ID: 20231012155324959-1343

Researcher: Thomas A. W. Bolton, Dimitri Van De Ville, Enrico Amico, Maria G. Preti, Raphaël Liégeois

WP: Other

PI: null

Abstract: Moving from association to causal analysis of neuroimaging data is crucial to advance our understanding of brain function. The arrow-of-time (AoT), i.e., the known asymmetric nature of the passage of time, is the bedrock of causal structures shaping physical phenomena. However, almost all current time series metrics do not exploit this asymmetry, probably due to the difficulty to account for it in modelling frameworks. Here, we introduce an AoT-sensitive metric that captures the intensity of causal effects in multivariate time series, and apply it to high-resolution functional neuroimaging data. We find that that causal effects underlying brain function are more clearly localized in space and time than functional activity or connectivity, thereby allowing us to trace neural pathways recruited in different conditions. Overall, we provide a mapping of the causal brain that challenges the association paradigm of brain function.

Publication DOI: https://doi.org/10.1101/2022.05.11.491521

Publication Link: https://www.biorxiv.org/content/10.1101/2022.05.11.491521v1

Data Type: null

Data Format: null

Data Link: https://github.com/TiBiUan/AoT_Benchmarking

Git: None