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British Journal of Psychology (2014) © 2014 The British Psychological Society www.wileyonlinelibrary.com

Dissociation of rapid response learning and facilitation in perceptual and conceptual networks of person recognition Christian Valt1, Christoph Klein1,2 and Stephan G. Boehm1* 1

Wolfson Centre for Clinical and Cognitive Neuroscience, School of Psychology, Bangor University, Bangor, UK 2 Department of Child and Adolescent Psychiatry, Psychotherapy and Psychosomatics, University of Freiburg, Germany Repetition priming is a prominent example of non-declarative memory, and it increases the accuracy and speed of responses to repeatedly processed stimuli. Major long-hold memory theories posit that repetition priming results from facilitation within perceptual and conceptual networks for stimulus recognition and categorization. Stimuli can also be bound to particular responses, and it has recently been suggested that this rapid response learning, not network facilitation, provides a sound theory of priming of object recognition. Here, we addressed the relevance of network facilitation and rapid response learning for priming of person recognition with a view to advance general theories of priming. In four experiments, participants performed conceptual decisions like occupation or nationality judgments for famous faces. The magnitude of rapid response learning varied across experiments, and rapid response learning co-occurred and interacted with facilitation in perceptual and conceptual networks. These findings indicate that rapid response learning and facilitation in perceptual and conceptual networks are complementary rather than competing theories of priming. Thus, future memory theories need to incorporate both rapid response learning and network facilitation as individual facets of priming.

Repetition priming is a prominent example of non-declarative memory; like all forms of non-declarative memory, it does not rely on the integrity of the medial temporal lobe (Squire & Zola, 1996) and is, accordingly, preserved in amnesia (Graf, Squire, & Mandler, 1984). Repetition priming is mainly demonstrated by faster and more accurate responses when information is processed repeatedly (Richardson-Klavehn & Bjork, 1988; Roediger & McDermott, 1993). At present, there are two contrasting theoretical views about the mechanisms underlying repetition priming. Most memory theories assume that priming is the result of facilitation in perceptual and conceptual networks (Bruce & Young, 1986, 2012; Burton, 1998; Humphreys, Lamonte, & Lloyd-Jones, 1995; Morton, 1969; Moscovitch, 1992; Richardson-Klavehn & Bjork, 1988; Roediger & McDermott, 1993; Squire, 2004; Tulving & Schacter, 1990). Alternatively, theories of rapid response learning argue that priming results from bindings between stimuli and responses (Horner & Henson, 2008; Schacter, Dobbins, & Schnyer, 2004). In the present paper, we

*Correspondence should be addressed to Stephan G. Boehm, Wales Institute of Cognitive Neuroscience, School of Psychology, Bangor University, Brigantia Building, Penrallt Road, Bangor LL57 2AS, UK (email: [email protected]). DOI:10.1111/bjop.12095

