Abstracts 2023-Inferring

Hugues Berry (https://www.inrialpes.fr/Berry/) is a research director, (i.e., a research full professor, with tenure) with Inria, the French national institute for research in digital science and technology. A computational neuroscientist, his research focuses on mathematical and computer models of the spatiotemporal dynamics of biochemical reactions involved in brain cells. In recent years, he has been focusing on the modelling of the reaction networks that support synaptic plasticity, especially endocannabinoid plasticity. He has also proposed models for the metabolic and signalling networks at play in astrocyte activity and in astrocyte-neuron interactions. From 2018 to 2023, he has served as deputy scientific director of Inria, in charge of the research in digital biology and health, implementing Inria’s strategy on the application of numerical sciences (applied mathematics, computer science, artificial intelligence) to biology and health. Since 2023, he is co-heading AIstroSight, a joint research group between Inria, the Hospices Civils de Lyon (Lyon University Hospital), and Université Claude Bernard Lyon 1. The overall goal of AIstroSight is to develop innovative numerical methods for neuropharmacology, the search of new drug candidates to treat brain diseases.

That astrocytes are important for brain functions has been known for long: they provide energy support to the neurons via neurovascular coupling, they also contribute to the blood-brain barrier. Nevertheless, more recent discoveries have led to realize that their interactions with the neurons are probably more intimate. In addition to their regulation of local potassium levels, they emit fine cytoplasmic processes that interact with synapses using the same types of mechanisms as those that support information transfer between the presynaptic and postsynaptic elements. This led to the emergence of the concept of a “tripartite synapse” as a new functional unit for information transmission. However, astrocytes are not easy to study for the experimentalist. They cannot be easily characterized by electrophysiology because they lack action potentials. And a substantial part of these cells is too thin to be observed by conventional light microscopy. As a result, a number of issues are still unclear: is intracellular calcium the support of astrocyte activity? If yes, in what part of the cell and with what integration rules? Do astrocytes release chemical messages, called gliotransmitter, that directly affect the synapses in vivo? Are there different subtypes of astrocytes, functionally? Is there a correlation between the (local) shape of the cell and the (local) function it performs? What metabolites do they provide to the neurons, and under what circumstances? Of course, the answers to these questions are crucial when one wants to build mathematical models for the effects of astrocytes. In this lecture, my goal is to give an overview of these open questions, and show how they are related to the ongoing effort toward the mathematical modelling of astrocytes and their interactions with neural networks.

Up-Down synchronization of neuronal networks is a regime of collective dynamics whereby a neuronal population spontaneously switches between periods of high collective firing activity (Up state) and periods of silence (Down state). Recent experimental evidence has reported that astrocytes can control the emergence of such Up-Down regimes in neural networks, although the involved mechanisms are uncertain. To explore how astrocytes can control this phenomenon, we have studied neural network models made of three populations of cells: excitatory neurons, inhibitory neurons and astrocytes, interconnected by synaptic and gliotransmission events. Using simulation and bifurcation analysis, we show that the presence of astrocytes in these models indeed promo