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JOURNAL OF THE EXPERIMENTAL ANALYSIS OF BEHAVIOR 511 NUMBER 1 (JANUARY)2016, 105, 123–132

IMPLICIT SEQUENCE LEARNING IN RING-TAILED LEMURS(LEMUR CATTA)

CAROLINE B. DRUCKER1, TALIA BAGHDOYAN

2, AND ELIZABETH M. BRANNON3,4

1DEPARTMENT OF NEUROBIOLOGY AND CENTER FOR COGNITIVE NEUROSCIENCE, DUKE UNIVERSITY2DEPARTMENT OF EVOLUTIONARY ANTHROPOLOGY, DUKE UNIVERSITY

3DEPARTMENT OF PSYCHOLOGY AND NEUROSCIENCE AND CENTER FOR COGNITIVE NEUROSCIENCE, DUKE UNIVERSITY4DEPARTMENT OF PSYCHOLOGY, UNIVERSITY OF PENNSYLVANIA

Implicit learning involves picking up information from the environment without explicit instruction orconscious awareness of the learning process. In nonhuman animals, conscious awareness is impossible toassess, so we define implicit learning as occurring when animals acquire information beyond what isrequired for successful task performance. While implicit learning has been documented in somenonhuman species, it has not been explored in prosimian primates. Here we ask whether ring-tailedlemurs (Lemur catta) learn sequential information implicitly.We tested lemurs in amodified version of theserial reaction time task on a touch screen computer. Lemurs were required to respond to any picturewithin a 2� 2 grid of pictures immediately after its surrounding border flickered. Over 20 trainingsessions, both the locations and the identities of the images remained constant and response timesgradually decreased. Subsequently, the locations and/or the identities of the images were disrupted.Response times indicated that the lemurs had learned the physical location sequence required in originaltraining but did not learn the identity of the images. Our results reveal that ring-tailed lemurs canimplicitly learn spatial sequences, and raise questions about which scenarios and evolutionary pressuresgive rise to perceptual versus motor-implicit sequence learning.Key words: implicit learning, sequence learning, ordinal reasoning, serial reaction time task, ring-tailed

lemurs

Dialing a phone number, riding a bike, tyinga shoe, and speaking a language are among themany sequential behaviors we learn to perform.Learning such activities often occurs outside ofour conscious awareness and without the needfor explicit instruction. For instance, as youngchildren, we acquire grammatical rules of thelanguage to which we are regularly exposed.Picking up information from a complexenvironment without conscious awareness ofwhat was learned or perhaps even that learninghas occurred is known as implicit learning(Cleeremans, Destrebecqz, & Boyer, 1998;Janacsek & Nemeth, 2012). Implicit learningcontrasts with explicit learning, a process ofdeliberate hypothesis-testing (Abrahamse,Jim�enez, Verwey, & Clegg, 2010). Implicitsequence learning is crucial for socialinteractions (Heerey & Velani, 2010; Lieber-man, 2000), language acquisition (Conway,Bauernschmidt, Huang, & Pisoni, 2010;Granena, 2013),music appreciation (Ettlinger,

Margulis, & Wong, 2011), and motor skills(Corkin, 1968), and may play a role in generalintelligence and personality (Kaufman et al.,2010). Thus, over the past several decades,research into the varieties and mechanisms ofimplicit learning has flourished in humans.However, relatively little attention has beenpaid to what sorts of information other animalsare capable of learning implicitly.In nonhuman animals, implicit learning is

difficult to disentangle from explicit learningbecause there are no behavioral markers ofconsciousness in other species. Thus, consciousawareness of what was learned cannot beassessed. In fact, animal studies typically donot specify whether any evident learning wasimplicit or explicit.An important exception is the study of

episodic memory, a form of explicit learning.For example, research with scrub jays (Aphe-locoma coerulscens) demonstrates memory forwhat, when, and where they have cacheddifferent food items (Clayton & Dickinson,1998), as well as which caches they have visitedpreviously (Clayton & Dickinson, 1999). Evenhere, though, the impossibility of attributingconsciousness to the birds’ recall of past eventsprevents their behavior from fulfilling the

Correspondence: Caroline B. [email protected]: 1-919-668-0333Fax: 1-919-681-0815doi: 10.1002/jeab.180

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definition of episodic memory in humans(Griffiths, Dickinson, & Clayton, 1999).