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investigated the relevance of these competing views for priming of person recognition with a view on advancing memory theories. Repetition priming is investigated with two main types of priming tasks, perceptual and conceptual, and it comprises two major forms, data-driven and conceptually driven priming (Jacoby, 1983; Richardson-Klavehn & Bjork, 1988; Roediger & McDermott, 1993). In perceptual tasks, participants identify stimuli or judge the stimuli concerning perceptually derived attributes. Face gender judgments and object symmetry judgments are examples of tasks based on perceptually derived information, whereas identification requires the matching of a stimulus to pre-experimentally established representations in semantic memory, such as identifying words in a lexical decision task and celebrity faces in a familiarity task. In conceptual tasks, participants judge stimuli concerning information retrieved from semantic memory, for example, the occupation of a person whose face is shown, the abstractness of a word, or whether an object is man-made or natural. Data-driven priming is sensitive to perceptual manipulations between study and test such as using different stimulus images or a modality change (Richardson-Klavehn & Bjork, 1988; Roediger & McDermott, 1993). Usually, data-driven priming is investigated with perceptual tasks, but it can also be present in conceptual tasks when there is no perceptual manipulation between study and test (Boehm & Sommer, 2012; Burton, 1998; Roediger & McDermott, 1993). Conceptually driven priming, in contrast, is not affected by perceptual manipulations (Richardson-Klavehn & Bjork, 1988; Roediger & McDermott, 1993), and it is investigated with conceptual tasks. In the domain of person recognition, data-driven priming is often investigated with familiarity tasks for faces or names (Bruce & Valentine, 1985; Burton, 1998). It is disrupted by perceptual manipulations such as inverting faces (Yin, 1969) and using different face images, indicating a perceptual component (Boehm, Klostermann, Sommer, & Paller, 2006; Schweinberger, Pickering, Jentzsch, Burton, & Kaufmann, 2002). It is abolished by changes from faces to names or vice versa (Burton, Kelly, & Bruce, 1998; Ellis, Flude, Young, & Burton, 1996; Johnston & Barry, 2006) indicating an additional abstract component (Boehm et al., 2006). Although a small amount of priming can be present when faces are shown only by their inner features (Goshen-Gottstein & Ganel, 2000), data-driven priming is usually absent in tasks like gender judgments that rely on perceptually derived information (Ellis, Young, & Flude, 1990). In tasks involving identification such as familiarity judgments, in contrast, priming is present even when the study phase involved no identification (Ellis et al., 1990). Conceptually driven priming occurs in conceptual tasks such as occupation or nationality judgment tasks, and is not affected by perceptual manipulations (Burton et al., 1998; Johnston & Barry, 2006). The theoretical background for priming of person recognition is provided by the influential person recognition model (Bruce & Young, 1986, 2012; Burton, 1998). This model proposes distinct processing stages at which priming of person recognition arises. According to this model, data-driven priming results from both improved structural encoding and strengthening the links between face recognition units (representations of familiar faces) and person identity nodes (Boehm et al., 2006; Burton, 1998). Conceptually driven priming results from a similar strengthening of the links between person identity nodes (representations of familiar persons) and semantic information units (Burton, 1998), which contain knowledge about a particular person like nationality and occupation (Bruce & Young, 1986, 2012; Burton, 1998). The person recognition model posits that priming results from facilitation in perceptual and conceptual networks induced by prior processing. This theoretical view is common to most currently dominating views on memory in domains beyond person

