Kambeitz-Ilankovic, Lana, Vinogradov, Sophia, Wenzel, Julian, Fisher, Melissa, Haas, Shalaila S., Betz, Linda, Penzel, Nora ORCID: 0000-0003-1624-386X, Nagarajan, Srikantan, Koutsouleris, Nikolaos ORCID: 0000-0001-6825-6262 and Subramaniam, Karuna (2021). Multivariate pattern analysis of brain structure predicts functional outcome after auditory-based cognitive training interventions. npj Schizophr., 7 (1). BERLIN: NATURE PORTFOLIO. ISSN 2334-265X

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Abstract

Cognitive gains following cognitive training interventions are associated with improved functioning in people with schizophrenia (SCZ). However, considerable inter-individual variability is observed. Here, we evaluate the sensitivity of brain structural features to predict functional response to auditory-based cognitive training (ABCT) at a single-subject level. We employed whole-brain multivariate pattern analysis with support vector machine (SVM) modeling to identify gray matter (GM) patterns that predicted higher vs. lower functioning after 40 h of ABCT at the single-subject level in SCZ patients. The generalization capacity of the SVM model was evaluated by applying the original model through an out-of-sample cross-validation analysis to unseen SCZ patients from an independent validation sample who underwent 50 h of ABCT. The whole-brain GM volume-based pattern classification predicted higher vs. lower functioning at follow-up with a balanced accuracy (BAC) of 69.4% (sensitivity 72.2%, specificity 66.7%) as determined by nested cross-validation. The neuroanatomical model was generalizable to an independent cohort with a BAC of 62.1% (sensitivity 90.9%, specificity 33.3%). In particular, greater baseline GM volumes in regions within superior temporal gyrus, thalamus, anterior cingulate, and cerebellum predicted improved functioning at the single-subject level following ABCT in SCZ participants. The present findings provide a structural MRI fingerprint associated with preserved GM volumes at a single baseline timepoint, which predicted improved functioning following an ABCT intervention, and serve as a model for how to facilitate precision clinical therapies for SCZ based on imaging data, operating at the single-subject level.

Item Type: Journal Article
Creators:
CreatorsEmailORCIDORCID Put Code
Kambeitz-Ilankovic, LanaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Vinogradov, SophiaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Wenzel, JulianUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Fisher, MelissaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Haas, Shalaila S.UNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Betz, LindaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Penzel, NoraUNSPECIFIEDorcid.org/0000-0003-1624-386XUNSPECIFIED
Nagarajan, SrikantanUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Koutsouleris, NikolaosUNSPECIFIEDorcid.org/0000-0001-6825-6262UNSPECIFIED
Subramaniam, KarunaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
URN: urn:nbn:de:hbz:38-599559
DOI: 10.1038/s41537-021-00165-0
Journal or Publication Title: npj Schizophr.
Volume: 7
Number: 1
Date: 2021
Publisher: NATURE PORTFOLIO
Place of Publication: BERLIN
ISSN: 2334-265X
Language: English
Faculty: Unspecified
Divisions: Unspecified
Subjects: no entry
Uncontrolled Keywords:
KeywordsLanguage
HIGH-RISK; ENHANCEMENT THERAPY; CORTICAL PLASTICITY; WORKING-MEMORY; SCHIZOPHRENIA; PSYCHOSIS; INDIVIDUALS; REMEDIATION; METAANALYSIS; DYSFUNCTIONMultiple languages
PsychiatryMultiple languages
URI: http://kups.ub.uni-koeln.de/id/eprint/59955

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