Job ID: 118120

PhD project: Identifying the distributed neural circuit for strategy selection

Position: Ph.D. Student

Deadline: 14 April 2024

Employment Start Date: 1 October 2024

Contract Length: 3 years

City: Marseille

Country: France

Institution: Aix-Marseille Université

Department: INT

Description:

The NeuroSchool PhD Program of Aix-Marseille University (France) has launched its annual calls for PhD contracts for students with a master’s degree in a non-French university. This project is one of the 13 proposed projects. Not all proposed projects will be funded, check our website for details.

State of the art
The brain has the remarkable ability to imagine different solutions to a problem and to rapidly switch between them to adapt to new situations. Such properties are essential for flexible behaviors but remain poorly understood. In mice, a premotor region called the secondary motor cortex (M2) can hold information about multiple decision strategies simultaneously. This “reservoir” of decision strategy could, in theory, provide a simple but powerful mechanism for flexibility, where new strategies are selected on the fly from the reservoir without the need to learn new computations. Nonetheless, whether the brain uses this solution is still controversial because experimental evidence of neural circuits performing such computations is sparse. Identifying the circuit underlying strategy selection is thus a timely challenge that will advance our understanding of distributed temporal information processing in the brain. 

Objectives
We will determine how a wide net of cortical and subcortical regions involved in sensory-motor transformation interact to support decision selection. 

Methods
Experiments: We will address our questions using mice in the context of foraging, a fundamental survival behavior shared among all animals, involving the search for resources in dynamic environments. Specifically, we will leverage a foraging task in virtual reality for head-fixed mice developed in the lab and use videography to monitor facial and body movements. During the behavior, we will record simultaneously large neuronal ensembles (hundreds of neurons) simultaneously in multiple brain region using next-generation Neuropixels probes. We will target M2 and connected areas known for their roles in rule and action selection. This includes sensory (somatosensory cortex and thalamus), frontal (orbitofrontal and anterior cingulate cortices) and motor (primary motor, dorsal striatum) areas. Analysis & models: We will dissect the computational properties of each region using multivariate regression and determine when information about task and decision variables first emerges. In collaboration with theoreticians, we will develop data-driven multi-regions recurrent neural network models that recapitulate activity propagation and make predictions about interactions between brain regions during strategy selection. 

Expected results
Results from this work will reveal how information is transformed across brain regions during the foraging decision. One specific prediction is that, while M2 encodes distributed information about multiple decision strategies, downstream motor regions (e.g. the striatum, M1), primarily represents the decision reflected behaviorally, which can be linearly decoded from M2 activity. Such a mechanism would concur with the hypothesis that M2 acts as a high-dimensional reservoir of decision strategy that are flexibly routed downstream. Our data-driven modelling approach will allow an unprecedented characterization of inter-areal communications, perhaps identifying changes in cortical dynamics as a general principle of flexibility. 

Feasibility 
The project is ambitious but highly feasible. The equipment (behavioral and recording set-ups) are in place and running at INT, with animals performing the task. A semi-automated pipeline for processing behavior and electrophysiology data is currently being developed. The training time required for each animal is relatively short (3 to 6 weeks). Therefore, we envision that the first 1.5 year will be dedicated to data collection and processing, and the second 1.5 year will be dedicated to analysis, modeling and paper writing. The project will be co-supervised by two researchers working in the same team at the Timone Neuroscience Institute: Fanny Cazettes (CRCN) and Guillaume Masson (DR1, HdR). The project is based on Fanny Cazettes’ scientific CNRS project and objectives, which has obtained a start-up funding from the Simons Foundation (NYC) in 2022. 

Expected candidate profile
The candidate is expected to have: (1) a solid scientific background in mathematics, physics or engineering, (2) coding proficiency (Python preferably), (3) a strong interest for systems neuroscience and (4) be willing to work with animal models.