# Altered asymmetry of functional connectome gradients in major depressive disorder

## TL;DR

This study finds that major depressive disorder disrupts brain connectivity asymmetry, affecting both sensory and higher-order cognitive regions.

## Contribution

The study introduces a novel approach to assess MDD-related asymmetry in functional gradients across brain hierarchies.

## Key findings

- MDD patients show altered asymmetry in primary sensory and transmodal brain regions compared to healthy controls.
- Abnormalities in functional gradient asymmetry are linked to cognitive processes like memory and visual processing.
- Intra- and inter-hemispheric asymmetric features predict depressive traits using BDI-II scores.

## Abstract

Major depressive disorder (MDD) is a debilitating disease involving sensory and higher-order cognitive dysfunction. Previous work has shown altered asymmetry in MDD, including abnormal lateralized activation and disrupted hemispheric connectivity. However, it remains unclear whether and how MDD affects functional asymmetries in the context of intrinsic hierarchical organization.

Here, we evaluate intra- and inter-hemispheric asymmetries of the first three functional gradients, characterizing unimodal-transmodal, visual-somatosensory, and somatomotor/default mode-multiple demand hierarchies, to study MDD-related alterations in overarching system-level architecture.

We find that, relative to the healthy controls, MDD patients exhibit alterations in both primary sensory regions (e.g., visual areas) and transmodal association regions (e.g., default mode areas). We further find these abnormalities are woven in heterogeneous alterations along multiple functional gradients, associated with cognitive terms involving mind, memory, and visual processing. Moreover, through an elastic net model, we observe that both intra- and inter-asymmetric features are predictive of depressive traits measured by BDI-II scores.

Altogether, these findings highlight a broad and mixed effect of MDD on functional gradient asymmetry, contributing to a richer understanding of the neurobiological underpinnings in MDD.