Post-doctoral position to study neural correlates of auditory learning in ferrets

 A 3-year post-doc position is available in the Neuro Platform of the Audition team (Laboratory of Perceptive Systems-LSP, ENS, Paris). The Neuro platform is a group of the LSP which investigates cognitive processes of auditory perception with electrophysiology and functional imaging in behaving animals. This project will be  conducted under the supervision of Yves Boubenec.

Project description:

Learning is a fundamental property of the cortex, enabling a broad range of cognitivefunctions occurring on multiple spatial and time-scales. However, the temporal dynamics andspatial interactions of the neural mechanisms underlying auditory learning remain largelyobscure. The aim of this post-doc position is to understand and track brain plasticity over both rapid (s/mn) andslower (day/week) time-scales in ferret auditory cortex during learning of a natural sound-based behavioral task.  Using a combination of multielectrode electrophysiology andfunctional ultrasound (fUS) imaging during learning, we will investigate changes in functional maps and theemergence of task-relevant signals in auditory cortex at the population level, in parallel to the sequential engagement of frontal cortex that further control and refine theserepresentations.

References:

• Bagur, S. , Averseng, M., Elgueda, D., David, S., Fritz, J., Yin, P., Shamma, S., Ostojic*, S. & Boubenec*, Y. (2018). Go/No-Go task engagement enhances population representation of target stimuli in primary auditory cortex. Nature Comm., 9, 2529 . doi:10.1038/s41467-018-04839-9
• Bimbard, C., Demene, C. , Girard, C. , Radtke-Schuller, S., Shamma, S., Tanter*, M. & Boubenec*, Y. (2018). Multi-scale mapping along the auditory hierarchy using high-resolution functional UltraSound in the awake ferret. eLIFE. doi:10.7554/eLife.35028.001

Start date:

Starting date for the position is September 1st, 2019 or later. The position is initially available for 3 years, with a possible extension by 1 year.

Requirements:

• The candidate should have a PhD (or be in the final stages of obtaining such a degree) in Neuroscience or areas related to quantitative analysis of neural data (imaging or electrophysiological data).
• Experience with data analysis along with strong programming and statistical skills (Matlab or python).
• Strong language and writing skills in English are required (note: speaking French is not required).

Please send a complete CV, a cover letter and contact information of two references boubenec@ens.fr,and feel free to send an email for more information!

Funding and salary: 

The position is funded by the ANR DynaMiC (30,000 euros/year net).