Reconstruction scheme for excitatory and inhibitory dynamics with quenched disorder: application to zebrafish imaging

Year: 2021

Authors: Chicchi L., Cecchini G., Adam I., de Vito G., Livi R., Pavone FS., Silvestri L., Turrini L., Vanzi F., Fanelli D.

Autors Affiliation: Univ Florence, Dept Phys & Astron, Florence, Italy; Univ Florence, CSDC, Florence, Italy; Univ Florence, Dept Informat Engn, Florence, Italy; European Lab Nonlinear Spect, Florence, Italy; Univ Florence, Dept Neurosci Psychol Drug Res & Child Hlth, Florence, Italy; INFN Sez Firenze, Florence, Italy; Natl Res Councily, Natl Inst Opt, Florence, Italy; Univ Florence, Dept Biol, Florence, Italy.

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.

Journal/Review: JOURNAL OF COMPUTATIONAL NEUROSCIENCE

Volume: 49 (2)      Pages from: 159  to: 174

More Information: Open Access funding provided by Universita degli Studi di Firenze
KeyWords: Network reconstruction; Neuroscience; Heterogeneous mean field approximation; Leak integrate and fire; Zebrafish larva
DOI: 10.1007/s10827-020-00774-1

ImpactFactor: 1.453
Citations: 4
data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2024-09-15
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