Discrimination of color-odor compounds by honeybees: Tests of a continuity model

Transcription

1 Animal Learning & Behavior 1987, 15 (2), Discrimination of color-odor componds by honeybees: Tests of a continity model P. A. COUVLLON and M. E. B'TERMAN University ofhaaii, Honoll, Haaii n experiments previosly reported, individal honeybees ere trained in a variety ofproblems to choose beteen to visally identical bt differently scented targets, one or the other of hich contained scrose soltion. The reslts cold be simlated accrately ith simple eqations for compting changes in associative strength prodced by reinforcement or nonreinforcement and for predicting choice on the basis of relative strength. n the present experiments, the targets sed differed in color as ell as in odor, and the animals ere trained in a variety of problems ith color-odor componds. Contrary to expectation, the ne reslts cold be simlated accrately iththe same eqations as before onthe frther assmption that the components of a compond gain and lose associative strength independently (independence rle) and that the associative strength of a compond is eqal to the sm of the strengths of its components (smmation rle). n recent experiments ith honeybees, e have stdied the discriminative learning of individal foragers shttling back and forth beteen the hive and the sill of an open laboratory indo (Covillon & Bitterman, 1985, 1986). On each visit, to differently scented gray targets ere presented, one ofthem containing a drop of5 % scrose soltion from hich there as feeding to repletion; if the target ithot scrose as chosen, immediate correction as permitted. The performance ofthe animals in a variety of problems (inclding sccessive reversal and ambigos-ee problems) as simlated qantitatively ith simple eqations for compting the strength of the association ofeach target ith scrose and for predicting choice on the basis of differential strength. Or strategy as first to look for the rle of choice in problems reqiring only the most primitive associative principles, and then to extend those principles in hatever ay might be necessary to deal ith the array of seemingly more complex associative phenomena discovered in previos ork on compond conditioning (Covillon & Bitterman, 1982; Covillon, Klosterhalfen, & Bitterman, 1983). The strategy as adopted on the perfectly testable assmption that the choice rle identified in the first experiments old contine to apply as the associative featres of the theory ere elaborated. As explained at the otset (Covillon & Bitterman, 1985), or primary interest has been in the associative learning of honeybees. We have been interested in choice secondarily, as an index of learning that is more reliable than latency of response to a single target and more efficient than resistance to extinction. Change in associative strength is expressed by a linear This research as spported by Grant BNS from the National Science Fondation. Helpfl advice from William T. Woodard is grateflly acknoledged, as is the assistance of Hien Lien, Philip Okamoto, Ssana Plaa, Todd Wade, and Mei Yee Wong in collecting the data. Reqests for reprints shold be addressed to the Bekesy Laboratory ofnerobiology, 1993 East-West Road, Honoll, Hl eqation (Bsh & Mosteller, 1951) in the no mch more familiar notation of Rescorla and Wagner (1972): VA = (3{>,-VA), ith VA representing the associative strength of alternative A, VA the change in strength prodced by reinforcement or nonreinforcement, ).. the asymptotic associative strength, and {3 the learning-rate parameter. Rescorla and Wagner's salience parameter, ex, does not appear in the eqation on the assmption that the odors sed are eqally salient; althogh associative strength may vary ith ex; the prediction of choice, hich (as ill be explained in a moment) is based on relative strength, does not. The vale of ).. is taken as hen there is reinforcement (on the assmption that the magnitde of reinforcement is maximal), hen there is no reinforcement, and provision is made in the model for the possibility that the vale of{3 is different for reinforcement and nonreinforcement (U{3 = incremental or p{:l, {3 = decremental or dori), When choice ofa is reinforced, VA = U{3{l- VA); hen it is not reinforced, VA = {3(-VA) = -{3' VA' The associative strength ofa relative to that of alternative B is designated as r A and is expressed by the eqation ra = VA/{VA+ VB), here VB is the associative strength of B. A simple compter program evalates r on the basis of the initial vales of VA and VB (hich are assmed to be greater than in conseqence ofpretraining ith the to stimli), dictates a choice, and then calclates the reslting change in associative strength. When A is the reinforced alternative on a given visit, VA alone is changed (incremented) if A is chosen initially; if B is chosen initially, VB is decremented and then VA is incremented. Choice is dictated by anyone ofa family ofpoer fnctions that may be incorporated in the program, that is, fnctions relating P A, the probability of choosing A, to ra' Copyright 1987 Psychonomic Society, nc. 218

