THEORETICAL REVIEW

What do we know about implicit false-belief tracking?

Dana Schneider & Virginia P. Slaughter & Paul E. Dux

# Psychonomic Society, Inc. 2014

Abstract There is now considerable evidence thatneurotypical individuals track the internal cognitions ofothers, even in the absence of instructions to do so. Thisfinding has prompted the suggestion that humans possess animplicit mental state tracking system (implicit Theory ofMind, ToM) that exists alongside a system that allows thedeliberate and explicit analysis of the mental states of others(explicit ToM). Here we evaluate the evidence for this hy-pothesis and assess the extent to which implicit and explicitToM operations are distinct. We review evidence showing thatadults can indeed engage in ToM processing even withoutbeing conscious of doing so. However, at the same time, thereis evidence that explicit and implicit ToM operations sharesome functional features, including drawing on executiveresources. Based on the available evidence, we propose thatimplicit and explicit ToM operations overlap and should onlybe considered partially distinct.

Keywords ImplicitTheoryofMind .ExplicitTheoryofMind .

False-belief tracking . Social cognition . Eyemovements .

Unconscious cognitive processes

Theory of Mind (ToM) reasoning or mentalizing refers to anindividual’s ability to infer the mental states of others, including

their beliefs, feelings, and intentions (Apperly & Butterfill,2009; Butterfill & Apperly, 2013; Frith & Frith, 2005; Low &Perner, 2012). ToM is a complex and dynamic cognitive processthat is engaged across a wide range of social activities.Cooperating and communicating with work colleagues,interacting with family and friends, thinking about others intheir absence, or simply asking a stranger for help all requireToM. Underscoring the importance of ToM for social function-ing are the social-communicative limitations seen in individualswith an autism spectrum disorder (ASD) or schizophrenia, whotypically show impairments, relative to neurotypicals, in ToMreasoning (Baron-Cohen, Leslie, & Frith, 1985; Brüne, 2005;Frith, 2004a, b; Frith & Hill, 2004; Moran et al., 2011). Further,across the neurotypical human lifespan, ToM abilities have beenshown to predict social functioning outcomes (Apperly,Samson, & Humphreys, 2009; Dumontheil, Apperly, &Blakemore, 2010; Henry, Phillips, Ruffman, & Bailey, 2013;Maylor, Moulson, Muncer, & Taylor, 2002; Phillips et al., 2011;Slaughter, Peterson, &Moore, 2013). Currently, there is consid-erable debate regarding the cognitive architecture underlyingToM. A recent, and particularly provocative claim, is thatneurotypical individuals can not only reason about others’ be-liefs, but also implicitly track them as social events unfold. Thatis, humans have the ability to register what is represented inanother person’s mind even in the absence of an intention to doso and without explicit knowledge of doing so. This claimentails a distinction between implicit and explicit ToMfunctions.

Much of the research that has prompted the proposal ofimplicit ToM comes from the field of developmental psychol-ogy. Specifically, by assessing indirect measures such as eyemovements, researchers have concluded that infants as youngas 7–15 months are able to register false beliefs (i.e., they canrecognize that others can have beliefs about the world that are

D. Schneider :V. P. Slaughter : P. E. Dux (*)School of Psychology, The University of Queensland, McElwainBuilding, St. Lucia, Queensland 4072, Australiae-mail: paul.e.dux@gmail.com

D. Schneider (*)Institute of Psychology, Department of General Psychology andCognitive Neuroscience, Friedrich Schiller University Jena, AmSteiger 3, Haus 1, 07743 Jena, Germanye-mail: msdanaschneider@gmail.com

Psychon Bull RevDOI 10.3758/s13423-014-0644-z

different from reality, based on outdated knowledge; Kovács,Téglás, & Endress, 2010; Onishi & Baillargeon, 2005; Surian,Caldi, & Sperber, 2007). These findings have prompted a revisionof thinking about the developmental trajectory of ToM, sincemore than 20 years of research employing explicit measures ofToM (e.g., verbal responses, pointing) indicated that accurateattribution of others’ false beliefs was not reliably demonstrateduntil children reach approximately 4 years of age (Wellman,Cross, & Watson, 2001). Thus, along with the proposal for animplicit–explicit ToM dimension, the results from the infancystudies suggest the existence of early and later developing ToMcapacities, whichmay or may not be developmentally continuous(Baillargeon, Scott, & He, 2010; Perner & Roessler, 2012). Inaddition, such findings have led to the hypothesis that along thedichotomy of implicit/explicit ToM functions, two opposing ToMsystems coexist in adults: that is, a rapidly operating, resource-efficient, and inflexible system, as well as a slower operating,resource-demanding, and flexible ToM system (Apperly &Butterfill, 2009; Back & Apperly, 2010).

This reviewwill outline and assess current evidence for andagainst the hypothesis of an implicit–explicit ToM distinction.To organize our review, we introduce the origins of the con-cept of implicit ToM reasoning, summarize terminology thathas been used to describe this new form of ToM, and evaluateassumptions made regarding its underlying mechanisms. Indoing this, we also explore relationships between the proposedimplicit and explicit ToM systems and examine the extent towhich they draw on overlapping cognitive resources.

Origin of the concept “implicit” Theory of Mind

In their now classic work, Clements and Perner (1994) demon-strated that children by the age of 2 years and 11 months showsensitivity to the beliefs of others in a standard false-belief task(sometimes also referred to as the “Sally–Anne” paradigm or thelocation-change false-belief test, originally devised by Wimmer& Perner, 1983). In this paradigm, a protagonist (e.g., Sally)places an object (e.g., a ball) in one location (e.g., a basket) andthen leaves the scene (e.g., she goes out of the room). In theprotagonist’s absence, another individual (e.g., Anne) moves theobject to a different location (e.g., a box) and then leaves thescene. (See Fig. 1.) Participants are then asked to report wherethe protagonist will look for the object when she returns.