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recognition, which posit similarly that repetition priming reflects facilitation in perceptual and conceptual networks (Humphreys et al., 1995; Morton, 1969; Moscovitch, 1992; Richardson-Klavehn & Bjork, 1988; Roediger & McDermott, 1993; Squire, 2004; Tulving & Schacter, 1990). On the neural level, this facilitation is usually explained as sharpening of the networks (Wiggs & Martin, 1998), reducing activity for repeated compared to unrepeated stimuli in the brain regions where these networks are located (Schacter & Buckner, 1998). A rather different and competing theoretical explanation for repetition priming is rapid response learning (Dobbins, Schnyer, Verfaellie, & Schacter, 2004). This theory posits that when a response to a stimulus is made, the stimulus and the response become bound; when the same stimulus is processed and the same response has to be made again later, the required response is retrieved from memory. Rapid response learning bears a strong similarity to other forms of stimulus-response binding such as instance-based theories of priming (Logan, 1990), event files (Hommel, 1998), negative priming (Allport & Wylie, 1999; Koch & Allport, 2006; Waszak, Hommel, & Allport, 2003, 2005), and task switching (Frings, Rothermund, & Wentura, 2007; Mayr & Buchner, 2006; Mayr, Buchner, & Dentale, 2009; Rothermund, Wentura, & De Houwer, 2005). Rapid response learning may lead to faster responses for repeated stimuli for three different reasons. Firstly, there could be a race between the response retrieved from memory and the response obtained from perceptual and conceptual networks or, secondly, the retrieval from memory might be quicker than obtaining the response from network processing (Logan, 1990) or, thirdly, because of the congruency of the two responses (Horner & Henson, 2009; Race, Badre, & Wagner, 2010; Race, Shanker, & Wagner, 2009). On the neural level, it has been proposed that rapid response learning leads to partially bypassing perceptual and conceptual networks (Horner & Henson, 2008; Schacter et al., 2004), resulting in the commonly found reduced activity for repeated stimuli in these networks (Schacter & Buckner, 1998). Rapid response learning binds at least two stimulus aspects with three response aspects (Horner & Henson, 2009, 2011b). It encompasses the concrete stimulus, such as the picture of an apple or the written name ‘apple’, and the meaning of the stimulus itself, such as the concept of an apple (Horner & Henson, 2011b). Hence, rapid response learning is larger when the two stimulus aspects are maintained at study and test compared to changing the concrete stimulus, for example, from the name to the picture of the object (Horner & Henson, 2011b). However, binding the meaning means that rapid response learning generalizes across different images of objects (Denkinger & Koutstaal, 2009; Wig, Buckner, & Schacter, 2009; but see Schnyer et al., 2007) and from the object picture to the object name (Horner & Henson, 2011a, 2011b, 2012). Likewise, three different response aspects can be bound: classification (e.g., ‘bigger’ than a shoebox), decision (‘yes’ or ‘no’), and action (‘left’ or ‘right’ finger press for a positive response; Dennis & Perfect, 2013; Horner & Henson, 2009, 2011b). The vast majority of studies have investigated rapid response learning by virtue of reversing the task instruction. For example, when the task instruction at study is ‘Is the object bigger than a shoebox?’, a large object would involve a classification of ‘bigger’ than a shoebox, a decision of ‘yes’ and the action ‘left’ button press. In the test phase, the task instruction would be reversed to ‘Is the object smaller than a shoebox?’ the decision and the action would thus be reversed to ‘no’ and ‘right’ button press. Such task reversal probes decision and action binding. Classification binding is usually investigated by the additional change of the referent object in the task instruction (e.g., shoebox) so that an object at study which is bigger (or smaller) than a shoebox becomes at test smaller (or

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EXPERIMENT 3 In Experiment 3, we tested decision/action binding in person recognition priming in an occupation judgment task and, in contrast to Experiments 1 and 2, changed from a single test phase to study–test cycles. Each study phase was followed immediately by a test phase; the task instructions were identical for faces in one study–test cycle and reversed between study and test phase for faces in the other study–test cycle. In addition, we removed the distracter task from the experiment, which reduces the lag between study and test exposure of faces and eliminates the disguising effect of the distracter phase on the link between study and test phases.

Materials and methods Experiment 3 was identical to Experiment 2 with the following exceptions.

Participants Forty-three adults took part in the experiment. The data from three participants were discarded because the overall accuracy was below 60% (chance performance is 50%); the mean age of the remaining 40 participants (25 females, 3 left-handed) was 21 years (range 18–37). Stimuli The stimulus set was enlarged to 208 grey-scale facial images of celebrities by incorporating four additional stimuli of similar properties.

Procedure The experiment consisted of an initial practice plus two study–test cycles. In study phases, 52 faces were presented in semi-random order three times. In test phases, 104 faces were presented in random order; half of them were repeated from the preceding study phase as primed faces, the other half were not presented in the experiment before and served as unprimed faces. For each participant, the faces were randomly split into four sets of 52 faces for the four conditions (unprimed identical, unprimed reversed, primed identical, primed reversed) with the constraint that each set contained 13 faces of each category of male actor, male non-actor, female actor, and female non-actor.

Data analyses Priming in accuracy and response times was assessed by comparing accuracy rates and response times of correct trials for the two primed conditions with the respective unprimed conditions of the same study–test cycle. Decision/action binding was assessed by comparing the two priming differences (unprimed–primed).

