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        <identifier>oai:figshare.com:article/33731620</identifier>
        <datestamp>2026-09-14T11:01:37Z</datestamp>
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        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>Data Sheet 1_Multidimensional EEG mechanisms and explainable prediction of responsiveness to posterior parietal HD-tDCS in chronic disorders of consciousness.pdf</dc:title>
          <dc:creator>Xiangyun Zou (12910967)</dc:creator>
          <dc:creator>Bin Jiang (196018)</dc:creator>
          <dc:creator>Chunyun Zhang (325321)</dc:creator>
          <dc:subject>Neuroscience</dc:subject>
          <dc:subject>disorders of consciousness</dc:subject>
          <dc:subject>FOOOF</dc:subject>
          <dc:subject>HD-tDCS</dc:subject>
          <dc:subject>nonlinear EEG</dc:subject>
          <dc:subject>spectral parameterization</dc:subject>
          <dc:description>&lt;p&gt;Transcranial direct current stimulation (tDCS) is a promising intervention for chronic disorders of consciousness (DoC), yet therapeutic responsiveness varies substantially across patients and does not conform to diagnostic boundaries. Contemporary theories of consciousness implicate the posterior parietal cortex as a critical node for conscious processing, but the electrophysiological mechanisms engaged by posterior parietal stimulation remain poorly characterized. High-definition tDCS (HD-tDCS) was applied over Pz in 42 patients with chronic DoC, who were stratified as responders (R+, n = 32) or non-responders (R−, n = 10) according to the emergence of new behavioral signs on the Coma Recovery Scale–Revised. Resting-state electroencephalography (EEG) was analyzed using spectral parameterization (FOOOF), band-limited estimates within two frequency windows informed by the ABCD framework (5–9 Hz and 20–35 Hz), recurrence quantification analysis (RQA), Lempel–Ziv complexity (LZc), and normalized spatial complexity (NSC). In R+ only, the aperiodic exponent decreased at four centro-parietal electrodes, power in the 20–35 Hz window increased at nine electrodes, RQA metrics decreased across 13–18 electrodes, LZc increased at 11 electrodes, and NSC in the 20–35 Hz window increased significantly (p = 0.0222). No corresponding changes were detected in R−. Relief-based feature selection identified the aperiodic exponent and the 20–35 Hz NSC feature from eight candidate biomarkers for training a Bayesian-optimized support vector machine. SHapley Additive exPlanations indicated comparable contributions from both features. These findings identify responder-specific changes in periodic and aperiodic spectral parameters and in nonlinear EEG descriptors following Pz-targeted HD-tDCS. They are consistent with modulation of cortical state and large-scale dynamics, but do not by themselves demonstrate excitation–inhibition rebalancing or thalamocortical loop reinforcement, and the single-arm design without sham stimulation precludes attribution of the observed changes specifically to HD-tDCS.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-14T11:01:37Z</dc:date>
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          <dc:type>Dataset</dc:type>
          <dc:identifier>10.3389/fnins.2026.1925503.s001</dc:identifier>
          <dc:relation>https://figshare.com/articles/dataset/Data_Sheet_1_Multidimensional_EEG_mechanisms_and_explainable_prediction_of_responsiveness_to_posterior_parietal_HD-tDCS_in_chronic_disorders_of_consciousness_pdf/33731620</dc:relation>
          <dc:rights>CC BY 4.0</dc:rights>
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