To successfully pass this test, participants must understandthat the protagonist’s actions will be based on what she be-lieves to be true, rather than the actual state of affairs. Thus,participants should indicate that Sally will look for the objectin the basket rather than the box. Typically, participants’responses to the Sally–Anne test question are measured usingdirect tests (e.g., verbal responses or pointing). In theirgroundbreaking variation of this task, Clements and Perner(1994) recorded children’s anticipatory gaze behavior toward

the two locations in the scene as well as asking the explicit testquestion. For the anticipatory gaze behavior, one would ex-pect participants to fixate first on and look longer at locationsthat are consistent with the beliefs and anticipated behavior ofthe protagonist (e.g., Sally moving toward the location that isin line with her false belief about the ball, thus the emptybasket). Clements and Perner found that 90 % of child partic-ipants looked at the location that was consistent with theprotagonist’s false-belief belief state; however, only55 % of them could explicitly indicate this location inanswering the explicit test question. Clements andPerner interpreted the differences between children’sperformance on the indirect looking measure and theiranswers to the direct question as evidence for distinct implicit

Fig. 1 “Sally–Anne” false-belief test: A protagonist (e.g., Sally, left char-acter) places an object (e.g., a marble) in one location (e.g., a basket), whileanother individual (e.g., Anne, right character) watches. Sally then leavesthe scene (e.g., she goes out of the room). In Sally’s absence, Anne nowmoves the object to a different location (e.g., a box). She then also leavesthe scene and Sally returns. At this point in time participants are asked toreport where Sally will look for the object. If participants understand thather actions will be based on what she believes to be true, rather than theactual state of affairs, they should indicate that Sally will look for themarble in the basket rather than the box. Sally will act on her false belief.Artist: Axel Scheffler, reusedwith permission fromElsevier. From Frith, U.(2001). Mind blindness and the brain in autism. Neuron, 32, 969–980

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and explicit ToM systems (“…the signs are that we are dealingwith a different type of knowledge; implicit as opposed toexplicit knowledge…”, p. 394, Clements & Perner, 1994).

Clements and Perner (1994) were the first to empiricallyinvestigate a difference between implicit and explicit ToM.Their investigations intended to tap the “consciousness” as-pects of ToM processing (i.e., the divergent moment for theability to actively reflect and report on ToM processes andbehavior; Low & Perner, 2012), building on work from thefield of memory (for a review, see Reber, 2013). Explicitmemory relates to the operation of intentionally and con-sciously remembering information, such as particular facts.In contrast, implicit memory is the ability to acquire informa-tion without conscious knowledge of doing so, such as how toperform a specific task. Classic examples of implicit memoryare tying a shoe or riding a bicycle (i.e., these types of taskscan be undertaken by people without remembering facts anddetails about the action procedure). In line with this distinc-tion, implicit ToM is the process of representing another’smental state without conscious access to this information.

The key findings of Clements and Perner (1994) have nowbeen replicated by several groups, further supporting thehypothesis that looking measures in false-belief tasks can tapunconscious ToM processes (Garnham & Perner, 2001; Low,2010; Ruffman, Garnham, Import, & Connolly, 2001). In acompelling study by Ruffman et al. (2001) using a Sally–Anne task, 3- to 5-year-old children had to bet on where astory character would look: either the location consistent withthe protagonist’s false belief or the actual location of theobject. The investigators reasoned that betting is a type ofconfidence measure, which, like a verbal or pointing behavior,requires explicit ToM processing. However, unlike pointing orverbal responses to a test question, both of which demand adichotomous response, betting allows an indication of greateror lesser certainty regarding an answer. As such, the Ruffmanet al. study investigated whether looking behavior actuallyindexes explicit knowledge of another’s belief state, but heldwith little confidence, by studying looking and betting behav-ior at the same time. If the looking measure actually reflects anexplicit ToM process, children’s betting should be consistent,reflecting the wide range of measurements for explicit false-belief understanding. By contrast, if looking behavior indexesa distinct system of earlier-developing, implicit knowledge,then children’s betting should be unrelated to their eye-gazepatterns. The authors found that children consistently bet onthe actual location of the object rather than the location repre-sented by the false belief of the character. At the same time,they reliably looked to the false-belief location. This wastaken as further evidence that looking measures are distinctfrom explicit false-belief reasoning, and therefore represent animplicit/unconscious ToM process.

Recent work with adults further supports the proposal thathumans have the capacity to represent unconsciously the

cognitions of others. Adapting a paradigm developed bySenju, Southgate, White, and Frith (2009), Schneider,Bayliss, Dux, and their colleagues used a false-belief antici-patory looking paradigm, as described above, utilizing eye-tracking technology. In addition, the authors also included anoffline, follow-up debriefing to assess the extent to whichadults were conscious of having engaged in ToM processing(Schneider, Bayliss, Becker, & Dux, 2012; Schneider, Lam,Bayliss, & Dux, 2012; Schneider, Slaughter, Bayliss, & Dux,2013). Specifically, Schneider and colleagues used movies todisplay a Sally–Anne type task, in which the protagonist inone scenario held a false belief and in the other a true beliefabout the location of an object. True-belief scenarios served ascontrol conditions and differed from false-belief scenarios inthat the protagonist knew at the end of the trial sequencewhere the object was located. In the task used by Schneiderand colleagues, at the end of each video sequence, for both thefalse- and true-belief scenarios (i.e., once the protagonist wasback in the room), the last shot of the sequence was displayedfor another 5 sec to allow measurement of participants’ antic-ipatory looking behavior. Crucially, in this time window,participants looked at the empty location (i.e., the locationthat contained no ball) for longer in false-belief than in true-belief conditions. Note that in the false-belief condition, theprotagonist falsely believed the ball to be at the empty location,whereas in the true-belief condition she correctly believed theball not to be at that location. Thus, participants demonstratedprocessing the belief state of the protagonist. In addition, aseven-item debriefing procedure (adapted from Bargh &Chartrand, 2000) was administered after the eye-tracking ses-sions, probing participants with increased specificity regardingtheir explicit/conscious insight into having engaged in a ToMprocess. This approach was sensitive enough to identify partic-ipants that were conscious of having tracked the belief states ofthe displayed protagonists (e.g., they would report that theynoticed that “Sally” had been tricked). Importantly, participantsthat showed no conscious registration of belief tracking never-theless displayed eye movements consistent with engaging inbelief processing. Thus, adult participants displayed eye-movement behavior indicative of false-belief processing,without being conscious of such behavior.

