MERLiN: Mixture Effect Recovery in Linear Networks

TL;DR

MERLiN introduces algorithms for causal inference in linear networks, enabling the recovery of meaningful causal variables from observed mixtures, with applications demonstrated on EEG data to identify brain signals affected by specific regions.

Contribution

The paper presents MERLiN, a novel family of algorithms that construct causal variables from linear mixtures, advancing causal inference in neuroimaging data analysis.

Findings

Successfully recovered cortical signals as causal effects in EEG data.

Extended MERLiN algorithms applied to different neuroimaging modalities.

Open-source implementation available for reproducibility.

Abstract

Causal inference concerns the identification of cause-effect relationships between variables, e.g. establishing whether a stimulus affects activity in a certain brain region. The observed variables themselves often do not constitute meaningful causal variables, however, and linear combinations need to be considered. In electroencephalographic studies, for example, one is not interested in establishing cause-effect relationships between electrode signals (the observed variables), but rather between cortical signals (the causal variables) which can be recovered as linear combinations of electrode signals. We introduce MERLiN (Mixture Effect Recovery in Linear Networks), a family of causal inference algorithms that implement a novel means of constructing causal variables from non-causal variables. We demonstrate through application to EEG data how the basic MERLiN algorithm can be extended for application to different (neuroimaging) data modalities. Given an observed linear mixture, the algorithms can recover a causal variable that is a linear effect of another given variable. That is, MERLiN allows us to recover a cortical signal that is affected by activity in a certain brain region, while not being a direct effect of the stimulus. The Python/Matlab implementation for all presented algorithms is available on https://github.com/sweichwald/MERLiN