CE37 - Neurosciences intégratives

Exact Reduction of Multiscale Neural Dynamics – ERMUNDY

Submission summary

The dynamics of large-scale brain networks are at the origin of the signals measured via human invasive and non-invasive recordings and imaging. The recent decade saw the emergence of a novel generation of mathematical network models acknowledging the large-scales, using personalized connectivity matrices derived from individual structural imaging data and reproducing functional brain imaging signals. These innovative modelling approaches have recently entered in the clinical domain including stroke, epilepsy and neuro-degenerative diseases. Key requirements for these models to be successful in applications of personalized medicine are high-quality connectomes, biologically realistic population models and good paradigms for proper validation.
Our project aims to directly address two of these latter requirements. We propose to extend to multiscale neural circuits a novel mathematical formalism, Exact Reduced Methodology (ERM), able to reproduce exactly the collective dynamics of large spiking neural networks, while taking into account properties of the constituent neurons and circuits. Notably we will focus on the ubiquitously observed coherent patterns of multi-frequency brain oscillations, including as well cross frequency-coupled (CFC) dynamics, that have been linked to cognitive function. We will use the novel population models as network nodes in large-scale brain networks, which we will build based on realistic human connectomes (eventually, personalized when single patient tractography data are available). So far connectome-based models were tested for resting state dynamics. Here we increase the predictive power significantly by introducing a new paradigm and performing systematic perturbation studies, thereby testing the response dynamics of the models far beyond the resting state. Experimentally we realize this paradigm by the systematic exploration of the individual brain signal transients in the cohort using: on one side intracranial electric stimulation and stereo-electroencephalography (SEEG) in epileptic patients in pre-surgical evaluation; and, on another side simultaneous transcranial magnetic stimulation (TMS) and electroencephalography (EEG). We will link the novel mathematical population models and empirical data by determining the Phase Resetting Curve (PRC) for the stimulated brain areas for each subject of the experiment and we will study the emergence of CFC and its stability to perturbations at population level. This information will enable us to infer the properties of the ERM-based connectome for the collective dynamics localised at the stimulated node as well as phase coupling to other locations recorded in EEG. Together the new theoretical framework, the novel paradigm and the link to human brain electrophysiological and imaging data, will enable us to examine central hypotheses on how the flexible inter-regional coordination is shaped by large-scale brain network dynamics. Since inter-regional oscillatory coherence is disrupted in a variety of psychiatric and neurological diseases, our research will enable: novel PRC- and CFC-based diagnostic tools; and, in perspective, the model-assisted design of non-invasive stimulation protocols for the selective “repair” of altered functional connections. Here we will explore this possibility by manipulating resting state functional connectivity with TMS and by studying the functional connectivity alterations in the language system induced by intracranial stimulation, putting it in systematic relation with the severity of the observed transient aphasia symptoms.

Project coordination

Alessandro Torcini (Laboratoire de Physique Théorique et Modélisation)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.


INS Institut de Neurosciences des Systèmes
LPTM Laboratoire de Physique Théorique et Modélisation

Help of the ANR 493,355 euros
Beginning and duration of the scientific project: October 2018 - 48 Months

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