Another key aspect of the study by Schneider, Bayliss et al.(2012) was that they employed a multiple-trial design. Inmany previous studies on implicit false-belief tracking, itwas common practice to test looking behavior on a single trialonly (because of the fact that most of the research workstemmed from the infant/child literature). However, socialinteractions are dynamic and often prolonged. Therefore itwas important to confirm that the eye-tracking resultsreflected the implicit analysis of others’ mental states, ratherthan a social orienting response, such as that triggered, forexample, by biological motion (Allison, Puce, & McCarthy,2000). Further, it helped to demonstrate whether eye-

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movement evidence for false-belief tracking simply reflectedbehavioral rule learning, rather than a representation of mentalprocesses (e.g., Perner & Ruffmann, 2005; Ruffman,Taumoepeau, & Perkins, 2012). Themultiple-trial design usedby Schneider, Bayliss et al. (2012) assessed the time course offalse-belief looking behavior. The authors reasoned that if asocial orienting response was responsible for the previouslyobserved implicit ToM eye-movement findings, then fast ha-bituation of these effects should be evident (as found fororienting processes; Asplund, Todd, Snyder, & Marois, 2010;Sokolov, Spinks, Näätänen, & Lyytinen, 2002). Similarly, abehavioral rule account would predict that the typically ob-served eye-movement behavior would take several trials todevelop. In contrast, if a social analysis/mental representationprocess was beingmeasured in implict false-belief tasks, then itwas predicted that the eye-movement behavior would be ob-served immediately and sustained over multiple trials. In sup-port for a social analysis/mental representation account, twoexperiments revealed that from the first trial, looking behaviorconsistent with false-belief tracking occurred and wassustained over a 1-hour period. Thus, it can be concluded withsome confidence that for children and adults, false-belief track-ing without instruction reflects ongoing social analysis thatoccurs without a conscious registration of this behavior.

In addition to anticipatory looking as a measure of false-belief understanding, one often sees violation-of-expectation(VoE) paradigms employed (e.g., Onishi & Baillargeon, 2005;Surian et al., 2007). Here, participants’ fixations are examinedin relation to unexpected events in false-belief scenarios. Inthese VoE studies, implicit belief processing is inferred ifparticipants show longer fixation times to scenarios in whichprotagonists behave in opposition to their belief (e.g., Sallymoves toward the ball’s actual location instead of the locationwhere she believes it to be). For example, in line withSchneider, Bayliss et al. (2012) and the social analysis/mental representation account, Yott and Poulin-Dubois(2012) found, using a VoE false-belief paradigm, that 18-month-olds displayed eye-movement behavior consistent withhaving learned a new rule (i.e., an object that disappears inlocation A can be found in location B). Despite this, whentested with a false-belief scenario, infants kept displaying theopposite pattern of eye movements, consistent with themhaving represented the belief state of a displayed protagonist.In further support of the social analysis/mental representationaccount of eye-movement behavior in false-belief tasks,Senju, Southgate, Snape, Leonard, and Csibra (2011) hadone group of 18-month-olds experience an opaque blindfoldand another one experience a transparent “trick” blindfold.Both groups then observed an actor wearing the blindfold theyhad just experienced while a puppet moved an object awayfrom its location. This meant that only in the opaque blindfoldgroup was a false-belief condition established, because in thetransparent blindfold condition, infants should have inferred

that the protagonist was always able to see. Interestingly, thiswas reflected in the infants’ anticipatory eye-movement be-havior. If eye-movement behavior could be explained bysituation or task factors, such as behavioral rules or statisticallearning, one would have expected the same anticipatory eye-movement behavior in both conditions.

Work with individuals with high cognitive abilities and aless severe autism spectrum disorder (ASD; Senju et al., 2009)has provided additional evidence for the proposal of distinctimplicit and explicit ToM systems. Specifically, Senju et al.(2009) found that adults with ASD passed explicit false-belieftasks, such as the Smarties task (i.e., in a box of Smarties, aparticipant finds pencils and is then asked what another per-son, who has not yet seen the contents of the box, wouldindicate to be in the box; Perner, Leekam, & Wimmer, 1987)or the Strange Stories task (i.e., naturalistic social stories,which concern the different motivations that can lie behindeveryday events/utterances that are not literally true (e.g.,being polite to spare somebody’s feelings); Happé, 1994), aspreviously found in other studies (Bowler, 1992; Peterson,Slaughter, & Paynter, 2007; Scheeren, de Rosnay, Koot, &Begeer, 2013). However, when probed on a false-belief antic-ipatory looking paradigm, these same participants failed todisplay eye-movement patterns consistent with implicit ToMprocessing. This pattern of results was later confirmed andextended by Schneider et al. (2013), who demonstrated thateven when tested over a prolonged time period, individualswith ASD did not demonstrate belief processing in anticipa-tory false-belief tasks, while passing explicit ToM measures.Thus, evidence is mounting that implicit and explicit ToMprocesses are indeed distinct.

