Principal investigator : Adrian PALACIOS.
On going work : Hardware and Software design of a new recording set-up to obtain spikes responses synchronized with natural stimulus presentation.
[A] Build an Images sequences generator
[B] Build an OLED programing device for stimuli presentation
[C] Implementation of a Spike Sorting Algorithm (in collaboration with O. Marre)
Collect existing and new experimental facts on standard and no-standard behaviors of retinal ganglions cells in order to understand the computational capabilities of the retina under natural scenes.
– Visual stimulator development : Artificial + Natural stimuli
– Natural image stimuli preparation
– Spike-sorting implementation and benchmarking
– Receptive field computation and benchmarking
Publications:
Abstract: This chapter focuses on methods from statistical physics and probability theory allowing the analysis of spike trains in neural networks. Taking as an example the retina we present recent works attempting to understand how retina ganglion cells encode the information transmitted to the visual cortex via the optical nerve, by analyzing their spike train statistics. We compare the maximal entropy models used in the literature of retina spike train analysis to rigorous results establishing the exact form of spike train statistics in conductance-based Integrate-and-Fire neural networks.
