Modeling and Computational Approaches and Neuro

7/31/2019 Modeling and Computational Approaches and Neuro

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HVORLLY SD

ODLNG ND

OPUTTOL PPROHS

TO NUROSN

George Reeke, Jr. and Olaf Sporns

h Nuscics stitut Nw N 00

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ct yas umus cmpu ms ha attmp t iumiaaspcts f havi hav appa Ths ms fm a hihy ht-gus cci a pat a it vs f scipti a y b giig pspctiv ath tha a igica Oths a ccwith h vus systm ut y sm istaia a cmp havigsystm this viw w atmpt t sci th assumpis a isf suts tai with sva f ths appachs iusatig ach wih

a fw ampe W mak ampt t hausivThs it appachs ct th wi ivgc f pii ha

xst ccg h pp f ms th whch aaptvhavi ca fuctiay sci ipy f is pysica asisi th vus systm a i h vy pssiiiy f ua paais f havi h atu a imitatis f ms hav wiyiscuss (g B 987 ss 1975 Gy a1966 Ky 1971 ach& Bv 988 iss 963 Pik & Pic 1988 Rk & Ema988 a 98 i 1990 Wiga & Fs 98) hs is

cussis hav vaiusy agu f h impac f fma us fpic th w f vutiay hisy i ustaighavi u i va agmt has ach hs issus

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598 RK SPORS

Or aim here is t cariy the reatiship etwee theretica apprachesa what has ee r miht ptetiay e epaie y the crrespimes. We imit rseves t mes tht eerate sme rm servae ehavir ecase sch mes are the mst ikey es t avi errrs

iterpreati that arise rm the scae hmcs prem(eeke & Eema 988)

I its mt asic rm the hmcs prem ccrs we a theryprpse t epai sme cass ehavir ives the acti a etitywhse itera mechaisms are t specie i that thery. his etityeera is ve t perrm sme eessary sset the ctis the rai tat s csiere y the meer t e t ermae t thethery at ha It ths cstittes a hmcs r itte ma y

virte havi at east sme the ctve capacities the i mathat ctais it Descartes thery visi was a eary eampe ahmar thery Oce visa impressis wee cveye t the pieaa critica eemets aaysis whih were t epaie the therywere pstate t ccr there The thery was ths icmpete

ay mer era etwrk mes ehavir i whih the ipta tpt are arras simate era ri ampites ma e iticize as hmar i that a hma srver is reqire t prviesitae era ipts a t ier the ehavir that w rest rm the

era tpts taie rm the me I ay particar case theseitpretive steps miht iavertety ctai key eemets the mechaisms that erie the phemea that the me is atempti tepai cri a iterate apprach t the mei ehaviri which ipts are acta sesrs a tpts are ata eectrs wrii a evirmet is mst ikey t avi versimpicati the premthat miht therwise reer tests a particar thery wrthess.

pt a iterate apprach t ehavir st eaves the meerwith a wie rae theretia a practia chies t east which

is the eve raizatiera cmptatia r psychicaatwhich epaatis r ehavir are sht Athh the ervs systemis iversay aree t prve a phsia sstrate r the ctr ehavir it is t s wiey aree tha e ees t sty the ervssystem t ersta ehavir Utimatey this chice epes esassessmet the casative reevace activity at the era eve phiher eves raiati Chice the psychica eve eies (rpstpes te pssity reati ehavir t era actvity chice a astrt cmptatia me ies th imprtace a ra

sms evtary a evepmeta histry et these chices are maeease sty the ervs system itse is s ict I a cmpeteerstai ehavir c e taie y physiica servati



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BHORLL BS MOLG 99

al w ca su ha h lvls f aai wul isaaa cmu mls wul cas aa i uscic uals

Mls hus hl isiuish his i h absc fcclusiv ima aa y mai icis f uvius cs

qucs fm iv assumis Thy mi his b s aaisclasss f aa whs lvac is hwis aa fuasacs mli ca hl i w ual a h lvs faiai, mii, f aml sas au ua ais b asm i samcs abu cua mais haca b cma wih avia aa fm sycy imsMls ca as iica which ascs f vaiaiiy i a aicula im a ima a aicula hy a which may safly i

mi whh a aicua m fus s funcis mus as wh i las sm asc f hav my scs ics i. T hav laa saus, a ml mus ica hcausal mchaisms f h sysm i m my simua isuu ( 99). Alhuh his isc is ah vus i hasb ss v y may auhs F aml is & s(1988) iscssi hi m f h ss is f cai s-i aial us sa ha h ac aa aaim [haach us i hi m] . . bviusy ca b ai ially

h bai bcaus ifmai s av bacwas aiy uhas a y h sii similaiy w m a imaaa caily sus h ccu ha h c a h wa by bac aai cmu i simia ways Ufua,s hm scuss a99 uaas ha w i saaumaa ha bhav iicay u ay i s f ss cahav ay i ia sucus a bav iy u ss i h ial s This hm uuy alis m cmsysms, such as h ai Thus, amu f avia siuai ca

v ha a m is cc a uima s mais imal vicai ia mchasms

h absc f suc vicai, w sus sm ciia b whichh ass f ms ca b visially assss sa ay m ha amas i h vm fhavialy as mli Ths a fw y a suvy f smcu mls i ach sval i classs wih a summay f hsai chaacisics w hav us classify a vaua hm

Citia o Succ o Modlih h usai ha w a cc wih h ass f havias ccus i h ilical w a wih ii icis



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6 K SOS

bul b bhv cs w sus h h m cmus b m by succssul hy: s ssum mus b css whvlbl xpml mus c xpl bhv . musc v cv hmucul mus mk sbl cs h b u by m.

Th h s bvus Thc sc hs ly b scuss bu h hmucul c ccu us sysm s wll s s hss u wh h ml sysm qus by xl hhs y f bhvl chcscs b ml f xml hbly c vml smul hs cs h usc c sysm wh h sm bls s h sysm u s m h cmb mus b ml v

h hmuculus pblm. Ms mls h by supvsl ( pm uc h c) (Rsbl198) c h hmuculus hs k.