Results Missing and early responses accounted for 0.4% of trials. The accuracy for primed identical faces was significantly higher than the accuracy for unprimed identical faces, z = 4.54,

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might have been overlooked. Indirect evidence about a possible presence of rapid response learning comes from experiments with study and test phases involving orthogonal conceptual tasks. Here, rapid response learning should be reduced, but not totally absent, because for some of the repeated trials, the decision (e.g., ‘yes’) and action (e.g., ‘left’ button press) in study and test phases are identical (Horner & Henson, 2009; Race et al., 2009). The evidence is mixed, showing reduced orthogonal-task compared to within-task priming with famous faces (Johnston & Barry, 2006) as a possible reflection of rapid response learning, but comparable orthogonal- and within-task priming when tested from faces to names or vice versa, giving no indication of rapid response learning (Burton et al., 1998; Johnston & Barry, 2006). Moreover, priming of person recognition is absent in some tasks like gender judgments, even when stimuli, tasks, classifications, decisions, and actions in study and test phases are the same, and in contrast, present in familiarity tasks even when the study phase involved gender judgments (Ellis et al., 1990). Priming of person recognition can also occur without any response at study (Bruce, Carson, Burton, & Kelly, 1998). In addition, abstract and perceptual contributions to data-driven priming (Boehm et al., 2006) as well as data-driven and conceptually driven priming (Boehm & Sommer, 2012) appear to be independent of each other. Although together these findings lack any strong indication of rapid response learning, it is important to investigate whether response learning is present in person recognition priming directly, in particular because, as we will outline in the following two sections, studies that have shown rapid response learning deviate in certain crucial design aspects. Secondly, priming is a one-shot phenomenon (e.g., Rugg et al., 1998). Priming for faces is robust after a single study presentation and gains only marginally from additional presentations at study (Lander, Bruce, Smith, & Hancock, 2009; Lewis & Ellis, 1999). Rapid response learning, in contrast, can be significant after a single study presentation (Dew & Giovanello, 2010; Dobbins et al., 2004; Horner & Henson, 2008, 2009), but is more robust after three study presentations (Schnyer et al., 2007). Thus, priming of person recognition is usually studied after a single study presentation, whereas prominent rapid response learning investigations argued for three study presentations (Horner & Henson, 2011b; Race et al., 2010; Schnyer et al., 2007; Wig et al., 2009). Consequently, rapid response learning might require multiple study presentations. Thirdly, rapid response learning is often studied with study–test cycles (Horner & Henson, 2009; Schnyer et al., 2007; Wig et al., 2009), which contrasts with a single test phase in priming studies of person recognition (Boehm & Sommer, 2012; Ellis et al., 1990). Study–test cycles usually have a shorter lag, raising the possibility of a shorter life span for rapid response learning compared to network facilitation. Participants also might realize that stimuli in the test phases are repeated from study phases and could therefore engage in episodic memory encoding or retrieval, or adopt different strategies that could modulate the expression of rapid response learning or network facilitation. Fourthly, we investigated the role of binding the classification. Classification binding is a recent component of response learning added to capture small remaining priming effects not explained by decision/action binding (Horner & Henson, 2009). From a theoretical viewpoint, a case can be made that priming of person recognition does not involve a classification because the conceptual tasks used depend on information from semantic memory without any further comparison with a given referent. Therefore, the decision and action can follow directly from the information retrieved from semantic memory without any additional computation involving the referent. For example, when

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participants have to respond with a right-hand key-press to actors, they could retrieve the occupation ‘actor’ upon seeing the face of Tom Hanks and proceed directly to pressing the key with their right hand. On the other hand, it could be argued that the retrieved occupation is matched with the occupation specified in the task instructions, such as ‘actor’, generating a classification available for binding.2 Hence, it is important to investigate classification binding. We addressed these four issues in a series of four experiments with direct measurements of rapid response learning. The first three experiments investigated decision/action binding, but not classification binding. This approach reflects the overwhelming contribution of decision/action binding to priming of object recognition. Classification binding, which leads to only marginal priming of object recognition, is investigated in the fourth experiment. The experiments started from a conventional design used to investigate priming of person recognition, moving in steps to a common design used to investigate rapid response learning in object recognition priming, but with famous faces instead. In Experiment 1, we examined whether decision/action binding has been overlooked in person recognition priming. In Experiment 2, we investigated the importance of multiple study presentations for decision/action binding. In Experiment 3, we addressed the relevance of study–test cycles. Finally, in Experiment 4, we rounded up the investigation of rapid response learning by assessing the role of classification binding. If priming of person recognition is dominated by rapid response learning, throughout our experiments, priming should result exclusively from rapid response learning. If facilitation in perceptual and conceptual networks explains priming of person recognition, we should find no evidence of rapid response learning. Considering the strong support for rapid response learning from object recognition priming and the strong support for network facilitation from person recognition priming, our studies might reveal that one or more of the addressed issues modulate the relative contributions of network facilitation and rapid response learning to priming. These results will help arbitrating between the two opposing views of rapid response learning and network facilitation and foster the development of overarching theories of priming.

