Two SV Professors awarded SNSF Advanced Grants

Professors Bart Deplancke and Carl Petersen. Credit: Alain Herzog (EPFL)

Professors Bart Deplancke and Carl Petersen. Credit: Alain Herzog (EPFL)

Professors Bart Deplancke and Carl Petersen at EPFL’s School of Life Sciences have been awarded Advanced Grants from the Swiss National Science Foundation.

Following Switzerland's non-association to Horizon Europe as of 2021, the SNSF has on the government's behalf launched the Advanced Grants, aimed at researchers who intended to apply for an ERC Advanced Grant in 2021, and who “have a track record of outstanding research over the past ten years”, and who are recognized as a leader in their respective fields.

Today, the SNSF has announced the awardees of the 2021 call for Advanced Grants call. Among them are Professors Bart Deplancke and Carl Petersen at the EPFL School of Life Sciences.

SinPhonies project description (Deplancke)

The ability to identify which genes are expressed in a single cell, called single cell transcriptomics (scRNA-seq), is revolutionizing biology by allowing us to address fundamental problems with unprecedented resolution, such as how cells develop into a plastic tissue or how they trigger disease. However, several major technological limitations of scRNA-seq remain.

The project, named SinPhonies for Single cell Phenomic technologies, aims to design two autonomous but synergistic technologies that each address a key limitation to advance single cell phenomena coupled to scRNA-seq.

"Synaptic mechanisms of reward-based learning" (Petersen)

How do we learn to react in new situations? Animals learn how to behave, in part, through reward-based learning. Appropriate responses are rewarded, which causes reinforcement learning. Although reward-based learning is a major driving force of adaptive behavior, the neural circuit mechanisms underlying the reinforcement learning of any specific goal-directed sensory-to-motor transformation remain to be precisely determined.

The project will focus on developing and applying advanced technologies for measuring, manipulating and modelling the neuronal activity and synaptic plasticity mechanisms in a precisely-defined cortical region of the mouse brain during fast single-session reward-based learning. Experimental data combined with sophisticated computational analyses will probe causal mechanisms of cell type-specific changes for reward-based sensorimotor learning in a neocortical microcircuit, as well as probing the roles of various neuromodulators.