Th s p (csscy wh blcl ) s ls why f smlb bcus hs s b h h bch Sm fh l fcs ms h csuc f bhvlmls h fllw ( m l scuss s v Elm1987 Thp & mb 1989)

1 Th w f h vus sysm s hhly vbl fm vul vul chs u h lm ch v

N sl cll h vus sysm uquly pucs sls h hv cul m ucbl p m. fc slclls h vus sysm my y m wh vy ll c

3 Nul pcsss lvly slw bhvl spss smulypclly ccu ms h cmpbl wh ly w squlul s.

4 Nul ccs uc Ccvy h vus sysm v c s s vy sslv h umb h wul b qu cml ccvy.

6 N ul mchsm s kw by whch h upu f u cb s cy s vlu

7 mchsm s kw by whch ymblc pss f-m cmpul cus c b c N squcs sm bw s 1

Exceptions to ths rul mght ext n the form of enzyme cascads capable of cayngout lmted equence of steps. Th mchanm hghly necnt n ts us of ndhly cpl of prntng rty, comple computtonl pocdu of the knd

envoned to et n computtonl model o cogntve poceng



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AVOALLY AS OL 60

Alhugh my re mel regr e r mre hee rer le ru el h re e wh all fm Whve e gm w yhe eul eg whhve gee ew r he u uh e (Reee

e l 990) Keye f h rh re he frmul f geerlhery vu ye u h e evlury hy e f evelme; he ue f lglly rel eleme amodel nevous sysem a opeaes accodn o s eoy, smulaedgeher wh eleme f rulr heye he evre whh h heye e he uleu berv behv lwlevel eurl eve h mule yem he rgrueg f he yem wh uh he ly egree eve rry u mle mr Th rhelbeely v eg hghy r ulurlly uee ehvr (ehee & Chgeu 99) uh vel rle lvgwhh hve bee he ube f umeu l elgee () uePee hee k u vlve re b l h e l well uer Ay rre hery e ee by yhe erelg ehue he ee we ree re e he hery feul gu ee (el 97 97 99)

E E

Se he 940 190 reerher egeer hve eme ree m h hw ege r ve ehvr hy(940) re h ve ehvr be ee he behv ye e f y eulbru wh he eve heurum w e rehe e by he rl prg egve eeb Sueuely hy (2) e-lre furher he ve uly hum ml ehvr

gehe wh Wee (94) beme fug fher f ybereCyere ee el he gleeg ehvr f rgm he b eh ee wh eebk el eh- v r he el ybere eue m he egf he h u hw uh ehvr wy lg ullvg rgm le f h eve e hy hme (92);Wler' lghfwg ehl re mh eul(93) erug eerehl eve uh Shmue (9) r Hwr' r (193) (Fr mre emle ee Kur-

we 990 ee 90) he e gleeg behv w ee he eee f ellgee he mel ue h uh behvrul e ee y e f meh rule (uh feeb) M



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60 SOS

c lv cul ucu f vu mf um ml m; v ml mlm mgl cm cl T vw m vy nul l f cgv cc w w fuclm (lc

1978 Pum 190)W mgc f cmu 190 g f mccl

l x clu ll c f um ml m T-g "lmlvg w fmul mccl c c u cmu (Nwl 198) mggl f vl cc f ml c hcgu vlml c f ml vl fuc- w lm ly g mucll c vcluc (Nl 199 f m c xm x &Wfg 1990; g & Elf 199 1 ) lug gu g,v w lly ly wly c vc w u cl f cmu gm m c f lgcll cl

T

Crrlav Mdl

ug ucc v m g w vmg fm cv c c f ylgcl fc cl wg m f v v cllgglv ml v cul mg c fuuv v f v m v mcc xl f c ccgy m cc v vu m l, c f uc vlu f v f cm

ORAWAR MODE cully ul xm f cl Rcg ml wc m cg lw c g f mul Pvlv g(Rcl & Wg 192) c Gluc l (1990), Rcl-Wg ml m ccu f cg gm y g cg () g f c w cul c muu (S uc l m m mu g

wc ucm uxc gv mulu m cu l:

= rJ3(-LseVs



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EHAVORAY AD MODE 603

where s a learnng rae parameer applale o s he orespondng parameer relang o he unondoned smuus () s hemaximum poibl vau of Vj, which i attain whn i th onyondoned smuus presen and s

V s he sm of he assoaon

senghs eween al he smus eemens presen n ha ral and he Thu, a mor timuu mnt a a, V nreases and Vdeeases onssen wh oseaons of long

Thi rationhip i intuitivy raonab, but uggt no mchaniticass for s predons Howee a suggese onneon emeged whenuon & Barto (9) how that th rationhip i mathmaticayquialen to th o-ca "lta rul f Wdrw & Ho (10) foadape aral neural newors and s heefore euaen o leas

qua ror minimization Thi convrgnc uggt a arch foneuronal rus ha mplemen he ResorlaWagner rule (Glu e al990 Wr uch circuit o b found would ti b nca of couo how xrmnay hir rlan o h Rcora-Wanr ul new of he numerous oganaonal!ees of he nerous sysem noledn een h mplt conition rpon. At mnmum an appropiatynhic nural mo wou b rquir to help unrtand th ro ofuch rus in he ehaoral paerns generaed he ssem as a whoe

Computational Models (Artfcial Inelligence)Articia intllignc mo a ba upon a computational mtaphoof ran fnon ha onsders daa represenaon and ruedrenmanipulation of nco infomation to b th nablin lmnt of cone sysems. Ths heoy has een mos houghfully and foefully seorh lshn (9) ral negene ytm ha een mossuessful n emlang asra and oga aspes of human ehaorphap bcau om o th ar ndeed cai ou foma reasonngHowvr, AI ha bn uccfu in aing with baic prcption,aegoaon and moemen n he world whh are argual (Reee &delman 19) prerequse o he aquson and manpulaon of fomalymbo em.