2 DSCRMNATON OF COLOR-ODOR COMPOUNDS BY HONEYBEES 219 To generate the choice fnctions, e se the scaling eqations for r Q.et. et..9 o z U) 8. 8 o.7 > ::::i iii.6 et. m.5, and p = p = s(2r-1)k s(1-2r)k for r <.5, hich, ith s=.5, yield a set of sigmoid crves passing thogh the points (,), (.5,.5), and (1,1). When K > 1, P changes sloly in the region of r=.5 and progressively faster at the extremes; hen K < 1, the opposite is tre; hen K = 1, the relationship beteen P and r is linear, as shon in Figre 1, here the crve for K = 1, s =.5 is inclded to provide a frame of reference. (The crves of Figre 1 are plotted only for r.5, becase all the fnctions are perfectly symmetrical for r <.5). Whens >.5,ithPtrncatedto::5 P::5 1, the fnctions are steeper, as shon by the crves plotted in Figre 1; the trncation implies, of corse, that the choice measre is insensitive to differences in extreme vales of r. For each fnction considered, e set ot to find the initial vale of VA = VB and the vales of U{3 and D{3 that old yield the minimal root-mean-sqare (RMS) deviation of predicted from obtained choices, and e compared the fnctions in terms oftheir minimal RMS deviations. Good fits ere achieved ith the clster of fnctions shon in Figre 1, of hich K=.75, s=.833 as marginally the best. n all cases, it as necessary to assme rapid learning-initial vales of VA and VB (generated by reinforcement in pretraining) on the order of.3 or.4, and {3 vales on the order of.2 or.25. We ere able in or previos experiments to simlate choice rather accrately on the basis of the differentially reinforced odors alone, ignoring sch perfectly dis-, ,-..., f.5 K.-..l-.-.L- -l- -L-_ 'A= VAl VA+ Val Figre 1. Five choice fnctions yielding good fits to the data of previos experiments (CoviUon & Bittennan, 1985, 1986) ith K=l, s=.5 inclded for reference. criminable properties of the targets as color (hich as the same gray for both) or position (hich as nondifferentially reinforced), and it may be ell no to consider hy that shold be. t is conceivable that color and position ere overshadoed by odor, hich old reqire a departre from the simple contigity-freqency principle of association incorporated in the model. Another possibility is that sensory components other than odor did, in fact, acqire appreciable associative strength, V e, adding eqally to the strengths of the differentially reinforced alternatives, and that by ignoring them e exaggerated r; it can be shon that, hen VA > VB, VA/(VA + VB) > (VA+ Vc)/(VA+ VB+2Vc), and the opposite hen VA < VB' f r as exaggerated (its absolte deviation from.5 ndly large), the error may have been compensated for in the fitting process by a flattening of the choice fnction, hich implies that, contrary to or expectations, complicating the associative featres ofthe model may indeed change or pictre of the choice fnction. n the present experiments, e set ot deliberately to do mlticomponent modeling, introdcing to colors as discriminable as the odors and differentially reinforcing them along ith the odors in ays designed to promote interaction and to facilitate its analysis. We contined to balance position, bt otherise, for the time being, to ignore it on the basis ofearlierevidencethat sggested that it might reqire special treatment (Kosterhalfen, Fischer, & Bitterman, 1978); position is not, after all, an intrinsic target property, bt is given only in relationship to the strctre ofthe visal field. Or strategy as to begin ith the basic "continity" assmptions (Hll, 1929; Spence, 1936)-thatthe associative strength ofeach component of a compond stimls changes independently ith reinforcement and nonreinforcement (independence rle), and that the associative strength of a compond is eqal to the sm ofthe strengths ofits components (smmation rle)-to try to identify points in the data at hich those assmptions might appear to be inadeqate, and then to think abot ho they might have to be spplemented or changed. The independence assmption is implemented in the model by separately incrementing or decrementing each componentofa reinforced ornonreinforcedcompond. Where A and B are the to odors, X and Y the to colors, and the animal is given a choice ofto colorodor componds. AXand BY. ith AXreinforced. VA and Vx are incremented independently ifthe animal goes first to AX lava = U{3(1- VA) and av x = Ut(1-V x»); if the animal goes first to BY. VB and Vy are decremented [avb = -D{3' VB and avy = -nit Vy) before VA and Vx are incremented. (t may be ell to emphasize that, despite the Rescora-Wagner notation, shared associative strength is not assmed.) By the smmation rle. VAX = VA + V x and VBy = VB+Vy. Choice beteen AX and BY is simlated by compting rax = V..!(VAX+VBY) and reading PAX from the choice fnction. Earlier experiments ith resistance to extinction as the measre of associative strength had given abndant evidence ofthe seflness ofthe smmation rle (Covillon

