Article Figures & Data
Figures
- Figure 2.
When the task involves differences in orientation as well as location, strong attention impairs subjects' ability to detect large orientation changes. A, Proportion correct as a function of normalized orientation change sorted by attention axis position as in Figure 1B, for recording sessions in which the orientation of the two stimuli differed by <45° (28/49 recording sessions). B, Proportion correct as a function of position on the attention axis for the largest and smallest orientation change bins. Conventions as in Figure 1C. C, D, Same as A and B for recording sessions in which the orientation of the two stimuli differed by >45° (21/49 recording sessions).
- Figure 1.
Fluctuations in attention change both the thresholds and slopes of psychometric curves. A, Schematic of the orientation change detection task. Two Gabor stimuli synchronously flashed on for 200 ms and off for a randomized 200–400 ms period. At an unsignaled time picked from an exponential distribution (minimum 1000 ms, mean 3000 ms, maximum 5000 ms), one of the stimuli was presented in a different orientation, and the monkey was rewarded for making a saccade to the stimulus that changed. Attention was cued in blocks, and the cue was valid on 80% of trials, meaning that on an “attend-left” block of trials (depicted here), 80% of orientation changes were to the left stimulus. The monkey was rewarded for correctly detecting any change, even on the unattended side. All analyses were performed on responses to the stimulus before the orientation change (black outlined panel). B, Fitted psychometric curves sorted by position on attention axis. Strong attention (red lines and large positive values) improves performance on difficult trials relative to weak attention (blue lines). Arrows indicate the two orientation change bins plotted in C. C, Proportion correct as a function of position on the attention axis for the largest and smallest orientation change bins. Error bars are bootstrapped 95% confidence intervals. D, E, Fitted threshold (D) and slope (E) as a function of attention axis position. Error bars are bootstrapped 95% confidence intervals.