Therefore we operationally define implicitlearning in animals as any learning that occurswhen animals acquire information beyond whatis required for successful task performance.Explicit learning, on the other hand, wouldinvolve learning that is necessary for successfultask performance, such as when subjects mustlearn to respond to a particular stimulus orfeature to obtain reward.

A common paradigm for assessing implicitlearning in humans is the serial reaction timetask (SRTT). In the original SRTT, an asterisksymbol was presented in one of four places on amonitor, and subjects were required to pressthe key on a keyboard that was directly belowthe symbol (Nissen & Bullemer, 1987). Whenthe sequence of four symbol positions repeated,subjects’ reaction time sharply decreased overthe course of the experiment; but, when thesymbol randomly appeared in different posi-tions, reaction times did not show this dramaticdecline. The percentage of correct choices alsoincreased moderately in the repeating condi-tion, but not in the random condition. Theseaccuracy and reaction time measures bothsuggest that subjects learned the repeatingsequence, despite the fact that the task didnot require learning the sequence.

Versions of the SRTT have been used toexplore implicit sequence learning in rodents,birds, and monkeys. For example, mice(Christie & Hersch, 2004) and rats (Christie& Dalrymple-Alford, 2004; Domenger &Schwarting, 2005) that were trained to nose-poke one of four holes according to a cue lightperformed more efficiently when the lightsappeared in a repeating sequence rather thanrandomly. Pigeons (Columba livia) pecking atkeys cued in a repeating sequence exhibitedhigher response times when a key was cued out-of-sequence (Helduser & G€unt€urk€un, 2012)(see also Locurto, Fox, & Mazzella, 2015).Rhesus macaques (Macaca mulatta) touching littargets on a computermonitor respondedmoreslowly when targets were cued in a randomrather than a fixed sequence (Lee & Quessy,2003; Procyk, Ford Dominey, Amiez, & Joseph,2000). Similarly, when rhesus macaques weretrained to use a joystick to respond to targetspresented on a computer monitor, responsetimes were faster for sequences that repeatedcompared to novel or randomized sequences

(Heimbauer, Conway, Christiansen, Beran, &Owren, 2011; Turner, McCairn, Simmons, &Bar-Gad, 2005). Finally, Locurto and colleagueshave performed several studies using the SRTTwith cotton-top tamarin monkeys (Saguinusoedipus) in which subjects touched a pictureappearing in one of several locations on atouch-screen. Tamarin monkeys respondedmore slowly during random than repeatingsequences across various reinforcement sched-ules and regardless of whether the sequence wasdefined based on the identity of the visualimages or spatially based on the requiredmotorresponses (Locurto et al., 2015; Locurto, Dillon,Collins, Conway, & Cunningham, 2013;Locurto, Gagne, & Levesque, 2009; Locurto,Gagne, & Nutile, 2010).

An unresolved question in the human SRTTliterature is the degree to which perceptualrelative to motor implicit sequence learningoccurs. When people are required to follow aparticular sequence, do they encode the physicalresponses required (i.e. the fifth, followed by thefirst, followed by the fourth position in a line) orthe identity of the items (i.e., the letter B,followedby the letterX, followedby the letterG),or perhaps both to differing extents? Somestudies have suggested that implicit sequencelearning is primarily based on motor responses(e.g., Verwey & Clegg, 2005; Willingham, 1999),others have found that learning can be specificto the perceptual stimuli (e.g., Clegg, 2005;Howard, Dennis, Howard, Yankovich, & Vaidya,2004), and still others have found evidence forboth types of learning within the same task (e.g.,Deroost & Soetens, 2006; Gheysen, Gevers,Schutter,Waelvelde,&Fias, 2009).This questionhas only been addressed in one nonhumananimal, cotton-top tamarins. In this case, themonkeys seemed to learn both types of informa-tion equally (Locurto et al., 2010).

