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I thank Dr Ringach for continuing this discussion (or debate if he prefers) on Opposing Views. Such discussions in a public forum like this are beneficial to society both in terms of learning more about science in general and about the controversy of using animals in science. I hope Dr Ringach keeps his promise to continue to post on Opposing Views given his history of agreeing to participate in debates then reneging. Note that Dr Ringach does not deny agreeing to a debate on prediction at UCLA as a condition of my participating in their panel discussion. Nonetheless, I will try to cover Dr Ringach’s points here. (Actually I will divide this essay into two parts, covering anesthesia etc. in the next essay. Covering large amounts of complicated material requires space and I again say that the interested reader should choose the more efficient and effective process and simply read Animal Models in Light of Evolution.)

To begin, if Dr Ringach senses reluctance on my part to conduct a full and complete debate on the subject of using animals in science via Opposing Views he is correct. In my first blog, long before Dr Ringach weighed in on this, I cautioned against thinking one can cover complicated science topics on forums like this:

. . . science education is not conducive to learning via Internet. Many controversies can be studied using the Internet, for example creation versus evolution, the validity of complimentary and alternative medicine, and the use of animals in science. But in order to really understand the nitty gritty science behind all these subjects one needs to go back to the last century. One needs to read books.

In order to really understand this issue one must understand so much material that it is much more efficient for the reader to read a book and for me to write one; which I did. To reproduce all the material in the Animal Models in Light of Evolution is unnecessary and not a prudent use of anyone’s time.

Another problem I find in having discussions like this, as opposed to a traditional debate, with researchers like Dr Ringach is that the reader, unlike the audience in a traditional public debate, cannot see Dr Ringach’s reactions to my points. In the 1700s, public debates were not the only way to learn about an issue. There were books, pamphlets, and town criers and so forth. But the reason debates were, and are, valuable is that when confronted with truth, most people exhibit a reaction the audience can discern. Such does not occur in blogs. Facial expressions are telling. It is easier to lie from behind your computer than in front of an audience with spotlights on you. It is also easier for me to pin researchers down on specific points in real time rather than in the delayed back and forth of blogs. (Think back on past presidential debates or even short debates on cable news channels. Immediately calling an oppoenent on obvious shortcomings of his argument has an effect. The audience also responds to sheer nonsense and falsehoods.) In summary, both debates, like the one we are having now and traditional debates, should be done. Each has a place.

So traditional public debates still have a place in society and, even if their place was not as important as it is, since Dr Ringach said we were going to have one on prediction, he should keep his word. In my opinion, the reason he is reneging is that after reading Animal Models in Light of Evolution he figured out he was going to lose.

As all of the debate so far really revolves around prediction I will go into a little more detail as to why it is important even for a basic researchers like Dr Ringach.

Part of science is saying exactly what you mean. Words in science have very specific meanings and prediction is one such word. But why is prediction so important? Prediction has a very specific meaning in science as a whole and this meaning does not vary from discipline to discipline. (Although the biological sciences are more statistics-based than the physical sciences.) If the meaning were pliable, then astrology could claim that it is a predictive discipline as occasionally what the horoscope said was going to happen actually did happen. Such occurrences are rare in astrology, but the point is that once we introduce probability (the number of times a modality, be it astrology or animal models, got the correct answer as opposed to missing the answer entirely) into the equation we are back to judging the modality by its positive and negative predictive value.

So what does this have to do with using animals in basic research like neuroscience research? I will here reproduce material from Animal Models in Light of Evolution, material that is in context and better explained there. In Appendix 3 we say the following:

The institutional pressures in the struggle for research funding are such that researchers must often make promissory notes about the potential human relevance of their research.

In other words, researchers make the claim that animal models are predictive. We continue:

Consistent with our earlier distinction between internalist and externalist considerations in the conduct of science, is the observation here that the proposed science may be good (an internalist claim)—and we do not dispute the worthiness of the proposals below—while the implied human benefits (an externalist claim) may be pro forma, unrealistic or speculative at best. It is often forgotten in these debates that good science is not necessarily socially relevant science. Biomedical researchers do not have the mathematicians’ luxury of toasting their discipline by saying, “To pure mathematics, may it never be any use to anyone,” but slavish service to social relevance is likely to stifle creativity, and forced lip service to such relevance is just plain wrong!

We then give examples of basic researchers asking for grant money and claiming that their research will in fact yield results that translate to humans. Even Dr Ringach in his NIH grant application for research using monkeys states:

The objective of this proposal is to understand the nature of ongoing cortical activity . . . Finally, the techniques and methods developed here will be instrumental in the design of cortical prostheses for the restoration of sensory function, which require the activity of a large population of neurons to be controlled using a limited number of stimulating electrodes.