With the intention of further teasing apart whatdistinguishing characteristics underlie implicit and explicitToM, Low and Watts (2013) recently reported an elegantadaptation of the Sally–Anne paradigm. The authors used aclassic false-belief location-change task and a novel false-belief identity-change task in both an implicit and explicit tasksetup. The implicit and explicit task setup was realized withanticipatory looking and a verbal/pointing response, respec-tively, toward the false-belief location. The false-beliefidentity-change task presented a protagonist and an object thathad two apparent identities (i.e., a red and a blue side to a toyrobot). Here, the red side of the toy robot was shown to theparticipants as it moved from one box to another (left to rightfrom the participant’s perspective). Once the toy robot reachedthe right box, it turned around (visible only to the participant),which revealed that it had two sides: a red one and a blue one.The toy robot then returned to the initial box, now showing itsblue side to the participant. At this time point the participantwould have recognized that the protagonist would have seenwith the first movement (to the right box) the blue side of thetoy robot and with the second move (to the left box) the redside of the toy robot. Thus, participants should infer that the

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protagonist believes that there are two objects in the scene(i.e., red and blue toy robots). In regard to anticipation, par-ticipants learned in previous familiarization trials that theprotagonist had a preference for blue objects. Thus, in theimplicit and explicit test, participants should have anticipated/indicated that the protagonist would reach toward the locationwhere he/she falsely believed the blue toy robot to be (i.e., theright box). The authors found that in the false-belief location-change task, adults, 4-year-olds, and the majority of 3-year-olds showed anticipatory looking in line with the false beliefof the protagonist. Further, they found that accuracy of explicitresponses increased as a function of age (3-year-olds: 31%; 4-year-olds: 75 %; adults: 100 %). On the implicit and explicitfalse-belief identity-change task, however, the majority ofparticipants in all age groups did not show anticipatorylooking in line with the false belief of the protagonist (3-and 4-year-olds: 6 %; adults: 25 %). This was found despitea typical explicit response, in which participants identified thebox location that was in line with the false belief of theprotagonist again as a function of age (3-year-olds: 13 %;adults: 95 %). This work implies that the implicit ToM systemmay lack the ability to differentiate several object identitiesand associated belief states in false-belief tracking tasks, incontrast to the explicit ToM system. This, in turn, suggests thatthe implicit ToM system may only track a subset of mentalstates, such as a protagonist’s beliefs about the location of anobject, but not beliefs about the object’s properties.

Empirical investigations of implicit ToM processes, asdescribed above, have also led to theorizing regarding false-belief tracking without instructions. For example, Vierkant(2012) suggested a differentiation between completely un-aware implicit false-belief understanding and aware implicitfalse-belief understanding. The first is described as an implicitToM understanding that is so encapsulated that it will haveonly very limited influence on integrated intentional behavior.Accordingly, this type of false-belief understanding isreflected in VoE paradigms (e.g., Kovács et al., 2010; Onishi& Baillargeon, 2005; Surian et al., 2007) or false-belief antic-ipatory looking (e.g., Clements & Perner, 1994; Schneider,Bayliss et al., 2012; Schneider, Lam et al., 2012; Southgate,Senju, & Csibra, 2007).

In contrast, aware implicit false-belief understanding isdescribed as implicit ToM knowledge that can guide inten-tional behavior, but does not figure in deliberative reports.Such implicit ToM understanding is reflected in intentionalaction tasks (see, e.g., Buttelmann, Carpenter, & Tomasello,2009). These tasks are designed to reveal the participant’sunderstanding of another person’s intention, for example, toopen a door, which the participant may act upon (e.g., bypulling the door handle for them). If implemented in a false-belief scenario, participants in this type of task may not be ableto explicitly report on their false-belief understanding (as inSchneider, Bayliss et al., 2012; Schneider, Lam et al., 2012);

however, they typically display behavior that indicates someaccess to belief processing.

For example, Buttelmann et al. (2009) presented a false-and true-belief helping paradigm to 2.5-year-old, 18-month-old, and 16-month-old children. The participants watched anadult attempt to open one of two locked boxes. This occurredafter a setup, which established a false- or true-belief scenariovia the adult’s movements in and out of the testing room. Inthe true-belief condition, the adult attempted to open the boxthat did not contain the toy. This indicated that the adultsimply wanted to open the box, since the setup establishedthat she knew the toy was located in the opposite box. In thefalse-belief condition, by contrast, the adult’s behavior was thesame but in this case she was apparently trying to access thetoy, because the setup had indicated that she falsely believedthe object to be in that box. The key variable here waschildren’s helping behavior. Interestingly, 75% of the childrenhelped the adult open the empty box in the true-belief condi-tion, whereas in the false-belief condition, around 83 % ofchildren opened the opposite box, which contained the toy.The authors concluded that in the false-belief condition, chil-dren opened the opposite box because they assumed that theprotagonist wanted the toy, but had a false belief as to where itwas located. This suggests that such young children have anunderstanding of the adult’s false beliefs, which they can actupon, but not explicitly report on.

For our understanding of an implicit/unconscious ToMprocess, the latter described conceptualization of an awareimplicit ToM process fits the concept of an explicit/conscious ToM process, simply operationalized differently(i.e., knowledge about another’s mental state is processedand used in subsequent behavior). However, it remains to beinvestigated whether cognitively healthy participants in anintentional action task show any conscious registration of theirbehavior. If not, this would suggest that this paradigm alsotaps implicit ToM.

