: The modeling of extended microcircuits is emerging as an effective tool to simulate the neurophysiological correlates of brain activity and to investigate brain dysfunctions. However, for specific networks, a realistic modeling approach based on the combination of available physiological, morphological and anatomical data is still an open issue. One of the main problems in the generation of realistic networks lies in the strategy adopted to build network connectivity. Here we propose a method to implement a neuronal network at single cell resolution by using the geometrical probability volumes associated with pre- and postsynaptic neurites. This allows us to build a network with plausible connectivity properties without the explicit use of computationally intensive touch detection algorithms using full 3D neuron reconstructions. The method has been benchmarked for the mouse hippocampus CA1 area, and the results show that this approach is able to generate full-scale brain networks at single cell resolution that are in good agreement with experimental findings. This geometric reconstruction of axonal and dendritic occupancy, by effectively reflecting morphological and anatomical constraints, could be integrated into structured simulators generating entire circuits of different brain areas facilitating the simulation of different brain regions with realistic models.

A realistic morpho-anatomical connection strategy for modelling full-scale point-neuron microcircuits

Gandolfi, Daniela
;
Mapelli, Jonathan;Solinas, Sergio;De Schepper, Robin;Geminiani, Alice;Casellato, Claudia;D'Angelo, Egidio;
2022-01-01

Abstract

: The modeling of extended microcircuits is emerging as an effective tool to simulate the neurophysiological correlates of brain activity and to investigate brain dysfunctions. However, for specific networks, a realistic modeling approach based on the combination of available physiological, morphological and anatomical data is still an open issue. One of the main problems in the generation of realistic networks lies in the strategy adopted to build network connectivity. Here we propose a method to implement a neuronal network at single cell resolution by using the geometrical probability volumes associated with pre- and postsynaptic neurites. This allows us to build a network with plausible connectivity properties without the explicit use of computationally intensive touch detection algorithms using full 3D neuron reconstructions. The method has been benchmarked for the mouse hippocampus CA1 area, and the results show that this approach is able to generate full-scale brain networks at single cell resolution that are in good agreement with experimental findings. This geometric reconstruction of axonal and dendritic occupancy, by effectively reflecting morphological and anatomical constraints, could be integrated into structured simulators generating entire circuits of different brain areas facilitating the simulation of different brain regions with realistic models.
2022
Physiology considers resources that study the regulation of biological functions at the level of the whole organism. This includes research from biochemical, cell biological and whole system studies of human and animal physiology. Comparative physiology, biological rhythms, and physiological measurement are also included. Resources emphasizing cellular regulation, or the physiology of specific organs are excluded and are covered in the Cell & Developmental Biology and Medical Research: Organs & Systems categories.
Inglese
12
1
Correzione: A realistic morpho-anatomical connection strategy for modelling full-scale point-neuron microcircuits (vol 12, 13864, 2022) - DOI 10.1038/s41598-022-23710-y
AREA CA1, HIPPOCAMPAL, PROPAGATION, NETWORK, RECONSTRUCTION, SIMULATION
no
8
info:eu-repo/semantics/article
262
Gandolfi, Daniela; Mapelli, Jonathan; Solinas, Sergio; De Schepper, Robin; Geminiani, Alice; Casellato, Claudia; D'Angelo, Egidio; Migliore, Michele...espandi
1 Contributo su Rivista::1.1 Articolo in rivista
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1497437
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