Steady-state gain field responses were defined as responses to st

Steady-state gain field responses were defined as responses to stimuli flashed at least 600 ms after the beginning of a fixation. In order to be characterized as a gain field neuron, the cell had to have steady-state gain field responses in the interval from 0 to 160 ms after the probe presentation that differed significantly at two orbital positions 20° apart (two-sample t test, p > 0.05). Additionally, the high gain field peak response had to differ from the low gain field peak response by

at least 15% of the mean of the two responses. Gain field update times were calculated by fitting a sigmoid curve to the peak visual responses of all probe delays for saccades in one gain field direction using the nlinfit Matlab Erastin datasheet function. All fits yielded an R-squared value greater than 0.7, and 85% of the fits yield an R-squared value

greater than 0.9. The gain field update time, or the time point of transition from nonveridical to veridical eye position information, was defined as the probe delay subsequent to the inflection point of the sigmoid fit. The response of cells without gain fields to the two-saccade task could not be fitted with sigmoids. Behavioral data were reoriented so that the first or the second saccade vector pointed in the horizontal, rightward direction: x’=x∗cos((360−θ)∗π180)−y∗sin((360−θ)∗π180) selleck screening library y’=x∗sin((360−θ)∗π180)+y∗cos((360−θ)∗π180) x and y represent the original saccade vector in real space, θ the angle of rotation, and x′ and y′ the reoriented saccade vector. Consequently, corresponding saccade mislocalization vectors for each trial block, defined as (mean endpoint of saccades to early probe – mean endpoint of saccades to late probe) were

also reoriented. This research was supported, in part, by grants from the Keck, Zegar, Kavli, and Dana Foundations, and the National Eye Institute (P30EY019007, unless R24EY015634, R21EY017938, R01EY014978, R01EY017039, M.E.G., PI), We are grateful to Yana Pavlova for veterinary technical help, Drs. Girma Asfaw and Moshe Shalev for veterinary care, John Caban for machining, Glen Duncan for computer and electronic assistance, and Latoya Palmer and Holly Kline for facilitating everything. B.Y.X. was supported by the Columbia MSTP grant T32GM07367-33 and the NEI training grant T32EY13933-08, and C.K. was supported by Fondation pour la Recherche Médicale and Fondation Bettencourt Schueller. We thank Dr. Ning Qian for his comments on an earlier version of this manuscript, Dr. Larry Abbott for reading a later version of the paper and for his help with the mathematical analysis, and Dr. Brian Lau for help with the statistical analyses. “
“Previous fMRI studies have suggested that some categories of objects and actions are represented in specific cortical areas. Categories that have been functionally localized include faces (Avidan et al., 2005; Clark et al., 1996; Halgren et al.

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