EXPERIMENT 1 In Experiment 1, we investigated whether decision/action binding has been overlooked in person recognition priming by directly measuring possible priming contributions from decision/action binding. For this purpose, we employed a conventional conceptual task for famous people based on occupation judgments (Boehm & Sommer, 2012; Johnston & Barry, 2006), with the exception that task instructions of one of the two study phases were reversed compared to the other study and the test phase. We used a design with multiple study and a single test phase, and separated the test phase from study phases by inserting a distracter task, in which participants were asked to discriminate upright from inverted objects. This is sometimes done in priming experiments (Bruce, Carson, Burton, & Ellis, 2000; McNeill, Burton, & Ellis, 2003) in order to conceal the relationship between study and test phases. Compared to the task instructions in the test phase (e.g., ‘actor’), task 2

We thank anonymous reviewers for this suggestion.

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instructions were identical (e.g., ‘actor’) in one study phase and reversed (e.g., ‘non-actor’) in the other study phase. Thus, for half of the repeated faces in the test phase the decisions/actions were identical in study and test phases, and for the other half the decisions/actions were reversed between study and test phases (e.g., from ‘yes’, ‘left’ to ‘no’, ‘right’). In keeping with conventional face priming studies, faces at study were presented once.

Materials and methods Participants From forty-five adults participating in the experiment, the data of five participants were discarded because the overall accuracy was below 60% (chance performance is 50%). The mean age of the remaining 40 participants (26 females) was 23 years (range 19–53). All participants had normal or corrected-to-normal vision and were right-handed by self-report. The study was approved by the local ethics committee, and all participants gave written informed consent.

Stimuli The stimulus set consisted of 204 grey-scale facial images of celebrities. Additional 20 pictures of celebrities, not used in the experiment, were used as practice stimuli. Half of the celebrities were males; half of the male and female celebrities were actors and the other half were non-actors. An additional 150 colour pictures of common objects, transposed on a white background, were used for the distracter phase; half of the objects were presented upright and the other half were presented upside-down. Among these pictures, 10 objects were randomly selected for practice with the distracter task; the remaining 140 objects were used for the experimental distracter task.

Procedure At the beginning of the experiment, participants received written instructions about the tasks and practiced the occupation (‘actor’, ‘non-actor’) and distracter tasks in three short runs with 10 stimuli each. The experiment proper consisted of two study phases, followed by the distracter task and the test phase. One of the study phases used the task instruction identical to that of the test phase; the other study phase used the reversed task instruction. The order of the two study phases was counterbalanced across participants. In addition, half of the participants performed ‘actor’ judgments in the test phase, while the other half performed ‘non-actor’ judgments at test, resulting in four counterbalances. The task instructions (‘Is the celebrity an actor/actress?’; ‘Is the celebrity a non-actor/non-actress?’) were displayed at the beginning of each phase. Task instructions for the distracter phase were for half the participants ‘Is the object correctly orientated?’ and for the other half ‘Is the object not correctly orientated?’. For each participant, the faces were randomly split into three sets of 68 faces for the three conditions (unprimed, primed identical, primed reversed) with the constraint that each set contained 17 faces for each category: male actor, male non-actor, female actor, and female non-actor. In each study phase, 68 faces were presented once in

