< Back to previous page

Publication

Connectivity between the cerebrum and cerebellum during social and non-social sequencing using dynamic causal modelling

Journal Contribution - Journal Article

This analysis explores the effective connectivity of the cerebellum with the cerebral cortex during the generation of correct sequences of social and non-social events, using dynamic causal modelling (DCM). Our hypothesis is that during human evolution, the cerebellum's function evolved from a mere coordinator of fluent sequences of motions and actions, to an interpreter of action sequences without overt movements that are important for social understanding. This requires efficient neural communication between the cerebellum and cerebral cortex. In a functional magnetic resonance imaging (fMRI) study, participants generated the correct chronological order of (non-)social events, including stories involving mechanical and social scripts, and true or false beliefs. Across all stories, a DCM analysis of these data revealed, as predicted, bidirectional (closed-loop) connections linking the bilateral posterior cerebellum with the bilateral temporo-parietal junction (TPJ) associated with behavior understanding, and this connectivity pattern was almost entirely significant. There was also a unidirectional connection from the right posterior cerebellum to the precuneus, but no direct connections with the dorsomedial prefrontal cortex (dmPFC). Moreover, all connections emanating from the bilateral posterior cerebellum were negative, indicative of some kind of error signal. Within the cerebral cortex, there were unidirectional connections from the bilateral TPJ to the dmPFC, as well as bidirectional connections between the precuneus and dmPFC, and between the bilateral TPJ. These results confirm that the effective connectivity between the posterior cerebellum and mentalizing areas in the cerebral cortex play a critical role in the understanding and construction of the correct order of social and non-social action sequences.

Journal: NeuroImage
ISSN: 1053-8119
Volume: 206
Publication year:2020
CSS-citation score:2
Accessibility:Open