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Multivariate pattern analysis of brain structure predicts functional outcome after auditory-based cognitive training

Lana Kambeitz-Ilankovic1,2, Sophia Vinogradov3, Julian Wenzel1,2

  • 1Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany.

NPJ Schizophrenia
|August 20, 2021
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Summary

Brain structure predicts cognitive gains in schizophrenia patients undergoing auditory-based cognitive training (ABCT). Greater baseline gray matter volumes in specific brain regions indicate better functional response to ABCT, aiding personalized treatment strategies.

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Area of Science:

  • Neuroimaging
  • Psychiatry
  • Cognitive Neuroscience

Background:

  • Cognitive training improves functioning in schizophrenia (SCZ), but responses vary significantly.
  • Predicting individual treatment response is crucial for optimizing therapies.

Purpose of the Study:

  • To identify baseline brain structural features that predict functional outcomes after auditory-based cognitive training (ABCT) in individuals with SCZ.
  • To develop a neuroanatomical model for personalized treatment selection in SCZ.

Main Methods:

  • Whole-brain multivariate pattern analysis using support vector machine (SVM) modeling on baseline gray matter (GM) volumes.
  • Nested cross-validation and out-of-sample validation on an independent cohort to assess model accuracy and generalizability.
  • Analysis focused on predicting higher versus lower functional outcomes post-ABCT.

Main Results:

  • The SVM model accurately predicted functional response to ABCT at the single-subject level (balanced accuracy 69.4%).
  • The model demonstrated generalizability to an independent cohort (balanced accuracy 62.1%).
  • Higher baseline GM volumes in the superior temporal gyrus, thalamus, anterior cingulate, and cerebellum predicted improved functioning.

Conclusions:

  • Baseline gray matter patterns can predict individual functional gains from ABCT in SCZ.
  • This neuroimaging-based approach offers a potential pathway for precision medicine in schizophrenia treatment.
  • Identifying structural biomarkers can guide the development of tailored cognitive interventions for SCZ.