Here, we ask whether a prosimian primate,the ring-tailed lemur (Lemur catta), exhibitsimplicit sequence learning. Prior work hasshown that ring-tailed lemurs can learn orderedinformation explicitly, when sequence knowl-edge is required for reinforcement (Merritt,MacLean, Jaffe, & Brannon, 2007), and thatthey can reason transitively about elements inan ordered list (Maclean, Merritt, & Brannon,2008). A second question this research asks iswhether lemurs are more apt to encode thesequence based on identity information, spatialinformation, or a combination of the two.

CAROLINE B. DRUCKER et al.124

We used a touch-screen version of the SRTTin which four images were presented simulta-neously on the screen, and subjects simply hadto touch the image with a flickering border.During training, the four images always ap-peared in the same location and the order inwhich they had to be touched repeated in apredictable pattern. For example, the sequencemight be picture A in location 4, followed bypicture B in location 1, followed by picture C inlocation 3, followed by picture D in location 2,and repeat. In three different testing condi-tions, the spatial sequence, the picture identitysequence, or both the spatial and pictureidentity sequences were changed. If lemurslearned the spatial (or identity) aspect of thetraining sequence, then they should respondmore slowly and/or make more errors duringtesting when the spatial (or identity, respec-tively) sequence was disrupted.

Method

SubjectsFour adult ring-tailed lemurs (Lemur catta),

three male (Berisades: 9 years old, Licinius:20 years old, and Teres: 18 years old) and onefemale (Sierra Mist: 5 years old), pair-housed inindoor/outdoor enclosures at the Duke LemurCenter were tested. Licinius and Teres hadextensive prior touch-screen experience innumerical and ordinal tasks; Berisades partici-pated in one previous numerical touch-screenstudy; and Sierra Mist had not previously used atouch-screen. Subjects had unrestricted accessto water and were fed normally throughout thisstudy. All procedures reported here wereapproved by the Duke Institutional AnimalCare and Use Committee.

ApparatusDuring testing, the subject animal was

separated from his or her cage mate, and aportable stainless-steel testing station (62cm X62cm X 33cm) housing all experimentalmaterial was placed in the subject’s homeenclosure (see Fig. 1). Stimuli were presentedon a 12-inch touch-sensitive computer monitor(Elo TouchSystems, Menlo Park, CA). A foodpellet reward delivery system (Med Associates,St. Albans, VT) was used to deliver 190-mgsucrose pellets (TestDiet, St. Louis, MO) belowthe screen. Plexiglas templates with holes for

the stimuli were placed over the monitor. Aplastic box was placed in front of the screen forthe lemurs to sit on in order to reach the screen.Stimulus presentation, reward delivery, datacollection, and data analysis were performedvia custom-written programs in MATLAB(Mathworks, Natick, MA) with the Psychophys-ics Toolbox add-on (Brainard, 1997; Kleiner,Brainard, & Pelli, 2007) (https://psychtoolbox.org).

ProcedureStimulus selection training. The goal of this

phase of training was to instruct the lemurs totouch a stimulus with a flickering border. Oneach trial, two colored rectangles appeared inany of nine locations (comprising a 3� 3 array)on the screen over a gray background, and an8- mm black-and-white border flickered (i.e.,the black and white areas swapped places)around one of them. The trial ended when thelemur touched the rectangle with the flickering

Fig. 1. Experimental task. A ring-tailed lemur sits infront of a touch screen and presses the one of four imageswith a flickering black-and-white border. After a subset ofcorrect presses, a pellet reward is delivered out of theapparatus near the lemur’s left foot in this photograph.

