lemahieu, I., & Boon, P. (2000). Influence of measurement noise and electrode mislocalisation on EEG dipole-source localisation. Medical and Biological Engineering and Computing, 38(3), 287–296. https://doi.org/10.1007/BF02347049

Wang, Y., & Gotman, J. (2001). The influence of electrode location errors on EEG dipole source localization with a realistic head model. Clinical Neurophysiology, 112(9), 1777–1780. https://doi.org/10.1016/s1388-2457(01)00594-6

---Review of Stereoelectroencephalography (sEEG) Data Analysis Methods in Epilepsy

Bullmore, E., & Sporns, O. (2009). Complex brain networks: Graph theoretical analysis of structural and functional systems. Nature reviews. Nature Reviews Neuroscience, 10(3), 186–198. https://doi.org/10.1038/nrn2575

Caune, V. (2018). Brain localization using SEEG recording [Université de Lorraine]. Hal Theses. https://theses.hal.science/tel-01685079

Chowdhury, F. A., Silva, R., Whatley, B., & Walker, M. C. (2021). Localization in focal epilepsy: A practical guide. Practical Neurology, 21(6), 481–491. https://doi.org/10.1136/practneurol-2019-002341

David, O., Blauwblomme, T., Job, A.-S., Chabardès, S., Hoffmann, D., Minotti, L., & Kahane, P. (2011). Imaging the seizure onset zone with stereo-electroencephalography. Brain, 134(10), 2898–2911. https://doi.org/10.1093/brain/awr238

Isnard, J., Taussig, D., Bartolomei, F., Bourdillon, P., Catenoix, H., Chassoux, F., Chipaux, M., Clémenceau, S., Colnat-Coulbois, S., Denuelle, M., Derrey, S., Devaux, B., Dorfmüller, G., Gilard, V., Guenot, M., Job-Chapron, A.-S., Landré, E., Lebas, A., Maillard, L., … Sauleau, P. (2018). French guidelines on stereoelectroencephalography (SEEG), Neurophysiologie Clinique, 48(1), 5–13. https://doi.org/10.1016/j.neucli.2017.11.005

Miller, K. J., & Fine, A. L. (2022). Decision-making in stereotactic epilepsy surgery. Epilepsia, 63(11), 2782–2801. https://doi.org/10.1111/epi.17381

Mito, R., Pedersen, M., Pardoe, H., Parker, D., Smith, R. E., Cameron, J., Scheffer, I. E., Berkovic, S. F., Vaughan, D. N., & Jackson, G. D. (2023). Exploring individual fixel-based white matter abnormalities in epilepsy. Brain Communications, 6(1), Article fcad352. https://doi.org/10.1093/braincomms/fcad352

Parvizi, J., & Kastner, S. (2018). Promises and limitations of human intracranial electroencephalography. Nature Neuroscience, 21(4), 474–483. https://doi.org/10.1038/s41593-018-0108-2

Paulo, D. L., Wills, K. E., Johnson, G. W., Gonzalez, H. F. J., Rolston, J. D., Naftel, R. P., Reddy, S. B., Morgan, V. L., Kang, H., Williams Roberson, S., Narasimhan, S., & Englot, D. J. (2022). SEEG functional connectivity measures to identify epileptogenic zones: Stability, medication influence, and recording condition. Neurology, 98(20), e2060–e2072. https://doi.org/10.1212/WNL.0000000000200386

Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. NeuroImage, 52(3), 1059–1069. https://doi.org/10.1016/j.neuroimage.2009.10.003

---Bridging Relational-Cultural Theory and QEEG: Toward a Neuroaffirming Model of Connection

Avent Harris, J. R., Haskins, N., Parker, J., & Lee, A. (2023). Womanist theology and relational cultural theory: Counseling religious black women. Journal of Creativity in Mental Health, 18(4), 458–476. https://doi.org/10.1080/15401383.2021.1999359

Beeson, E. T., & Field, T. A. (2017). Neurocounseling: A new section of the journal of mental health counseling. Journal of Mental Health Counseling, 39(1), 71–83. https://doi.org/10.17744/mehc.39.1.06

Fingelkurts, A., & Fingelkurts, A. (2022). Quantitative electroencephalogram (qEEG) as a natrual and non-invasive windo into loving brain and mind in the functional continuum of healthy and pathological conditions. Applied Sciences, 12(9), Article 9560. https://doi.org/10.3390/app12199560

Gregory, J. C., Romero, D., & Jones, M. (2023). Exploring single- case research design with individualized anxiety-based neurofeedback protocols and session data. NeuroRegulation, 10(3), 159–169. https://doi.org/10.15540/nr.10.3.159

Hafeez, A., Azhar Ali, S. S., Mumtaz, W., Moinuddin, M., Adil, S. H., & Al-Saggaf, U. M. (2019). Investigating neurofeedback protocols for stress mitigation: A comparative analysis of different stimulus contents. IEEE Access, 7, 141021–141035. https://doi.org/10.1109/access.2019.2944202

Hershberger, J. M. (2021). A relational-cultural theory approach to work with survivors of sex trafficking. Journal of Creativity in Mental Health, 16(4), 456–466. https://doi.org/10.1080/15401383.2020.1790457

Lenz, S. (2016). Relational-cultural theory: Fostering the growth of a paradigm through empirical research. Journal of Counseling and Development, 94(4), 415–428. https://doi.org/10.1002/jcad.12100

Miller, J. B. (1976). Toward a new psychology of women. Beacon Press.

