Author

Katherine Wilson Scangos

University of California, San FranciscoORCID 0000-0001-7983-7767Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 3

Signature Assays, Organisms & Methods

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Assay:electronic health records· 3 Organism:human· 3 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1

Frequent Co-Authors

A. Krystal· 1 shared Altona Tufanoglu· 1 shared Andrew C. HeusseriD· 1 shared Ankit N. KhambhatiiD· 1 shared Anna Rose Childress· 1 shared Anna WexleriD· 1 shared Anne Eden EvinsiD· 1 shared Bijan PesaraniD· 1 shared

Activity by Year

2020-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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1 shared paperNeuroscience

A. Krystal

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Author profile →

3 papers

Recent·Most cited

Localizing electrophysiologic cue-reactivity within the nucleus accumbens guides deep brain stimulation for opioid use disorder

Liming Qiu, Young‐Hoon Nho, Robert L Seilheimer, Min Jae Kim, Altona Tufanoglu, Nolan Williams, Anna Wexler, David W. Oslin, Bruno Millet, Katherine Wilson Scangos, Bijan Pesaran, Anne Eden Evins, Robert Mark Richardson, Anna Rose Childress, Casey H. Halpern

The paper uses electrophysiological data from the nucleus accumbens to guide deep brain stimulation for opioid use disorder, showing suppression of drug-related cravings with targeted stimulation.

Nature Communications · Jan 29, 2026Peer-reviewedNeuroscience

A Gaussian process model of human electrocorticographic data

Lucy L. W. Owen, Tudor A. Muntianu, Andrew C. Heusser, Patrick M. Daly, Katherine Wilson Scangos, Jeremy R. Manning

The paper introduces a Gaussian process model to infer high spatiotemporal resolution neural activity from low-density intracranial recordings across individuals and tasks.

Cerebral Cortex · Apr 20, 2020Peer-reviewedNeuroscience

Distributed Subnetworks of Depression Defined by Direct Intracranial Neurophysiology

Katherine Wilson Scangos, Ankit N. Khambhati, PM Daly, LW Owen, JR Manning, JB Ambrose, E Austin, Heather E. Dawes, A. Krystal, EF Chang

This study uses direct neural recordings to identify two subnetworks associated with depression, characterized by hypoconnectivity and hyperconnectivity in specific brain regions.

bioRxiv · Feb 14, 2020 · PreprintNeuroscience