2014年9月
Do rational numbers play a role in selection for stochasticity?
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
 巻
 8
 号
 記述言語
 英語
 掲載種別
 研究論文（学術雑誌）
 DOI
 10.3389/fncom.2014.00113
 出版者・発行元
 FRONTIERS RESEARCH FOUNDATION
When a given tissue must, to be able to perform its various functions, consist of different cell types, each fairly evenly distributed and with specific probabilities, then there are at least two quite different developmental mechanisms which might achieve the desired result. Let us begin with the case of two cell types, and first imagine that the proportion of numbers of cells of these types should be 1:3. Clearly, a regular structure composed of repeating units of four cells, three of which are of the dominant type, will easily satisfy the requirements, and a deterministic mechanism may lend itself to the task. What if, however, the proportion should be 10:33? The same simple, deterministic approach would now require a structure of repeating units of 43 cells, and this certainly seems to require a far more complex and potentially prohibitive deterministic developmental program. Stochastic development, replacing regular units with random distributions of given densities, might not be evolutionarily competitive in comparison with the deterministic program when the proportions should be 1:3, but it has the property that, whatever developmental mechanism underlies it, its complexity does not need to depend very much upon target cell densities at all. We are immediately led to speculate that proportions which correspond to fractions with large denominators (such as the 33 of 10/33) may be more easily achieved by stochastic developmental programs than by deterministic ones, and this is the core of our thesis: that stochastic development may tend to occur more often in cases involving rational numbers with large denominators. To be imprecise: that simple rationality and determinism belong together, as do irrationality and randomness.
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 リンク情報
 ID情報

 DOI : 10.3389/fncom.2014.00113
 ISSN : 16625188
 ORCIDのPut Code : 15293288
 Web of Science ID : WOS:000342173400001