Learning and memory phenomena in a complex sensory environment: a neuroheuristic approach

Neuroheuristic Research Group, University of LausanneQuartier Dorigny, CH-1015 Lausanne, Switzerland, Email: avilla@neuroheuristic.orgAbstract The concept of interdependent communica-tions systems and Wiener's assertion that a machine thatchanges its responses based on feedback is a machine thatlearns, denes the brain as a cybernetic machine. Systemstheory has traditionally focused on the structure of systemsand their models, whereas cybernetics has focused on howsystems function, how they control their actions, how theycommunicate with other systems or with their own compo-nents. However, structure and function of a system cannotbe understood in separation and cybernetics and systemstheoryshouldbeviewedastwofacetsofasingleapproach,dened as the neuroheuristic approach.1. IntroductionNorbert Wiener, a mathematician, engineer and socialphilosopher, coinedthewordcyberneticsfromtheGreekword meaning steersman. He dened it as the science ofcontrol and communication in the animal and the machine[1]. Many other denitions have followed since then, butingeneralcyberneticstakesasitsdomainthedesignordis-coveryandapplicationofprinciplesofregulationandcom-munication. Early work sought to dene and apply prin-ciples by which systems may be controlled. More recentwork has attempted to understand how systems describethemselves, control themselves, and organize themselves.The cerebral cortex is not a single entity but an impres-sive network formed by an order of tens of millions of neu-rons, most of them excitatory, and by about ten times moreglial cells. Ninety percent of the inputs received by a cor-tical area come from other areas of the cerebral cortex. Asa whole, the cerebral cortex can be viewed as a machinetalking to itself and could be seen as one big feedback sys-temsubjecttotherelentlessadvanceofentropy,whichsub-verts the exchange of messages that is essential to contin-ued existence (Wiener, 1954). This concept of interdepen-dent communications systems, also known as systems the-ory, coupled with Wiener's assertion that a machine thatchanges its responses based on feedback is a machine thatlearns, denes the cerebral cortex as a cybernetic machine.Therefore, the focus of investigation is shifted from com-munication and control to interaction. Systems theory hastraditionally focused more on the structure of systems andtheir models, whereas cybernetics has focused more onhow systems function, that is to say how they control theiractions, how they communicate with other systems or withtheir own components. However, structure and function ofa system cannot be understood in separation and cybernet-ics and systems theory should be viewed as two facets of asingle approach, dened as the neuroheuristic approach. 2. Classical and Interactive ComputationMcCulloch and Pitts [2] proposed a modelization of thenervous system as a nite interconnection of logical de-vices. For the rst time, neural networks were consid-ered as discrete abstract machines, and the issue of theircomputational capabilities investigated from the automata-theoretic perspective. Further developments of this per-spective opened up the way to the theoretical approach toneural computation [3, 4, 5]. A Turingmachine (TM)consistsofainnitetape,aheadthat can read and write on this tape, and a nite programwhich, according to the current computational state of themachine and the current symbol read by the head, deter-mines the next symbol to be written by the head on thetape, the next move of the head (left or right), and the nextcomputational state of the machine. The classical Turingparadigmofcomputationcorrespondstothecomputationalscenario where a system receives a nite input, processesthis input, and either provides a corresponding output ornever halts. According to the Church-Turing Thesis, theTuring machine model is capable of capturing all possibleaspects of algorithmic computation [6]. The concept of a Turing machine with advise (TM /A)provides a model of computation beyond the Turing lim-its. It consists of a classical Turing machine provided withan additional advise function : N ! f 0;1g