Extracting Root-Causal Brain Activity Driving Psychopathology from Resting State fMRI

TL;DR

This paper introduces SOURCE, a novel method to identify localized root-causal brain activity driving psychiatric symptoms from resting-state fMRI, enhancing interpretability and specificity of neuroimaging findings.

Contribution

The paper presents a bilevel structural causal model and SOURCE method that link symptom dimensions to localized brain activity, revealing root-causal drivers in psychiatric disorders.

Findings

SOURCE recovers localized root-causal BOLD activity maps

Increases interpretability and anatomical specificity

Consistent with known neurobiological mechanisms

Abstract

Neuroimaging studies of psychiatric disorders often correlate imaging patterns with diagnostic labels or composite symptom scores, yielding diffuse associations that obscure underlying mechanisms. We instead seek to identify root-causal maps -- localized BOLD disturbances that initiate pathological cascades -- and to link them selectively to symptom dimensions. We introduce a bilevel structural causal model that connects between-subject symptom structure to within-subject resting-state fMRI via independent latent sources with localized direct effects. Based on this model, we develop SOURCE (Symptom-Oriented Uncovering of Root-Causal Elements), a procedure that links interpretable symptom axes to a parsimonious set of localized drivers. Experiments show that SOURCE recovers localized maps consistent with root-causal BOLD drivers and increases interpretability and anatomical specificity relative to existing comparators.