| Literature DB >> 33826050 |
Lorenzo Chicchi1,2, Gloria Cecchini3,4, Ihusan Adam1,2,5, Giuseppe de Vito6,7, Roberto Livi1,2,8, Francesco Saverio Pavone1,6,9, Ludovico Silvestri1,6,9, Lapo Turrini1,6, Francesco Vanzi6,10, Duccio Fanelli1,2,8.
Abstract
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.Entities:
Keywords: Heterogeneous mean field approximation; Leak integrate and fire; Network reconstruction; Neuroscience; Zebrafish larva
Year: 2021 PMID: 33826050 DOI: 10.1007/s10827-020-00774-1
Source DB: PubMed Journal: J Comput Neurosci ISSN: 0929-5313 Impact factor: 1.621