SO Rueased prolem song has a long hsoy n eg Newelle al 95) arly ssems lear ur from an inucint nowedgeba an tn o fai whn oui a narrow pobem omanlhough om wores eleed ha nsuen nowedge was he mosimportant dcincy of uba ytm an attmpt to rmy it by

onsrung ee ager oleons of eeyday fas expessd as formaproduon ules (Guha & Lna 199) Lair e al (196) a heproem of mprong he reasonng al of ruleased ytm. Thy



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6 & SS

onstruted R a probesong progra tha attepts to earnrom ts own eorts a song probems The R arhteture norporaes eemens rom (see beow) and onans wo e eementsdered rom an anass o human probemsong behaor he rsteement unersa subgoang s a proess desgned o brng he enrepower of the syse o bear on any new probem that arses When Rdoes no now how to dede wha to do nex n a partuar stuaon treaes a subgoa o dede tha ueston and hen atemps to resoe thasubgoa hs partuar eegan appaton o the omputer senenoon of reurson an sueed n auoaay breang a arge probedown nto smaer subprobems The other eemen hunng s aehans for prong he sste's eeny a song preous

enounered probems b nng he resut o a han of reasonng o thenta ondons n suh a wa tha the ntermedate reasonng seps arebypassed hen a smar se of ondtons ours aer hunng may beonsdered a sor of ahe for ned probemsong steps

Tess arred out wth R show good agreemen wth reatonmedaa rom human earnng expermens oweer e net daa nhem eaon me daa ae no onuse fo dedng nenamehansms s no ear to wha exen he essenta nwardoongmehansms of OR an hep t nrease ts "understandng of raon-

shps beween enttes n the word f hose reatonshps are not dedubefrom ts enoded nowedge and rues s aso not ear how a puatebooga sysem based on R oud eoe oban ts nta uota ofsmbos and rues and aod faa parass when aaabe rues proednadeuae o deermne aon Nonetheess OR ha pred o be ausefu too o studng aspets of human probe song

ACT* Ths mode deeoped by nderson (1) (the nae sgnesadape ntro of though * s a resed erson) aempts o

rea ognton as a ruebased system n muh the same way as Rreas probmsong Dearate nowedge auson an proeduraearnng are treated as smary as possbe The anaog o OR exendsto the mehansm or rue ompaon whh resembes hunngand o he exense ess edng good agreement wh poweraw dataobtaned n huan earnng experents The mode s one of few o beapped to human anguage auson n hs as * earns wordmeanngs and sntax from exampes by assung onepts enoded asrues are aread gen n genera agreement wth the ews of hos(1) n ths respe t shares the assupon of essenta a programs nudng R tha meanng an be represented entreywthn orma symbo ssems Ths assumpon has been srenuousy



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HAVOALLY AS OG 60

llened (Bd ) e need sybls n l systems tqe menn by ntetns wt te wld tsde f te systemtself s een well dsssed y Ptnm (1) nd Hd (10), wdeses te dlty s te "syml ndn plem

Emeren BehavorIn eent yes, te nlty f stndd I t slve flly te plems fplnnn nd nlln mvemens n te el wld s led esene nteest wtn t I mmnty n te bevl ptesf blgl gnsms M eent wk s enteed n te desgn ftl smlted ts evn dn t l pnplesmmn t mny f tese systems s tt te ntenl ntl me

nsms nete pess explt epesentns n ntn entld"wld mdel Insted, tese systems, vsly lled "tnmsents (Mes 0 "nmts (Meye & lsn et ntn veysmpe ntenl tetes ften dvded nt tnms mdles emned tn f sevel mdles n pde fly mple evss s wlkng, vdne, nd edefllwng s pp t desnn bts s nfmed y Mnsky (18) vew tt ntelne s mpsed ny ent ents te "sety nd (evewed n Reee)

SSMON n mptnt ne w s tt psedy Bks (1 1), w s ged tt lssl I systms peten wy tt nnt e tnsptle t te el wld He ttempts tvd entled pessng nd mplex ntenl epesenttns ltete by desnn mdlzed ntl systems n w e mdleenetes by tself sme pt te vell ev e dles ened n slled "sbsmptn tete n mptnt desnfete tt det ntenntns between ndvdl mdles e d

wd (esemln, f emple, te ll nept f ltel nbtn) e mtted tete nte exmple f ts pp s mlet desned y nnell (10), w lles empty sd ns nn nstted ewld envnment nnells bt des nt vepesstent sttes t s detly dven y evnts n te wld t ll tms n elted st f smltns nsped y neetll sevtns,Bee (10) desned smltn f n tl nset tt sws smpleeeent bev s s ltn, wnden, edelwn ndfeedn lt te bevl epete te smltn s lely te

est pewed nnetvty te system ppes t sw dptve ndexle bev wtn ts ven envnment

Mny f te ely evements f syste wt "mrent ev



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606 REEKE & PRN

are ute mpreve and t encouragng that A reearcher have beennped by tudyng anmal behavo. oeve the ntence on modulaachtectue and peed behavoal epetoe lkely to be too etctve hen te approach caled up to reproduce o eplan te behavor

o hger anmal A key tructural eature o hgher nervou ytem the connectedne o ndvdual neuron thn and beteen unctonallypecaled regon provdng multmodal memory and a ngle coherentpctue o e old. Leanng and memory are mportant n hapng anoanm nteacton th t envonment. In ou ve emeentbehavor lkely to reman lmted to the doman o nectlke creatureand all hot o beng able to model the behavor o hgher vertebrate

Aral Nural Nworhe ter artcal neural netork (ANN) and connectont ytemencompa a de varety o ytem that contan mpl computatonaleleent that ae heurtcally modeled on neuon and ae nteconnectedn netok Such ytem have a htory at leat a long a that o AI (eMcCulloch & Ptt 13) but early reult ere dcouragng (Mnky &Papert 1969 and erou development reumed only recenty Artcalneural netork ytem are extremely dvere and e reer te reader toother ource or more detaled ummare and crtcm (Graubard 1

