Brain Network Connectivity During Resting-State and a Visuospatial Task as a Biomarker for Spatial Neglect in Stroke Patients.

Background: Spatial neglect (SN) is a common visual attention deficit affecting stroke patients due to large-scale disruptions within brain networks. Most studies have focused only on resting-state, but effective rehabilitation requires a clearer understanding of how brain networks change during vis...

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Publicado en:Neurorehabilitation & Neural Repair Vol. 40; no. 6; pp. 482 - 495
Autores principales: Haddadshargh, Golnaz, Gall, Richard, Grattan, Emily S., Ostadabbas, Sarah, Wittenberg, George F., Akcakaya, Murat
Formato: pictorial research tables/charts Journal Article
Publicado: Sage Publications Inc. Jun2026
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jun2026
      vid: 40
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      pub: Sage Publications Inc.
      place: Thousand Oaks, California
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        atl: Brain Network Connectivity During Resting-State and a Visuospatial Task as a Biomarker for Spatial Neglect in Stroke Patients.
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        au:
          Haddadshargh, Golnaz
          Gall, Richard
          Grattan, Emily S.
          Ostadabbas, Sarah
          Wittenberg, George F.
          Akcakaya, Murat
        affil: Rehab Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA
      sug:
        subj:
          Unilateral Neglect Evaluation
          Stroke Patients
          Brain Mapping
          Biological Markers Diagnostic Use
          Spatial Perception
          Electroencephalography Methods
          Task Performance and Analysis
          Pennsylvania
          Human
          Male
          Female
          Middle Age
          Aged
          Aged, 80 and Over
          Descriptive Statistics
          Academic Medical Centers
          Neuropsychological Tests
          Pearson's Correlation Coefficient
          Wilcoxon Signed Rank Test
          Data Analysis Software
          Funding Source
          Middle Aged: 45-64 years
          Aged: 65+ years
          Aged, 80 & over
          Male
          Female
      ab: Background: Spatial neglect (SN) is a common visual attention deficit affecting stroke patients due to large-scale disruptions within brain networks. Most studies have focused only on resting-state, but effective rehabilitation requires a clearer understanding of how brain networks change during visuospatial tasks. Objective: This study aims to identify network disruptions associated with neglect by comparing resting-state and task-based electroencephalography (EEG) connectivity patterns in stroke patients with and without neglect. Methods: We recorded EEG data from 28 stroke patients using the augmented reality (AR)-based EEG-guided neglect detection system (AREEN) during resting-state and a visuospatial task. Connectivity was measured using coherence in delta, theta, alpha, and beta bands for both conditions, with gamma-band coherence assessed only during the task. Graph-based metrics were applied to model network-level disruptions. Classification models evaluated the significance of connectivity features to find patterns predictive of neglect. Results: The neglect group showed reduced connectivity in frontal and right parieto-occipital (ParOcc) regions, primarily in beta and theta bands, during both conditions, with additional gamma-band connectivity differences in the task condition, compared to the non-neglect group. Conversely, connectivity was greater in central and midline regions, which may indicate a maladaptive shift in network organization. Classification models accurately classified patients into neglect and non-neglect groups (resting-state: 87.0% ± 0.7%; task: 80.9% ± 16.0%). Feature importance analysis identified eigenvector and closeness centrality within frontal, right ParOcc, and central regions as key predictors. Conclusions: Network disruptions can effectively identify SN and provide potential targets for connectivity-based rehabilitation. Future studies should investigate whether these interventions improve attention and recovery in stroke patients. This study was registered at ClinicalTrials.gov under ID NCT04187131.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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