Figure 3. Analysis of a four-alternative orientation-change detection task with the m-ADC model. A, Spatial four-alternative, orientation-change detection task. The monkey initiated a trial by fixating on a zeroing dot in the center of the screen. Following trial initiation, four stimuli (oriented gratings) were presented, one in each visual quadrant. After an unpredictable interval (800–2700 ms), the screen went blank (150–300 ms). Then, the four stimuli reappeared. On 50% of trials, one of the four gratings had changed in orientation by 10–90° (change trials), and on the remaining trials none of the stimuli had changed (catch trials). The animal was rewarded for making an eye saccade diagonally opposite to the location of the changed stimulus (antisaccade) when a change had occurred, and was rewarded for maintaining fixation on the zeroing dot (NoGo) when no change had occurred (see Materials and Methods). Catch trials constituted 50% of all trials, and during change trials, the orientation change could happen with equal probability (25%) at any one of the four locations. B, Observed response counts (numbers within cells) and conditional response probabilities (shading of cells). Data pooled across orientation change values in n = 22 experiments. Rows, Change locations (as defined in A); last row (φ), no-stimulus (catch). Columns, Response locations (as defined in A); last column (φ), NoGo responses. Cells outside of white square, Cells representing misses and false-alarm rates used to derive model parameters. Other conventions are the same as in Figure 2B. C, ML estimates of sensitivities and criteria for each location estimated from data in B. Bar shading, Numerical convention for identifying the target's quadrant, as in A. Error bars, ML standard error. D, Response probabilities predicted from the model plotted against experimentally observed response probabilities. Triangles, Probabilities not used for fitting the model (predictions). Shaded dots, Probabilities used to fit the model. E, Model predictions for the central 4 × 4 cells of the contingency table based on model parameters estimated from only the last row and the last column of the contingency table (misses and false alarms); conventions as in B. F, Criteria (c, open triangles) and psychophysical functions of sensitivity (d, circles) for various orientation change values estimated for each quadrant (defined in A) from only 8 of 25 contingencies (B, cells outside the highlighted box). Values of d and c were estimated by binning the orientation change values into 16° bins. Black line, Naka–Rushton fit to the psychophysical function. Error bars, ML standard error. G, Psychometric functions of the proportion of observed responses (filled circles) and model predictions (open triangles) based on the sensitivity and criteria estimates from F. The eight plots are arranged as four matched pairs (top and bottom). The top subplot of each pair (black symbols) shows the percentage correct (hits) as a function of change magnitude (psychometric function of accuracy). The bottom subplot of each pair (colored symbols) shows the percentage errors (incorrect/misidentifications) as a function of change magnitude. The four pairs are spatially aligned with the four corresponding locations of change occurrence (A). In each plot, colors indicate the locations of the responses relative to the location of change. Black, Response to the location of change; blue, response to the diagonally opposite location; red, responses to the location in the same vertical hemifield; green, responses to the location in the opposite hemifield.