Hanon & Olon 10 cClelland et al 16 Peer et al 1 Poggo10; umelhart et al 16; Smolenky 1 Zoneter et a 10). Art-cal neurl netork have been condered vluable or modelnbchavor becaue they do not reure he explct enumeraton o rulecommonly eued n A or alternatvely becaue they can be ued tomplement dtbuted epeentaton o ulebaed ytem (ouetky &Hnton 1) oever ANN hare th A the undamental unctonalt (Bechel 1) aumpton that categore ext a pror n theorld ndependent o a concou oberver and that behavor can becomputed by an orgnm bae o detectble regulrte n te envronment or xample ejnok t al (1) ugget that a eld calledcomputatonal neuocence an be dened to eek comptatonal explanaton o nevou ytem uncton In the ve one o the majorreearch obectve o computatonal neurocence to dcover the algo-rthm ued n the bran oever other author have argued tronglythat the bran doe not operate by ue o algorthm (Edelman 1) butrather that many elemen that cannot be ormaled uch a analogy and

metaphor, are necearly nvolved (Johnon 1 Lako 1 earle12) To te etent that thee argument ae coect the each o banalorthm tart rom too narro a preme and lkely to hre omeo the hortomn o A We decrbe here a e o the more ucceul



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EA VOAY AED MODE 0

ANN moes h n e ineee ineenen of omuiondesiptions euse they enete some fom of ehvio

AEED MODE ise ( 98) esse he oems of pe eo

nition nd the iity of nims to nvite tod ememd oith the i of visie ndmks. He egn ith ee unitsesine o eseme ein neuons found in oen hiomus(OKeefe Ne 98). he mode units esponded to visu sene t iu oion y summin he esonses of othe units ht eeive y he esene of iniviu nmks hen hese eeunits ee modied to espond ony hen the osev s in ptiu(ody tned) oiention etive to he sene hei opt o eused to guide nvigtion to home oion Hoeve fo esons

invovin the mehod of omining oniing ieion iniions fomieent unts the esuing movement ks ee not s iet s theyou e o n u nm. s oem s eimne y ong ntentive eiy deived poedue fo ominin vies. Possieneu ontes of this tentive poeue ee not identied.

MHY MUPHY (Me 990 99) is kinemti ontoe nd pthpnne tht ontos oot m se on veo imges. t is ehps mostnoeothy fo ominin AI nnin tehniques ith onnetionis

hitetue fo oeve onto of the m MUPHY ontins netoksih units h espon to ojets in he visu sene (oje eoniionis simie y efu ono of ighin onitions) joint nes nveoity nd hnd dieton hese neoks deveop n impiit kinemti moe of the mem system, thus voiing the need fo nexpiit desition of the sysem's geomety. his sysem n guie them o unosue ges he AI omonen s he iiy oeh ojets in the pesene of ostes he etive suess of this AI-ANN hyi inites tht eh poh n o some eent omemen

spets tht e king in the othe.

AT his system (uesein 988, 99) hs simi os o thoseof MUPY, ut they e ompished entiey ith neu netokimpementtion he m funtions in theedimension od ndthee e to vieo mes to ovide steeosoi vision. isu inutmps e oute vi ys of juste eights onto te mps hihin tn emt m moto signs. (Mutipe mps fo dieent nges of jointnes minimie poems use y the ossiiity of ehing e

vi moe thn one omntion of nges) he need to sove the diutinvese ynmis poem o the oot m is voided y evetinin sttey A ndom tivity eneto is used to tivte the tetmp n the m moves to oesponding nom position he m s



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08 EEE

vsualed by he cameas hus poduc acvy he pu maps.Coeces eee pu ad ae maps ae adused fo bes mach.Afe may als a obe plaed ayhee he vsal eld evokesav the p maps smla o ha evoked du a y hemae of he am self a ha locao poeced o h ae map houhhe coecos ha have bee adused hs acvy auomacally moveshe am o s he poso eeded o ecep he oec. I he vesodesibed IFANT s o oeed ih he aeoiao o he aeas e oe ha s appopae o each ad asp.

MAV Baloch & Waxma (99) descbe a cool sysem fo a mobleobo wh a modla dsbed ahee based o heoea poposals o Gosse (Gosse 98 Gossbe & chmauk 98). The

obo s desed o espod o smple lhed paes dsplayed o CTscees I leas o dscmae dee paes depede of helocao se ad oeao. A smple aaloue of Pavlova codo s sed o a he deve o appoah some sm ad avodohes. al vso ad moo ool o loomoto ae mplemetedva coveoal compoal ehqes vsal obe eooehavoal codo ad eye moo cool ae hadled by ANNs.The auhos aemp o deal h he polem hc s oed mosohe models of cooll mulple ehavos ih a sle sysem. Thss doe by s a smple model of emooal saes.

Alo OMA desced eo MAVIN s oe o he mosamos eual ewok oo ool sysems ye aemped. Alhohcea smplcaos have ee made s vsual ad moo coolsusysems MAVN eeally avods uoloca assumos. Thedeee of behavioal hess ha wll emee fom fuhe es wth hssysem w e ees o obseve.

TH EA ME HAVG YM Aleaves o he

models peeted above have bee poposed ad may e stvelyompaed wh them. Nelsos () aleatve o pses model ovsa hom voves omao of de aoao ewee eaedvsual paes ad moo ommads. Bahe e al (988) cool a moleoo y eal eok echques ad popose a mehod o exacsymoli epeseaos fom he eal e fo p o a AI avaooe a ask hat as acomplshed a moe ad ho fasho iMUPY. Eckmlle 990 poposes a ual aula lace oememe ad epod moveme aeoes a oo oolleha s ue dee om ha o Kupesei. Veschue e al (99)have desied a moe o a auoomos oo ha s copleey seoa ad does o ely o pedeed kowlede abo he old.



