Neural dynamics underlying prospective motor control

Organisation/Company NeuroSchool, Aix-Marseille Université Research Field Psychological sciences » Psychology Biological sciences » Biology Medical sciences Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher (R1) Established Researcher (R3) Application Deadline 26 Apr 2026 - 22:00 (UTC) Country France Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Oct 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer 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 proposed projects. Not all proposed projects will be funded, check our website for details.

State of the art : To act efficiently, many animals including humans plan their actions before executing them. Planning is what allows us to refine, change, or cancel an impending action, and as such, is a core component of cognitive and motor flexibility. Yet, despite its fundamental role in behavior, our understanding of the circuit logic and underlying algorithms orchestrating planning in the brain is still remarkably incomplete. While prior work has mostly focused on the planning of simple and isolated movements in response to external stimuli, our natural behavior is inherently prospective: humans plan and organize extended action sequences, continuously refine them through sensory feedback, and make them increasingly fluid with practice. Understanding how the brain represents such future-oriented and temporally evolving planning processes is therefore a critical challenge for neuroscience.

Objectives : This PhD project aims to establish a population-level, dynamical understanding of how neural circuits encode planning horizon, the temporal depth over which future actions are represented, and how this representation evolves with practice and sensory feedback

Methods: The candidate will exploit multi-areal chronic neural recordings from premotor and parietal cortex, aligned with eye-tracking and kinematic measures, during variably constrained reaching tasks to: 1) characterize preparatory neural dynamics underlying complex action sequences, 2) track their learning-dependent reorganization, and 3) investigate how sensory and oculomotor signals contribute to the selection of planning strategies. State-space and neural manifold analyses will be used to identify planning-related representations beyond low-dimensional movement preparation.

Expected results : By introducing planning horizon as an explicit neural variable, this project aims to advance dynamical systems theories of motor planning and learning, providing foundations for anticipatory, planning-aware decoding strategies. In particular we hypothesize an increase of the planning horizon with extensive practice of complex action sequences that will be reflected in systematic modulation of preparatory dynamics.

Feasibility : The dataset used in the project has already been collected (authorization Apafis# v4) which minimizes the experimental risks/delays and will help expedite the publication process. Moreover, the student will be guided in its work by two experts in monkey electrophysiology and motor control and the analysis of high-dimensional neural datasets (Thomas Brochier & Nicolas Meirhaeghe).

Expected candidate profile : The ideal candidate should have strong background in neuroscience and sufficient expertise in mathematics (linear algebra) and computer science to handle complex data (fluent in Python/Matlab). Interests or prior experience in motor control and dynamical systems would be a plus.