On that note, the same applies to the above-mentionedbetting task, implemented by Ruffman et al. (2001). It maybe that participants bet on certain locations without consciousknowledge of their behavior; thus, it may also be more appro-priate to term this behavior an implicit ToM operation. Thesetypes of innovative belief tasks are very important in thedebate about whether the implicit and explicit ToM systemshould be considered entirely distinct or whether they shouldrather be viewed as a continuum. Further, these approachesmay clarify whether implicit ToM is a developmental founda-tion for explicit ToM, and they therefore represent one system,or whether they develop in parallel, and thus represent twosystems (Apperly & Butterfill, 2009; Baillargeon et al., 2010;Perner & Roessler, 2012).

To date, only two studies have attempted to address thequestion of whether implicit and explicit ToM capacities areunderpinned by one or two systems, and relatedly, if these

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capacities develop in continuation or in parallel (Clements,Rustin, & McCallum, 2000; Thoermer, Sodian, Vuori, Perst,& Kristen, 2012). Clements and colleagues reported in atraining study, in a sample of over 90 children (ages 2 yearsand 10 months to 5 years), that only when children showedevidence of anticipatory looking in false-belief tasks, wastraining beneficial for improving their performance on explicitfalse-belief tasks. This work suggests that implicit ToM pro-cessing is a promoter/precursor for successful explicit ToMunderstanding. Similarly, Thoermer et al. (2012) reported, in alongitudinal study with a sample of 70 infants, that anticipa-tory looking in a false-belief task at 18 months significantlypredicted explicit false-belief reasoning at 48 months, and thislink was independent of general verbal ability. Interestingly,this was found only for matching implicit and explicit false-belief tasks (i.e., the location-change test), but not fornonmatching implicit and explicit false-belief tasks (i.e., im-plicit: the location-change test, explicit: the false-content test[e.g., Smarties task]). Therefore, this might indicate that im-plicit and explicit ToM capacities are distinct mechanisms,which are related only when they have overlapping situationalfeatures, that is, the same task. Thus, whether success onimplicit false-belief tasks is indeed a promoter/precursor forexplicit ToM processing—of which false-belief reasoning isonly one of many cognitive operations—remains a crucialtopic of investigation. Further discussions on this point willfollow later in the review.

Collectively, the above studies help shape the formulationof an implicit ToM system; however, at the same time theyhave motivated other investigations, which led to a range ofdifferent findings and thus brought along a variety of terms todescribe implicit ToM. Labels such as “nonverbal,”“nonelicited,” “passive,” “intuitive,” “spontaneous,” “socialperceptual,” “automatic,” “bottom-up,” “very simple,” “min-imal,” and “innate” have been introduced to describe theoperations thought to underlie implicit tracking of others’beliefs. In the following section we unpack these terminolo-gies and provide an analysis of what each implies inrelation to relevant psychological mechanisms. We alsoassess evidence for and against the involvement of suchmechanisms in implicit ToM.

What processes underlie “implicit” false-belief tracking

Because false-belief tasks can be administered with bothverbal (e.g., stories: Saxe & Kanwisher, 2003) and nonverbal(e.g., cartoons: Gallagher et al., 2000; animated shapes:Castelli, Frith, Happé, & Frith, 2002; Castelli, Happé, Frith,& Frith, 2000) stimuli, a body of work has investigated howthese different delivery formats influence ToM. A number ofdifferent nonverbal tasks have been introduced, for examplespontaneous behavior measurements (see, e.g., Scott, He,

Baillargeon, & Cummins, 2012; Senju et al., 2009; Surian &Geraci, 2012), passive measurements (Geangu, Gibson,Kaduk, & Reid, 2012), and indirect reaction time measures(Kovács et al., 2010). In spontaneous and passive behaviormeasurements, researchers expose participants to ToM mate-rial, such as a Sally–Anne location-change task, without anyinstructions, and observe spontaneous behavior (e.g., lookingpatterns, as described above) or physiological activity (e.g.,electroencephalography). In indirect reaction time measures,participants perform an unrelated task while observing differ-ent belief conditions. For example, Kovács et al. (2010) hadparticipants detect a ball behind an occluder (sometimes pres-ent, sometimes absent) at the end of a movie sequence asquickly and as acurately as possible. The movie sequencesdisplayed false- and true-belief scenarios; however, this wasirrelevant to the participant’s task. Using this setup, the au-thors found that the ball was detected faster when participantsor protoganists in the movies correctly believed the ball to bebehind the occluder than when they did not believe so.

A key motivation for the development of such nonverbalToM paradigms is to control or eliminate the contribution oflanguage, working memory, inhibition, and other executiveoperations to perform on these tasks (Hale & Tager-Flusberg,2003; McKinnon & Moscovitch, 2007; van der Meer,Groenewold, Nolen, Pijnenborg, & Aleman, 2011).Removing the influence of these variables is particularlyuseful in ToM studies involving very young, healthy, orclinical populations that have limited linguistic, symbolic, orexecutive capacities (Samson, Apperly, Chiavarino, &Humphreys, 2004; Scott et al., 2012; Senju et al., 2009;Senju et al., 2010). ToM tests with reduced peripheral de-mands often show very different patterns than standard ex-plicit ToM tasks. For example, as discussed above, childrenmuch younger than 4 years of age register the false-beliefstates of others (Southgate et al., 2007) but most fail explicitfalse-belief tasks prior to that age (Wellman et al., 2001). Inaddition, some researchers have tried to reduce peripheral taskdemands to isolate ToM processes in order to explore whichbrain regions are involved in processing the mental states ofothers (Castelli et al., 2000, Gallagher et al., 2000; Geanguet al., 2012). Gallagher et al. (2000) used a story comprehen-sion task (i.e., a version of the Strange Stories task) and acartoon task (i.e., a task in which a cartoon was displayed,which could only be understood if an attribution of a beliefstate to one of the characters was made) and found that themedial prefrontal cortex activated less in the nonverbal car-toon task relative to the comprehension task.