3 22 COUVLLON AND BTTERMAN & Bitterman, 198), bt evidence also of compond niqeness (Covillon & Bitterman, 1982), hich has sometimes been held to contradict it, and evidence of overshadoing (Covillon & Bitterman, 198, 1982; Covillon et al., 1983), hich may seem incompatible ith the independence rle. We had every expectation, in fact, that or ne experiments soon old prodce reslts that cold not be simlated ithotdepartre from these rles. Or only qestion as abot hat changes old be reqired. METHOD Sbjects The sbjects ere honeybees (Apis mellifera) that ere foraging for nectar. They came from or on hives, sitated in the vicinity of the laboratory, and all ere experimentally naive. Procedre ndividal bees ere pretrained to fly from their hives to the laboratory and drink to repletion from a large drop (abot 1 1'1) of 5% scrose soltion on a target that as set on the sill of an open indo. An animal as selected at random from a grop of foragers at a feeding platform eqipped ith a large jar of 1%-12% scrose soltion, carried in a small matchbox to the laboratory, and placed on the target. There it as permitted to drink its fill of 5 % soltion (dring hich time it as marked ith a spot of colored lacqer) and then to fly to the hive. Typically, the animal retrned to the laboratory of its on accord in 3-4 min, contining thereafter to shttle back and forth beteen the hive and the laboratory as long as food as available. f the marked bee did not retrn to the laboratory after the first placement, it as picked p again at the feeding platform (here it sally cold be fond), carried back to the laboratory, and set don on the target once more. The pretraining ended ith the bee's second retrn to the laboratory of its on accord. The targets ere covered petri dishes ofclear plastic, 5.5 ern in diameter. n each cover, to hich a disk of green or ble plastic of the same diameter as the cover cold be cemented, eight eqally spaced holes,.5 ern in diameter, ere drilled at the oter circmference. The dishes themselves contained ads of cotton that either ere impregnated ith the scent of geraniol or the scent of peppermint or ere nscented. n all, eight sets of targets ere sed in the training: green-nscented, ble-nscented, gray-geraniol, gray-peppermint, green-geraniol, ble-geraniol, green-peppermint, and ble-peppermint. The covers sed on each visit ere ashed and exchanged for others in the same set after the visit in order to balance extraneos stimli. For prposes of pretraining only, there ere three additional sets of targets, one ith gray covers and labeled ith both odors, and to ith covers half-green and half-ble, one nscented and the other labeled ith both odors. The pretraining procedre in every case as to place the animal carried in from the feeding station onto a target that presented all of the stimli it old enconter in its sbseqent training. On each training visit, the animal fond to targets set 1 em apart on a line parallel to the oter edge of the indo sill. One ofthe targets contained a large drop of 5% scrose soltion, and the other contained a large drop of tap ater that as distingishable from the scrose only by taste. The target first chosen by the sbject on each visit as recorded, and the trial ended hen the animal had fond the correct target, fed to repletion, and gone back to the hive. The varios training problems ill be described as the reslts are presented. Each sbject as trained only in a single experiment, ith no feer than 8 sbjects per problem and sometimes considerably more. RESULTS Color Verss Odor n modeling or previos reslts for odors, e ere able to ignore their salience, hich as assmed to be eqal. Fortnately, e can contine to ignore salience in or ork ith to dimensions, becase the reslts of three different experiments give no reason to assme a difference in the salience of the odors and colors sed, as indexed either by rate oflearning or by competition for control of choice. One-dimensional training. Shon in Figre 2 is the performance of to grops of 8 sbjects each that ere trained for 1 visits either ith nscented green verss ble targets or ith geraniol- verss peppermint-scented gray targets. For half the color animals, green as reinforced, and for the rest, ble as reinforced; for half the odor animals, geraniol as reinforced, and for the rest, peppermint as reinforced; for both grops, the reinforced alternative as presented eqally often on the right and on the left in qasi-random seqence. (These balancing procedres ere employed rotinely in the varios training problems and ill not in general be referred to again.) t may be seen in Figre 2, hich is plotted in terms of the proportion of animals in each grop choosing correctly on each visit, that the to colors ere discriminated as readily as the to odors. The mean nmber of errors as 1.5 in the color problem and 1.75 in the odor problem (for the median test, Fisher's exact p=.24). To-dimensional training ith one relevant dimension. Plotted in Figre 3 is the performance ofto grops of 8 animals each that ere trained for 1 visits to choose beteen targets that differed both in color (green vs. ble) and in odor (geraniol vs. peppermint). For the colorrelevant animals, color as differentially reinforced and odor as nondifferentially reinforced (e.g., greenpeppermintpositivevs. ble-geraniol negative on half the visits and green-geraniol positive vs. ble-peppermint.6 t-.4 cr cr.2... COLOR _ ODOR. a VSTS Figre 2. The perfonnance of to grops of animals in a onedimensional problem, one trained ith color and the other ith odor.