SEQUENCE LEARNING IN RING-TAILED LEMURS 125

border, and the next trial began after anintertrial interval of 0.3 s for correct trials and1.5 s for incorrect trials. Accuracy was thepercentage of trials on which the lemur firsttouched the stimulus with the flickering border.The trial did not end until the lemur touchedthe rectangle with the blinking border. Upontouching the correct rectangle, a positive toneplayed and a reward was delivered probabilisti-cally. Reinforcement began at 100%, and wasreduced to 75%, 50%, and 25% after twosequential sessions with median responsetimes (RTs) under 2.5 s and accuracies of atleast 90%, or accuracies of at least 85% (or80%) if the subject had already completed10 (or 20, respectively) sessions at the samereinforcement level. Each session was termi-nated when the lemur received 50 pellets andconsisted of between 50 and 200 trials. Subjectscontinued to the next training phase aftercompleting three sequential sessions at 25%reinforcement with median RTs (excludingtrials after receiving a pellet) under 2.5 s andaccuracies of at least 85%.

Implicit sequence training. The goal of thenext phase of training was to have the lemursimplicitly learn a four-response sequence. Fourpictures (comprising a 2� 2 array) werepresented on the screen. The black-and-whiteflickering border appeared around each ofthe four pictures in a predictable sequence. Thesequence was predictable based on both theorder of the images (e.g., bird, flower, ocean,monkey) and the spatial locations (e.g., topright, bottom left, top left, bottom right). Afterthe first blinking stimulus was touched, theborder disappeared and immediately beganflickering around the second stimulus, and soforth. Each time the lemur touched thestimulus with the flickering border, a positivetone played, and a reward was delivered on apseudorandomly-selected 25% of trials (underthe constraint that reward followed a touch toeach stimulus an equal number of times). Theborder flickered around the four stimuli in afour-item repeating sequence, i.e. ABCDABCD.Crucially, lemurs were not required to learn thissequence in order to obtain reward, but only totouch the stimulus with the flickering border, asin stimulus selection training. The four loca-tions and images used were the same for allsubjects, but the spatial and identity sequencesduring training followed two different patterns,with Licinius and Sierra Mist receiving one

pattern, and Berisades and Teres receiving theother. Each session consisted of 200 trials (onetrial is one correct touch to a stimulus),equivalent to 50 repetitions of the four-itemsequence. Subjects initially completed either30 sessions of implicit sequence training, or atleast 20 sessions if their median RT (excludingtrials after a reward, and the session’s first trial)fell below 1 s in their last session.

Testing. The procedure during testing wasthe same as in implicit sequence training: Fourpictures appeared onscreen and the lemur hadto touch the stimulus with a flickering border.The predictable sequence used in the previousphase of training was disrupted in threedifferent ways to determine what the lemurshad learned in the implicit training phase. Inthe Spatial-Novel condition, the image patternremained the same as in training, but therequired motor pattern was novel. In theIdentity-Novel condition, the spatial patternremained the same as in training, but the imagepattern was novel. In the Both-Novel condition,both the spatial pattern and the image patternwere disrupted. Subjects completed two testingsessions in each condition. In between testingconditions, subjects completed anotherfive sessions of implicit sequence training tore-familiarize them with the baseline sequence.All subjects completed Both-Novel testing first,and the orders of Spatial- and Identity-Noveltesting were counterbalanced across subjects:Berisades and Sierra Mist completed Spatial-Novel testing before Identity-Novel testing,whereas Licinius and Teres completed Iden-tity-Novel testing before Spatial-Novel testing.

Data analysis. First, we examined whetherresponse time (RT) decreased over implicitsequence training by creating a generalizedlinear regression model (GLM) with predictorssubject and session number, and their interac-tion. We excluded the RT to the first trial andany trial after reward delivery. We furtherexcluded any trial for which RT was greaterthan two standard deviations above the meanRT for each subject (3.52% of trials forBerisades, 1.67% for Licinius, 0.56% for Teres,and 3.02% for Sierra Mist). Finally, we normal-ized the RT data by subtracting the mean RT ofthe remaining trials for each subject from thatsubject’s RTs.

