[Comp-neuro] PhD position in theoretical and experimental neuroscience

Nicolas P. Rougier nicolas.rougier at inria.fr
Fri Jul 24 13:53:17 CEST 2020


PhD position in theoretical and experimental neuroscience
Application deadline: 15/08/2020

What:  PhD position in theoretical and experimental neuroscience
Where: Bordeaux, France
When:  October 2020 (3 years duration)
Who:   Nicolas Rougier (Inria) & Arthur Leblois (CNRS)

A PhD position is available at Inria Bordeaux Sud-Ouest center and 
the
Institute of Neurodegenerative Disease in Bordeaux, France.

Candidate profile
=================

The future PhD candidate must have a ​strong experience at both the 
theoretical and experimental level​. In particular, the following 
qualities and skills will be highly valued, if not required:

* Solid bases in maths and/or physics;
* Previous experience in experimental neuroscience;
* Programming experience (Python or similar coding language);
* Experience in machine learning or data mining is a plus;
* Good English reading/speaking skills.

How to apply
============

Please send your application (CV, letter of motivation, and the 
names and email
addresses of one or two persons who can provide recommendation 
letters) to
Dr. Nicolas Rougier (nicolas.rougier at inria.fr) and Arthur Leblois
(arthur.leblois at u-bordeaux.fr) before the 15/08/2020.

Proposed research
=================

Temporally precise movement patterns underlie many motor skills 
and innate
actions, yet the origin of temporal control in motor behaviors 
remains
unclear. While cortical motor regions traditionally have been 
viewed as
encoding features of motor gestures, these models do not address 
how sequences
of motor gestures are produced or appropriately timed. Recently, a 
number of
studies have suggested that, beyond just representing features of 
motor output,
motor regions may have intrinsic oscillatory dynamics or 
sequential dynamics to
act as their own pattern generators. However, in the order of 
milliseconds, the
neural and anatomical correlates of time processing are still 
largely unknown
because the dominant model, which is based on internal clock fails 
at giving
account on experimental data. Understanding the neural dynamics 
underlying the
acquisition and performance of complex sensorimotor tasks has been 
hindered by
the complexity of the underlying brain networks in common animal 
models used in
neuroscience (e.g. rodents or primates). In particular, the 
complex
interactions between cortical areas (primary and secondary motor 
cortex in
rodents, motor, premotor and supplementary motor areas in 
primates) related to
many different sensorimotor associations and motor skills is
daunting. Conversely, in birds, the sensorimotor skill of song 
production and
its learning has a dedicated set of interconnected brain nuclei 
known as the
“song system”, making them an outstanding model to study the 
neural mechanisms
of vocal learning and more generally, of sensorimotor 
learning. Songbirds
indeed rely on learned vocalizations to communicate during 
courtship or
aggressive behaviours. Just as speech learning in humans, vocal 
learning in
young birds requires the coordination of vocal muscles to 
reproduce previously
experienced adult vocalizations. Song learning is also limited to 
a critical
period during development and heavily relies on auditory feedback.

The proposed research lies at the interface of neurophysiology, 
cognitive
science, applied mathematics, and theoretical physics. The 
concepts and methods
that will be used will draw on single neuron physiology, 
electrophysiological
studies in behaving animals, statistical mechanics, dynamical 
system theory,
and stochastic differential equations. To this end, we will 
combine a
theoretical approach (development of a mathematical model of the 
timing system)
and an experimental one (chronic neural recording in awake birds, 
behavioural
manipulations). Therefore, a collaboration with a team of 
physiologists at the
Institute of Neurodegenerative Diseases, and in particular with 
Arthur Leblois
who has a long-established expertise in the neural mechanisms 
underlying vocal
learning in songbirds. The model will be designed under the 
supervision of
Nicolas Rougier who has extensive experience in computational 
modelling.
Predictions of the model will then be tested experimentally by 
measuring
neuronal activity in the brain areas controlling song timing in 
songbirds under
the supervision of Arthur Leblois. Chronic electrophysiological 
recordings in
singing birds are routinely performed in the lab of Arthur 
Leblois, and will be
implemented in a protocol allowing the induction of plasticity in 
the duration
of song syllables in young adult birds over short periods of time.


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