PhD defense of Julien BALLBÉ Y SABATÉ

Julien BALLBÉ Y SABATÉ

Data-driven investigation of the heterogeneity of neuronal biophysical properties in the cerebral cortex

Abstract

Heterogeneity of neuronal biophysical properties is thought to play a crucial role in network properties. Yet a precise qualification and quantification of these neuronal properties’ heterogeneity is still lacking.

To leverage from the increasing number of publicly available databases of intracellular electrophysiological recordings, we designed a database-structure-independent data treatment pipeline, with the aim of overcoming the difference in databases’ organization, compensating for differences in curation, as well as proposing characterization methods versatile and robust enough to account for the intrinsic diversity of neuronal properties.

We use this pipeline to gather multiple databases of electrophysiological recordings and characterize the heterogeneity of biophysical properties according to different factors (e.g., cellular type, cortical layer, cortical area, animal…), while limiting the variance due to differences originating from database-specific acquisition protocols. This cross-database analysis of neuronal diversity represents a crucial step toward the establishment of biophysically constrained neuronal network models. Indeed, heterogeneity is known to represent a crucial aspect of neuronal networks, yet it has mainly been studied using theoretical variance (i.e., increasing the variance around the mean for particular properties).

Therefore, precisely reproducing electrophysiological heterogeneity at the neuronal level in network models can provide valuable insights as to the multiscale interaction mechanisms supporting the emergence of more complex network dynamical properties. To understand the role of biological neuronal heterogeneity in network dynamics,  we aim to construct a comprehensive large-scale neuronal network model that incorporates various aspects of neuronal networks (i.e., connectivity, synapses dynamics, cortical layer-specific cell type densities...) in a biologically constrained manner. This approach will be grounded in previous experimental studies from the literature that provide insights into the diverse characteristics of cortical networks.

Supervision

• Lyle J. Graham

Jury

• Lyle J. Graham, Docteur, Directeur de Thèse

• Michele Giugliano, Professeur, Rapporteur

• Frédéric Gambino, Docteur, Rapporteur

• Isabelle Férézou, Docteur, Examinatrice

• Michael Graupner, Docteur, Examinateur

• Joana Lourenço, Docteur, Examinatrice

• Fleur Zeldenrust, Docteur, Examinatrice