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Anandamohan Ghosh

Researcher at Centre national de la recherche scientifique

Publications -  16
Citations -  781

Anandamohan Ghosh is an academic researcher from Centre national de la recherche scientifique. The author has contributed to research in topics: Default mode network & Nonlinear system. The author has an hindex of 6, co-authored 10 publications receiving 678 citations. Previous affiliations of Anandamohan Ghosh include National Chemical Laboratory.

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Journal ArticleDOI

Noise during Rest Enables the Exploration of the Brain's Dynamic Repertoire

TL;DR: It is shown that comparable resting state networks emerge from a stability analysis of the network dynamics using biologically realistic primate brain connectivity, although anatomical information alone does not identify the network.
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Cortical network dynamics with time delays reveals functional connectivity in the resting brain.

TL;DR: By tuning the propagation velocity in a network based on primate connectivity, a hypothesis that time delays in the network dynamics play a crucial role in the generation of temporally coherent fluctuations is tested.
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Parameter estimation in spatially extended systems: the Karhunen-Lóeve and Galerkin multiple shooting approach.

TL;DR: In this paper, a combination of multiple shooting, Karhunen-Loeve decomposition and Galerkin's projection methodologies is used for spatiotemporal dynamics for coupled map lattices and continuous time domain systems.
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Simple model for bursting dynamics of neurons.

TL;DR: A simple one-dimensional model which requires only one phase variable to describe the phenomenon of parabolic bursting is introduced and it is demonstrated that the structure of the parameter space remains independent of the number of spikes per burst.
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Phase description of spiking neuron networks with global electric and synaptic coupling.

TL;DR: This work constructs a mathematical model based on a planar simplification of the Morris-Lecar model and demonstrates analytically that electric and synaptic coupling are differently expressed on the level of the network's phase description with qualitatively different dynamics.