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April 19, 2026Open Access

Independent component analysis of brain network alterations associated with cognitive impairment in coal workers’ pneumoconiosis

Key Points

The aim is to explore changes in brain functional networks in Coal Workers' Pneumoconiosis and their relation to cognitive impairment.
Used independent component analysis (ICA) on resting-state fMRI data to identify neural networks.
Included 91 subjects divided into CWP patients with and without cognitive impairment and healthy controls.
Assessed cognitive function using Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA).
Analyzed both intra-network and inter-network functional connectivity (FC) for identified networks.
Identified eight resting-state networks (RSNs) including DMN and ECN.
CWP-CI group showed alterations in FC primarily between hVN-SN and hVN-DAN.
CWP-nonCI group exhibited enhanced FC in multiple network pairs compared to healthy controls.
Significant correlations found between altered FC, cognitive performance, and pulmonary function.

Abstract

This study aimed to investigate alterations in brain functional networks in Coal Workers’ Pneumoconiosis (CWP) using independent component analysis (ICA), a data-driven method that separates resting-state networks from fMRI data without requiring predefined regions of interest. And we will explore their correlations with clinical indicators and cognitive functions. A total of 91 subjects were finally included after strict inclusion and exclusion criteria, comprising 33 CWP patients with cognitive impairment (CWP-CI), 31 CWP patients without cognitive impairment (CWP-nonCI), and 27 demographically matched healthy controls (HCs). The resting-state fMRI and cognitive assessments using the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Clock Drawing Test (CDT) were performed in all subjects. Following data preprocessing, ICA was employed to identify resting-state networks (RSNs), and both intra-network and inter-network functional connectivity (FC) analysis were conducted. The correlations were assessed between significantly altered FC, clinical indicators and cognitive scale scores. Eight RSNs were identified, including the default mode network (DMN), executive control network (ECN), salience network (SN), dorsal attention network (DAN), sensorimotor network (SMN), higher visual network (hVN), auditory network (AUN), and basal ganglia network (BG). Intra-network connectivity analysis revealed a significant difference within SMN. Inter-network connectivity analysis revealed specific alterations. Compared to the HC group, the CWP-nonCI group exhibited enhanced FC in multiple network pairs, including hVN-SN, hVN-DMN, ECN-SN, DAN-BG, DMN-BG and SMN-SN, while the CWP-CI group primarily showed enhanced FC between hVN-SN and hVN-DAN. Furthermore, compared to the CWP-nonCI group, the CWP-CI group demonstrated significantly reduced FC between BG-AUN and SN-DMN. Some of the altered inter-network FC was significantly correlated with pulmonary function, cognitive scale scores, and work duration. CWP patients exhibited specific reorganization of FC between brain networks. These findings suggested that disrupted inter-network functional communication may serve as a key neural mechanism in CWP-related cognitive impairment, providing new neuroimaging evidence for its basis.

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