Discriminating IR light with visual cortex.

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Discriminating IR light with visual cortex. Discriminating IR light with visual cortex. A, Learning curve for IR-discrimination task using V1 (n = 6 animals). Note animals typically surpassed criterion (85% correct) within the first day. B, Direct comparison of learning curve for the same task with V1 implants (blue) and S1 implants (green; n = 15 for S1 implants). C, Same information as in B, but with learning curve superimposed when an animal has just a single IR sensor on its head (single-sensor learning data are from a previous study [Thomson et al. 2013]; n = 4 animals). D, Trial-based moving average analysis of performance in IR discrimination task. The curve shows percentage correct as a function of trial number (moving average of 20 trials) from same data shown in A. E, Same analysis as in C, but with S1-implanted animals shown in green for direct comparison. F, Performance in IR-discrimination task as a function of angle θ between the ports (see Fig. 1A). Includes data from V1 and S1 implanted animals with four IR sensors, as well as data from S1-implanted animals with a single IR sensor for comparison (blue, green, and red lines respectively with mean ± SEM percentage correct). G, Performance of naive V1- and S1-implanted animals (mean ± SEM percentage correct), that were not pretrained on a visual discrimination task (solid lines). Data from S1-implanted animals that were pretrained on a visual discrimination task are included for comparison. There is no significant difference, among any of the three groups, in the number of sessions it takes to reach 85% correct in the task (p > 0.05, two-tailed t test). Eric E. Thomson et al. eNeuro 2017;4:ENEURO.0262-17.2017 ©2017 by Society for Neuroscience