Nonlinear collision between propagating waves in mouse somatosensory cortex

Autor: M. Di Volo, I. Férézou

Publikováno v: Scientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)

Abstract How does cellular organization shape the spatio-temporal patterns of activity in the cortex while processing sensory information? After measuring the propagation of activity in the mouse primary somatosensory cortex (S1) in response to singl

Externí odkaz: https://doaj.org/article/79bde5071bca4cfdae7fa27e473936c5

A mean-field approach to the dynamics of networks of complex neurons, from nonlinear Integrate-and-Fire to Hodgkin–Huxley models

Autor: Alain Destexhe, M. di Volo, Charlotte Héricé, M. Jedynak, L. Dalla Porta, Cristiano Capone, P. Muratore, E. Köksal Ersöz, Selma Souihel, Damien Depannemaecker, Yann Zerlaut, O. Chehab, M. Carlu

Publikováno v: Journal of Neurophysiology
Journal of Neurophysiology, 2020, 123 (3), pp.1042-1051. ⟨10.1152/jn.00399.2019⟩
Journal of Neurophysiology, American Physiological Society, 2020, 123 (3), pp.1042-1051. ⟨10.1152/jn.00399.2019⟩
Journal of Neurophysiology, American Physiological Society, In press, ⟨10.1152/jn.00399.2019⟩

We present a mean-field formalism able to predict the collective dynamics of large networks of conductance-based interacting spiking neurons. We apply this formalism to several neuronal models, from the simplest Adaptive Exponential Integrate-and-Fir

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79be53f8013973d65f930b138546acd7
https://doi.org/10.1152/jn.00399.2019

How single node dynamics enhances synchronization in neural networks with electrical coupling

Autor: Elena Bonacini, Raffaella Burioni, Cinzia Soresina, M. Di Volo, Alessandro Vezzani, Maria Groppi

Publikováno v: Chaos, solitons and fractals 85 (2016): 32–43. doi:10.1016/j.chaos.2016.01.009
info:cnr-pdr/source/autori:E. Bonacini, R. Burioni, M. di Volo, M. Groppi, C. Soresina, and A. Vezzani/titolo:How single node dynamics enhances synchronization in neural networks with electrical coupling/doi:10.1016%2Fj.chaos.2016.01.009/rivista:Chaos, solitons and fractals/anno:2016/pagina_da:32/pagina_a:43/intervallo_pagine:32–43/volume:85

The stability of the completely synchronous state in neural networks with electrical coupling is analytically investigated applying both the Master Stability Function approach (MSF), developed by Pecora and Carroll (1998), and the Connection Graph St

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5741d49f80e6e3c00fcbf3203ed7c2ed
https://doi.org/10.1016/j.chaos.2016.01.009

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