A group of students from the EITN Spring School in Computational Neuroscience recently published an article in the Journal of Neurophysiology. The final version was published in March 2020.

Each year, the European Institute for Theoretical Neuroscience (EITN) organizes a Spring School in Computational Neuroscience. Students form thematic groups to work on predefined subjects with a tutor. This article emerged from the project "Mean-field". The results were very impressive. Thus, the course director Alain Destexhe and the tutors, Matteo di Volo and Cristiano Capone, decided to write an article. The paper, where all students are co-first authors, was reviewed and finally published.

In this publication, the authors present a mean-field formalism able to predict the collective dynamics of large networks of neurons modeled with biophysically realistic representations, such as conductance-based Hodgkin-Huxley models.
 

Read the full research article: 

Carlu M, Chehab O, Dalla Porta L, Depannemaecker D, Héricé C, Jedynak M, Köksal Ersöz E, Muratore P, Souihel S, Capone C, Zerlaut Y, Destexhe A, di Volo M. A mean-field approach to the dynamics of networks of complex neurons, from nonlinear Integrate-and-Fire to Hodgkin–Huxley models. J Neurophysiol123: 1042–1051, 2020. First published online on December 18, 2019.