A recent challenge to the completeness of some influential models of l
ocal-motion detection has come from experiments in which subjects had
to detect a single dot moving along a trajectory amidst noise dots und
ergoing Brownian motion. We propose and test a new theory of the detec
tion and measurement of visual motion, which can account for these sig
nal-in-Brownian-noise experiments. The theory postulates that the sign
als from local-motion detectors are made coherent in space and time by
a special purpose network, and that this coherence boosts signals of
features moving along non-random trajectories over time. Two experimen
ts were performed to estimate parameters and test the theory. These ex
periments showed that detection is impaired with increasing eccentrici
ty, an effect that varies inversely with step size. They also showed t
hat detection improves over durations extending to at least 600 msec.
An implementation of the theory accounts for these psychophysical dete
ction measurements.