Frontiers in Neuroinformatics (Aug 2024)

Investigating cortical complexity and connectivity in rats with schizophrenia

  • Zongya Zhao,
  • Zongya Zhao,
  • Zongya Zhao,
  • Yifan Feng,
  • Yifan Feng,
  • Menghan Wang,
  • Menghan Wang,
  • Jiarong Wei,
  • Jiarong Wei,
  • Tao Tan,
  • Tao Tan,
  • Ruijiao Li,
  • Ruijiao Li,
  • Heshun Hu,
  • Heshun Hu,
  • Mengke Wang,
  • Mengke Wang,
  • Peiqi Chen,
  • Peiqi Chen,
  • Xudong Gao,
  • Xudong Gao,
  • Yinping Wei,
  • Yinping Wei,
  • Chang Wang,
  • Chang Wang,
  • Chang Wang,
  • Zhixian Gao,
  • Zhixian Gao,
  • Zhixian Gao,
  • Wenshuai Jiang,
  • Wenshuai Jiang,
  • Wenshuai Jiang,
  • Xuezhi Zhou,
  • Xuezhi Zhou,
  • Xuezhi Zhou,
  • Mingcai Li,
  • Mingcai Li,
  • Mingcai Li,
  • Chong Wang,
  • Chong Wang,
  • Chong Wang,
  • Ting Pang,
  • Ting Pang,
  • Ting Pang,
  • Yi Yu,
  • Yi Yu,
  • Yi Yu

DOI
https://doi.org/10.3389/fninf.2024.1392271
Journal volume & issue
Vol. 18

Abstract

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BackgroundThe above studies indicate that the SCZ animal model has abnormal gamma oscillations and abnormal functional coupling ability of brain regions at the cortical level. However, few researchers have focused on the correlation between brain complexity and connectivity at the cortical level. In order to provide a more accurate representation of brain activity, we studied the complexity of electrocorticogram (ECoG) signals and the information interaction between brain regions in schizophrenic rats, and explored the correlation between brain complexity and connectivity.MethodsWe collected ECoG signal from SCZ rats. The frequency domain and time domain functional connectivity of SCZ rats were evaluated by magnitude square coherence and mutual information (MI). Permutation entropy (PE) and permutation Lempel-Ziv complexity (PLZC) were used to analyze the complexity of ECoG, and the relationship between them was evaluated. In addition, in order to further understand the causal structure of directional information flow among brain regions, we used phase transfer entropy (PTE) to analyze the effective connectivity of the brain.ResultsFirstly, in the high gamma band, the complexity of brain regions in SCZ rats is higher than that in normal rats, and the neuronal activity is irregularity. Secondly, the information integration ability of SCZ rats decreased and the communication of brain network information was hindered at the cortical level. Finally, compared with normal rats, the causal relationship between brain regions of SCZ rats was closer, but the information interaction center was not clear.ConclusionThe above findings suggest that at the cortical level, complexity and connectivity are valid biomarkers for identifying SCZ. This bridges the gap between peak potentials and EEG. This may help to understand the pathophysiological mechanisms at the cortical level in schizophrenics.

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