However, it is key to note that investigations into “implicit”ToM processing that rest on nonverbal delivery formats orspontaneous, passive, or indirect response formats are notprincipally concerned with examining whether ToM behavioroccurs outside of consciousness. Further, simply reducingperipheral task demands does not guarantee that a pure ToM

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operation is isolated. Therefore, these types of studies do littleto disambiguate potentially distinct and overlapping opera-tions involved in implicit/unconscious and explicit/consciousToM processes.

Apart from these reduced peripheral demand investiga-tions, another concept and term used in the literature to de-scribe ToM processing in the absence of explicit instructionsis stimulus-driven/bottom-up ToM (Blakemore & Decety,2001). Based on biological motion investigations (e.g., mov-ing dots/animated triangle paradigms: Atkinson, Dittrich,Gemmell, & Young, 2004; Castelli et al., 2002; Castelliet al., 2000; eye-gaze, hand-, and body-movements para-digms: Allison et al., 2000) this line of work considers thatthe perception of action serves as a prerequisite forrepresenting another’s mental state (Frith & Frith, 1999).From this viewpoint, humans even infer complex internalmental states, such as beliefs, from displays of simple two-dimensional shapes, as long as the movement of the shapes is“animate” (i.e., it is self-propelled, its path is nonlinear, and itundergoes sudden changes of velocity). For example, a recentexperiment by Surian and Geraci (2012), using anticipatorylooking in a false-belief task, suggested that 17-month-oldsshow false-belief attributions to animated geometric shapes(e.g., circles and triangles). The authors concluded that evenvery young children could analyze the actions of unfamiliaragents to anticipate their future behavior, even in the absenceof any morphological features that are typical of naturalagents. Whether such nonintentional ascription of mentalstates to biological motion is the driving force behind apossible distinction between implicit and explicit ToM pro-cesses remains to be seen. Stimulus-driven ToM operationsmay allow for an implicit/unconscious ToM process to fall inplace; at the same time, stimulus-driven ToM mechanismsmay also be needed for explicit ToM processes (as is sug-gested, for example, in Leslie’s model on ToM operations[1987; 1994a; 1994b], described in detail below).

A considerable amount of work has also been undertakentesting the umbrella term of resource-efficient ToM process-ing. Particularly, researchers have tried to answer to whatextent individuals may “automatically” represent the mentalstate of another person/character/animated agent. Put differ-ently, are inferences about beliefs, desires, and intentionsmade automatically when people attend to the behavior ofan agent, or are such inferences made ad hoc, according toneed? There is empirical support for both automatic(Friedman & Leslie, 2004; Kovács et al., 2010; Leslie &Thaiss, 1992; Low & Watts, 2013; Onishi & Baillargeon,2005; Qureshi, Apperly, & Samson, 2010; Sperber &Wilson, 2002; Wertz & German, 2007) and nonautomaticToM (Apperly, Riggs, Simpson, Chiavarino, & Samson,2006; Back & Apperly, 2010; Keysar, Lin, & Barr, 2003;Schneider et al., 2012). The first theoretical ToM modelproposed by Leslie (1987; 1994a; 1994b) predicts that ToM

processes have a foundation in a core mechanism.Specifically, it is suggested that if certain forms of agentbehavior are present, this specialized ToM mechanism(ToMM) turns on reflexively and attempts to calculate thecreature’s mental states. As soon as ToMM has dissected thebehavior of an agent to infer a set of candidate beliefs, then aseparate executive processor identifies and selects the appro-priate belief content from among the options. According tothis theory, only with this second step is the belief ascriptionprocess complete (Leslie, Friedman, & German, 2004; Leslie,German, & Polizzi, 2005). Applying this model, one couldassume that anticipatory looking behavior in implicit ToMtasks reflects this reflexively acting ToMM, whereas explicitToM processes are the result of the executive selection pro-cessor. However, contrary to the proposal of such areflexively/automatically operating ToMM system stands ev-idence from a recent study on implicit false-belief tracking inadults (Schneider, Lam et al. 2012). Schneider and colleaguesused a dual-task protocol in which they had participants watchfalse- and true-belief scenarios while measuring their antici-patory eye-movement behavior. One group of participants justwatched the belief movies (no load condition); another group,in addition to the movies, was presented with an auditory letterstream, which needed to be ignored (low-load condition), andanother group counted the number of two-back letter repeti-tions in the letter stream and reported them at the end of themovies (high-load condition). The authors found that with theincreased secondary working-memory load, implicit false-belief belief tracking was not observed. Thus, based onestablished criteria for automaticity (see below), it might bethat as soon as agentlike behavior is available, the ToMmechanism does not turn on reflexively or that working-memory load disrupts this reflex. Criteria for automaticityinclude that the behavior and thoughts draw, at a minimum,on capacity-limited processing resources (i.e., short-termmemory, attention); that they are unconscious, unintentional,and uncontrollable; that they show no benefit from practice;and that they function under all circumstances at a constantlevel (Bargh, 1994; Hasher & Zacks, 1979). Note that Leslie’sToM module theory does not explicitly go against the predic-tion that both the ToMmechanism and the selection processormay require processing resources. Thus, to unequivocallyconfirm whether the ToM module operates reflexively orimplicit ToM mechanisms are automatic, at least the last twocriteria still require investigation.

