PT  - JOURNAL ARTICLE
AU  - Juan Pablo Franco
AU  - Peter Bossaerts
AU  - Carsten Murawski
TI  - The neural dynamics associated with computational complexity
AID  - 10.1101/2022.01.05.475102
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.01.05.475102
4099  - http://biorxiv.org/content/early/2022/01/05/2022.01.05.475102.short
4100  - http://biorxiv.org/content/early/2022/01/05/2022.01.05.475102.full
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.