BBS Call For Commentators: The Tag Assignment Problem

[Stevan Harnad]

Below is the abstract of a forthcoming target article to appear in
Behavioral and Brain Sciences (BBS), an international,
interdisciplinary journal providing Open Peer Commentary on important
and controversial current research in the biobehavioral and cognitive
sciences. To be considered as a commentator or to suggest other appropriate
commentators, please send email to:
	 harnad at confidence.princeton.edu              or write to:
BBS, 20 Nassau Street, #240, Princeton NJ 08542  [tel: 609-921-7771]
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A SOLUTION TO THE TAG-ASSIGNMENT PROBLEM FOR NEURAL NETWORKS

Gary W. Strong                    Bruce A. Whitehead
College of Information Studies    Computer Science Program
Drexel University                 University of Tennessee Space Institute
Philadelphia, PA 19104 USA        Tullahoma, TN 37388 USA

ABSTRACT: Purely parallel neural networks can model object recognition
in brief displays -- the same conditions under which illusory
conjunctions (the incorrect combination of features into perceived
objects in a stimulus array) have been demonstrated empirically
(Treisman & Gelade 1980; Treisman 1986). Correcting errors of illusory
conjunction is the "tag-assignment" problem for a purely parallel
processor: the problem of assigning a spatial tag to nonspatial
features, feature combinations and objects. This problem must be solved
to model human object recognition over a longer time scale. A neurally
plausible model has been constructed which simulates both the parallel
processes that may give rise to illusory conjunctions and the serial
processes that may solve the tag-assignment problem in normal
perception. One component of the model extracts pooled features and
another provides attentional tags that can correct illusory
conjunctions. Our approach addresses two questions: (i) How can objects
be identified from simultaneously attended features in a parallel,
distributed representation? (ii) How can the spatial selection
requirements of such an attentional process be met by a separation of
pathways between spatial and nonspatial processing? Analysis of these
questions yields a neurally plausible simulation model of tag
assignment, based on synchronization of neural activity for features
within a spatial focus of attention.

KEYWORDS: affordance; attention; connectionist network; eye
movements; illusory conjunction; neural network; object recognition;
retinotopic representations; saccades; spatial localization