## Design for a brain"This book is not a treatise on all cerebral mechanisms but a proposed solution of a specific problem: the origin of the nervous system's unique ability to produce adaptive behaviour. The work has as basis the fact that the nervous system behaves adaptively and the hypothesis that it is essentially mechanistic; it proceeds on the assumption that these two data are not irreconcilable. It attempts to deduce from the observed facts what sort of a mechanism it must be that behaves so differently from any machine made so far. Other proposed solutions have usually left open the question whether some different theory might not fit the facts equally well: I have attempted to deduce what is necessary, what properties the nervous system must have if it is to behave at once mechanistically and adaptively. The concepts of organisation, behaviour, change of behaviour, part, whole, dynamic system, co-ordination, etc.--notoriously elusive but essential--were successfully given rigorous definition and welded into a coherent whole. But the rigour and coherence depended on the mathematical form, which is not read with ease by everybody. As the basic thesis, however, rests on essentially commonsense reasoning, I have been able to divide the account into two parts. The main account (Chapters 1-18) is non-mathematical and is complete in itself. The Appendix (Chapters 19-22) contains the mathematical matter"--Preface. (PsycINFO Database Record (c) 2007 APA, all rights reserved). |

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### Contents

1 | |

The Absolute System | 203 |

Stability | 216 |

Parameters | 222 |

Stepfunctions | 232 |

The Ultrastablc System | 243 |

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### Common terms and phrases

absolute system action active adaptation amoeboid animal animal’s assumed become behave brain canonical equations cause cerebral cerebral cortex change value CHAPTER co-ordination complex concept conditioned reﬂex consider constant cortex critical deﬁned deﬁnition determined diagram of immediate difﬁculty displacement disturbance dynamic system environment essential variables example experiment experimenter fact feedback Figure ﬁnal ﬁnd ﬁnite ﬁre ﬁrst ﬁxed ﬂow function funetions given homeostat idempotent immediate effects independent initial interact joined learning line of behaviour living organism machine magnet main variables matrix mechanisms method movement multistable system muscles natural selection nervous system neurons null-function number of variables observed occur parameter part-functions phase-space position primary operations properties random reaction region relation representative point resting shown speciﬁed stabilised stable ﬁeld stable system step-function changes step-function form step-function values stimulation subsystems sufﬁcient Suppose system’s temperature tend terminal ﬁeld theorem tion ultrastable system uniselector unstable usually whole zero