Causal Modeling of fMRI Time-series for Interpretable Autism Spectrum Disorder Classification

TL;DR

This paper presents a causality-inspired deep learning model for ASD classification using fMRI time-series data, capturing non-linear interactions between brain regions and providing interpretable insights into ASD-related brain activity.

Contribution

The study introduces a novel causality-based deep learning approach that improves ASD classification accuracy and offers interpretable insights into brain region interactions.

Findings

Achieved 71.9% accuracy and 75.8% AUC on ABIDE dataset.

Identified key ROIs like the precuneus and cerebellum linked to ASD.

Validated findings with existing literature on ASD brain abnormalities.

Abstract

Autism spectrum disorder (ASD) is a neurological and developmental disorder that affects social and communicative behaviors. It emerges in early life and is generally associated with lifelong disabilities. Thus, accurate and early diagnosis could facilitate treatment outcomes for those with ASD. Functional magnetic resonance imaging (fMRI) is a useful tool that measures changes in brain signaling to facilitate our understanding of ASD. Much effort is being made to identify ASD biomarkers using various connectome-based machine learning and deep learning classifiers. However, correlation-based models cannot capture the non-linear interactions between brain regions. To solve this problem, we introduce a causality-inspired deep learning model that uses time-series information from fMRI and captures causality among ROIs useful for ASD classification. The model is compared with other baseline and state-of-the-art models with 5-fold cross-validation on the ABIDE dataset. We filtered the dataset by choosing all the images with mean FD less than 15mm to ensure data quality. Our proposed model achieved the highest average classification accuracy of 71.9% and an average AUC of 75.8%. Moreover, the inter-ROI causality interpretation of the model suggests that the left precuneus, right precuneus, and cerebellum are placed in the top 10 ROIs in inter-ROI causality among the ASD population. In contrast, these ROIs are not ranked in the top 10 in the control population. We have validated our findings with the literature and found that abnormalities in these ROIs are often associated with ASD.