ArticleBMC medical imaging2026
Independent component analysis of brain network alterations associated with cognitive impairment in coal workers' pneumoconiosis.
Article in BMC medical imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis 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.
methodsA 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.
resultsEight 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.
conclusionsCWP 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.