Journal Article

Neuronal couplings between retinal ganglion cells inferred by efficient inverse statistical physics methods

Monasson, Rémi, Leibler, Stanislas, Cocco, Simona

2009

Overview

Complexity of neural systems often makes impracticable explicit measurements of all interactions between their constituents. Inverse statistical physics approaches, which infer effective couplings between neurons from their spiking activity, have been so far hindered by their computational complexity. Here, we present 2 complementary, computationally efficient inverse algorithms based on the Ising and \"leaky integrate-and-fire\" models. We apply those algorithms to reanalyze multielectrode recordings in the salamander retina in darkness and under random visual stimulus. We find strong positive couplings between nearby ganglion cells common to both stimuli, whereas long-range couplings appear under random stimulus only. The uncertainty on the inferred couplings due to limitations in the recordings (duration, small area covered on the retina) is discussed. Our methods will allow real-time evaluation of couplings for large assemblies of neurons.

• Publisher: National Academy of Sciences,National Acad Sciences
• Subject: Action Potentials / Algorithms / Amacrine cells / Animals / Approximation / Biological Sciences / Biophysics - methods / Caudata / Cells / Complexity theory / Computer Simulation / Correlations / Electrical couplings / Electrodes / Electrophysiology - methods / Ganglia / Humans / Ising model / Measurement / Models, Biological / Models, Neurological / Models, Statistical / Nerve Net / Neurons / Neurons - metabolism / neurophysiology / Physical Sciences / Physics / Reptiles & amphibians / Retina / Retina - physiology / Retinal Ganglion Cells - metabolism / Retinal Ganglion Cells - physiology / salamanders and newts / Statistical physics / Time Factors / uncertainty