Understanding combinatorial neuromodulation using biophysical models

Description du projet

Un aperçu moléculaire du contrôle de l’activité neuronale

Le cerveau utilise des messagers chimiques appelés neuromodulateurs, tels que la dopamine, la sérotonine et l’acétylcholine, pour réguler l’activité neuronale et adapter le comportement. Les déséquilibres au sein de ces systèmes sont à l’origine de troubles très répandus, notamment la dépression et la schizophrénie. Si les neuromodulateurs ont fait l’objet d’études approfondies, la manière dont plusieurs d’entre eux agissent simultanément pour façonner la dynamique des circuits neuronaux reste mal comprise. Soutenu par le programme Actions Marie Skłodowska-Curie, le projet NEUROMODelling vise à établir le premier cadre global de contrôle neuromodulatoire combiné. Dans ce contexte, les chercheurs intégreront des enregistrements simultanés de l’activité neuronale et des niveaux de multiples neuromodulateurs à une modélisation computationnelle. Les résultats permettront de faire progresser la compréhension fondamentale de la régulation des états cérébraux et jetteront les bases d’une recherche translationnelle sur les déséquilibres neuromodulateurs dans les troubles neurologiques et psychiatriques.

Objectif

Neuromodulators are key controllers of neuronal activity, orchestrating brain state transitions that allow humans to adapt their behaviour to internal needs and environmental demands. Disruptions in the neuromodulatory balance lead to highly prevalent mental and mood disorders, including depression and schizophrenia, identified as top priorities by the WHO.

Neuromodulators are released simultaneously and target neurons express multiple receptors for all of them, yet crucially, how they jointly shape the activity and dynamics of neuronal circuits remains largely unknown. To solve this question, we need to describe and explain how neuromodulator receptors activation mechanistically influences neuronal activity, from the perspective of both biophysics and dynamical systems.

This project will address this critical gap in our understanding of the brain by integrating, for the first time, the analysis of simultaneous neuronal and multi-neuromodulator recordings with mean-field and mechanistic biophysical models, to accurately map how changes in the neuromodulatory landscape modulate circuit dynamics and support different behaviours. These results will guide future research, and lay the foundations for translational studies on how neuromodulatory imbalances drive neurodegenerative and mood disorders.

In summary, this project will leverage my experience in neural data analysis and modeling with the unique experimental capacity and available data in the host lab, enabling us for the first time to generate a holistic framework for addressing the role of combined neuromodulators in organizing neuronal activity.

This fellowship will accelerate my path to independence, that will enable me to establish and implement my research program focused on how the complex combination of physiological signals, internal brain states, and anatomical constraints shape spontaneous brain activity.