RT Journal Article
SR Electronic
T1 The neural dynamics associated with computational complexity
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.01.05.475102
DO 10.1101/2022.01.05.475102
A1 Juan Pablo Franco
A1 Peter Bossaerts
A1 Carsten Murawski
YR 2022
UL http://biorxiv.org/content/early/2022/01/05/2022.01.05.475102.abstract
AB Many everyday tasks require people to solve computationally complex problems. However, little is known about the effects of computational hardness on the neural processes associated with solving such problems. Here, we draw on computational complexity theory to address this issue. We performed an experiment in which participants solved several instances of the 0-1 knapsack problem, a combinatorial optimization problem, while undergoing ultra-high field (7T) functional magnetic resonance imaging (fMRI). Instances varied in two task-independent measures of intrinsic computational hardness: complexity and proof hardness. We characterise a network of brain regions whose activation was correlated with both measures but in distinct ways, including the anterior insula, dorsal anterior cingulate cortex and the intra-parietal sulcus/angular gyrus. Activation and connectivity changed dynamically as a function of complexity and proof hardness, in line with theoretical computational requirements. Overall, our results suggest that computational complexity theory provides a suitable framework to study the effects of computational hardness on the neural processes associated with solving complex cognitive tasks.Competing Interest StatementThe authors have declared no competing interest.