Paper List

期刊: ArXiv Preprint
发布日期: 2026-03-13
Computational NeuroscienceDynamical Systems

Pulse desynchronization of neural populations by targeting the centroid of the limit cycle in phase space

University of Padua | Abdus Salam International Center for Theoretical Physics | Université Paris Dauphine-PSL

Ramón Guevara, Marco Zenari, Giorgio Nicoletti, Elisa Marini, Samir Suweis, Sandro Azaele, Marco Formentin
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30秒速读

IN SHORT: This work addresses the core challenge of determining optimal pulse timing and intensity for desynchronizing pathological neural oscillations when the underlying dynamical system is unknown, by leveraging a robust geometric feature in phase space.

核心创新

  • Methodology Introduces a pulse desynchronization control strategy based on targeting the geometric centroid of the limit cycle in phase space, a point shown to be robust to changes in the coupling constant (ε).
  • Methodology Utilizes bivariate neural activity signals (e.g., X and Y averages) as feedback input, moving beyond traditional univariate approaches (like local field potential alone) to extract richer phase-space information.
  • Theory Demonstrates analytically and numerically that the centroid lies within a region of maximal return times to the limit cycle after perturbation, making it an effective target for prolonging desynchronized states with minimal pulses.

主要结论

  • Numerical simulations of a coupled FitzHugh-Nagumo system (N=1000) show the centroid's location is nearly independent of the coupling parameter ε (tested for ε ∈ {0.1, 0.2, 0.3, 0.4}), providing a robust target.
  • The centroid is strategically located near the dx/dt=0 nullcline within the region of maximal return times (visualized via interpolated heatmaps), delaying the system's return to the synchronized limit cycle.
  • The proposed control strategy, exploiting bivariate input and the centroid target, aims to achieve desynchronization with a significantly lower number of pulses compared to previous adaptive search methods, potentially reducing clinical side effects.
研究空白： Current closed-loop feedback desynchronization methods often rely on univariate signals and adaptive search strategies requiring many pulses, posing an inverse problem when system dynamics are unknown and increasing potential invasiveness.

摘要: The synchronized activity of neuronal populations can lead to pathological over-synchronization in conditions such as epilepsy and Parkinson disease. Such states can be desynchronized by brief electrical pulses. But when the underlying oscillating system is not known, as in most practical applications, to determine the specific times and intensities of pulses used for desynchronizaton is a difficult inverse problem. Here we propose a desynchronization scheme for neuronal models of bi-variate neural activity, with possible applications in the medical setting. Our main argument is the existence of a peculiar point in the phase space of the system, the centroid, that is both easy to calculate and robust under changes in the coupling constant. This important target point can be used in a control procedure because it lies in the region of minimal return times of the system.