Job Offer: 3-year PhD Grant in PhysioNet Team, In Vivo Group
3-year PhD Scholarships – Call for PhD Applications 2018 for students who validated a master’s from non-French universities
Aix-Marseille University (AMU) - PhD program in Integrative and Clinical Neuroscience
Title: Role of Nucleus Reuniens neurons in long term memory consolidation - Research project #16
Supervisors: Pascale Quilichini & Monique Esclapez
See the call in details and apply on NeuroMarseille.org _ DEADLINE: April 13th 2018
- State of the art
The long-term consolidation of information requires a dialogue between the hippocampus (HPC) and the prefrontal cortex (mPFC) (1-4). Within days, the information initially encoded by the HPC is gradually transferred to the mPFC (5-7), and such function involves the coordination of cell assemblies (i.e. a group of functionally connected neurons coding for the representation of the information) in both structures during slow wave sleep (8-11). However, the underlying mechanisms are poorly known. The Nucleus Reuniens (NR) is an anatomical relay connecting bi-directionally HPC and mPFC (12, 13). It is essential to long-term memory (14) and we have recently shown that NR is responsible for functionally coupling both structures during slow wave sleep (15).
The first objective of this PhD project is to determine how NR neurons control the recruitment of cell assemblies in HPC and mPFC. NR presents a specific neuronal type that sends axonal projections to both mPFC and HPC (16, 17), and such connectivity place them as ideal functional hubs. The second objective is to characterize their role in long-term memory consolidation.
This project uses a multi-disciplinary approach. Adult rats will be trained in a cheeseboard maze to quantify the long-term memorization of a rewarded location. Tetrodes and silicon probes will be implanted in the HPC, mPFC and NR to collect local field potentials and multi-unit activities. State-of-the-art mathematical treatment of the electrophysiological signal (some developed in the institute) will be used to correlate the network and neuronal activities to behavior to analyze the impact of NR activity on the recruitment of HPC and mPFC cell assemblies. The role of the double-projecting neurons in NR will be characterized using a double retrograde virus approach (18, 19) : a AV-2-CRE_GFP injected in HPC and a CAV-2-DIO_mCherry- coupled to a DREADD or an opsin under CRE control in mPFC will allow specific manipulation of these neurons. The chemical or light activation/inactivation of such neuronal sub-population at key moment of the consolidation will provide a way to establish causal links between these neurons activity and long-term memory.
- Expected Results
Our previous work already showed that the NR neurons activity is mandatory to couple mPFC and HPC, hence we expect to (i) quantify how it modulates the recruitment of cell assemblies in these structures and (ii) highlight the double-projection neurons as central hubs for processing long-term consolidation of memories. This project will provide the first core mechanisms underlying long-term memory.
- Feasibility over the 3-year period, including project financial support and ethics committee authorizations
This PhD project comes within the scope of a larger project on the HPC-mPFC-NR network, hence the candidate will be working within a team. Its objectives are focussed enough to be reached within 3 years. All the experimental and analysis tools are already available in the institute, which is composed of scientists of all the backgrounds explored by this project. We collaborate with the IGMM in Montpellier for the viral approach. The project is approved by the Comité d’Ethique de Marseille (Nº 01451-02).
- Expected Candidate Profile
The candidate must have a neuroscience background, preferentially in electrophysiology. The candidate must be comfortable working with behaving animals and motivated to learn and use multiple approaches: surgery, electrophysiological recordings, behavioral testing, functional anatomy, chemo/optogenetics and analysis (which involves coding with Matlab and Python).
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