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BHAVOALLY BASD ODN 09

h mdl cn cnditind t ppch tts nd vid stcls ritrry psitins in its nvirnmcnt

"

In this sctn dl riy ith mdls tht incrprt m rlss listic ntmicl nd physlicl chrctistics Sm f thsmdls hv n inttd in vll chitcts tht ltimly pdc hvir Althh As s nl principls hristiclly t sst slins t prticlr prlms rlistic nrl mdls r dsindth dint prps in mind hy hlp s t ndrstnd spciclicl phnmnn rprdc ctl physilcl xpimnts, rn pdictins pssi xprimns AmsInrsn t

l 1990; Millr t l 1989; Prsn t l 198; r t l 1989) r, discss f xmpls nd thir ptntil rlvnc fr ndrstndinrin fnctin

NUR MDS F MR SYSMS h cncti t l rnitn nd hvi is spcilly cls f nrl city nrtinrhythmic tpt pttrns H hythmic tt cn m frm thctivity f f nrns hs n rkd t f svl systms thpylric ntrk f th crstcn stmtstric nlin th nrrs

f simmn mvmnts in th mrin mllsc Toni nd lcmtinin th lcs h nl sis f simmin mvmnts in th lmpry l vrtt hs n xtnsivly stdd th xpmntlly nd nntk mdls y Grillnr Grllnr t l 1991 Gillnr & Mtsshim1991) n th mds ltntn st ctvty s nd n sntlspinl ntrks tht cntin rltivly smll nmr f lldndnns vl typs f cndctncs incldin tht pdcd y vldpndn mhylsprt NMA) chnnls r xplicilymdld, mkn it pssil t sv h spcic ichmcl mdi

ctins nnc ll ntk hvi F xmpl s in th cntxpimnt th fncy f th rhythmic ctivity tht th ntrk prdcs dpnds n th lvl f thpplid NMDA rillnr t l 1988)n dditin t mdlin th nrtin f hythmic mvmnts ithin nspinl smnt smltins hv ddssd intsmntl cdintinnd th l f snsy inpt Gillnr t l 1990 Willms t l 1990)hs stdis hv shn ht i is pssil t cnstc nrlly sdmdls tht prdc simpl hvir, in this cs, lcmtin

n cntrstin stdy ckry t l 1989) sd iliclly lss pr

ssiv ckpptin nrk t mdl th systm h cnlsithdrlndin mvmnts in th lch Whil tin tht thir mdls nt physliclly rlistic Lckry t l mk th st rmnt



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60 REEE & SPONS

ha nonhlss dmonsras ha knon anoml faurs hy

hav nludd mus sun o pfom h ask assgnd o hm,aus hy an do so vn n h lss nral akpropaaon norkThs rsmls h usaon of ak propagaon gvn y Zpsr &

Andrsn (988) and mnond aovBaus of h vasly grar omplxy of h undrlyng nual mh-

ansms, h a sll vry f nually asd modls of havor n hghrvrras Som hav arud ha h sudy of smpl oransms, suhas Aplysia, ll ulmaly rval prnpls ha hold also for hghrvrras I appars o us hovr, ha h havor of hhr vrras ll no omplly undrsood y aumulang and laor-ang nva uy Aqua nual ods of vahavor ll hav o rood n h full omplxy of vrra anaomyand physoloy.

VSUY GDD BHV N MPHB Sval modls, ollvlyalld Rana computatrx, hh addrss vsuall gudd haor n rogsand oads, hav n onsrud y Ar (Ar 989, 99) Svralomonns dal h h frogs noal ssm and h oganzaonof al olumns (Laa al 98), as ll as h dph ppon, douhavo, and pryprdaor dsrmnaon (rvans Pr al 985).n a rn nural smulaon of h frogs rna, um, and halamnul, an & Ar (99) xamn possl nura sras for hdsrmnaon of omlk smul Basd on hr smulaons, hsauhors pd ha parn dsmnaon s ahvd n h anrorhalamus, hh s anaomally an arly snsory ara Morovr, ang& A prd ran havoral hararss (dshauaon hahs) for ss of sul ha hav no y n d n h al anal

Synh Nural odls

als modls of havn nvous sysms qu a horal andmodln aroah ha onsdrs mulpl ornaonal lvls nludnsyna, nuronal, aa, and loal lvls of h nrvous sysm hphnoyp of an oransm (ral or hypohal) and s hsory of smulaon and rsonss n h nvonmn h synh nual modlngapproah k al 990a) alludd o arlr as dsgnd o fulll hsrqumns Synh nural modln uss larsal smulaons osudy naons n vns a all hs lvls Baus all lvanvarals ar rprsnd n h omur orrlaons n vns n

dn ran aras, as ll a n vns n h an and n hsmulad nvonmn, an radly rordd and analyd hsapproah rqurs a omprhnsv hory of h nrvous sysm h on



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BHVRY BSD MDG 1 1

poy n h ss sb s h hoy of non goupson NG)

A gng pnp of h NG mn198 198 1989) s h h nvous sysm ops y son onpxsng vn n vopny gn popons osnpss Aong o h ho sh son s vn b h pvv of bhvo s pom by h ognsm I s ompsh yn oon of synp snghs ng o h foon ofsongy nonn o ovs o nuons knon s nuongoups. A num of suh goups foms po h un hnhh son os ompon bn non gops n p-

o m by sm poss of son s o nhnn ofpv bhvo by n snghnng o knng of synponnons no hn, n fo hos gops hos v onbso h bhvo.

A n omponn of h ho s h noon of n hh s fom of ongong, po hng of sgns bn non p-os n h s o n phs. n fnons o ss hsponss onssn oss n non pos ny onm n oss sm nvonmn suons oung n

ms. fs h xpsson of muuy onssn pns ospons n h pos nk hus ngs sp sponssn pos h psn n snsomos o sbmoshs fog h bss of gob mppngs h k o h sson of sm.

v ky pons of h TNGS hv oun xpmn suppo.I p En 98) h nuon goups o b fon oxs s o popuons of songy nonn nuons h osh h pv pops n mpo pns of shg.

