Pattern Formation in a Spiking Neural-Field of Renewal Neurons

التفاصيل البيبلوغرافية
العنوان: Pattern Formation in a Spiking Neural-Field of Renewal Neurons
المؤلفون: Dumont, Gregory, Tarniceriu, Carmen Oana
سنة النشر: 2024
المجموعة: Quantitative Biology
مصطلحات موضوعية: Quantitative Biology - Neurons and Cognition, 35B32, 35Q80
الوصف: Elucidating the neurophysiological mechanisms underlying neural pattern formation remains an outstanding challenge in Computational Neuroscience. In this paper, we address the issue of understanding the emergence of neural patterns by considering a network of renewal neurons, a well-established class of spiking cells. Taking the thermodynamics limit, the network's dynamics can be accurately represented by a partial differential equation coupled with a nonlocal differential equation. The stationary state of the nonlocal system is determined, and a perturbation analysis is performed to analytically characterize the conditions for the occurrence of Turing instabilities. Considering neural network parameters such as the synaptic coupling and the external drive, we numerically obtain the bifurcation line that separates the asynchronous regime from the emergence of patterns. Our theoretical findings provide a new and insightful perspective on the emergence of Turing patterns in spiking neural networks. In the long term, our formalism will enable the study of neural patterns while maintaining the connections between microscopic cellular properties, network coupling, and the emergence of Turing instabilities.
Comment: 23 pages, 10 figures
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2406.01167
رقم الأكسشن: edsarx.2406.01167
قاعدة البيانات: arXiv