Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
505-02-001 / 271-01-053 ISMRM Abstract

Identifying network states linked to the therapeutic efficacy of deep brain stimulation for OCD

Primary: Brain Function and fMRI - fMRI & Neuromodulation
Secondary: Neuro - Neuromodulation
505-02-001 · Insights into Psychiatric Disorders and the Human Connectome · Wednesday, 13 May, 8:20 AM–10:10 AM · Ballroom West
271-01-053 · ISMRM AMPC Selected Posters · Sunday, 10 May, 7:00 AM–2:00 PM · Traditional Posters
Keywords: Effective Connectivity Dynamic Functional Connectivity FMRI and neuromodulation Obsessive and Compulsive Tendencies Co-activation Pattern
Accepted
David U Mikhael 1,2, Natalya Slepneva3, Starlette Khim3, Tenzin Norbu3, Philip A Starr4, Moses Lee3, Melanie A Morrison1,2
1Department of Radiology and Biomedical Imaging, University Of California, San Francisco (UCSF), United States of America
2UCSF-UC Berkeley Graduate Program in Bioengineering, United States of America
3Department of Psychiatry and Behavioral Sciences, University Of California, San Francisco (UCSF), United States of America
4Department of Neurological Surgery, University Of California, San Francisco (UCSF), United States of America
Presenting Author: David U Mikhael

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References

1. Mar-Barrutia, L. et al. Deep brain stimulation for obsessive-compulsive disorder: A systematic review of worldwide experience after 20 years. World J. Psychiatry 11, 659–680 (2021). doi:10.5498/wjp.v11.i9.659 [doi]
2. Denys, D. et al. Efficacy of Deep Brain Stimulation of the Ventral Anterior Limb of the Internal Capsule for Refractory Obsessive-Compulsive Disorder: A Clinical Cohort of 70 Patients. Am. J. Psychiatry 177, 265–271 (2020). doi:10.1176/appi.ajp.2019.19060656 [doi]
3. Slepneva, N. et al. Therapeutic DBS for OCD Suppresses the Default Mode Network. Hum. Brain Mapp. 45, e70106 (2024). doi:10.1002/hbm.70106 [doi]
4. Van Den Boom, B. J. G. et al. Unraveling the mechanisms of deep-brain stimulation of the internal capsule in a mouse model. Nat. Commun. 14, 5385 (2023). doi:10.1038/s41467-023-41026-x [doi]
5. Preti, M. G., Bolton, T. A. & Van De Ville, D. The dynamic functional connectome: State-of-the-art and perspectives. NeuroImage 160, 41–54 (2017). doi:10.1016/j.neuroimage.2016.12.061 [doi]
6. Liu, X., Chang, C. & Duyn, J. H. Decomposition of spontaneous brain activity into distinct fMRI co-activation patterns. Front. Syst. Neurosci. 7, (2013). doi:10.3389/fnsys.2013.00101 [doi]
7. Liu, X., Zhang, N., Chang, C. & Duyn, J. H. Co-activation patterns in resting-state fMRI signals. NeuroImage 180, 485–494 (2018). doi:10.1016/j.neuroimage.2018.01.041 [doi]
8. Zamani Esfahlani, F. et al. High-amplitude cofluctuations in cortical activity drive functional connectivity. Proc. Natl. Acad. Sci. 117, 28393–28401 (2020). doi:10.1073/pnas.2005531117 [doi]
9. Whitfield-Gabrieli, S. & Nieto-Castanon, A. Conn : A Functional Connectivity Toolbox for Correlated and Anticorrelated Brain Networks. Brain Connect. 2, 125–141 (2012). doi:10.1089/brain.2012.0073 [doi]
10. Zhang, Y. et al. Longitudinal atlas for normative human brain development and aging over the lifespan using quantitative susceptibility mapping. NeuroImage 171, 176–189 (2018). doi:10.1016/j.neuroimage.2018.01.008 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/505-02-001