Publications by authors named "Mauricio Girardi-Schappo"

4 Publications

  • Page 1 of 1

Altered communication dynamics reflect cognitive deficits in temporal lobe epilepsy.

Epilepsia 2021 Apr 11;62(4):1022-1033. Epub 2021 Mar 11.

Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.

Objective: Although temporal lobe epilepsy (TLE) is recognized as a system-level disorder, little work has investigated pathoconnectomics from a dynamic perspective. By leveraging computational simulations that quantify patterns of information flow across the connectome, we tested the hypothesis that network communication is abnormal in this condition, studied the interplay between hippocampal- and network-level disease effects, and assessed associations with cognition.

Methods: We simulated signal spreading via a linear threshold model that temporally evolves on a structural graph derived from diffusion-weighted magnetic resonance imaging (MRI), comparing a homogeneous group of 31 patients with histologically proven hippocampal sclerosis to 31 age- and sex-matched healthy controls. We evaluated the modulatory effects of structural alterations of the neocortex and hippocampus on network dynamics. Furthermore, multivariate statistics addressed the relationship with cognitive parameters.

Results: We observed a slowing of in- and out-spreading times across multiple areas bilaterally, indexing delayed information flow, with the strongest effects in ipsilateral frontotemporal regions, thalamus, and hippocampus. Effects were markedly reduced when controlling for hippocampal volume but not cortical thickness, underscoring the central role of the hippocampus in whole-brain disease expression. Multivariate analysis associated slower spreading time in frontoparietal, limbic, default mode, and subcortical networks with impairment across tasks tapping into sensorimotor, executive, memory, and verbal abilities.

Significance: Moving beyond descriptions of static topology toward the formulation of brain dynamics, our work provides novel insight into structurally mediated network dysfunction and demonstrates that altered whole-brain communication dynamics contribute to common cognitive difficulties in TLE.
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April 2021

Subsampled Directed-Percolation Models Explain Scaling Relations Experimentally Observed in the Brain.

Front Neural Circuits 2020 15;14:576727. Epub 2021 Jan 15.

Departamento de Física, Universidade Federal de Pernambuco, Recife, Brazil.

Recent experimental results on spike avalanches measured in the urethane-anesthetized rat cortex have revealed scaling relations that indicate a phase transition at a specific level of cortical firing rate variability. The scaling relations point to critical exponents whose values differ from those of a branching process, which has been the canonical model employed to understand brain criticality. This suggested that a different model, with a different phase transition, might be required to explain the data. Here we show that this is not necessarily the case. By employing two different models belonging to the same universality class as the branching process (mean-field directed percolation) and treating the simulation data exactly like experimental data, we reproduce most of the experimental results. We find that subsampling the model and adjusting the time bin used to define avalanches (as done with experimental data) are sufficient ingredients to change the apparent exponents of the critical point. Moreover, experimental data is only reproduced within a very narrow range in parameter space around the phase transition.
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January 2021

Hints from statistical physics and graph theory to build synthetic connectomes: Comment on "What would a synthetic connectome look like?" by I. Rabinowitch.

Phys Life Rev 2020 Jul 18;33:19-21. Epub 2020 Mar 18.

Unidade Acadêmica Especial de Ciências Exatas, Universidade Federal de Goiás - Regional Jataí, GO, 75801-615, Brazil. Electronic address:

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July 2020

Phase diagrams and dynamics of a computationally efficient map-based neuron model.

PLoS One 2017 30;12(3):e0174621. Epub 2017 Mar 30.

Departamento de Física, Universidade Federal de Santa Catarina, 88040-900, Florianópolis, Santa Catarina, Brazil.

We introduce a new map-based neuron model derived from the dynamical perceptron family that has the best compromise between computational efficiency, analytical tractability, reduced parameter space and many dynamical behaviors. We calculate bifurcation and phase diagrams analytically and computationally that underpins a rich repertoire of autonomous and excitable dynamical behaviors. We report the existence of a new regime of cardiac spikes corresponding to nonchaotic aperiodic behavior. We compare the features of our model to standard neuron models currently available in the literature.
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August 2017