ArticleNeuroreport2026
Frequency-dependent alterations of degree centrality in patients with poststroke depression: a resting-state functional MRI study.
Article in Neuroreport, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundPoststroke depression (PSD) severely impedes functional recovery among stroke survivors. However, the neural mechanisms underlying PSD remain poorly understood. This study aimed to investigate aberrant intrinsic brain activity in PSD patients using multiband degree centrality analysis.
methodsA total of 84 patients with acute cerebral infarction were enrolled, including 35 patients with PSD and 49 non-PSD patients. All participants underwent resting-state functional MRI. Degree centrality values across the conventional, slow-4, and slow-5 frequency bands were compared between groups. Spearman correlation analysis was conducted to evaluate the relationships between regional degree centrality alterations and depressive symptoms.
resultsRelative to the non-PSD group, patients with PSD exhibited consistently decreased degree centrality in the right dorsolateral prefrontal cortex (DLPFC) across all three frequency bands, while reduced degree centrality in the left DLPFC was specifically identified in the slow-4 band. In the slow-4 band, the PSD group showed significantly elevated degree centrality in the left pallidum, left middle temporal gyrus, left fusiform gyrus, and corpus callosum, whereas no brain regions displayed increased degree centrality in the slow-5 band. Correlation analyses revealed that slow-4 degree centrality values in the left DLPFC were negatively correlated with Self-rating Depression Scale scores, whereas degree centrality values in the left pallidum were positively correlated with depressive severity.
conclusionPSD patients exhibited distinct frequency-dependent patterns of abnormal intrinsic brain connectivity, with the slow-4 band showing the most prominent functional alterations. These findings provide novel insights into the neural mechanisms underlying PSD and may facilitate the identification of frequency-specific functional biomarkers for PSD.
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