Once again this reviewer reveals his difficulty grasping the larger issues of perception and consciousness. What is being presented in this paper is not a specific theory to be stacked up against other specific theories in a detailed side-by-side comparison, but a general paradigmatic hypothesis, an alternative way of thinking about the nature of visual processing.

Theories are validly proposed at different levels of generality, from very specific neurophysiological theories involving the mechanism of action potentials and neurotransmitter release, all the way to more general theories of computational or representational principles. In fact there have been many theories published which are at least as general and non-specific as the present model, including Selfridge's Pandemonium theory, Triesman's Feature Integration Theory, Neisser's Iconic Memory Theory, Thorndyke's Schemas concept, Rosch's Prototype theory of memory, Kosslyn's theory of mental imagery, Atkinson & Schiffrin's model of memory, Gibson's theory of Direct Perception, Biederman's Geon theory, Crick's theory of quantum consciousness, Pribram's holographic theory, De Valois' Fourier theory, McClelland's Interactive Activation Model, Kirkpatrick's Simulated Annealing concept, McClelland's PDP approach, etc. All of these theories have been rightfully published in the literature even in the absence of either direct neurophysiological or psychophysical evidence, or complete mathematical specification (and sometimes both), because until the essential principles of operation of the brain have been established beyond a doubt, such theories enrich the discussion of possible principles and mechanisms of neurocomputation.

Even if such theories are ultimately rejected, they serve the invaluable purpose of supplying a reference point, or "handle" available in all subsequent discussions on the issue, even if those references are cited only as examples of wrongful approaches. Every unique and original concept of neurocomputation deserves to be exposed to the community, to make it available to be judged on its merits by the larger community of scientists, many of whom may have access to additional evidence not available to either the author or to the reviewers, which may help to either support or refute the proposed theory.

There are altogether too many researchers in psychology today with an intimate knowledge of the details of their own narrow specialty, who have come to convince themselves that the larger issues have little relevance to their work. It is the rare scientist who has a good understanding of the limits of the paradigm within which they operate.

This paper was originally submitted as Part I of a two-part paper, the second part of which delves deeper into the details of the computational properties of the model, in a manner that this reviewer would probably find more satisfactory. In that paper I present a detailed comparison between Grossberg's model and the MLRF model, and show the fundamental limitations of the former approach. However I could not submit Part II by itself, because it rests on a number of principles which were developed in the present paper, and the two papers together would be just too big for a single submission.

It seems however that two-part papers are so unusual these days that they cause confusion in the editorial staff. So I resubmitted Part I as a single paper, with the intention that, when it was accepted for publication (Hah!), I would then submit Part II as a follow-on. In case the reviewer should be interested, (Hah! Ha ha ha!!!) the original two-part version of the paper is available at...

Computational Implications of Gestalt Theory I: A Multi-Level Reciprocal Feedback (MLRF) to Model Emergence and Reification in Visual Processing
http://cns-alumni.bu.edu/~slehar/webstuff/orivar/orivar1.html

Computational Implications of Gestalt Theory II: A Directed Diffusion to Model Collinear Illusory Contour Formation
http://cns-alumni.bu.edu/~slehar/webstuff/orivar/orivar2.html