In a further effort to characterize humans’ capability totrack others’ beliefs in the absence of being conscious of doingso, various authors have proposed names for the “implicit”ToM system; among these are “very simple” (Fodor, 1992),“social perceptual” (Tager-Flusberg, 2001), and “minimal”(Apperly & Butterfill, 2009; Butterfill & Apperly, 2013). Allthese proposals entail the same broad idea, mainly, that a fast,cognitively less demanding ToM system exists beside a slow

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and cognitively demanding ToM ability. For example,Apperly and Butterfill (2009) formulate that their minimalToM process does not involve the representation of proposi-tional attitudes (e.g., beliefs) but that it allows for less involvedrepresenting of mental-state-like elements. Specifically, thisview suggests that the demands on perspective taking withregard to oneself or another are crucial when discriminatingbetween effortless and efficient versus effortful and slow ToMoperations. Minimal ToM operations are hypothesized to in-volve lower-level perspective calculations: For example, whatone sees, thinks, or knows might not be seen, thought about,or known by another agent (e.g., What object/thought isavailable to her?). In contrast, in full ToM operations, ahigher-level perspective-taking plays a key role in the judg-ment processes. For example, an object or thought viewed byoneself and another may nevertheless give rise to differencesin what is perceived by each person about this object/thought(e.g., How is this object/thought represented by her?). Suchfunctional differentiation of the minimal and full ToM systemis consistent with results from the above-mentioned study byLow and Watts (2013). To reiterate, Low and Watts (2013)used an object with two identities, which needed to be trackedwith regard to the multiple beliefs it induced for a protagonistin a Sally–Anne scenario. Implicit as well as explicit ToMbehavior was measured, and only the latter reflected process-ing of beliefs regarding the object’s properties. Thus, thesefindings suggested that the minimal/efficient ToM systemdiffers from the full/slow ToM system, at least with regardto its ability to track multiple object identities.

In line with this finding, Apperly and Butterfill (2009) haveproposed their minimal ToM system as a distinct faculty thatsupports cognitively fast, efficient, but inflexible ToM reason-ing across the entire lifespan. In addition, the authors suggestthat the minimal ToM system is not a developmentalpromoter/precursor to the full adult ToM system, but that bothsystems develop in parallel—particularly based on the ideathat both systems demand opposing flexibility properties (i.e.,the implicit system: guidance of online social interaction andcommunication vs. the explicit system: top-down guidance ofsocial interaction and reasoning about the causes and justifi-cations of mental states). Other theoretical ToM models(Baillargeon et al., 2010; Leslie, 1987, 1994a, 1994b), as wellas empirical work (Clements et al., 2000; German & Cohen,2012; He, Bolz, & Baillargeon, 2011; Surian & Geraci, 2012;Thoermer et al., 2012), have suggested, in contrast, a contin-uous trajectory of development from the implicit ToM systemto the explicit ToM system. Some authors even suggest thatToM functions are an innate capacity (Leslie, 1987, 1994a,1994b; Baillargeon et al., 2010): This line of work takes themost recent implicit false-belief tracking data in very younginfants (e.g., 7- month-olds, Kovács et al., 2010) as evidencefor the idea that we are born with a ToM ability. In addition, itis argued that prior to the preschool period, supporting

executive abilities, which would allow us to consciouslyrepresent behavior indicative of ToM understanding, are stillundeveloped.

The broad differentiations between the minimal and fullToM systems as described by Apperly and Butterfill (2009;see also Perner & Roessler, 2012) fit approximately with ourdescription of the implicit/unconscious and explicit/consciousToM operations. However, we argue that in terms of cognitivefeatures, implicit and explicit ToM do not represent entirelydistinct mechanisms. This is predominantly based on recentstudies examining the involvement of executive functions inimplicit false-belief tracking behavior.

Cognitive characteristics of the implicit/unconsciousand explicit/conscious ToM system

As shown repeatedly in the developmental literature, ToMprocesses are complex and involve operations that draw, atleast in their traditional explicit task formats (e.g., verbalresponses to a false-belief task), on a range of general cogni-tive functions (Perner & Lang, 1999). Among these are inhib-itory control, planning, language abilities, general intelli-gence, and working memory (Astington & Jenkins, 1999;Benson, Sabbagh, Carlson, & Zelazo, 2013; Hale & Tager-Flusberg, 2003; Sabbagh, Xu, Carlson, Moses, & Lee, 2006).

Many recent adult investigations have confirmed that inhi-bition abilities, particularly the inhibition of one’s own perspec-tive, play a crucial role when solving explicit false-belief tasks(Rothmayr et al., 2010; Samson, Apperly, Kathirgamanathan,& Humphreys, 2005; van der Meer et al., 2011; Zhang, Sha,Zheng, Ouyang, & Li, 2009). For example, Rothmayr et al.(2010) showed, using a within-subjects design, that a belief-reasoning task (i.e., a classic explicit false- and true-belief task)and a response inhibition task (i.e., the same false- and true-belief task in a go/no-go setup) activated distinct brain areas.However, at the same time, a substantial overlap for bothprocesses was identified in the right superior dorsal medialprefrontal cortex, the right temporoparietal junction (TPJ), thedorsal part of the left TPJ, as well as the lateral prefrontal areas.

Further, it has been shown that working-memory abilitiesare crucial for classic ToM operations in adults (Bull, Phillips,& Conway, 2008; Dumontheil, Apperly, & Blakemore, 2010;Lin, Keysar, & Epley, 2010; McKinnon &Moscovitch, 2007;Phillips et al., 2011). For example, Lin et al. (2010) showed ina difficult explicit ToM task that under conditions of reducedworking-memory capacity, people are less effective in apply-ing their ToM abilities. Specifically, the authors employed thedirector communication task (Keysar, Barr, Balin, & Brauner,2000). Here, the participant and a director sit across the tablefrom each other, with several objects arranged in a grid ofboxes between them. Some of the objects are mutually visible,whereas others are visible only to the participant. Participants

