Chance, Repetition, and Error in the Development of Normal Nervous Systems

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CHANCE, REPETITION, AND ERROR IN THE DEVELOPMENT OF NORMAL NERVOUS SYSTEMS PETER G. H. CLARKE* Peter G. H. Clarke is maître assistant in the Department of Anatomy at the Université de Lausanne, Switzerland, a department which houses one of Western Europe's most distinguished neuroanatomy units. He was born in London in 1946, one of identical twins (we wonder if his brother writes as well). After high school he won a scholarship in engineering at Saint Peter's College, Oxford. Changing fields, Clarke received his Ph.D. from Keele University, working with Professor D. M. MacKay on visually evoked potentials. He then spent 3 years with Professor D. Whitteridge of Oxford, recording from single cells in the visual cortex. The year 1974-1975 was spent at Washington University Medical School in Saint Louis with Professor W. M. Cowan. Here he observed what appeared to be developmental errors in the visual system of chick embryos—the direction of his thinking in this essay. Married to Stéphanie Hosek, also a developmental neurobiologist, Clarke writes religious poetry, enjoys cross-country skiing and tennis, and has forsaken the art of chess because of lack of time. The more that is discovered of the intricate organization of the nervous system, the more it seems remarkable that the genes can successThe author is sincerely grateful to Drs. D. O. Frost, G. M. Innocenti, M. Jouandet, H. Koppel, H. P. Lipp, and D. M. MacKay, who made valuable comments on the numerous drafts of this essay, all of which were typed by Mrs. C. Vaclavik. Professor H. Van der Loos provided facilities and access to his reprint collection, including many of Cajal's papers. Supported by grant 3776 from the Swiss National Science Foundation. *Institut d'Anatomie, Rue du Bugnon 9, 101 1 Lausanne-Chuv, Switzerland.© 1981 by The University of Chicago. All rights reserved 003 1 -5982/82/250 1 -0257$0 1 .00 2 I Peter G. H. Clarke · Chance, Repetition, and Error fully specify its development. The specificity and detail of the interneuronal connections in higher mammals is testified by the meticulous selectivity with which many neuronal classes respond to sensory stimuli, particularly in the visual system (e.g., [1, 2]) but elsewhere too (e.g., [3]). Yet the human genome contains less than 1010 bits of information [4]— perhaps far less than 1010, since there is an unknown degree of repetition in the DNA. There is, therefore, at least 10 times too little information even to specify which hemisphere of the brain each of a man's 1011 or so neurons should occupy, let alone the hundreds or thousands of connections that each neuron makes. For reasons such as these, it is generally assumed that there must be an important random or unspecified factor in the formation of neural connections in higher vertebrates (e.g., [5]); but even in so-called simple nervous systems—such as those of daphniae and leeches, which are famed for the remarkable constancy which can be demonstrated down to the level of individual neurons, dendrites, and axons [5, 6]—there has to be some limit to the precision of neuronal development. That limit and its manifestations are the subject of this essay. In particular, I shall argue that, owing to the limited supply of genetic information, errors must and do occur in the development of all normal brains. I shall argue that these errors are of two kinds, both of which are in some cases reduced or eliminated during later development. Repetitive Structures Can Be Generated Using Relatively Little Information Most biological tissues are highly repetitive, containing limited numbers of cell types, and the nervous system is no exception. Moreover, here it is not only the types of cell that repeat but also the patterns of connections between them. Such repetition presumably makes for efficient use of genetic information, since all that needs to be encoded is the basic unit and the number required. It is not surprising, therefore, that considerable repetition is found in all structures that contain large numbers of neurons; if this were not so, the genetic information required would be excessive. A classic case is the cerebellum, whose granule cells probably outnumber...

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