Computational modeling of cortical interactions during comparative decision making.

Interacting with our environment constantly requires to use different sources of information. For example, detecting a friend in a crowded environment requires to compare sensory representation to cognitive representation (such as specificity of visual characteristics of our friend). We recently proposed that one specific area of the parietal cortex plays an important role during the comparison of what we are looking at to what we are looking for. We hypothesized that this area integrates and compares bottom-up sensory information (what we are looking at) to top-down cognitive representation (what we are looking for) from the prefrontal cortex in order to encode signal related to the behavioral significance of the stimuli which can be used during decision making processes.
Based on these data, we developed a network of artificial spiking neurons whose activity reproduce crucial aspects of our experimental data. This internship is to (i) develop and enhance this computational model of the parietal cortex,to develop and include an model of (ii) the prefrontal and (iii) the visual cortex and to test interactions within this large cortical network. This will allow us to test how this bio-inspired network reacts to different stimulation as well as to develop new hypothesis. The student will work in closed collaboration with Guilhem Ibos and Laurent Perrinet.
In addition, the student will participate to behavioral training of two non-human primates to perform a task which will allow us to test the interactions between sensory, cognitive and decision-related systems. Further electrophysiological experiments will allow us to directly test the hypothesis raised during this master 2 internship.

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