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Precision, Reliability, and Information-Theoretic Analysis of Visual Thalamocortical Neurons

Department of Neuroscience, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania

Submitted 23 August 2006; accepted in final form 15 June 2007

High-order statistics of neural responses allow one to gain insight into neural function that may not be evident from firing rate alone. In this study, we compared the precision, reliability, and information content of spike trains from X- and Y-cells in the lateral geniculate nucleus (LGN) and layer IV simple cells of area 17 in the cat. To a stochastic, contrast-modulated Gabor patch, layer IV simple cells responded as precisely as their primary inputs, LGN X-cells, but less reliably. LGN Y-cells were more precise and reliable than LGN X-cells. Also, within each LGN cell type, 1) responses to the same stimulus were nearly identical if they shared the same center sign and 2) responses of neurons with the same center sign were nearly identical to the responses of neurons of opposite center sign if the stimulus' contrasts were inverted. These results suggest simple cells receive highly precise and synchronous LGN input, resulting in precise responses. Nonetheless, the response precision of simple cells was greater than expected. Finally, information-theoretic calculations of our cell responses revealed that 1) LGN X-cells encoded information at half the rate of LGN Y-cells but 2.5 times the rate of layer IV simple cells; 2) LGN cells encoded information in their responses using temporal patterns, whereas simple cells did not; and 3) simple cells used more of their information capacity than LGN X-cells. We propose mechanisms that simple cells might use to ensure high precision.

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