4 DSCRMNATON OF COLOR-ODOR COMPOUNDS BY HONEYBEES 221 ( COLOR.-. ODOR B 9 1 VSTS Figre 3. The performance of to grops of animals in a todimensional problem, one trained ith color relevant and the other ith odor relevant. negative on the rest). For the odor-relevant animals, odor as differentially reinforced and color as nondifferentially reinforced (e.g., green-peppermint positive vs. blegeraniol negative and ble-peppermint positive vs. greengeraniol negative). The crves sho that learning to respond in terms of the colors rather than the odors as as rapid as learning to respond in terms ofthe odors rather than the colors. The mean nmber oferrors as 2.38 in the color-relevant problem and 2.25 in the odor-relevant problem (median test, exact p=.34). Transfer after confonded training. n another experiment, 64 animals ere trained for either 6 or 2 visits on a confonded problem, ith one color-odor compond (e.g., green-geraniol) reinforced and the other (blepeppermint) nreinforced. Then half the 6-visit animals and half the 2-visit animals ere trained for 1 visits ith color relevant and odor irrelevant, and the rest ere trained ith odor relevant and color irrelevant (a 2 x 2 design ith 16 animals in each grop). The idea here as that performance in the second problem might indicate that the animals had relied primarily on color rather than odor, or on odor rather than color, in the first problem. Consider an animal that is trained in the first problem ith green-geraniol reinforced and ble-peppermint nreinforced and mst choose beteen green-peppermint and ble-geraniol on the first visit of the second problem: f it has learned primarily abot odor in the first problem and if odor is relevant in the second (ble-geraniol reinforced), it ill choose correctly and have little difficlty on sbseqent visits, bt ifit has learned primarily abot color rather than odor in the first problem, or if color rather than odor is relevant in the second problem, it ill tend to choose incorrectly. The experiment as done ith to different amonts oftraining in the first problem on the chance that the animals might learn first abot one ofthe dimensions and only later abot the other, or even that they might learn first abot both dimensions andcome only later to attend primarily to one of them. n Figre 4, the reslts for all animals trained in the color-relevant problem are compared ith those for all animals trained in the odor-relevant problem. The reslts for animals ith 6 training visits in the first problem are pooled ith those for animals ith 2 visits, becase amont of training in the first problem made no difference (median test, exact p=.5). The to crves sho mch the same pattern ofchoice in the color-relevant and odor-relevant problems. On the first, third, and forth visits, in hich the animals encontered componds different from those experienced in the prior confonded training, the color-relevant performance as somehat better than the odor-relevant performance, sggesting more control by color, althogh the difference is not significant. Themean nmber oferrorsas 1.44in the colorrelevant problem and 1.63 in the odor-relevant problem (median test, exact p =.4). t seems reasonable, then, to proceedith or simlations on the assmptionof eqal salience for all of the stimli employed. The ease ith hich e have been able to find a pair ofcolors as discriminable as the odors may be srprising in vie of general assertions in the literatre that bees learn abot odor more qickly than they learn abot color (e.g., Gold, 1982, p. 255; Lindaer, 1971, p. 44). t shold be obvios, hoever, that the otcome ofsch experiments ill depend on the particlar colors and odors employed, their intensity and similarity, and the manner oftheir presentation. Feer errors ill be made in training ith a pair of dissimilar colors or odors than ith a pair of similar ones, hich means that the similarity of the alternatives mst be eqated in any comparison ofthe rate ofcolor and odor learning. The otcome oftraining in to-dimensional problems ith one dimension relevant and the other irrelevant mst depend as ell on the relative intensity ofthe stimli qite apart from modality. n or first comparison ofcolor-relevant and odor-relevant problems (Klosterhalfenet al., 1978), hich actally involved (among others) the same colored plastics sed here, the odor discrimination as somehat more rapid than the color discrimination, primarily, e sspect, becase the odors ere more intense; not only ere the odor ells larger, bt the animals ere trained in an enclosre throgh hich there as less air movement than there as :: ::.2... COLOR.-. ODOR. a B 9 1 VSTS Figre 4. The performance of to grops of ldimals in a todimemional problem, one trained ith color relevant and the other ith odor relevant, after both had been trained in a confonded problem.

5 222 COUVLLON AND BfTERMAN at an open laboratory indo. Experiments that old jstify generalizations sch as Gold's and Lindaer's simply have not been done, and it is not clear at all, in fact, jst ho one old do them properly. One- Verss To-Dimensional Problems To begin to get some idea of ho ell or continity model is able to deal ith mlticomponent data, e compared the performanceof separate grops ofbees in onedimensional problems and in for different to-dimensional problems-a confonded problem, to color-relevant problems ith odors that varied either ithin or beteen pairs, and a color-relevantproblem ith a constant irrelevant odor. Confonded compared ith one-dimensional training. Plotted in Figre 5 is the performance on visits 1-1 ofthe 32 animals, previosly referredto, that ere trained for 2 visits in a confonded problemith the colors green and ble and the odors geraniol and peppermint. That peformance is compared ith the performance of the 16 animals, also previosly referred to, that ere trained in one-dimensional