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        <identifier>oai:figshare.com:article/33829348</identifier>
        <datestamp>2026-09-16T05:45:03Z</datestamp>
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          <dc:title>Data Sheet 3_Attenuated sensorimotor hemodynamic responses and altered cortical dynamics during passive proprioceptive-related stimulation after stroke: a multidimensional fNIRS study.docx</dc:title>
          <dc:creator>Hui Sun (107933)</dc:creator>
          <dc:creator>Qiuyuan Fu (24961231)</dc:creator>
          <dc:creator>Yichen Jiang (4042880)</dc:creator>
          <dc:creator>Guangyue Zhu (6666632)</dc:creator>
          <dc:subject>Neurology and Neuromuscular Diseases</dc:subject>
          <dc:subject>cortical dynamic network</dc:subject>
          <dc:subject>functional near-infrared spectroscopy</dc:subject>
          <dc:subject>proprioceptive processing</dc:subject>
          <dc:subject>recovery-phase complexity</dc:subject>
          <dc:subject>stroke</dc:subject>
          <dc:description>Objective&lt;p&gt;This study aimed to use functional near-infrared spectroscopy to investigate abnormalities in cortical activity and dynamic network mechanisms associated with proprioceptive processing after stroke. We integrated conventional hemodynamic features, latent-state organization, directed connectivity, and recovery-phase complexity analyses to explore multidimensional changes in cortical dynamics.&lt;/p&gt;Methods&lt;p&gt;Patients with stroke and healthy controls underwent baseline motor and sensory assessments and completed a block-designed proprioceptive task during fNIRS recording, consisting of six alternating 30-s stimulation and 30-s rest periods. After preprocessing, ROI-level oxygenated hemoglobin (HbO) time series were extracted. Conventional temporal features included area under the curve (AUC), onset latency, peak amplitude, post-stimulus residual activation, recovery slope, and time-to-peak. Latent state analysis was performed using a Gaussian mixture model to derive fractional occupancy (FO), mean dwell time (MDT), and transition characteristics. Directed connectivity during prestimulus, stimulation, and recovery phases was assessed using a sliding-window multivariate autoregressive model with partial directed coherence (PDC). Recovery-phase dynamics were further quantified using sample entropy, mean multiscale entropy, recurrence rate (RR), determinism (DET), and mean diagonal line length (Lmean).&lt;/p&gt;Results&lt;p&gt;A total of 62 participants, including 30 patients with stroke and 32 healthy controls, underwent a passive thumb movement task during fNIRS recording. Conventional HbO analysis showed that between-group differences were mainly confined to the left sensorimotor cortex, where the stroke group differed significantly from healthy controls in AUC (p = 0.023), peak amplitude (p = 0.003), and recovery slope (p = 0.018). No other ROI showed significant between-group differences, although marginal trends were observed in the right prefrontal and right sensorimotor cortices. Latent state analysis identified six states. Healthy controls more frequently occupied State 1 and State 5, whereas the stroke group more frequently occupied State 3 and State 6, and showed longer MDT in State 2 and State 3. Directed connectivity analysis revealed phase-dependent shifts in both groups, with the stroke group showing stronger prefrontal–sensorimotor reorganization across prestimulus, stimulation, and recovery phases. Recovery-phase complexity analysis demonstrated significantly higher global RR, DET, and Lmean in the stroke group, whereas sample entropy and mean multiscale entropy did not remain significant after correction. ROI-level complexity differences did not survive multiple-comparison correction.&lt;/p&gt;Conclusion&lt;p&gt;Abnormal proprioceptive processing after stroke is characterized not only by altered local activation, but also by dynamic state shifts, phase-specific reorganization of information flow, and increased regularity with reduced flexibility during recovery.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-16T05:45:03Z</dc:date>
          <dc:type>Dataset</dc:type>
          <dc:type>Dataset</dc:type>
          <dc:identifier>10.3389/fneur.2026.1848276</dc:identifier>
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          <dc:rights>CC BY 4.0</dc:rights>
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