This was my very first paper, and I had no help from any of my "advisors", since none of them wanted to have anything to do with the ideas in my thesis. Consequently the paper was written with a naivety that was eventually beaten out of me by a long series of rejections, of which this was the very first. Initially I was completely baffled by this rejection, as I had been by the prominant lack of interest in this idea by any of my thesis advisors, since it appeared to me that either this idea is complete nonsense, or it is a very interesting and significant alternative concept of neurocomputation that deserves at the very least to be exposed to the wider community to see if it can be confirmed or refuted by additional evidence. I was encouraged by comments such as:
"There is a consensus among all readers that the topic is interesting and the work contains some novel ideas." (Editor)
"the problem is extremely important and the approach is very attractive" (Reviewer B)
"The problem addressed by the author is of major importance and receives increasing attention in the literature." (Reviewer B)
"The idea of harmonic interactions among groups of cooperative cells is intriguing, and explanations of visual phenomena in terms of dynamic interactions are certainly topical. Furthermore, as current theoretical accounts of the perception of illusory corners are lacking, any contribution to explaining such phenomena would be welcome." (Reviewer C)
But with those kind of comments, I could not begin to understand why the paper had been rejected. Surely a radical new theory of neurocomputation deserves at the very least to be investigated as thoroughly as possible, given the fundamental limitations of our conventional notions of neurocomputation. This rejection, and several others later on, gave me a better understanding of some of the principles of academic publication.
In the first place, I discovered that most reviewers seem to view a paper as if it were a class assignment, i.e. an exercise to demonstrate that the author knows how to present a scientific argument in the proper format. As in a classroom exercise, the substance of the paper is secondary to its adherence to proper form and protocol, and therefore a paper can actually be rejected merely for improper form, even if it presents a radical new theory to address some of the fundamental problems of contemporary neuroscience! This was a revelation to me, as I had been working under the assumption that journal submission was not a rehersal but the real thing, and that novel solutions to important problems in neuroscience would be welcomed and encouraged.
Another unexpected discovery for me was that many people in cognitive neuroscience do not seem to be aware of the fundamental problems with contemporary notions of neurocomputation, and therefore they do not feel the compulsion that I felt to seek out an alternative paradigm.
I got a much better understanding of these issues years later, after reading Kuhn's book The Structure of Scientific Revolutions. Kuhn explains how the paradigmatic foundations of a science are not themselves subjected to the same rules of evidence applied to theories presented within a paradigm, because paradigms by their very nature are a set of initial assumptions which you can choose to either accept or reject. In this sense the Harmonic Resonance paradigm is no different than the Neuron Doctrine, and should not be held to a higher standard of proof just because it is proposed at a later date. Every unique and original paradigm deserves at the very least to be exposed to the larger community to allow individual researchers to make up their own minds on the matter. However I was also to discover that although everyone has heard of Kuhn and the idea of the paradigm shift, very few seem to have actually read the book, or to understand its significance.
It was only six years later that I resubmitted this material, although in greatly revised form. The reason why it took so long was partly because of my puzzlement as to why the paper was rejected in the first place. In the meantime I got busy with other theoretical ideas, and some of those ideas eventually led to changes in this model. During my post-doc at Schepens under Eli Peli I discovered some new perceptual phenomena that confirm the model, and I developed a new way to simulate the theory. My work on the Harmonic Resonance Theory led me to reformulate the model so that the nodes of the vibration represent the edges, not the anti-nodes.
the speculation about a new form of neural coding is fascinating but mainly a conjecture at this point.
Yes but so is the Neuron Doctrine itself. This conjecture is at least as valid as that paradigm. But the Neuron Doctrine is no more than a template theory, an idea whose limitations are well known, and harmonic resonance offers a way around those very limitations. This editor does not understand the paradigmatic nature of the neuron doctrine.
Reviewer B offers many detailed comments, some of which call into question the uniqueness of the model and the specific role played by harmonic resonance.
Are we on the same page? Reviewer B said nothing of the sort!
As Reviewer A points out, it does not lead to much in the way of testable predictions. ... Running simulations to postdict particular displays is at best an exercise preliminary to confirming a model by scientific experiment.
The phenomena addressed by this paper, i.e. illusory contours of collinear, orthogonal, diagonal, and other configurations, are not addressed by any existing model, and therefore this theory attempts to explore new theoretical territory. It is the first model to address this data. If the model can be shown to replicate those phenomena, that would be a significant and unique achievement. The fact that the model postdicts (!) those phenomena instead of predicting them is immaterial. If it is the only to be able to do so then it is worthy of publication!
it is not clear how the proposed model, predicts what is perceived.
Yes this point is well taken. I should have discussed exactly what the output of the model actually represents, as I do in my MLRF paper.