Non gops ompos of sm n s n xhbng ohnpns of vy hv bn mons n h vs o Gy &ng 1989) n moo ox Muhy & 199) omns of ovnons n non ox Yus 1992) ou b y vopmn psos o non gops Ls vn o h xsn of sh gops oms om oh pos of o onon shgs n fqn obsvons of sng of nuonsh sm pv pops n mny s of h bn Th sso vn fo h oun o n hn n bn os. nons ong ooo onnons n gv s o m-po oons bn sn non gops khon 1988Eng 1991 Nson 1992) Ths nngs onnng goups



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2 K & SNS

and reentry uort fundamental remie of the theory nonethele thetheory ill require eriou revion if mortant bran function are honto deend on the activity o ingle neron or if cortical roceing i

eentially feedforard and hierarchical ith only minor role for intra-or interareal reentry.Selective mechanim have been modeled in detail at the level of nae

Chaneux & ehaene 989; Finkel & Edelman 98) local neuronalrou Finel & Edelman 985 Pearon et al 98 Sorn et al 989)ad the reentrant interaction of mltle cortical ma Finkel & Edelman989 Sorn et a99 Tononi et a992a). Here e focu on the ehaviorof a mulated automaton called arin III eeke et al 990a eee& Sorn 990).

DWN I arin i a model of a hyothetical ime organimdeined to tet the main idea of the TNS. It ha a movable eye and afourjointed arm ith hich it can reach out and ra objct n it todimenional environment. Thee eector ere choen to ermit imlecategoriation and motor action to be modelled in a imulated environmenta more comle ytem that oerate in the real orld i decrbedbelo. The nervou ytem of arin comre aout 0 interconnected netork, ith a total of 50000 neuron and 20000 ynae.

The connection initial connection trenth and rule for cell reoneand ynatic modication are ecied arametrcally for each netorkto etablh ermive condtion for the deired ehavior to e electedut either rior inforatio aout articuar timui or ecit aorithm for neural comutation are ecied. Traning of behavioralreone unuervied i.e. it roceed in the abence o internal orexternal rereentation of deired reone or feedack of detailed errorignal nto the ytem y a teacher. The adative value o reone idetermined olely by their conequence criteria for the election of

reone are given neural ereion y internal "value ytem that arereumed to arie n animal from evolutionary contraint.

Vlu n arin the modication of ynae of certanclae i biaed by heteroynatc inut from ecialied et of neuronhoe reone reect the automaton loal evaluation of it recentbehavor. hee neuron have connectivite that allo them to reondto the outcome of adative behavior and a uch they intantiate valueytem eeke & delman 98) Value ytem do not redee te exact

ay a ehaioral reone i eecuted or determne articular ercetualcategorie. ather they imoe iae on ynatc modicaton deend-in on the outcome of reviou nteraction ith the environment. Obviouly value ytem mut be imle enough to erform ther functon



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BEAAY BAED MDENG 1

ply as a onsn o heir geneically dtmind anatomy andllla pysiology. tis not t as ty old onstitt ytanot xampl o iddn omnli in nal modls.

Val systms opat by sponding to t onsqns o bavio

post ato. Ti otpt inns lag poplations o synapti onntions in a dis and modlatoy asion t is no attmpt tostimat and ot os at individa synapss as is t as o hebakpopagation taining l sd in many ANNs T is smblan btn t s o val systms in ain III and som vaiantso mo ntly dsibd inomnt laning (Maoni t al1991ab s also tton Bato 1981). Val systms an b ndstoodas basi voltionay adaptations tat dn boad bavioal goals oan oganism in tms o ti ogniabl onsqns.

Val systms a basd on stts in al nvos systms Caatisti ats o t val ptois sd in ain inld tpsn o snsoy ants a lativ lak o intnal od and topo-graphy, and diue and widepread eerent tha heerynapicay inu-n lag poplations o synapss. val bainstm nli appantlypsnt in all mammalian spis av idspad nt onntionsand psmably modlatoy inn on otial ativity (Fallon Loglin 198). T los ols o ampl snds ot axons to lag

and divs gions o t bal ot (Foot t al 198 Gatt Poll 19) val asnding monoamingi and oingi b systms spially inn sponss o oial at nons(vid in oot & Moison 198). Ts b systms old also binvolvd in ailitation o ampliation o synapti poplations in titagt aas and ts old sv as biologial olats o val systms

Genel popee o Dn I' un nd np ule A simlationpogam (t Cotial Ntok imlato"CN) (k Edlman

198) as ittn to pmit t onsttion o vy gna nal ntoksystms. n addition to nal ptos povids o t smlationo t snsoy modalitis vision to and nstsa gnals omhe imulaed ene are eneraed in he om o nonal aciviy inpecazed s tat an b onntd to any o t na ptois int modl. On t moto sid t may b on o mo ys it lataland vtia obital motions and on o mo ams it mltipl jointsa ontolld by nons in spid ptois tat a dsignatd as"moto ptois.

n t nstantiation o ain I dsibd a singl y and a snglam were used. Fur e f inercnneced reperire were conruced: afovation and nang olomoto sysm a aing sysm sing a



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4 REEKE & SPORNS

single mutiinted arm a tuhexplratin ytem uing a ierent setf "muse in he me rm, nd reentrant tegriing ytem. Thefur syem geher frm n umn ple f unmus ehavirinvving enritr rdinatn and ipe ategrizatin tiulu

bjetsThe repne f neurna unit in Darwin are determined y a

repne nin h h em rrespnding a linear summain fhrehded ynpi inpu, nie, upu urin, dey f previuativity, depressin, and refratry perds Training urs y peranenalteratns in ynapti weight arding t the equatin

where and} peify pst and presynapti els, respetively; representstime; is parameter that adut the vera rate synapti hange; S ishe timeaveraged ativity f ell i is an ampiatin threhd relating pynapi iviy m i he verage nenrain f hypheialpstsynapi "mdifying susne hat is prdued hen presynptiativiy is preent, and that deays expnenialy; is an mpatinthrehd reatin t prenapti ativit i the anitude f heternapti input r reevant vaue hee neurn i an apiatinthrehld reing vaue; and R is a rue seer ha ay e set t +