problems, either ith nscented green and ble targets or ith geraniol- and peppermint-scented gray targets (the to crves of Figre 2 pooled). There is no clear evidence of smmation-the mean nmber of errors as 1.34 in the confonded problem and 1.63 in the one-dimensional problem (median test, exact p =.17). This otcome is predicted by the continity model on the assmption of eqal salience. n a discrimination beteen AX+ and BY-, reinforcing AXeqally increments VA and Vx, hile nonreinforcedexperienceith BYeqally decrements VB and Vy. With Vx = VA and Vy= VB, rax= VAX/(VAX+VBy) = (VA+ VX)/(VA+Vx+ VB+ Vy) = 2VA/2(VA+ VB) = r». X and Y contribte nothing, then, to the ease of discrimination, althogh the animals do learn abot them. Where X and Yare less salient than A and B, performance in the confonded problem ill be better than in X+Y- (according to the continity model), althogh no better than in A+B-. That the animals trained in the confonded problem learned both abot color and abot odor is sggested by.8 o :: U tj n:: n:: o CONFOUNDED.... ONE-DMENSON o VSTS Figre S. The performance of to grops of animals, one trained in a confonded problem and the other in a one-dimensional problem ith color or odor. the fact that they shifted as readily to the color-relevant problem as to the odor-relevant problem (Figre 4). Nevertheless, e analyzed the data in one other ay in order to examine the possibility that individal animals ere attending primarily to one or the other dimension in the confonded training. Of 64 sbjects trained in the confondedproblem, 3 chose correctlyon the first visit of the second problem, and their performance in the next nine visits as compared ith that of the 34 sbjects that chose incorrectly. f correct choice on the first visit reflected a set for the relevant dimension and incorrect choice reflected a set for the irrelevant dimension, better sbseqent performance old be expected ofthe animals that had chosen correctly, bt no significant difference as fond. The mean nmber oferrors in visits 2-1 as.93 for the animals hose first choice as correct and 3 for the animals hose first choice as incorrect (median test, exact p =.47). Modes of presenting irrelevant stimli. We trn no to a comparison of the performance of three grops of bees trained for 1 visits to discriminate beteen green and ble in the presence of nondifferentially reinforced peppermint and geraniol, bt ith the odors presented in different ays. For a grop of 8 irrelevant-ithin animals, the alternative componds alays differed in odor (e.g., green-peppermint positive vs. ble-geraniol negative and green-geraniol positive vs. ble-peppermint negative). For 8 irrelevant-beteen animals, both alternatives ere scented ith peppermint on half the visits and ith geraniol on the rest (green-peppermint vs. ble-peppermint and green-geraniol vs. ble-geraniol). For 8 constantirrelevant animals, only one or the other of the to odors as sed throghot (green-peppermint vs. ble-peppermint for half the animals and green-geraniol vs. blegeraniol for the rest). One of or interests here as in the possibility that the irrelevant-ithin problem might be more difficlt than the irrelevant-beteen problem becase of more sccessfl competition for attention by odor in the ithin case; there is some evidence of sch an effect in rats (Wortz & Bitterman, 1953), althogh it may have qite another explanation. We ere interested in the constant-irrelevant problem becase in some earlier ork (Covillon et al., 1983) it had seemed to be more difficlt than the irrelevant-beteen problem. Performance in the three problems is compared in Figre 6, hich gives no indication of differential difficlty. The mean nmber of errors as 2.37 for ithin, 2.69 for beteen, and 2.6 for constant (Krskal Wallis H=2.2, p >.3). Eqal performance in the three problems is, in fact, predicted by the continity model. With A and B (the odors) nondifferentially reinforced in the irrelevant-ithin and irrelevant-beteen problems, VA = VB, and rax is the same in all problems VAX/(VAX+VBy) = VAX/(VAX+YAY)' Why the constantirrelevant problem shold have been relatively difficlt nder the qite different conditions of or previos experiment, e are nable to say.

6 DSCRMNATON OF COLOR-ODOR COMPOUNDS BY HONEYBEES 223 i a::: a::: CONSTANT.2... BETWEEN... WTHN VSTS Figre 6. The performance of three grops of animals trained in to-dimensional problems ith color relevant and odor either irrelevant-ithin, irrelevant-beteen, or constant. Confonded training verss to-dimensional training ith one relevant dimension. The continity model clearly sggests that performance ill be better in the confonded color-odor problem than in problems ith one dimension relevant and the other irrelevant. We have aeady shon that raj{ in the confonded problem (AX+BY-) is eqal to ra in the one-dimensionalproblem (A+B-). Forthe to-dimensional problem ith one relevant and one irrelevant dimension (e.g., AX+BY- and A Y+BX-), raj{ = (VA+ VX)/(VA + V x+ VB+ Vy). With X and Y nondifferentially reinforced (V x =Vy ), raj{= (VA+VX)/(VA+VB+2Vx ), and, since VB < VA, raj{ < r». This dedction from the continity model is confirmed by Figre 7, in hich the confonded crve of Figre 5 is compared ith a color-relevant crve based on the pooled data of Figre 6. The mean nmber of errors is 1.34 for the confonded problem and 2.38 for the problems ith only one of the to dimensions relevant, a significant difference by the median test (exactp=.2). n or previos ork, too (Covillon et al., 1983), performance as better ith color and odor confonded than ith color relevant and odor irrelevant or ith odor relevant and color irrelevant. Other To-Dimensional Problems Here e consider performance in several different todimensional problems chosen in the hope of defining the limitations of the continity model. One ne problem as a