To assess whether the lemurs had learned theidentity or spatial sequence, we comparedRTs in the training and test conditions. We


compared mean normalized RT for each testcondition to the mean RT for the last twotraining sessions prior to that test conditionfor each subject. We ran a 4 (subject) X 6(condition) ANOVA on RT, where the sixconditions were the three testing conditionsand the three training blocks prior to eachcondition. We considered the training blocksseparately in the ANOVA to account for ordereffects (e.g., the subject may have become fasterat responding as the experiment proceeded).Additionally, we ran similar ANOVAs using onlythe first 10, 25, 50, and 100 trials of the finaltraining and first testing sessions in eachcondition, as well as the full 200-trial finaltraining and first testing sessions (rather thanthe two final training and two testing sessions)in each condition. To further examine differ-ences in RT among testing conditions, wecreated a GLM predicting normalized RTfrom testing condition (spatial, identity, both,or neither [i.e., training]) and subject. Finally,we defined an error as a trial in whichthe subject touched a stimulus that was notflickering prior to ultimately touching thestimulus with the flickering border. We ranchi-square tests to assess whether error rates—that is, choice accuracy—differed among theconditions.

Results

Over the course of the 20 implicit sequencetraining sessions, subjects’ response timessignificantly decreased (overall differencefrom constant model: F12022¼ 37, p< .0001;coefficient for session: b¼ −0.0430, t¼ −13.85,p< .0001). This decrease suggests that subjectslearned the sequence, although it could alsoreflect increasing facility with the general taskdemands.Subjects’ sequence learning was confirmed

by an increase in RT during testing (Fig. 2). AnANOVA revealed a significant main effect ofcondition (F5¼ 28.24, p< .0001), no maineffect of subject (F3¼ 0.00017, p¼ 1), but asignificant condition-by-subject interaction(F15¼ 2.718, p¼.00036). Tukey-Kramer post-hoc tests revealed that the differences betweenBoth-Novel testing and the immediately pre-ceding training block (M¼ 0.153s, CI¼[0.0837, 0.2226], p< .0001), and betweenSpatial-Novel testing and the immediatelypreceding training block (M¼ 0.1955s, CI¼

[0.1264, 0.2646], p< .0001), were significant,whereas the difference between Identity-Noveltesting and the immediately preceding trainingblock was not significant (M¼ 0.0407s, CI¼ [−0.281, 0.1096], p¼ .5415). All individualsubjects (Fig. 3) performed more slowly inBoth-Novel testing than in the immediatelypreceding training block (significant at p< .05only for SierraMist) and in Spatial-Novel testingthan in the training block immediately before it(significant at p< .05 for Berisades, Teres, andSierra Mist). Berisades, Teres, and Sierra Mistshowed small but nonsignificant increases in RTin Identity-Novel testing compared to theimmediately preceding training block, whereasthe reverse pattern was exhibited by Licinius(all p s> .1).If the effects of spatial and identity sequence

disruption were additive, then we should expectRTs to be significantly greater for Both-Novelcompared to Spatial-Novel. To test this predic-tion, we ran a GLM predicting normalized RTfrom the binary factors Image-Novel (1 inImage- and Both-Novel testing, 0 in trainingand Spatial-Novel testing), Spatial-Novel (1 inSpatial- and Both-Novel testing, 0 in trainingand Image-Novel testing), and their interac-tion, as well as subject. The overall model wassignificantly different from the constant model(F7004¼ 22.6, p< .0001). The only significantcoefficient was for Spatial-Novel (b¼ 0.1777,

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Fig. 2. Response time across conditions. The threedifferent testing conditions are indicated on the x-axis. Themean normalized RT in each testing condition is shown indark gray, and the mean normalized RT in the trainingblock preceding each testing condition is shown in lightgray. Error bars represent standard error of the mean. Thedifferences between Both-Novel testing and training, andbetween Spatial-Novel testing and training, were significant,whereas the difference between Identity-Novel testing andtraining was not (see text for statistics).


t¼ 8.942, p< .0001; all other p s> .1). Thispattern of results indicates that the increasein RT during Both-Novel testing could beattributed entirely to the change in the spatialsequence, with no contribution from thechange in the identity sequence.

To address the possibility that the effects ofsequence disruption—particularly those of thevisual sequence—may have quickly washed outover the course of testing, we performedadditional tests including only the first testingsession in each condition, and the final trainingsession before it. We ran five ANOVAs using thefirst 10, 25, 50, or 100 trials from each of thesesessions, or the full 200-trial sessions. Weincluded the same number of trials from thebeginning of the final training sessions in orderto control for any possible changes in behaviorover the course of each session.

