| Autor: |
Chicchi, Lorenzo, Cecchini, Gloria, Adam, Ihusan, de Vito, Giuseppe, Livi, Roberto, Pavone, Francesco Saverio, Silvestri, Ludovico, Turrini, Lapo, Vanzi, Francesco, Fanelli, Duccio |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Journal of Computational Neuroscience 49, 159-174 (2021) |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1007/s10827-020-00774-1 |
| Popis: |
An inverse procedure is developed and tested to recover functional and structural information from global signals of brains activity. The method assumes a leaky-integrate and fire model with excitatory and inhibitory neurons, coupled via a directed network. Neurons are endowed with a heterogenous current value, which sets their associated dynamical regime. By making use of a heterogenous mean-field approximation, the method seeks to reconstructing from global activity patterns the distribution of in-coming degrees, for both excitatory and inhibitory neurons, as well as the distribution of the assigned currents. The proposed inverse scheme is first validated against synthetic data. Then, time-lapse acquisitions of a zebrafish larva recorded with a two-photon light sheet microscope are used as an input to the reconstruction algorithm. A power law distribution of the in-coming connectivity of the excitatory neurons is found. Local degree distributions are also computed by segmenting the whole brain in sub-regions traced from annotated atlas. |
| Databáze: |
arXiv |
| Externí odkaz: |
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