psedodiscrimination (neither the colors nor the odors differentially reinforced), and another as a dimensional shift (color relevant and odor irrelevant after training ith odor relevant and color irrelevant). We also sed three problems in each ofhich the colors ere reinforced on a 75:25 schedle (one color on three of for visits and the other color on the rest) ith the odors reinforced on a 5:5, 75:25, or 1: schedle. Transfer after tre discrimination and psedodiscrimination. To grops of 16 animals each ere trained for 1 visits ith color relevant and odor irrelevant. For one grop, this training folloed 16 visits ith odor relevant and color irrelevant (dimensional shift). For the second grop, it folloed 16 psedodiscrimination visits on hich both color and odor ere nondifferentially reinforced (green-peppermint vs. ble-geraniol on half the visits and green-geraniol vs. ble-peppermint on the rest, ith each compond eqally often positive and negative). We ere interested here in trying to model psedodiscrimination as e had earlier modeled nondifferential reinforcement ofodor alone (Covillon & Bitterman, 1985), as ell as in the possibility that the psedodiscrimination experience might have a deleterios effect, either general or specific to the stimli employed, on sbseqent performance (learned irrelevance). We ere interested also in ho ell e might be able to model dimensional shifting ithot the assmption of attentional modification (Stherland & Mackintosh, 1971). The performance ofthe to grops in the second stage oftraining (ith color relevant and odor irrelevant) is plotted in Figre 8. The crve for the psedodiscrimination animals looks very mch like that for naive animals trained from the otset on the same problem (Figre 3), hich is to say that the psedodiscrimination experience had no effect (median test, exact p =.25). fthe nondifferentially reinforced odors and colors acqired sbstantial associative strengthin the first stage oftraining, it as not sfficient, given the rate oflearning and the shape ofthe choice fnction, to prodce measrable impairment of performance in the second stage. The marked early flctation in the crve for the dimensional-shift animals is readily nderstandable in terms of the training schedle. On the first and third visits of the second stage, the no-positive color as presented ith the formerly negative odor and the no-negative color as presented ith the formerly positive odor; on the second visit, the no-positive color as presented ith the formerly positive odor and the no-negative color as presented ith the formerly negative odor. Reslts of this sort, reported for rats (Bitterman & Coate, 195), painted trtles (Graf & Tighe, 1971), and goldfish (Tennant & Bitterman, 1973), are easily nderstood in terms of continity theory. 75:25 color problems ith odor on varios schedles. Three grops of 12 animals each ere trained for.8 i5 G.6.4 a::: a::: 8.2 CONFOUNDED. ONE-RELEVANT VSTS Figre 7. The performance of to grops of animals in todijnemiona problems, one confondedand the otherith color relevant (one-relevant).

7 224 COUVLLON AND BTTERMAN is n: n:.2 -. AfTER PO.-. SHfT VSTS Figre 8. The performance of to grops of animals in a todimensional problem ith color relevant, one after psedodiscrimination (PD) and the other after training ith odor relevant (dimensional shift). 16 visits ith the colors reinforced on a 75:25 schedleone color positive on 12 visits and the other positive on the remaining visits, in qasi-random seqence. For one grop, the odors ere nondifferentially reinforced (a 5:5 schedle); for the second, the odors, like the colors, ere reinforced on a 75:25 schedle; and for the third, one of the to odors as consistently reinforced (1:). We had no qalitative prediction ofhat the performance in each case old be like, bt ere interested, to begin ith, only in hether it cold be simlated ith reasonable accracy on the basis ofthe continity assmptions. The obtained and simlated reslts are presented belo folloing a description of the simlation procedre. Simlations Visit-by-visit performance in each of the folloing problems as simlated: 1. The one-dimensional problem: A+B-. 2. Threeto-dimensional problems ith one relevant dimension: X+Y- ith A and B irrelevant ithin pairs (AX+BY-, BX+AY-), irrelevant beteen pairs (AX+AY-, BX+BY-), or constant (AX+AY-). 3. The confonded problem: AX+BY-. 4. Transfer from the confonded problem to the todimensional problem ith one dimension relevant and the other varying ithin pairs. 5. The to-dimensional psedodiscrimination problem: AX+BY-, BY+AX-, AY+BX-, BX+AY-. 6. Transfer from the psedodiscriminationproblem to the to-dimensional problem ith one dimension relevant and the other varying ithin pairs. 7. Transfer from the to-dimensional problem ith one dimension relevant and the other varying ithin pairs to the same problem ith relevant and irrelevant dimensions interchanged (dimensional shift). 8. The to-dimensional problem ith one dimension on a 75:25 reinforcement schedle and the other on a 5:5 schedle. 9. The to-dimensional problem ith one dimension on a 75:25 schedle and the other on a 75:25 schedle. 