An Approach To The Complexity Of Neural Circuits

This week, Shlens et al. try to simplify the study of neuronal networks, a potential boon for the mathematically challenged neuroscientist. The authors examined the network of ON and OFF parasol retinal ganglion cells (RGCs) in the macaque monkey retina. Their 512-electrode recordings allowed them to sample most, if not all, of the parasol RGCs in a 3-5 mm circle of peripheral retina. To reduce the number of possible input patterns for n cells from ∼2n, the authors applied two constraints. Each input pattern contacts only two cells, establishing pairwise connectivity, and all connected cells must be adjacent. The number of possible patterns was thus reduced to around n2. An analysis of multi-neuron firing patterns indicated that the pairwise and adjacent interactions could account for the experimental results. In principle, this means that by recording from pairs of neighboring cells in a network one can understand the function of the entire circuit (sort of).

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Jonathon Shlens, Greg D. Field, Jeffrey L. Gauthier, Matthew I. Grivich, Dumitru Petrusca, Alexander Sher, Alan M. Litke, and E. J. Chichilnisky

Source: News tips from the Journal of Neuroscience

Contact: Sara Harris
Society for Neuroscience
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An Approach To The Complexity Of Neural Circuits