0, r - fr vriu minatin the ign f he three threhldedterm in he quin Pitive vlues fR ead enhnemen f synpseith rreated pre and ptsynapti ativity (eletin) ( eb 199,whe pped rue did nt inrprate vaue ytem) negative valuefR lead t suppresin f uh ynapses (hmestis) By hie f theparameter n the ynapti rue it i pibe t imuae any f a widevarey deren knd ynapses, h prperes rrespndng, frexampe, the f ynapses uing dierent neurransmier The resulting diverity f pssibiies ha been referred as transmier gi

(dema ) (r detaied eriptin te repne and api-atin funin ued n Darwin , ee Reee et a 1990a)

Behvor ofDrwn Darwin ud veate n bjes in it envn-ent tra their vement reah ut with it ar and tuh theirsurfaes, rae heir nurs, nd repnd rding t heher n eelnged a priulr egry (dened y visul nd ile riues)t ensitr yems (ultr and reahing yts) behavedntiall at rndm Respnding t jet n the simuaed envirnment,

Darwin generated expratr mtr ativity (randm eye mvemensr aing gesure with it arm s inerna ve ytem repnded he nsequene f hee pnanus mr as and ninuuly



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BEHARAY BAE MENG 6 5

innc icin f synpic cnncins (in s css hslg ssory o motor twors Ar rltvly shor po of m(o th rr of fw hunrs to thouss of trls Drw I's motorsysms fuco wh hgh ccurcy ocs prs ywhr whn

h vronm wr trc vsully n grsp y th rm (gur I) In is us f rnom movns o r inmc systm hN ANT ml iscuss v hs s frs in cmn wih hslcv prgm us o r rchg movms Drw . Howvr IAT slcs gls whch irctly spcfy h l poso orposur f th rm whrs Drw III slcts gsurs whch rc thcours of h r owr s gol Thus h ynics f ovm r rvos sysm coro Drw o IAT

chng in Drwin III ws incrpr n highrlv hvirl

pr clug smulus cgoro cog rspos I thctgorto sysm vsul cl sgls wr com s rsu f rcprcl rr rcos w vsul uchcnrs hvirl r ws rir if n c ws vislly sripn h umps o ts surfc Ths rx "c h oct wyrm h viniy f h un Whin lis Drwin Is hvrcoul coo"rwrg rsposs t o cgoy of ocsgv rs to mr crs rspos frqucy with full grlizin o ll lcins within h nvirnmn n rs f hcgry n pr f h rinig s Cnioig cul rplyrvrs y switchng h rwr from o cory to nothr

I summry Drw III or opportuy o vsu rlvts t rt lvlssyps cll group wor sysm hvorwth gv m pro Drw III show ssormotorcornin i coctio wih h mrnc of rltvly rc prcplcrizin Alhuh Drwin I hs m fw sps n h ircinofcono lrning cnn y lrn n fshio h woul l

o chg s hvorl rsposs y rch fsho towr vrnl smuli s cosqunc f ts own prc rng n hsss woul rqur grr lorto of rl vlurl ssn h iliy cpl ths in cnncins wn ctry nr cnrs

ARWN AN NMA cly w hv gu to xplor th pplcliy of sythc nur lg t hvor rworl vron (Elmn t 1992 W hv sgn urlly org uliply

piv vic (NOMAD cnrll y sil nrvs sys hcompl syst s cll Drwin I h nrvus sysm of Drw Icnins snsry n r nwrs nlgs hs in Drwin I



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6 16 RK & PORNS

whh e srehs he rd y d lueS a w hv dmsred h OAD e ried r lih mi i rdm h d pprh d sr rd uesrm lue ues sed lue ss rd heir rse se

(mdd by r nduvy) Embddng syse n a awrd nvirnmn hp vid vra pib pi f appra

) nvimt

Ey

8

6 4 4

0 X-POSTON XQO

. . , m

A I

4 8

Annu.R

ev.Neurosci.1993.16:597-623.

Downloadedfromwww.annualr

eviews.org

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BHVIRY BSD MDNG 6 17

based sula l Realwld sul ae heel he ade aable ha sulaed es ad s hader bas he ssesresses b (adeel r delberael) basg he sula r-l he eual delg as aled ealwld arfas suh asNOMD ers a uque esg grud fr behag eural dels

ae ehe Daw ad Daw V hae desraed haeualleel dels a be uled he behaal leel The shw hasud f he bra he hee ad he ere as a al ssehels larf a ases f bra sruure ha are hewse exl-able The ake ssble udersad hw he aaal araead des f he eus sse a be eeed as ke eledfeaues ha lead s fual aables as sues f se ad

err be ere hugh lex adaas Fall he delsshw ha e NG rdes a here ad eaus der fe wa h he ba gh aqure s adul fual eeehugh aeed eua ad deeleal ehass whu aeed fr huul eeal eahes ae sbl shees adfal easg

