Dissociable changes in functional network topology underlie early category learning and development of automaticity

TL;DR

This study uncovers how different brain network topologies underlie early category learning and automaticity, highlighting the distinct roles of subcortical and cortical areas through network analysis.

Contribution

It integrates neurocomputational theories with network science to reveal dissociable brain network changes during different stages of category learning.

Findings

Initial learning linked to efficient subcortical integration

Automaticity associated with lower subcortical clustering and higher cortical centrality

Distinct network patterns predict behavioral improvements

Abstract

Recent work has shown that multimodal association areas-including frontal, temporal and parietal cortex-are focal points of functional network reconfiguration during human learning and performance of cognitive tasks. On the other hand, neurocomputational theories of category learning suggest that the basal ganglia and related subcortical structures are focal points of functional network reconfiguration during early learning of some categorization tasks, but become less so with the development of automatic categorization performance. Using a combination of network science and multilevel regression, we explore how changes in the connectivity of small brain regions can predict behavioral changes during training in a visual categorization task. We find that initial category learning, as indexed by changes in accuracy, is predicted by increasingly efficient integrative processing in subcortical areas, with higher functional specialization, more efficient integration across modules, but a lower cost in terms of redundancy of information processing. The development of automaticity, as indexed by changes in the speed of correct responses, was predicted by lower clustering (particularly in subcortical areas), higher strength (highest in cortical areas) and higher betweenness centrality. By combining neurocomputational theories and network scientific methods, these results synthesize the dissociative roles of multimodal association areas and subcortical structures in the development of automaticity during category learning.