Varying Information Complexity in Functional Domain Interactions in Schizophrenia

Ishaan Batt, Anees Abrol, Zening Fu, Vince Calhoun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Understanding the associations of the structural and functional patterns of the brain is vital. Recent studies have focused on utilizing this information within and across the different functional and anatomical domains (i.e., groups of brain networks) using neuroimaging data. In this work, we use a Bayesian optimization-based method known as the Tree Parzen Estimator (TPE) to identify variation in the nature of information encoded by different functional magnetic resonance imaging (fMRI) sub-domains of the brain. We show by repeated cross-validation on a schizophrenia classification task that specific sub-domains may require more sophisticated learning architectures to contribute optimally to classification, while others require less complicated ones. Our findings reveal the need for adaptive, hierarchical learning frameworks catering to features from different sub-domains to optimally identify features enabling the prediction of the outcome of interest.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1042-1047
Number of pages6
ISBN (Electronic)9781728195742
DOIs
StatePublished - Oct 2020
Event20th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2020 - Virtual, Cincinnati, United States
Duration: Oct 26 2020Oct 28 2020

Publication series

NameProceedings - IEEE 20th International Conference on Bioinformatics and Bioengineering, BIBE 2020

Conference

Conference20th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2020
CountryUnited States
CityVirtual, Cincinnati
Period10/26/2010/28/20

Keywords

  • Bayesian Optimization
  • fMRI
  • Functional Connectivity
  • Hyperparameter Optimization
  • Multilayer Perceptron
  • Schizophrenia
  • Sub-domain Analysis

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Molecular Biology
  • Artificial Intelligence
  • Computer Science Applications
  • Biomedical Engineering
  • Modeling and Simulation
  • Health Informatics

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