This study investigates a biologically constrained computational model of the hippocampal-cortical circuit incorporating magnetic-flow feedback to elucidate the nonlinear dynamical mechanisms through which magnetic stimulation modulates network states and drives transitions among memory-related neural rhythms. Bifurcation analysis characterizes the response of the hippocampal CA3 excitatory population to variations in the magnetic-flow feedback coefficients. One-parameter bifurcation analysis identifies critical bifurcations governing rhythm initiation, stability, and complexity, whereas two-parameter bifurcation diagrams show that cortical feedback expands the oscillatory regime more strongly than hippocampal feedback. Combined feedback produces the largest expansion and generates closed torus-bifurcation curves, indicating quasi-periodic dynamics. An automated sharp wave ripple (SWR) detection algorithm quantifies the incidence of model-derived SWR-related events across feedback conditions, thereby relating changes in the magnetic-flow feedback coefficients to changes in simulated SWR-related rhythmic activity. We further examine how SWR counts depend on two key CX1 microcircuit parameters: excitatory self-connection strength and local connectivity probability. Comparative analysis of SWR distributions illustrates how the network transitions from baseline quiescence or irregular firing to coherent, feedback-driven rhythmic discharge. SWR-count heatmaps further map the modulation of SWR-related activity across the parameter space. Collectively, these results establish a theoretical framework for understanding how magnetic-flow feedback modulates hippocampal-cortical dynamics and SWR-related activity, providing a basis for investigating targeted magnetic neuromodulation in memory-related neural processes.
Citation: Xin Jiang, Jialiang Nie, Denggui Fan, Lixia Duan. Magnetic flow drives hippocampal-cortical memory rhythm shifts through bifurcation dynamics[J]. Electronic Research Archive, 2026, 34(12): 8756-8785. doi: 10.3934/era.2026369
This study investigates a biologically constrained computational model of the hippocampal-cortical circuit incorporating magnetic-flow feedback to elucidate the nonlinear dynamical mechanisms through which magnetic stimulation modulates network states and drives transitions among memory-related neural rhythms. Bifurcation analysis characterizes the response of the hippocampal CA3 excitatory population to variations in the magnetic-flow feedback coefficients. One-parameter bifurcation analysis identifies critical bifurcations governing rhythm initiation, stability, and complexity, whereas two-parameter bifurcation diagrams show that cortical feedback expands the oscillatory regime more strongly than hippocampal feedback. Combined feedback produces the largest expansion and generates closed torus-bifurcation curves, indicating quasi-periodic dynamics. An automated sharp wave ripple (SWR) detection algorithm quantifies the incidence of model-derived SWR-related events across feedback conditions, thereby relating changes in the magnetic-flow feedback coefficients to changes in simulated SWR-related rhythmic activity. We further examine how SWR counts depend on two key CX1 microcircuit parameters: excitatory self-connection strength and local connectivity probability. Comparative analysis of SWR distributions illustrates how the network transitions from baseline quiescence or irregular firing to coherent, feedback-driven rhythmic discharge. SWR-count heatmaps further map the modulation of SWR-related activity across the parameter space. Collectively, these results establish a theoretical framework for understanding how magnetic-flow feedback modulates hippocampal-cortical dynamics and SWR-related activity, providing a basis for investigating targeted magnetic neuromodulation in memory-related neural processes.
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Xin Jiang, Jialiang Nie, Denggui Fan, Lixia Duan. Magnetic flow drives hippocampal-cortical memory rhythm shifts through bifurcation dynamics[J]. Electronic Research Archive, 2026, 34(12): 8756-8785. doi: 10.3934/era.2026369
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