Formal Models of the Network Co-occurrence Underlying Mental Operations

PLoS Comput Biol. 2016 Jun 16;12(6):e1004994. doi: 10.1371/journal.pcbi.1004994. eCollection 2016 Jun.

Abstract

Systems neuroscience has identified a set of canonical large-scale networks in humans. These have predominantly been characterized by resting-state analyses of the task-unconstrained, mind-wandering brain. Their explicit relationship to defined task performance is largely unknown and remains challenging. The present work contributes a multivariate statistical learning approach that can extract the major brain networks and quantify their configuration during various psychological tasks. The method is validated in two extensive datasets (n = 500 and n = 81) by model-based generation of synthetic activity maps from recombination of shared network topographies. To study a use case, we formally revisited the poorly understood difference between neural activity underlying idling versus goal-directed behavior. We demonstrate that task-specific neural activity patterns can be explained by plausible combinations of resting-state networks. The possibility of decomposing a mental task into the relative contributions of major brain networks, the "network co-occurrence architecture" of a given task, opens an alternative access to the neural substrates of human cognition.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Brain / physiology*
  • Cognition / physiology*
  • Female
  • Humans
  • Learning / physiology*
  • Machine Learning
  • Male
  • Models, Neurological*
  • Nerve Net
  • Neurons / physiology
  • Young Adult

Grants and funding

This study was supported by the Deutsche Forschungsgemeinschaft (DFG, BZ2/2-1 and BZ2/3-1 to DB; International Research Training Group IRTG2150), the German National Academic Foundation (DB), Amazon AWS Research Grant (DB), the START-Program of the Faculty of Medicine, RWTH Aachen (DB), and the MetaMRI associated team (BT, GV). The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 604102 (Human Brain Project). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.