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Data-Driven Extraction of a Nested Model of Human Brain Function.

Taylor Bolt1, Jason S Nomi2, B T Thomas Yeo3

  • 1Department of Psychology, University of Miami, Coral Gables, Florida 33124, tsb46@miami.edu l.uddin@miami.edu.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
|June 22, 2017
PubMed
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This summary is machine-generated.

A hierarchical model reveals a domain-general "focused awareness" process underlying brain activation patterns. This general factor, along with specific subfactors, explains most brain activity variations across diverse cognitive tasks.

Area of Science:

  • Cognitive Neuroscience
  • Neuroimaging
  • Psychology

Background:

  • Distinct brain activation patterns emerge with different task demands.
  • A common superordinate pattern of activation/deactivation is observed across various tasks.
  • Existing research suggests a need for a unifying framework for brain activation phenomena.

Purpose of the Study:

  • To investigate a hierarchical model of brain activation patterns.
  • To determine if a nested factor structure underlies commonly observed activation patterns.
  • To identify a domain-general psychological process and its manifestations.

Main Methods:

  • Exploratory bifactor analysis applied to 108 human brain activation maps.
  • Analysis encompassed cognition, perception, action, and emotion domains.
Keywords:
bifactor analysiscognitive ontoloytask fMRItask-negativetask-positivetaxonomy

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  • Latent variable approach to identify underlying factor structures.

    • Main Results:

    • A general factor explained 52.37% of variance in brain activation patterns, representing a superordinate activation/deactivation pattern.
    • Subfactors explained an additional 31.02% of variance, linked to specific task contexts.
    • The nested factor structure demonstrated a superior fit to the data compared to non-nested models.

    Conclusions:

    • A nested factor structure provides a unifying framework for understanding brain activation.
    • Results support a domain-general "focused awareness" or "attentional episode" process.
    • This model facilitates a biologically informed, data-driven taxonomy of psychological processes.