ur 1 () chemac dagram f he ubem f Darw I. Objec (ppled quare rgh f Em bx) m wh a "rm a pr f whch ewedb he ee (large uare lm f hl ; all cl vo. Movo th d th ootd (boom) coolld b h oclooo d cht cvl Th ditl dit coti toch o d th ttl t otc th d o oct Th ctozto cv o t o th clt o th vi eld ad rm jot co tht gl ov Th tcec to a hghed vl ct d coltg oto gal erme Cla f rg pae hee epee a ee lead clacaf bjec ad eeuall eld a up baed b ale ha ca acae ree memef he am. (B) rac f pah ak b he p f he am befre () ad ae right rag ccle. ag pceeded a fllw r each f 3 ral he ar wa placed a adard p wh he p a he p where he raecre derge (or ) wahe allwed me fr x ccle ad apc chage ccurred depedg up heucce f he meme elae a arge bjec whe p hw b he aea he rgh. fer rag meme ha reached he bec a drec ah hae beeeleced. () Drb f caegra freqece. Obec are grped accrdg he umber f alg repe ccurg egh al wh e er f aw caegra em Aca f he alg epe a a me wh 5ccle melm each al acaed he arm ad remed he bjec frm he erme. Eachuch ccrree wa cued a a "rejec repe. If epe ccured wh heccle me lm he ral wa eded ad a ew bjec wa eered. Objec are arraged

e cm depedg he frequec wh whch he me wh a repe. her Darw a rc egae ehlgcal ale aached "bmp adrped bjec. (Par A ad C reprdced wh perm f he eurcece ReearcFuda Pr B reprduced wh erm f e Crell her Ceer.)



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6 18 REEK & SPORNS

SUMMARY AND CONCLUSIONS

The alms inreile avanes ha have reenl ured in he wef uers avaiae sieniss i a isilies have eurae anelsin neura ewrk an ehaviral mels Sme hese haveeen nsaine me he imainain he amme ha rue ilal as. Their relevane fr he eeimenal neusienishus vaies rm ase ase. Sme mels (e Gillners mel amre swimin mvees) are s lse ase n kw neur-aam an euhsi ha i emes ssie eneae aes reise eerimenal eiins her mels (suh as UPYa D) us eurilial riniles i heir arhieures u

n ra an ariular ranism lhuh i is haer relae hesu f hese mels f he sud f real aials he fulll a imralaa re Th make sile insihs in hw ehavi is n-rlle neunal aivi ha wul e unainale in real animalsusin esen mehs.

Thus even he eesses neual melin have rvie a useulimeus wha is unuel a s rmisin arah ineraindaa fr he varius disilies ered wih ehavir ad he iThe rlems have een ine u man auhrs (se iains in ur

inui) an a hase mre riial evaluain aears haveeu We he ha ur rief suve f els ased wie ierenhereial arahes u all aime a elainin ehavi will enurae riia ass e ade s i e aure eld suh ashemamis we an ee ha mre mlee ls wil re aevauai heeial hheses aains he enire availaeeviene rahe ha us a ew einen es ases Suh evluain willmake ssile a muh mre rius elusin f invali r insisenhereial ideas r suh suies a muh smalle u mre rus sef asi riiles a e eeed emere Fr he erseivearded ur deli udies i aears esseial ha mdelie inrm a eneral her ain unin. n his wrk he he neurnal u selein rvies a useul asis r urher wk virue f is nsisen wih asi evluina and hilial ri-ies an he we f he seei aradim shae eual newsin ehaviral aaive direis

ACNOWLDGMENTS

he auhr esearh was arie u as a he heeial neu-il eseah am a The eursienes nsiue whih is su



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BEHAVORALLY BASED MODELNG 9

d hgh h Nsins Rsh ndn h ndinis m s his sh fm h Jhn D nd hinT MAth ndin nd h i P My h sO n is W M K ndin ew We hn G M

dmn mny h disssins nd ii sggsin

Lterature ted

mbrsIgrs Grgr R, chG. 1990. mti f lcrt r-frms hirrchc clstrig ene 4744

dr R 93. The rchitecture of

Cognition. mbrid M HrrdUirbib M 1 9 9 1 . rl mchisms f

isumtr crditi Th utif ana omputatrx. I rom Anmals toAnmats. Pro. rst nt. on on mulaton of Adapte Behaor, d. .Mr . W Wils . 3-30. Cm-bridg Mss M Prss

rbib M 1989. Visumtr cr-diti rl mdls d rctlrbtics ur ordnatonmphbians omparisons Models, andRobots

d P wrt M. rbb 1 2 1 1 . w Yrk Plumshb W R. 1952. Dsign for a Bran .

d Chm & Hllhb W R 1940. dtis d i-

lbrium J Ment 86: 47883Blch Wxm . M. 9 9 1 . Visl

lrig dti xcttis dbhirl cditiig f th mbilrbt MVI Neural Netw. 4 3

Brh Dr W B. rg C C9 lt f ccurt ur-mrhc lrthm fr utmrbt I d. R ckmillr C dr Mlbr 2.Brli pringe-Verlag

Bchtl W. 1988. hlosophy of Mnd AnOvervew for ogntve ene HillsdlN rbm

Br R. D. 990. ntellgene as AdapteBehaor An xperment n omputatonaNeuroethology Bst cdmic

Bckhrd M. H 99 Cgt rr-tt i th bri Enyl Human Bo2 558

Blck 97 rubl wth fuctl-

m. Percpton and Cognition Issues nth Foundations of sychology d C W. 261325. Mili: UiMi Ps

Br R d 1987. Artl ntelgeneThe ase Aganst d Cm lm

Brs R . 1 9 9 1 . w rch trbtc Science 53 73

Brk R . 1989. rbt tht wlk

mrt bhir frm crfllld twrk Neural omp 1 253 62

Crts Pr F. r R . . rbib M 1985. r mdl f irctis sb-srig rrdtr dicrimi dsi rfrc i r mhibi. .Theor Bo. 1 1 3 1 17

Chgux P Dh . 99.rl mdl f cgt fctis.ognton 33 63-109

Chmk . 1 986 Crtesian Lnguists w Yrk Hrr & Rw

Cll H 1990 Mnimalist Mobile

obotcs. Colony-tyl Architctur foran Artal ratre Bt cdmic

Cx Wlf G T d 1990. Autonomous obot Vehles w rk ir-Vrl

Dh Chgx P 1989. immdl f rfrtl crtx fcti idldrss tsks. J ogn Neuros. 46

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