Matched filtering in motion detection and discrimination

When humans detect and discriminate visual motion, some neural mechanism extracts the motion information that is embedded in the noisy spatio-temporal stimulus. We show that an ideal mechanism in a motion discrimination experiment cross-correlates the received waveform with the signals to be discriminated. If the human visual system uses such a cross-correlator mechanism, discrimination performance should depend on the cross-correlation between the two signals. Manipulations of the signals' cross-correlation using differences in the speed and phase of moving gratings produced the predicted changes in the performance of human observers. The cross-correlator's motion performance improves linearly as contrast increases and human performance is similar. The ideal cross-correlator can be implemented by passing the stimulus through linear spatio-temporal filters matched to the signals. We propose that directionally selective simple cells in the striate cortex serve as matched filters during motion detection and discrimination.