Work

Inferring causal relations from multivariate data using Large-Scale Augmented Granger Causality (lsAGC)

Year: 2025

Type: article

Abstract: Causal inference from high-dimensional and short time-series data is crucial to scientific discovery across diverse fields. Yet, standard approaches frequently fail under these constraints. We propose Large-scale Augmented Granger Causality (lsAGC), integrating dimension reduction, a Granger-based predictive framework, and data augmentation, to handle large-scale networks even when T

Source: NeuroImage

DOI: 10.1016/j.neuroimage.2025.121616

Authors: Axel Wismüller, Ali Vosoughi, Akhil Kasturi

Institutions: Ludwig-Maximilians-Universität München, University of Rochester

Language: English

Topic: Functional Brain Connectivity Studies

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $3,540

Funders: National Institutes of Health, National Institute on Drug Abuse