Mini-course "Mean field models for brain activity at the mesoscopic scale" [Part 2]

Speaker: Matteo di Volo, Laboratoire de Physique Théorique et Modélisation. Cergy Paris Université. Cergy-Pontoise, France.

Summary: Accurate population models are needed to build very large-scale neural models, but their derivation is difficult for realistic networks of neurons. I will discuss different mean field techniques employed to develop neuronal population models [1,2], with their advantaged and drawbacks. I will then introduce more recent developments in this field [3,4], where population models are today able to describe very accurately the collective behaviour of neuronal networks. Finally, I will discuss how these models are employed to explain microscopic mechanisms standing behind emergent phenomena measured at the mesoscopic scale in the brain, such as propagating waves in the cortex [5,6].

[1] Wilson & Cowan, Biophys J. 12, 1-24 (1972)
[2] E. Montbro', D. Pazo', and A. Roxin,Phys. Rev. X5, 021028(2015)
[3] di Volo, M., Destexhe, A. Scientific Reports 11, 1-11 (2021)
[4] Goldobin, di Volo & Torcini Physical Review Letters 127, 038301 (2021)
[5] Chemla et al. Journal of Neuroscience 39, 4282 (2019)
[6] di Volo & Férézou, Scientific Reports 11, 19630 (2021)