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Abnormal trial-to-trial variability in P300 time-varying directed eeg network of schizophrenia

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Abstract

Cognitive disturbance in identifying, processing, and responding to salient or novel stimuli are typical attributes of schizophrenia (SCH), and P300 has been proven to serve as a reliable psychosis endophenotype. The instability of neural processing across trials, i.e., trial-to-trial variability (TTV), is getting increasing attention in uncovering how the SCH “noisy” brain organizes during cognition processes. Nevertheless, the TTV in the brain network remains unrevealed, notably how it varies in different task stages. In this study, resorting to the time-varying directed electroencephalogram (EEG) network, we investigated the time-resolved TTV of the functional organizations subserving the evoking of P300. Results revealed anomalous TTV in time-varying networks across the delta, theta, alpha, beta1, and beta2 bands of SCH. The TTV of cross-band time-varying network properties can efficiently recognize SCH (accuracy: 83.39%, sensitivity: 89.22%, and specificity: 74.55%) and evaluate the psychiatric symptoms (i.e., Hamilton’s depression scale-24, r = 0.430, p = 0.022, RMSE = 4.891; Hamilton’s anxiety scale-14, r = 0.377, p = 0.048, RMSE = 4.575). Our study brings new insights into probing the time-resolved functional organization of the brain, and TTV in time-varying networks may provide a powerful tool for mining the substrates accounting for SCH and diagnostic evaluation of SCH.

Graphical abstract

Schematic view of the TTV in time-varying networks, as well as the patient’s recognition and psychiatric symptoms prediction based on the anomalous TTV of SCH. The TTV is getting increasing attention in understanding the “noise” brain of SCH, whereas a perspective in a time-varying directed network still lacking. We proposed to focus on the TTV in a time-varying directed EEG electroencephalogram (EEG) network to uncover how the brain unstably organizes during cognition processes and probe the instability of neural processing across trials during the P300 task process to find the potential mechanisms that account for the cognitive disturbance of SCH. Based on the P300 task EEG of SCHs and HCs, we revealed anomalous TTV in time-varying networks across the delta, theta, alpha, beta1, and beta2 bands of SCH. And the TTV of cross-band time-varying network properties can efficiently recognize SCH and evaluate the psychiatric symptoms.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (#62103085), the Open Project of Henan Key Laboratory of Brain Science and Brain Computer Interface Technology (HNBBL230203), the STI 2030-Major Projects (#2022ZD0208500).

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Author notes

  1. Chanlin Yi, Fali Li and Jiuju Wang contributed equally to this work.

Authors and Affiliations

  1. The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Chanlin Yi, Fali Li, Yuqin Li, Jiamin Zhang, Wanjun Chen, Lin Jiang, Dezhong Yao & Peng Xu

  2. School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, 611731, China

    Chanlin Yi, Fali Li, Yuqin Li, Jiamin Zhang, Wanjun Chen, Lin Jiang, Dezhong Yao & Peng Xu

  3. Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu, 2019RU035, China

    Fali Li & Dezhong Yao

  4. Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, China

    Fali Li

  5. Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China

    Jiuju Wang, Peng Xu & Wentian Dong

  6. School of Electrical Engineering, Zhengzhou University, Zhengzhou, 450001, China

    Dezhong Yao

  7. Radiation Oncology Key Laboratory of Sichuan Province, Chengdu, 610041, China

    Peng Xu

  8. Rehabilitation Center, Qilu Hospital of Shandong University, Jinan, 250012, China

    Peng Xu

  9. Department of Neurology, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China

    Baoming He

  10. Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, 610072, China

    Baoming He

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  1. Chanlin Yi
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Yi, C., Li, F., Wang, J. et al. Abnormal trial-to-trial variability in P300 time-varying directed eeg network of schizophrenia. Med Biol Eng Comput 62, 3327–3341 (2024). https://doi.org/10.1007/s11517-024-03133-9

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