By Simona Olmi (Sesto Fiorentino, Italy).

I will first give a brief overview of the next generation neural mass models, which represent a complete new perspective for the development of exact mean field models of heterogeneous spiking networks [1]. Then I will report recent results on the application of this formalism to reproduce relevant phenomena observed in neuroscience ranging from cross-frequency coupling [2] to theta-nested gamma oscillations [3]. I will finally show how these neural masses can be extended to mimic several operations associated with synaptic-based working memory [4] and to organize neural coding for multi-item messages when introducing spike-frequency adaptation [5].

References

[1] E.Montbrió, D.Pazó, A.Roxin. “Macroscopic description for networks of spiking neurons.” Physical Review X 5.2 (2015): 021028; S. Coombes, Á. Byrne. “Next generation neural mass models.” In Nonlinear dynamics in computational neuroscience, pp. 1-16. Springer, Cham (2019).

[2] A.Ceni, S. Olmi, A. Torcini, D. Angulo Garcia, “Cross frequency coupling in next generation inhibitory neural mass models”, Chaos ,30, 053121 (2020)

[3] M. Segneri, H.Bi, S. Olmi, A.Torcini, “Theta-nested gamma oscillations in next generation neural mass models”, Frontiers in Computational Neuroscience , 14:47 (2020)

[4] H. Taher, A. Torcini, S. Olmi, “Exact neural mass model for synaptic-based working memory”, PLOS Computational Biology , 16(12):e1008533 (2020)

[5] A. Ferrara, D. Angulo-Garcia, S. Olmi, A. Torcini, “Population spiking and bursting in coupled next generation neural masses with spike-frequency adaptation”, in preparation.


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