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<p>Diagnosing patients with a Prolonged Disorders of Consciousness (pDoC) is challenging due to the inherent limitations of the behavioral assessments recommended by international rehabilitation guidelines. To address this, we applied temporal graph theory to resting-state EEG recordings from 217 patients with severe Acquired Brain Injury (sABI), with and without pDoC. Higher temporal degree centrality in the <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\theta\)</EquationSource> </InlineEquation> and <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\delta\)</EquationSource> </InlineEquation> bands, as well as a higher burstiness coefficient, were found in the pDoC group. In contrast, lower temporal correlation coefficient was observed in the <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\alpha\)</EquationSource> </InlineEquation> band in the pDoC group compared to the eMCS group. Furthermore, the analysis of separate frequency bands revealed different behavior of the average topological overlap, with higher values in the eMCS group in the <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(\alpha\)</EquationSource> </InlineEquation> band and higher values in the pDoC group in the <InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(\delta\)</EquationSource> </InlineEquation> band. Thus, repeatability of <InlineEquation ID="IEq6"> <EquationSource Format="TEX">\(\alpha\)</EquationSource> </InlineEquation>-connectivity between t-graphlets, the capability of sustaining more periodic-like changes in all-bands connectivity, and the higher integration of temporal network were found to be correlated with consciousness, providing valuable insights on the time-varying neural architecture of pDoC patients.</p>

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Temporal network instability and low-frequency overconnectivity underlie disorders of consciousness in severe brain injury

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月6日

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  • Diletta Bartolini,
  • Piergiuseppe Liuzzi,
  • Sara Secci,
  • Bahia Hakiki,
  • Maenia Scarpino,
  • Rachele Burali,
  • Azzurra di Palma,
  • Tanita Toci,
  • Antonello Grippo,
  • Francesca Cecchi,
  • Andrea Frosini,
  • Andrea Mannini

摘要

Diagnosing patients with a Prolonged Disorders of Consciousness (pDoC) is challenging due to the inherent limitations of the behavioral assessments recommended by international rehabilitation guidelines. To address this, we applied temporal graph theory to resting-state EEG recordings from 217 patients with severe Acquired Brain Injury (sABI), with and without pDoC. Higher temporal degree centrality in the \(\theta\) and \(\delta\) bands, as well as a higher burstiness coefficient, were found in the pDoC group. In contrast, lower temporal correlation coefficient was observed in the \(\alpha\) band in the pDoC group compared to the eMCS group. Furthermore, the analysis of separate frequency bands revealed different behavior of the average topological overlap, with higher values in the eMCS group in the \(\alpha\) band and higher values in the pDoC group in the \(\delta\) band. Thus, repeatability of \(\alpha\) -connectivity between t-graphlets, the capability of sustaining more periodic-like changes in all-bands connectivity, and the higher integration of temporal network were found to be correlated with consciousness, providing valuable insights on the time-varying neural architecture of pDoC patients.