Sapiro, B., & Quiroz, S. R. (2022). Authenticity, vulnerability, and shame in peer relationships among marginalized youth living with mood and anxiety disorders. Journal of Child and Family Studies, 31(11), 3192–3208. https://doi.org/10.1007/s10826-022-02358-2

Spears, J. R., Romero, D. E., Robertson, D. L., & Prasath, P. R. (2025). Development of neurofeedback training competencies for counselors: A delphi study. Counselor Education and Supervision, 63(4), 364–378. https://doi.org/10.1002/ceas.12318

---EEG-Based Source Localization (ESL) of Epilepsy Spikes Onset Zone Using Interictal Activity in Pediatric Case Series

Cox, B. C., Danoun, O. A., Lundstrom, B. N., Lagerlund, T. D., Wong-Kisiel, L. C., & Brinkmann, B. H. (2021). EEG source imaging concordance with intracranial EEG and epileptologist review in focal epilepsy. Brain Communications, 3(4), Article fcab278. https://doi.org/10.1093/braincomms/fcab278

Ebersole J. S. (2000). Sublobar localization of temporal neocortical epileptogenic foci by source modeling. Advances in Neurology, 84, 353–363.

Eom T. H. (2023). Electroencephalography source localization. Clinical and Experimental Pediatrics, 66(5), 201–209. https://doi.org/10.3345/cep.2022.00962

Gavvala, J. R., & Ebersole, J. S. (2024). EEG source imaging. Journal of Clinical Neurophysiology, 41(1), 1. https://doi.org/10.1097/WNP.0000000000001046

Lantz, G., Spinelli, L., Seeck, M., de Peralta Menendez, R. G., Sottas, C. C., & Michel, C. M. (2003). Propagation of interictal epileptiform activity can lead to erroneous source localizations: A 128-channel EEG mapping study. Journal of Clinical Neurophysiology, 20(5), 311–319. https://doi.org/10.1097/00004691-200309000-00003

Lee B. L. (2023). Understanding the usefulness of electroencephalography source localization. Clinical and Experimental Pediatrics, 66(5), 210–211. https://doi.org/10.3345/cep.2022.01480

Verhellen, E., & Boon, P. (2007). EEG source localization of the epileptogenic focus in patients with refractory temporal lobe epilepsy, dipole modelling revisited. Acta Neurologica Belgica, 107(3), 71–77.

---Phase Lag and Neural Synchrony in Early Brain Development: Insights From QEEG Brain Metrics in Children With Autism

Bressler, S. L., & Menon, V. (2010). Large-scale cortical networks and attention. Trends in Cognitive Sciences, 14(6), 277–290. https://doi.org/10.1016/j.tics.2010.04.004

Kayhan, E., Meyer, M., O’Reilly, J. X., Hunnius, S., & Bekkering, H. (2019). Nine-month-old infants update their predictive models of a changing environment. Developmental Cognitive Neuroscience, 38, Article 100680. https://doi.org/10.1016/j.dcn.2019.100680

Kunze, I. M., Hunold, A., Haueisen, J., Jirsa, V., & Spiegler, A. (2016). Transcranial direct current stimulation changes resting state functional connectivity: A large-scale brain network modeling study. NeuroImage, 140, 174–187. https://doi.org/10.1016/j.neuroimage.2016.02.015

Orekhova, E. V., Elsabbagh, M., Jones, E. J. H., Dawson, G., Charman, T., Johnson, M. H., & The BASIS Team. (2014). EEG hyper-connectivity in high-risk infants is associated with later autism. Journal of Neurodevelopmental Disorders, 6, Article 40. https://doi.org/10.1186/1866-1955-6-40

Stam, C. J., Tewarie, P., Van Dellen, E., van Straaten, E. C. W., Hillebrand, A., & Van Mieghem, P. (2014). The trees and the forest: Characterization of complex brain networks with minimum spanning trees. International Journal of Psychophysiology, 92(3), 129–138. https://doi.org/10.1016/j.ijpsycho.2014.04.001

Uhlhaas, P. J., & Singer, W. (2006). Neural synchrony in brain disorders: Relevance for cognitive dysfunctions and pathophysiology. Neuron, 52(1), 155–168. https://doi.org/10.1016/j.neuron.2006.09.020

