Decoding Depression Severity From Intracranial Neural Activity

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dc.citation.firstpage445en_US
dc.citation.issueNumber6en_US
dc.citation.journalTitleBiological Psychiatryen_US
dc.citation.lastpage453en_US
dc.citation.volumeNumber94en_US
dc.contributor.authorXiao, Jiayangen_US
dc.contributor.authorProvenza, Nicole R.en_US
dc.contributor.authorAsfouri, Josephen_US
dc.contributor.authorMyers, Johnen_US
dc.contributor.authorMathura, Raissa K.en_US
dc.contributor.authorMetzger, Brianen_US
dc.contributor.authorAdkinson, Joshua A.en_US
dc.contributor.authorAllawala, Anusha B.en_US
dc.contributor.authorPirtle, Victoriaen_US
dc.contributor.authorOswalt, Deniseen_US
dc.contributor.authorShofty, Benen_US
dc.contributor.authorRobinson, Meghan E.en_US
dc.contributor.authorMathew, Sanjay J.en_US
dc.contributor.authorGoodman, Wayne K.en_US
dc.contributor.authorPouratian, Naderen_US
dc.contributor.authorSchrater, Paul R.en_US
dc.contributor.authorPatel, Ankit B.en_US
dc.contributor.authorTolias, Andreas S.en_US
dc.contributor.authorBijanki, Kelly R.en_US
dc.contributor.authorPitkow, Xaqen_US
dc.contributor.authorSheth, Sameer A.en_US
dc.date.accessioned2024-05-08T18:56:08Zen_US
dc.date.available2024-05-08T18:56:08Zen_US
dc.date.issued2023en_US
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.en_US
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.2023.01.020en_US
dc.identifier.digital1-s20-S0006322323000483-mainen_US
dc.identifier.doihttps://doi.org/10.1016/j.biopsych.2023.01.020en_US
dc.identifier.urihttps://hdl.handle.net/1911/115640en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
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.en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.titleDecoding Depression Severity From Intracranial Neural Activityen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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