Abstract
There is an ongoing debate as to whether cognitive processes arise from a group of functionally specialized brain modules (modularism) or as the result of a distributed nonlinear process (dynamical systems theory). The former predicts that tasks that recruit similar brain areas should have an equivalent degree of similarity in their connectivity. The latter allows for differential connectivity, even when the areas recruited are largely the same. Here we evaluated both views by comparing activation and connectivity patterns from a large sample of healthy subjects (N=242) that performed two executive control tasks, color-word Stroop task and Multi-Source Interference Task (MSIT), known to recruit similar brain areas. Using a measure of instantaneous connectivity based on edge time series as outcome variables, we estimated task-related network profiles as connectivity changes between incongruent and congruent information conditions. The degree of similarity of such profiles at the group level between both tasks was substantially smaller than their overlapping activation responses. A similar finding was observed at the subject level and when employing a different method for defining task-related connectivity. Our results are consistent with the perspective of the brain as a dynamical system, suggesting that task representations should be understood at both node and edge (connectivity) levels.
Significance Statement There exist two contrasting views of the brain that yield different predictions of how cognition is represented. In the modular view, similar cognitive processes should have similar connectivity profiles. In contrast, a dynamical systems view allows for multiple network configurations in these situations. Here we tested both views using two tasks, color-word Stroop and Multi-Source Interference Task (MSIT), that evoke a similar brain response. Using a novel approach of instantaneous connectivity we first estimated the connectivity changes during both tasks and subsequently found that their similarity was substantially smaller than the patterns of brain activation. These findings reinforce the view of brain as a dynamical system and shed light onto how cognitive processes may be quantitatively modeled.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Conflict of interest statement: The authors declare no competing financial interests.