When he says “the restoration of sensory function” he is promising (explicitly in my opinion although some would claim it is only implied) the restoration of sensory function in humans. In an article he mentions his research results as being applicable to humans:

To conclude, our quantitative estimate of spatial scale indicates that LFPs are more local than often recognized. LFP signals can faithfully report the selectivity of cortical populations but only if the underlying map varies on a similar or larger scale. In addition to cat V1, there may well be other instances of such a match. For example, if movement encoding maps in the human motor cortex were to vary on a similar scale, then LFP recordings could indeed constitute a promising source of signals to drive a motor prosthesis (Andersen et al., 2004). These considerations and our quantitative estimate provide a guide to the interpretation of the increasing number of studies that rest on LFP recordings.

Another article:

This methodology may pave the way to evaluating the similarities and differences in visual cortical processing when the cortex is faced with stimulus ensembles of varying complexity. The method may also generalize the classification image technique so that correlated noise and multiple feature maps can be used in the study of human psychophysical performance.

Lest there be any misunderstanding of Dr Ringach’s intent, consider this from his home page:

We study how vision works in humans.  How is that the brain appears to effortlessly parse the activity of millions of photoreceptors in the eye to yield a perceptual collection of objects and a description of their relationships?  How does vision help in the planning and execution of motor actions?  How do we recognize faces?  How do we see?

That is not subtle.

Researchers like Dr Ringach cannot have it both ways. They cannot tell society and the NIH that their research is going to explain human disease or cure human disease or explain why a drug works in humans the way it does by studying animals then fall back on the FACT that what they are doing is actually basic research which has no such expectations.

This raises the question: What is basic research (also called pure science, basic science research, blue sky research, and pure research)? Lets consult the experts.

J. J. Thomson, the discoverer of the electron, stated in 1916: “By research in pure science I mean research made without any idea of application to industrial matters but solely with the view of extending our knowledge of the Laws of Nature” (1) [p198]. The Organisation for Economic Cooperation and Development said basic research is: “Experimental or theoretical work undertaken primarily to acquire new knowledge of phenomena and observable facts without any particular application or use in view. It is usually undertaken by scientists who may set their own agenda and to a large extent organise their own work” (2).

The House of Commons Select Committee on Science and Technology stated basic research “[A]ddresses fundamental, curiosity-driven science (3).” Basic research, almost all agree, is curiosity-driven as opposed to goal-oriented, unless by goal one means the desire to increase knowledge. Arthur Kornberg referred to this in an Editorial in Science in 1995 where he stated: “We are urged: Do strategic basic research! Do targeted basic research! How can we make clear the oxymoronic nature of these terms?” (4)

The Institute for Laboratory Animal Research stated:

Animal research is also important in another type of research, called basic research. Basic research experiments are performed to further scientific knowledge without an obvious or immediate benefit. The goal of basic research is to understand the function of newly discovered molecules and cells, strange phenomena, or little-understood processes. In spite of the fact that there may be no obvious value when the experiments are performed, many times this new knowledge leads to breakthrough methods and treatments years or decades later. (5) [p20]

If Dr Ringach wishes to claim that his animal-based research and the animal-based research of others is not being done in order to learn things about humans, then we have no disagreement. He can simply say as much as we can go on with whatever debate he wants. (He will still need to explain the website, articles, and grant applications saying the opposite, however.) We state very emphatically in Animal Models in Light of Evolution that basic research using animals is scientifically viable. HOWEVER! When Dr Ringach asks how society can learn about the human brain without studying animals then he is making the prediction claim. And without a debate on prediction he is getting away with an assumption that he cannot prove and that is in fact false. That is why the prediction issue is vital. There is no sense discussing any other aspect of using animals if in the final analysis Dr Ringach is going to fall back on the claim that animals can predict human response to drugs and disease.

Prediction is what Animal Models in Light of Evolutionis all about. It takes over 400 pages to adequately explain and the argument cannot be reproduced here in bits and pieces. Neither can organic chemistry or calculus-based physics or orthopedic surgery. The notion that complicated science cannot be explained in what is essentially sound bites is not original with me.


1. Lord Rayleigh. The Life of Sir J.J. Thomson: Cambridge University Press, 1942.

2. Organisation for Economic Cooperation and Development. The Measurement of Scientific and Technical activities: Proposed Standard Practice for Surveys of Research and Development. Paris, 1963.

3. House of Commons Select Committee on Science and Technology. Blue Skies Research Tenth Report: House of Commons. Session 2006-2007 2007.

4. Kornberg A. Science in the stationary phase. Science 1995;269:1799.

5. ILAR. Science, Medicine, and Animals: National Academies Press, 2004.


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