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Gustavo Deco

Researcher at Pompeu Fabra University

Publications -  720
Citations -  30047

Gustavo Deco is an academic researcher from Pompeu Fabra University. The author has contributed to research in topics: Resting state fMRI & Medicine. The author has an hindex of 78, co-authored 635 publications receiving 23808 citations. Previous affiliations of Gustavo Deco include Technische Universität München & University of Barcelona.

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Emerging concepts for the dynamical organization of resting-state activity in the brain

TL;DR: Three large-scale neural system models of primate neocortex that emphasize the key contributions of local dynamics, signal transmission delays and noise to the emerging RSNs are reviewed.
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The Dynamic Brain: From Spiking Neurons to Neural Masses and Cortical Fields

TL;DR: It is argued that elaborating principled and informed models is a prerequisite for grounding empirical neuroscience in a cogent theoretical framework, commensurate with the achievements in the physical sciences.
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Key role of coupling, delay, and noise in resting brain fluctuations

TL;DR: In numerical simulation, the dynamics of a simplified cortical network using 38 noise-driven (Wilson–Cowan) oscillators, which in isolation remain just below their oscillatory threshold are studied, indicating the presence of stochastic resonance and high sensitivity to changes in diffuse feedback activity.
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Ongoing Cortical Activity at Rest: Criticality, Multistability, and Ghost Attractors

TL;DR: This approach offers a realistic mechanistic model at the level of each single brain area based on spiking neurons and realistic AMPA, NMDA, and GABA synapses and fits quantitatively best the experimentally observed functional connectivity in humans when the brain network operates at the edge of instability.
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Can sliding-window correlations reveal dynamic functional connectivity in resting-state fMRI?

TL;DR: It is shown that in typical resting-state sessions of 10 min, it is almost impossible to detect dFC using sliding-window correlations, and it is found that most of the functional connections are in fact dynamic.