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J Neurosci. 2017 Jul 26;37(30):7263-7277. doi: 10.1523/JNEUROSCI.0323-17.2017. Epub 2017 Jun 20.

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

Author information

1
Department of Psychology, University of Miami, Coral Gables, Florida 33124, tsb46@miami.edu l.uddin@miami.edu.
2
Department of Psychology, University of Miami, Coral Gables, Florida 33124.
3
Electrical and Computer Engineering, Clinical Imaging Research Center, Singapore Institute for Neurotechnology and Memory Network Program, National University of Singapore, Singapore 119077, and.
4
Neuroscience Program, University of Miami Miller School of Medicine, Miami, Florida 33136.

Abstract

Decades of cognitive neuroscience research have revealed two basic facts regarding task-driven brain activation patterns. First, distinct patterns of activation occur in response to different task demands. Second, a superordinate, dichotomous pattern of activation/deactivation, is common across a variety of task demands. We explore the possibility that a hierarchical model incorporates these two observed brain activation phenomena into a unifying framework. We apply a latent variable approach, exploratory bifactor analysis, to a large set of human (both sexes) brain activation maps (n = 108) encompassing cognition, perception, action, and emotion behavioral domains, to determine the potential existence of a nested structure of factors that underlie a variety of commonly observed activation patterns. We find that a general factor, associated with a superordinate brain activation/deactivation pattern, explained the majority of the variance (52.37%) in brain activation patterns. The bifactor analysis also revealed several subfactors that explained an additional 31.02% of variance in brain activation patterns, associated with different manifestations of the superordinate brain activation/deactivation pattern, each emphasizing different contexts in which the task demands occurred. Importantly, this nested factor structure provided better overall fit to the data compared with a non-nested factor structure model. These results point to a domain-general psychological process, representing a "focused awareness" process or "attentional episode" that is variously manifested according to the sensory modality of the stimulus and degree of cognitive processing. This novel model provides the basis for constructing a biologically informed, data-driven taxonomy of psychological processes.SIGNIFICANCE STATEMENT A crucial step in identifying how the brain supports various psychological processes is a well-defined categorization or taxonomy of psychological processes and their interrelationships. We hypothesized that a nested structure of cognitive function, in terms of a canonical domain-general cognitive process, and various subfactors representing different manifestations of the canonical process, is a fundamental organization of human cognition, and we tested this hypothesis using fMRI task-activation patterns. Using a data-driven latent-variable approach, we demonstrate that a nested factor structure underlies a large sample of brain activation patterns across a variety of task domains.

KEYWORDS:

bifactor analysis; cognitive ontoloy; task fMRI; task-negative; task-positive; taxonomy

PMID:
28634305
PMCID:
PMC5546402
[Available on 2018-01-26]
DOI:
10.1523/JNEUROSCI.0323-17.2017
[Indexed for MEDLINE]
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