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are therefore conscious of the fact that the director does notknow about certain objects. One situation might be that theparticipant sees two glasses: one glass mutually visible, andone occluded for the director. On critical trials, the directorinstructs the participant to move an object, but the instructionscan occasionally apply to a hidden object; for example, thedirector could say, “move the glass up one slot,” referring tothe mutually visible glass. In this instance, “the glass” tends tobe interpreted egocentrically; therefore the expression wouldbe ambiguous, because the participant can see two glasses. Itnow requires ToM abilities to solve this task—the director’sperspective has to be taken into account to identify the mutu-ally visible target glass. Eye-gaze behavior of participants wasanalyzed in Lin et al. (2010) to identify which object partic-ipants would first fixate on until reaching for one. InExperiment 1 the authors found that participants with lowerworking-memory capacities would take a longer time from firstnoticing the target until finally reaching for it than participantswith higher working-memory abilities. In Experiment 2, theauthors found that when participants performed the directorcommunication game along with a secondary working-memory task (i.e., a digit-memorizing task) they took longerfrom fixating the target object until reaching toward it underhigh, relative to low, load conditions. In addition to the fact thatthis type of work provides compelling evidence that explicitToM processes need the support of executive functions, such asinhibitory control and working-memory resources, it also indi-cates that the previously mentioned process-pure ToM opera-tions might be very hard to validly isolate.

Along those lines, quite recently, researchers have alsostarted to examine whether executive resources are necessaryfor implicit ToM operations. For example, in a study thattested 18-month-old infants, Yott and Poulin-Dubois (2012)found a strong relationship between working-memory capac-ities and implicit false-belief tracking abilities. As describedabove, Yott and Poulin-Dubois (2012) employed a VoE para-digm and found that after infants learned a new rule (i.e., anobject that disappears in location A can be found in location B),

they did not show looking-time evidence for this learning, butrather kept displaying the looking behavior consistent withfalse-belief processing (i.e., longer fixation times toward loca-tions consistent with a violation of the expected behavior).Crucially, this effect was highly correlated with performanceon a working-memory task (i.e., a detouring task on whichinfants had to learn that a toy should only be retrieved frombehind a plastic cover after a knob was manipulated). Thiswork converges with that of Schneider, Lam et al. (2012),who found using a dual-task paradigm that increasedexecutive/working-memory load impaired implicit false-belieftracking (see above) while not influencing anticipatory eyemovements in general. These initial results suggest that bothinfants’ and adults’ implicit false-belief tracking abilities alsodraw on working-memory resources.

Conclusions

A review of previous studies in both child and adult popula-tions suggests that false-belief tracking in the absence ofinstructions should be described as a social analysis processthat can occur without conscious registration of having en-gaged in such behavior. (For an overview of the definingstudies in the field of implicit false-belief tracking, seeTable 1.) It appears functionally similar to, but distinct from,explicit/conscious ToM, which is available to conscious pro-cesses. This distinction is supported by the research involvingindividuals with ASD, which has shown that explicit, but notimplicit ToM, can be demonstrated in this population, and byresearch showing the opposite pattern in neurotypical infantsand toddlers. Further support for a distinction between implicitand explicit ToM mechanisms comes from research demon-strating that, in contrast to the explicit ToM system, theimplicit ToM system tracks people’s beliefs about objectlocations but apparently fails to track people’s beliefs aboutobject identities. In sum, there is convincing evidence for theproposal of distinct ToM processes.

Table 1 Summary of findings in the field of implicit false-belief tracking

Study Findings

Clements & Perner, 1994 Three-year-olds demonstrate implicit false-belief processing via eye-gaze measuresbut no explicit false-belief processing via verbal responding.

Schneider, Bayliss et al., 2012 Implicit false-belief tracking via anticipatory looking is evident in typical adults andit is sustained over an hour of testing. Post-experimental debriefing procedure confirmsthat implicit false-belief tracking occurs outside adults’ consciousness.

Senju et al., 2009/Schneider et al., 2013 Adults with ASD demonstrate explicit false-belief processing (verbal responding) butnot implicit false-belief processing (anticipatory looking), and this difference issustained over time.

Low & Watts, 2013 The implicit false-belief tracking system represents object locations but not objectidentities, whereas the explicit system represents both.

Schneider, Lam et al., 2012 Implicit false-belief tracking is disrupted by working-memory load.

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At the same time, we stress that many studies in the past didnot have the core motivation of defining the cognitive mech-anisms involved in implicit/unconscious mental-state process-ing. As described in detail above, some work has simplyreduced the demands of the delivery and response format ofToM tasks. Although such work helped shape the concept ofan implicit ToM system, it did not necessarily isolate theconsciousness aspect of ToM. In this regard we highlightedrecent work in adults, which showed that implicit ToM pro-cesses should not be considered automatic when employingclassic criteria. Rather, it appears that implicit and explicitToM processes share certain characteristics such as a demandon working-memory resources. In line with this finding,we also pointed toward past evidence in children, whichindicated that implicit ToM abilities might operate as apromoter/precursor for explicit ToM functions. Thus, atthis point we conclude that previous descriptions ofminimal ToM operations approximately fit our conceptof the implicit/unconscious ToM system; however, webelieve that the description of the implicit ToM processas resource-efficient is unwarranted, given the evidencethat implicit ToM processes are at least partially relianton executive functions.

In future work we believe it would be fruitful to further shedlight on what elements of information processing are crucialfor complex social analysis processing. For example, to date itis still unclear what role the protagonist/s may play: Does theirpresence at certain times in belief scenarios trigger implicitversus explicit belief reasoning? In addition, future work onimplicit ToM processes should evaluate whether describedcapacity limitations can be overcome with training. It will alsobe vital that the range of tests used in order to assess partici-pants’ ability to implicitly infer other types of mental states areexpanded. Indeed, being able to represent the feelings, desires,and intentions of others, in addition to beliefs, is a key charac-teristic of explicit ToM (Premack & Woodruff, 1978).

Author note D.S. was supported by a University of Queensland PhDCentennial Scholarship, and P.E.D. by an Australian Research CouncilDiscovery Grant and APD and Future Fellowships (DP0986387;FT120100033).

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