When only 10 trials from each session wereincluded, there was nomain effect of condition(F5¼ 1.83, p¼ .11) nor a condition by subjectinteraction (F15¼ 1.21, p¼ .27). When 25 trials

were included, there was a significant maineffect of condition (F5¼ 3.82, p¼ .0022) andno condition by subject interaction (F15¼ 1.05,p¼.40). Post-hoc Tukey-Kramer tests revealedthat the difference between spatial-novel test-ing (M¼ 0.297s, CI¼ [0.222, 0.372]) andthe training preceding it (M¼ −0.080s, CI¼[−0.155, −0.0054]) was significant with p< .05,but the differences between both-novel testing(M¼ 0.159s, CI¼ [0.084, 0.235]) and thetraining preceding it (M¼ −0.076s, CI¼[−0.150, −0.001]), and identity-novel testing(M¼ 0.017s, CI¼ [−0.058, 0.092]) and thetraining preceding it (M¼ 0.028s, CI¼[−0.046, 0.102]) were not. This same patternof effects by condition held when 50 or 100trials were included (although there were alsosignificant condition by subject interactions);that is, the difference between Spatial-Noveltesting and the training before it was signifi-cant, but the differences between Identity-Novel and Both-Novel testing and the trainingsessions before them were not significant at the

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Fig. 3. Raw response time across conditions for each individual subject. The two subjects in the top row (Berisades andSierra Mist) received Identity-Novel testing before Spatial-Novel testing. The two subjects in the bottom row (Licinius andTeres) received Spatial-Novel testing before Identity-Novel testing. The three different testing conditions are indicated onthe x-axes. The mean RT in each testing condition is shown in dark gray, and the mean RT in the training block precedingeach testing condition is shown in light gray. Error bars represent standard error of the mean.


p< .05 level. When all 200 trials from eachsession were included, there was again a maineffect of condition (F5¼ 17.55, p< .0001) and acondition by subject interaction (F15¼ 1.72,p¼.027). Now, post-hoc Tukey-Kramer testsrevealed significant differences at p< .05between Both-Novel testing (M¼ 0.062s, CI¼[0.038, 0.085]) and the training before it(M¼ −0.054s, CI¼ [−0.077, −0.030]), as wellas between Spatial-Novel testing (M¼ 0.150s,CI¼ [0.127, 0.174]) and the training before it(M¼ −0.112s, CI¼ [−0.136, −0.089]), but stillno significant difference between Identity-Novel testing (M¼ 0.010s, CI¼ [−0.013,0.034]) and the training before it (M¼ −0.081s,CI¼ [−0.105, −0.058]). Thus, we find noevidence that changing the identity sequencealtered lemurs’ behavior, even at the verybeginning of testing.To complement the RT analyses, we next

examined error rates. A chi-square test indi-cated that there were significant differences inerror rates across conditions (x2¼ 30.18,p< .0001). Follow-up chi-square tests compar-ing each testing condition to the immediatelypreceding training block, and using a Bonfer-roni-corrected threshold p-value of .05/3¼.0167, revealed that subjects made significantlymore errors during Spatial-Novel testing(5.76%) than the immediately preceding train-ing block (2.30%, x2¼ 18.16, p¼ .00002). Thesame analyses for the rates in Identity-Noveltesting (2.71% vs. 3.15%, x2¼ 0.3910, p ¼ .53),and Both-Novel testing (4.86% vs. 4.81%,x2¼ 0.0037, p¼.95) were not significant.

