The contrasts of the stimuli were matched either in cone contrast or in multiples of detection threshold, as described below.
We used a high suprathreshold contrast scaled in multiples of detection threshold (25 × detection threshold) for all stimuli in order to maximize signal strength across the different chromatic conditions.
Because the apparent chromatic strength is closer between the 2 axes under the condition of Lamp = 0.08 and Samp = 0.80, and this ratio is close to the multiples of color detection thresholds, all hue angles used in the present study were represented by the angle defined under this condition.
In addition, in a series of experiments with different S-cone contrasts, we established in a systematic way that when stimulations along the L − M and S axes were equated by the multiples of color detection thresholds (i.e., Lamp = 0.08 and Samp = 0.80), there was an over-representation of the voxels preferring S-cone selective hue directions.
These data were acquired with a basic set of Weber contrasts for L-cone responses (Lamp = 0.08) and S-cone responses (Samp = 0.80), which were perceptually determined so that the chromatic modulation between colors along the L − M and S axes was roughly equaled in the multiples of chromatic detection thresholds.
In the second contrast set (Fig. 1), the stimulus contrasts were presented at equivalent multiples of their respective detection thresholds.
In Section 6 and Section 7, comprehensive simulation and analysis are presented, including bit error rate (BER) performance, ambiguity analysis, multiple target detection, detection threshold, and detection probability.
Furthermore, the multiple detection algorithm is based on a threshold which decides the minimum number of detections in each cluster to be considered as a detection.
As the model behavior depends nonlinearly on multiple parameters, effects of these system parameters on detection thresholds will be a subject of future work.
