Hierarchical dynamics of informational patterns and decision-making

Abstract

Traditional studies on the interaction of cognitive functions in healthy and disordered brains have used the analyses of the connectivity of several specialized brain networks—the functional connectome. However, emerging evidence suggests that both brain networks and functional spontaneous brain-wide network communication are intrinsically dynamic. In the light of studies investigating the cooperation between different cognitive functions, we consider here the dynamics of hierarchical networks in cognitive space. We show, using an example of behavioural decision-making based on sequential episodic memory, how the description of metastable pattern dynamics underlying basic cognitive processes helps to understand and predict complex processes like sequential episodic memory recall and competition among decision strategies. The mathematical images of the discussed phenomena in the phase space of the corresponding cognitive model are hierarchical heteroclinic networks. One of the most important features of such networks is the robustness of their dynamics. Different kinds of instabilities of these dynamics can be related to ‘dynamical signatures’ of creativity and different psychiatric disorders. The suggested approach can also be useful for the understanding of the dynamical processes that are the basis of consciousness.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 15, 2016
Source ID
10.1098/rspb.2016.0475

Entities

People

  • M. I. Rabinovich
  • Pablo Varona

Organizations

  • Ministry of Economy, Industry and Competitiveness
  • Office of Naval Research
  • University of California, San Diego

Tags

Fields of Study

  • Biology

Readers

  • Artificial Intelligence
  • Neuroscience
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • Space