Discussion

We examined whether ring-tailed lemursspontaneously and implicitly encode spatialand identity sequences. Subjects were trained totouch stimuli with flickering borders and werepresented with sequences of images withflickering borders that maintained a consistentspatial and identity order. After 20 sessions witha sequence that remained constant both in theorder of the stimulus identity and spatiallocations, all four lemurs’ response timesdecreased substantially. We confirmed thatthe drop in lemurs’ RT resulted from learningsome aspect of the training sequence, ratherthan some other general factor like anincreased facility with the touch screen task,by testing them with novel sequences that

disrupted both the spatial and identity informa-tion in the original sequence. In this case,response time significantly increased. Thisfinding suggests that lemurs encoded themotorsequence required, the order of the picturesthemselves, or both types of information tosome degree.We then asked whether lemurs found spatial

or identity information to be more salient. Wefound that changing only the order of thepictures themselves while keeping the spatialsequence constant did not significantly affectRT; however, the reverse did significantlyimpact RT. This result held even when weconsidered only the early testing trials. Addi-tional analyses suggested that changingboth spatial and identity components of thesequence did not result in additive impacts onRT. Together, these results suggest that lemurslearned the spatial sequence, but not theidentity of each image in the sequence.Although identity information was an availablecue for the lemurs, it seems that the flashingborder and the spatial information overshad-owed it.Our finding that lemurs learned the spatial,

but not the identity information in a repeatingsequence stands in contrast to the findings ofLocurto and colleagues (2010) in cotton-toptamarins. These monkeys acquired bothmotor and perceptual sequential information.Although it is possible that this is a truedifference between ring-tail lemurs and tamarinmonkeys, it is equally possible that the differentpatterns of results stem from methodologicaldifferences.For instance, we did not include any intertrial

interval between stimuli or between repetitionsof the sequence, whereas tamarin monkeysreceived a 5-s white screen prior to the firstelement in a chain and a 20-second black screenfollowing the final element (Locurto et al.,2009, 2010, & Experiment 1 of 2013), or a 1-sITI between every pair of elements (Locurtoet al., 2013, Experiment 2). It could be thatforcing subjects to pause between responsesencouraged perceptual encoding of theresponses. Also, for tamarins, images appearedone-at-a-time onscreen, whereas in our studyall four images remained onscreen the entiretime. Although it might be expected that theconsistent exposure in our study could lead togreater encoding of the visual array, it is alsopossible that the sudden appearance of each


item in Locurto et al. (2010) caused subjects topay more attention to its identity. Moreover,because our stimuli remained onscreen, lemurscould have very quickly become accustomed tothe new visual arrangement. In addition, for thetamarins, visual learning was initially testedfollowing visual-only training: That is, duringtraining, the images appeared in randomlocations on the screen, so there was norepeating motor pattern (Locurto et al., 2009,and Experiment 1 of Locurto et al., 2010). It ispossible that if lemurs were trained in this way,then they would also show sensitivity to theimage identity. Finally, tamarins in Experiment2 of Locurto et al. (2010) which were trainedwith the same image appearing in a repeatingspatial pattern not only showed evidence ofmotor learning, but also of visual learning; theirreaction times increased during “Wild Card”testing when a novel image was displayed. It ispossible that if we had introduced entirely novelimages during Visual-Only Testing, rather thana reordering of the same four images used intraining, then lemurs’ response times wouldhave increased. Further experiments moreclosely mirroring the procedures of Locurtoand colleagues (2010) would help determinewhether there are species differences inthe implicit sequence learning tendencies oflemurs and tamarins.

It is of course possible that future researchusing different parameters may reveal thatlemurs can implicitly encode identity informa-tion. In addition to the possibilities discussedin the previous paragraph, it could be thatthe images used in this study were not salientenough for ring-tailed lemurs to effectivelydiscriminate them. However, the images aresimilar to those used in other studies fromour group where reward was contingent upondiscriminating identity information (e.g.,Merritt et al., 2007). It is also notable thatrhesus monkeys (Kornell & Terrace, 2007) andpigeons (Staniland, Colombo, & Scarf, 2015)failed to encode visual sequential informationwhen tested in a sequence-learning task where a“hint” in the form of a border around thecorrect image was present.

Another reason that spatial, but not visuallearning may have occurred in our study is thatspatial learning could have facilitated themotorspeed of task performance, thereby bringingsubjects closer to reinforcement. It is less clearhow visual learning would have enabled faster

movements and thus produced an earlierreward. Using a different task paradigm, inwhich visual learning would be beneficial to thesubject, might reveal this form of implicitlearning.