---Neuroregulation in Virtual Reality

Berger, A. M., & Davelaar, E. J. (2018). Frontal alpha oscillations and attentional control: A virtual reality neurofeedback study. Neuroscience, 378, 189–197. https://doi.org/10.1016/j.neuroscience.2017.06.007

Berger, L. M., Wood, G., & Kober, S. E. (2022). Effects of virtual reality-based feedback on neurofeedback training performance—A sham-controlled study. Frontiers in Human Neuroscience, 16, Article 952261. https://doi.org/10.3389/fnhum.2022.952261

Botrel, L., Kreilinger, A., Müller, M., Pfeiffer, M., Scheu, V., Vowinkel, N., Zechner, R., Käthner, I., & Kübler, A. (2025). The influence of time and visualization on neurofeedback-guided parietal alpha downregulation and sense of presence in virtual reality. Frontiers in Neuroscience, 19, Article 1476264. https://doi.org/10.3389/fnins.2025.1476264

Cannard, C., Delorme, A., & Wahbeh, H. (2024). Identifying HRV and EEG correlates of well-being using ultra-short, portable, and low-cost measurements. bioRxiv. https://doi.org/10.1101/2024.02.23.581823

Frewen, P., Mistry, D., Zhu, J., Kielt, T., Wekerle, C., Lanius, R. A., & Jetly, R. (2020). Proof of concept of an eclectic, integrative therapeutic approach to mental health and well-being through virtual reality technology. Frontiers in Psychology, 11, Article 858. https://doi.org/10.3389/fpsyg.2020.00858

Kober, S. E., Wood, G., & Berger, L. M. (2024). Controlling virtual reality with brain signals: State of the art of using VR-based feedback in neurofeedback applications. Applied Psychophysiology and Biofeedback. https://doi.org/10.1007/s10484-024-09677-8

Salminen, M., Järvelä, S., Kosunen, I., Ruonala, A., Hamari, J., Ravaja, N., & Jacucci, G. (2023). Meditating in a neurofeedback virtual reality: Effects on sense of presence, meditation depth and brain oscillations. Behaviour and Information Technology, 43(12), 2750–2764. https://doi.org/10.1080/0144929X.2023.2258231

---The Efficacy of Neurofeedback for Anxiety

Yang, X., Fang, Y., Chen, H., Zhang, T., Yin, X., Man, J., Yang, L., & Lu, M. (2021). Global, regional and national burden of anxiety disorders from 1990 to 2019: Results from the Global Burden of Disease Study 2019. Epidemiology and Psychiatric Sciences, 30, Article e36. https://doi.org/10.1017/S2045796021000275

---Neurofeedback for Arachnophobia a Randomized Controlled Clinical Trial of the Anxiety Neural Network and of Spider Phobia: Preliminary Results

dos Santos, N. A., Andrade, S. M., & Calvo, B. F. (2013). Detection of spatial frequency in brain-damaged patients: influence of hemispheric asymmetries and hemineglect. Frontiers in Human Neuroscience, 7, Article 92. https://doi.org/10.3389/fnhum.2013.00092

Granado, L. C., Ranvaud, R., & Peláez, J. R. (2007). A spiderless arachnophobia therapy: Comparison between placebo and treatment groups and six-month follow-up study. Neural Plasticity, 2007(1), Article 010241. https://doi.org/10.1155/2007/10241

Hinze, J., Röder, A., Menzie, N., Müller, U., Domschke, K., Riemenschneider, M., & Noll-Hussong, M. (2021). Spider phobia: Neural networks informing diagnosis and (virtual/augmented reality-based) cognitive behavioral psychotherapy—A narrative review. Frontiers in Psychiatry, 12, Article 704174. https://doi.org/10.3389/fpsyt.2021.704174

Price, J., & Budzynski, T. (2009). Anxiety, EEG patterns, and neurofeedback. In T. H. Budzynski, H. K. Budzynski, J. R. Evans, & A. Abarbanel (Eds.), Introduction to quantitative EEG and neurofeedback: Advanced theory and applications (2nd ed., pp. 453–472). https://doi.org/10.1016/B978-0-12-374534-7.00017-4

Schulte-Rüther, M., Markowitsch, H. J., Fink, G. R., & Piefke, M. (2007). Mirror neuron and theory of mind mechanisms involved in face-to-face interactions: A functional magnetic resonance imaging approach to empathy. Journal of Cognitive Neuroscience, 19(8), 1354–1372. https://doi.org/10.1162/jocn.2007.19.8.1354

---Toward a Universally Applicable Self-Report Measure of Interoception: Developing the Invariant MAIA-SF Across Health-Related Background Characteristics

Kline, R. B. (2024). How to evaluate local fit (residuals) in large structural equation models. International Journal of Psychology, 59(6), 1293–1306. https://doi.org/10.1002/ijop.13252

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2025-12-19

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