Cerebral Cortex, Vol 8, 385-396, Copyright © 1998 by Oxford University Press
PR Roelfsema and W Singer
Natural visual images are typically composed of multiple objects, which
need to be segregated from each other and from the background. The visual
system has evolved to capture a great variety of cues that allow a
meaningful segmentation of the visual input. One of these cues is
connectedness. Connected image regions are likely to belong to a single
visual object, whereas disconnected image regions typically belong to
different objects. The visual system should therefore be rather proficient
in recovering connected image regions. In the present article we will
review evidence in favour of an important role of connectedness detection
for figure-ground segmentation, and speculate on the physiological
mechanisms that allow the visual system to perform this non-trivial task.
We argue that biologically plausible feedforward networks are maladapted
for the detection of connectedness. It is proposed that neurons that
respond to connected image regions are linked by a network of recurrent
connections that we call the interaction skeleton. Neurons spread a tag
through the interaction skeleton, which labels cells that respond to the
same perceptual object. Tag-spreading costs time and is therefore
inconsistent with extremely rapid object recognition. We will discuss the
pros and cons of two such tags: synchrony and rate modulation.
REVIEWS
Detecting connectedness
Graduate School Neurosciences Amsterdam, The Netherlands Ophthalmic Research Institute (KNAW), Department of Visual System Analysis, Academic Medical Centre (UvA).
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