It should also be noted that Both-Noveltesting always occurred before either Visual-Novel or Spatial-Novel testing. Although weincluded five additional sessions of implicitsequence training between testing conditions, itis possible that exposure to the Both-Novelcondition altered behavior in the subsequenttesting conditions, and an effect might havebeen observed in the Visual-Novel conditionhad it been run first. This issue is relevant to thecontroversy in the human literature over thepredominance of motor versus perceptualimplicit learning. Understanding how thesetwo types of learning evolved could shed lighton which situations should favor the use ofmotor or perceptual cues, and on whetherimplicit sequence learning involves sharedor entirely distinct cognitive structures formotor and perceptual sequences.

The experiment reported here did notattempt to dissociate spatial learning atthe stimulus stage from motor learning at theresponse stage. The physical location on thescreen where the flickering border appearedwas always the same as the response location thesubjects needed to touch. The increase in RTsin the Spatial- and Both-Novel tests could beexplained by the lemurs encoding the spatiallocation of either the stimulus or the response.The former case would be an example ofperceptual learning. Whether stimulus-basedor response-based learning predominates inhuman implicit sequence learning has been acontentious issue, with task conditions being alikely determinant of which type of learningoccurs (Abrahamse et al., 2010). Additionalstudies are needed to tease apart whetherlemurs’ learning of the location sequencerelied on perceptual spatial learning or motorresponse learning.

Another avenue for future research would bea comparison of implicit sequence learningabilities across different lemur species. Ring-tailed lemurs have been shown to possesssophisticated ordinal reasoning abilities(Merritt et al., 2007), outperforming otherlemur species in certain tasks (Maclean et al.,2008). In light of these species differences inexplicit sequence learning, it would be


interesting to examine whether other lemurscan implicitly learn sequences. Becauseother animals including rodents (Christie &Dalrymple-Alford, 2004; Christie & Hersch,2004; Domenger & Schwarting, 2005) and birds(Helduser & G€unt€urk€un, 2012; Locurto et al.,2015) are able to implicitly acquire sequences,we expect that other lemurs would be able to doso as well, but the speed and degree of learningmay vary across species. Such a comparisonmight lend insight into the evolutionary pres-sures favoring the capacity for implicit learning.For instance, if ring-tailed lemurs outperformother species that live in smaller social groups,then implicit sequence learning may haveevolved alongside explicit sequence learningto support complex social structures. Alterna-tively, if other lemur species are equally capableof implicit sequence learning, then it may be afundamental skill necessary for survival in avariety of ecological niches.A final important caveat is that our study did

not actually attempt to differentiate betweentypes of learning. We defined implicit learningas encoding of information that was notnecessary for successful task performance. Bythis definition, we argue that any learning ofspatial or identity sequence information wasimplicit. However, we did not assess potentialexplicit knowledge of the sequence. Regardless,our study demonstrates that ring-tailed lemursencode a spatial sequence even when knowl-edge of this sequence is not required forreinforcement in the task. Our study furthersuggests that lemurs are less inclined to encodea sequence based on visual identity cues. To ourknowledge, this study is the first demonstrationof implicit learning in a prosimian primate. Itopens the door for comparative studies ofimplicit learning across ecologically diverselemur species.

Acknowledgments

We thank Ryan Brady, Marlee Butler, MonicaCarlson, and JaneMcConnell for assistance withdata collection, as well as David Brewer, ErinEhmke, and the entire Duke Lemur Center stafffor support of and help with this study. Thismaterial is based upon work supported bythe National Science Foundation GraduateResearch Fellowship Program under GrantNo. 1106401, and the Holland-Trice GraduateFellowship in Brain Science and Disease, to

CBD; an Independent Study Grant to TBand Assistantship Funding to Jane McConnellfrom the Duke Undergraduate ResearchSupport Office; the Duke Lemur Center’sMollyGlander Award to TB, Ryan Brady, and JaneMcConnell; and the James McDonnell ScholarAward to EMB.

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Received: August 18, 2015Final Acceptance: November 11, 2015


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