Volume 17, Number 20,
Issue of October 15, 1997
pp. 7954-7966
Copyright ©1997 Society for Neuroscience
Correspondence Noise and Signal Pooling in the Detection of
Coherent Visual Motion
Received March 4, 1997; revised July 25, 1997; accepted July 25, 1997.
Horace Barlow and
Srimant P. Tripathy
Physiological Laboratory, Downing Site, Cambridge CB2 3EG, United
Kingdom
In the random dot kinematograms used to analyze the detection of
coherent motion in the middle temporal visual area (MT) and in
psychophysical experiments the exact way that dots are paired between
successive presentations is not known by the observer. We show how to
calculate the limit to coherence threshold caused by this uncertainty,
which we call "correspondence noise." We compare ideal thresholds
limited only by this noise with those of human observers when dot
density, ratio of dot numbers in two fields, area of stimulus, number
of fields, and method of generation of the coherent dots are varied.
The observed thresholds vary in the same way as the ideal thresholds
over wide ranges, but they are much higher. We think this difference is
because the ideal detector takes advantage of the high precision with
which dots are placed in the kinematograms, whereas the neural motion system can only operate with low precision. When kinematograms are
generated with decreased precision of dot placement, the ideal detector
no longer has this advantage, and the gap between ideal and actual
performance is greatly reduced. Because the signals that result from
objects moving in the real world are scattered over broad ranges of
direction and velocity, high precision is not needed, and it is
advantageous for the motion system to pool information over broad
ranges. Other mismatches between kinematograms and the neural motion
system, and internal noise, may also elevate human thresholds relative
to the ideal detector. The importance of external noise suggests that
the neurons of MT form a vast array of optimal filters, each matched to
a different combination of parameters in the multidimensional space
required to define motion in patches of the visual field.
Key words:
correspondence noise;
coherent motion;
statistical
efficiency;
integration;
matched filters;
MT or V5;
global motion
Previous Article | Next Article
