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Exploring the dynamical transitions on an epileptic hippocampal network model and its modulation strategy based on transcranial magneto-acoustical stimulation

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Abstract

The mechanisms of network and transition dynamics of epileptiform activity remain unclear. In general, the transitions of epileptiform discharges comprise slow interictal discharges, ictal discharges and postictal depression. Studies have indicated that network properties and the inherent parameters of neuronal models have great impacts on the transitions. Recently, a novel neuromodulation technique, transcranial magneto-acoustical stimulation (TMAS), has been tested for its efficiency experimentally and computationally. In this paper, we establish a biophysical computational network model of an ictogenic hippocampus area to investigate the underlying transitions mechanisms and reveal neuromodulation mechanisms combined with TMAS. Results demonstrate that long distance connections caused by increased connection probability and the number of nearest-neighbour edges make the network more random and focused. The cooperation of network topological structure and neuronal parameters including ion concentration and inherent external input of neurons could induce epileptic transitions. Moreover, the focused ultrasound transducer has the ability to launch and focus the transcranial ultrasound wave to the hippocampal area in the depth of the three-layer tissue. By coupling with a static magnetic field, the proposed modulated induced TMAS currents can terminate epileptiform activity but consumes more energy by regulating magnetic strength. However, changing modulation frequency was unable to fully suppress seizures. These computational results offer an explanation of the mechanisms of neurodynamics of epileptiform discharges and its neuromodulation by TMAS.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Funding

This research was supported by the National Natural Science Foundation of China (Grant Nos. 12102014, 11932003, 32271361 and 12202022) and the National Key Research and Development Program of China (Grant Nos. 2021YFA1000200 and 2021YFA1000202).

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Authors and Affiliations

  1. Department of Biomedical Engineering, College of Chemistry and Life Science, Beijing University of Technology, Beijing, 100124, China

    Liyuan Zhang, Yuejuan Xu, Youjun Liu & Bao Li

  2. Cell and Developmental Biology, University College London, London, WC1E 6BT, UK

    Gerold Baier

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  1. Liyuan Zhang
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  2. Yuejuan Xu
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Contributions

LZ: Conceptualization, Methodology, Software, Writing original draft, Writing-reviewing and editing. YX: Designed, Performed the research, Analyzed the data, Writing the original draft. GB: Conceptualization, Methodology, Writing-reviewing and editing. YL: Conceptualization, Writing-reviewing. BL: Conceptualization, Methodology, Software, Writing-reviewing and editing.

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Correspondence to Bao Li.

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Zhang, L., Xu, Y., Baier, G. et al. Exploring the dynamical transitions on an epileptic hippocampal network model and its modulation strategy based on transcranial magneto-acoustical stimulation. Nonlinear Dyn (2024). https://doi.org/10.1007/s11071-024-09476-0

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