Open AccessTowards an ontology of cognitive processes and their neural substrates: A structural equation modeling approach
Author(s) -
Teal S. Eich,
David B. Parker,
Yunglin Gazes,
Qolamreza R. Razlighi,
Christian Habeck,
Yaakov Stern
Publication year - 2020
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0228167
Subject(s) - cognition , cognitive psychology , psychology , episodic memory , structural equation modeling , animal cognition , set (abstract data type) , functional magnetic resonance imaging , cognitive neuroscience , similarity (geometry) , latent variable , neuroimaging , cognitive science , computer science , artificial intelligence , neuroscience , machine learning , image (mathematics) , programming language
A key challenge in the field of cognitive neuroscience is to identify discriminable cognitive functions, and then map these functions to brain activity. In the current study, we set out to explore the relationships between performance arising from different cognitive tasks thought to tap different domains of cognition, and then to test whether these distinct latent cognitive abilities also are subserved by corresponding “latent” brain substrates. To this end, we tested a large sample of adults under the age of 40 on twelve cognitive tasks as they underwent fMRI scanning. Exploratory factor analysis revealed 4-factor model, dissociating tasks into processes corresponding to episodic memory retrieval, reasoning, speed of processing and vocabulary. An analysis of the topographic covariance patterns of the BOLD-response acquired during each task similarity also converged on four neural networks that corresponded to the 4 latent factors. These results suggest that distinct ontologies of cognition are subserved by corresponding distinct neural networks.