1. The to-dimensional problem ith one dimension on a 75:25 schedle and the other on a 1: schedle. The simlations ere done ith each of the five choice fnctions that yielded the best fits to the combined data of or previos one-dimensional experiments (Figre 1). Simlations ere done also ith K = 1, s =.5, hich did not yield a good fit to the earlier data, simply to be sre that the shape ofthe choice fnction contined to matter. For each fnction, there ere 1 simlations ith for vales of initial VA=VB=VX=Vy (.1,.2,.3,.4), five vales of U{3 (.15,.2,.25,.3,.35), and five vales of D{3 (the same as for U(3) combined factorially. Each simlation as done ith 1 stat bees trained exactly as the real bees had been trained in each of the 1 problems. A simple compter program evalated r on the basis ofthe initial V vales, dictated response on the basis of the choice fnction, and then calclated the reslting changes in associative strength. Goodness of fit as measred in termsofthe RMS deviation of the simlated from the obtained proportions of choices, one comptation on the basis of ntransformed proportions and another after arcsin transformation, each proportion, P, being replaced by an angle, C/>, measred in degrees, according to the eqation, c/>=(1817r)sin- 1P s.. The RMS scores based on ntransformed proportions have more intitive meaning bt-becase the variance of a proportion decreases ith distance from.5-may not give sfficient eight to small deviations at the extremes of the scale. Each comptation as based on 18 deviations selected to provide a conservative indication of goodness of fit. Since the theory as developed originally to deal ith the one-dimensional problem, and since (as has aeady been noted) predictions for the one-dimensional problem and for the confonded problem are mathematically identical ith eqally salient components, the fit to the onedimensional problem (1) as not considered in the comptations. Frthermore, since the predictions for the three different treatments of the irrelevant dimension in problems ith one relevant and one irrelevant dimension (2) are (again as aeady noted) mathematically identical, the comptations ere based on deviations ofthe combined simlations for the three treatments from the combined performance of the grops trained ith the three treatments (Figre 6); to do otherise might be to exaggerate the goodness of fit. The 18 choices sed in the comptations consisted of the folloing: (a) visits 2-1 (9 choices) ith combined treatments in (2)-thefirst visit as exclded becase any deviation from.5 either simlated or in the actal performance mst be sampling error; (b) visits 2-1 (9 choices) in (3); (c) visits 1-1 (1 choices) in (4); (d) visits 2-16 (15 choices) in (5); (e) visits 1-1 (1 choices) in (6); (f) visits 1-1 (1 choices) in (7); (g) visits 2-16 (15 visits) in (8); (h) visits 2-16 (15 choices) in (9); and (i) visits 2-16 (15 choices) in (1). The five choice fnctions that had yielded good fits in or previos ork ith one-dimensional problems con-

8 DSCRMNATON OF COLOR-ODOR COMPOUNDS BY HONEYBEES 225 tined to yield good fits here. The best ere for K =.75, s =.833 (RMS for ntransformed proportions =.114) and for K=.5, s=.625 (RMS =.115), both ith the parameters V A=VB=VX=Vy=.4, U{j=.15, D{j=.25 very mch the same as those that yielded the best fits to the one-dimensional data. For the other three fnctions, the RMS vales ere.127 or.128. For K= 1, s=.5, by contrast, the minimal RMS as.163. The arcsin transformation made little difference: Again, the best fits ere for K=.75, s=.833 and for K=.5, s=.625 (arcsinrms = 8. loin both cases), hile the arcsin RMS vales for the other three choice fnctions ranged from 9.2 to 9.5 ; for K=, s=.5, it as 12.. All the simlations shon in the figres that follo are for K =.75, s =.833; initial V vales =.4, U{j=.15, D{j=.25. n Figre 9, simlated performance in a onedimensional problemis compared ith simlated performance in a confonded problem. No smmation is predicted, and, as shon in Figre 5, no smmation as obtained. Figre 1 shos simlated performance in to-dimensional problems ith one relevant dimension and the irrelevant stimli presented in three different ays (ithin, beteen, or constant). No differences are predicted, and as may be seen in Figre 6, no differences ere obtained. n Figre 11, simlated performance in a confonded problem is compared ith simlated performance in a problem ith one relevant and one irrelevant dimension. 6 U t U W:: :: CONFOUNDED Figre 9. Simlated performance in confonded and onedimensional problems. 6.6 t-.4. -;--, OE--;DES?N o VSTS :: :: CONSTANT BETWEEN..-. WTHN VSTS Figre 1. Simlated performance in to-dimensional problems ith one dimension relevant and the other either irrelevant-ithin, irrelevant-beteen, or constant..8 6 is.6 t-.4 :: :: CONFOUNDED..-. ONE-RELEVANT o VSTS Figre 11. Simlated performance in a confonded problem and in a to-dimensional problem ith one relevant dimension. 6.6 t-.4 :: :: ,----, o VSTS Figre 12. Obtained (large circles) and simlated (small circles) performance in a to-dimensional problem ith one relevant dimension after training in a confonded problem. The prediction that the confonded performance ill be better is confirmed by the empirical reslts shon in Figre 7, althogh the obtained difference seems a bit smaller than the predicted difference. Figre 12 compares obtained and simlated performance ith one relevant and one irrelevant dimension after confonded training. The obtained performance is represented by pooling the reslts for the color-relevant and odor-relevant animals (Figre 4), hich are not significantly different and shold not be, according to the theory, if color and odor are eqally salient. Obtained and simlated psedodiscrimination performance are plotted in Figre 13. The flctations in the obtained performance are not simlated very closely, bt the discrepancies do not seem to be de to systematic error; it shold be noted that e are orking here ith proportions in the region of.5. Figre 14 shos the sbseqent performance, obtained and simlated, in training ith one dimension relevant and the other irrelevant. No detrimental effect of the psedodiscrimination experience on the sbseqent performance is either predicted (compare ith the one-relevantcrveoffigre 11) or obtained (compare ith the one-relevant crve of Figre 7). The obtained and simlated dimensional shifts (from odor-relevant to color-relevant) are shon in Figre 15. f there is any meaningfl discrepancy here, it is that the real bees accomplish the shift somehat more rapidly than the stat bees.

