Local stimulus disambiguation with global motion
filters predicts adaptive surround modulation
Humans have no problem segmenting different motion stimuli despite the ambi-
guity of local motion signals. Adaptive surround modulation, i.e., the apparent
switching between integrative and antagonistic modes, is assumed to play a cru-
cial role in this process. However, so far motion processing models based on
local integration have not been able to provide a unifying explanation for this phe-
nomenon. This motivated us to investigate the problem of local stimulus disam-
biguation in an alternative and fundamentally distinct motion-processing model
which uses global motion filters for velocity computation. Local information is
reconstructed at the end of the processing stream through the constructive inter-
ference of global signals, i.e., inverse transformations. We show that in this model
local stimulus disambiguation can be achieved by means of a novel filter embed-
ded in this architecture. This gives rise to both integrative and antagonistic effects
which are in agreement with those observed in psychophysical experiments with
humans, providing a functional explanation for effects of motion repulsion (see Dellen and Torras, Neural Networks, 2013).