Decoding Depression Severity From Intracranial Neural Activity

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dc.citation.firstpage445
dc.citation.issueNumber6
dc.citation.journalTitleBiological Psychiatry
dc.citation.lastpage453
dc.citation.volumeNumber94
dc.contributor.authorXiao, Jiayang
dc.contributor.authorProvenza, Nicole R.
dc.contributor.authorAsfouri, Joseph
dc.contributor.authorMyers, John
dc.contributor.authorMathura, Raissa K.
dc.contributor.authorMetzger, Brian
dc.contributor.authorAdkinson, Joshua A.
dc.contributor.authorAllawala, Anusha B.
dc.contributor.authorPirtle, Victoria
dc.contributor.authorOswalt, Denise
dc.contributor.authorShofty, Ben
dc.contributor.authorRobinson, Meghan E.
dc.contributor.authorMathew, Sanjay J.
dc.contributor.authorGoodman, Wayne K.
dc.contributor.authorPouratian, Nader
dc.contributor.authorSchrater, Paul R.
dc.contributor.authorPatel, Ankit B.
dc.contributor.authorTolias, Andreas S.
dc.contributor.authorBijanki, Kelly R.
dc.contributor.authorPitkow, Xaq
dc.contributor.authorSheth, Sameer A.
dc.date.accessioned2024-05-08T18:56:08Z
dc.date.available2024-05-08T18:56:08Z
dc.date.issued2023
dc.description.abstractBackground Disorders of mood and cognition are prevalent, disabling, and notoriously difficult to treat. Fueling this challenge in treatment is a significant gap in our understanding of their neurophysiological basis. Methods We recorded high-density neural activity from intracranial electrodes implanted in depression-relevant prefrontal cortical regions in 3 human subjects with severe depression. Neural recordings were labeled with depression severity scores across a wide dynamic range using an adaptive assessment that allowed sampling with a temporal frequency greater than that possible with typical rating scales. We modeled these data using regularized regression techniques with region selection to decode depression severity from the prefrontal recordings. Results Across prefrontal regions, we found that reduced depression severity is associated with decreased low-frequency neural activity and increased high-frequency activity. When constraining our model to decode using a single region, spectral changes in the anterior cingulate cortex best predicted depression severity in all 3 subjects. Relaxing this constraint revealed unique, individual-specific sets of spatiospectral features predictive of symptom severity, reflecting the heterogeneous nature of depression. Conclusions The ability to decode depression severity from neural activity increases our fundamental understanding of how depression manifests in the human brain and provides a target neural signature for personalized neuromodulation therapies.
dc.identifier.citationXiao, J., Provenza, N. R., Asfouri, J., Myers, J., Mathura, R. K., Metzger, B., Adkinson, J. A., Allawala, A. B., Pirtle, V., Oswalt, D., Shofty, B., Robinson, M. E., Mathew, S. J., Goodman, W. K., Pouratian, N., Schrater, P. R., Patel, A. B., Tolias, A. S., Bijanki, K. R., … Sheth, S. A. (2023). Decoding Depression Severity From Intracranial Neural Activity. Biological Psychiatry, 94(6), 445–453. https://doi.org/10.1016/j.biopsych.2023.01.020
dc.identifier.digital1-s20-S0006322323000483-main
dc.identifier.doihttps://doi.org/10.1016/j.biopsych.2023.01.020
dc.identifier.urihttps://hdl.handle.net/1911/115640
dc.language.isoeng
dc.publisherElsevier
dc.rightsExcept where otherwise noted, this work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND) license. Permission to reuse, publish, or reproduce the work beyond the terms of the license or beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleDecoding Depression Severity From Intracranial Neural Activity
dc.typeJournal article
dc.type.dcmiText
dc.type.publicationpublisher version
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