9 226 COUVLLON AND BTTERMAN Figres sho obtained and simlated performance in the three problems ith the colors reinforced on a 75:25 schedle and the odors on a 5:5 schedle (Figre 16), a 75:25 schedle (Figre 17), or a 1: schedle (Figre 18). The ide flctations in obtained proportions ofcorrect choice are tracked satisfactorily by the model. t shold be noted that goodness of fit is limited by random error in the simlation process (as) and in the data (ad), as ell as by model error (am). To estimate as, e did a second simlation for 1 stat bees ith K =.75, s=.833, V A=VB=.4, U3=.15, D3=.25. On the basis of the RMS deviation of the to sets of simlated vales from each other, hich is.56, as may be estimated from the eqation a/+a s 2 = (.56)l as.4. On the assmption of independence, it is possible also to estimate adm (ad and am combined) from the eqation a s 2+adm2 = (.114)l as.16. As e have pointed ot before (Covillon & Bitterman, 1986), the reliability of the data is a serios limitation in this ork. The nmber of stat bees can be increased easily (to minimize as), bt the nmber of real <5.6 - :::.4 ::: VSTS Figre 13. Obtained (large circles) and simlated (small circles) performance in psedodiscrimination training..8 < ::: ::: r-r-,..., o VSTS Figre 14. Obtained (large circles) and simlated (small circles) performance in a to-dimensional problem ith one relevant dimension after training in a psedodiscrimination problem. o.8 6 ::.6 - :::.4 ::: o.2. o VSTS Figre 15. Obtained (large circles) and simlated (smal circles) performance in a dimensional shift problem..6 - :::.4 ::: VSTS Figre 16. Obtained (large circles) and simlated (smal circles) performance in a to-dimensional problemith one dimension reinforced on a 75:25 schedle and the other on 5:5. bees can be increased sbstantially (to minimize ad) only at considerable expense. DSCUSSON The performance of or honeybees in a variety of problems reqiring the discriminationof color-odor componds gives no qalitative indication of noncontinity and can, in fact, be simlated qantitatively ith considerable accracy on the basis of a simple component model incorporating the independence and smmation rles. The problems stdied ths far do not, of corse, maximally constrain the model, and it might even be anticipated that honeybees can solve problems (sch as the conditional discrimination, AX+BX- and BY+AY-) hich cannot in principle be handled by the model in its present form, bt or strategy has been to approach the potential difficlties gradally. n considering ne directions, it is helpfl to inqire into the strengths as ell as the eaknesses of the model that is taken as the point of departre, and e kno no that the strengths are sbstantial. We certainly can say that the hypothesis abot the general shape of the choice fnction based on or previos ork ith one-dimensional problems is spported by the reslts for to-dimensional problems. Frthermore, the variety of those problems and the good fits achieved

10 DSCRMNATON OF COLOR-ODOR COMPOUNDS BY HONEYBEES 227 Figre 17. Obtained Oarge circles) and simlated (small circles) performance in a to-dimensional problem ith both dimensions reinforced on 75:25 schedles..8 (5 ( VSTS VSTS Figre 18. Obtained (large circles) and simlated (small circles) performance in a to-dimensional problem ith one dimension reinforced on a 75:25 schedle and the other on 1:. sggest that the associative featres of the model may not be intrinsically rong, bt in need, at most perhaps, of some spplementation and refinement. t is conceivable, for example, that conditional discrimination and other configral phenomena can be modeled sccessflly on the principle of ' 'afferent neral interaction, " hich as proposed by Hll (1943), either, as he did, ith a generalization fnction that ltimately ill be necessary in any case or ith compond-niqe components (Rescorla, 1972; Whitlo & Wagner, 1972). Nor old change in the associative featres ofthe model inevitably be reqired by the discovery of some sort of attentional or saliencemodlating mechanism, hich might easily be grafted onto the existing strctre. t shold be noted, hoever, that no indication of sch a mechanism appeared in or early ork on dimensional transfer in color-odorproblems (Klosterhalfen et al., 1978). The. most serios deficiency of the present model may lie in its faie to provide for the development of inhibition, hich has aeady been fond in extinction tests (Covillon & Bitterman, 198), bt to hich the present experiments ere not designed to be sensitive. t is hen e come to address the problem of inhibition more directly that e may be called pon to make some fndamental revisions ofthe model, as, for example, to sbstitte increment in inhibition for redction in V, ith all of the attendant difficlties (Woodard & Bitterman, 1976), or, as did Rescorla and Wagner (1972), to permit V to take on negative vales, itself by no means a troble-free alternative. Given the relative simplicity of the animal ith hich e are dealing and the remarkable efficiency ofor training techniqe, it may not be too nrealistic, hoever, to hope for more rapid progress than has been possible in ork ith vertebrates. REFERENCES BTTERMAN, M. E., & COATE, W. B. (195). 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