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random order. In the distracter phase, 140 pictures of object were displayed in random order. In the final test phase, all 204 faces were presented in random order, with 68 faces in each of the three conditions: primed identical (repeated from the study phase with the identical task instruction), primed reversed (repeated from the study phase with the reversed task instruction), and unprimed (not presented in the experiment before). Faces were presented at a size of 8.6 9 11.6 deg (width 9 height) for 600 ms, separated by a fixation cross for 2,400 ms in study and for 1,900 ms in test phases. Object pictures were presented at a size of up to 8.6 9 8.6 deg (width 9 height) for 600 ms and separated by a black fixation cross on white background for 2,400 ms. Participants pressed the F and J keys of a computer keyboard with their left and right index fingers for ‘Yes’ and ‘No’ answers, respectively. Instructions emphasized both speed and accuracy.

Data analyses Only data from the test phases are reported. Trials were considered correct when the correct response occurred between 200 ms after face onset and before the next face presentation.3 Accuracy was analysed with Wilcoxon-signed-rank tests because the data did not show a normal distribution. Response times for unprimed and primed faces were analysed from correct trials only. Paired-samples two-tailed t-tests were used for priming and rapid response learning comparisons. Priming was assessed by comparing accuracy rates and response times for the two primed conditions with the unprimed condition; decision/action binding was assessed by comparing accuracy rates and response times between the two primed conditions. The significance level was a = .05 for all comparisons. The effect of the order of study phases (identical first and reversed second vs. reversed first and identical second) on the magnitude of decision/action binding was analysed with an independent-samples two-tailed t-test.

Results Missing and early responses accounted for 0.4% of trials. The accuracies for primed identical and primed reversed faces were significantly higher than the accuracy for unprimed faces, zs ≥ 3.61, ps ≤ .001 (Table 1). The larger accuracy gain of 0.8% for primed identical compared to primed reversed faces was not significant, z = 1.30, p = .194. Priming resulted in significant shorter response times for both primed identical, t (39) = 10.82, p < .001 and primed reversed faces, t(39) = 10.89, p < .001 (see Figure 1). Response times between primed identical and primed reversed faces did not differ significantly (M = 7 ms, SE = 8), t(39) = 0.85, p = .401, indicating the lack of significant decision/action binding (see Figure 2). Decision/action binding did not depend on the order of study phases, t(38) = 1.31, p = .199, and it was not significant for any order of study phases, ts(19) ≤ 1.41, ps ≥ .175.

3 A common practice in studies on rapid response learning is the exclusion of trials in test phases when a corresponding response in study phases was incorrect in order to exclude the effect of wrong response bindings. When we analyse the present data that way, the overall pattern of response time effects does not change.

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Table 1. Accuracy in the experiments across conditions Classification Decision/action Experiment 1 Unprimed Primed Experiment 2 Unprimed Primed Experiment 3 Unprimed Primed Experiment 4 Unprimed Primed

Same Identical

Orthogonal Reversed

Identical

Reversed

81.2 (1.3) 87.5 (1.1)

79.8 (1.5) 75.6 (1.6)

80.2 (1.4) 85.2 (1.1)

84.4 (1.1) 72.9 (1.6)

79.0 (1.5)

77.9 (1.3)

74.0 (1.8) 83.0 (1.3)

75.1 (1.4) 79.9 (1.7)

81.2 (1.1) 87.3 (0.9)

80.8 (1.2) 82.1 (1.1)

Note. Accuracy (and standard error) shown in %.

Figure 1. Response times in Experiment 1 as a function of priming condition. Error bars represent standard errors.

Discussion The results show clear priming effects for both primed identical and reversed faces. The magnitude of these priming effects did not differ, however, indicating that after a single study presentation decision/action binding does not significantly contribute to person recognition priming. These findings show that indeed decision/action binding as possible priming source has not been overlooked in person recognition priming. In Experiment 1, faces at study were presented once. As discussed in the introduction, a single study presentation is common in most priming studies of person recognition as well as in other stimulus domains, but it deviates from multiple study presentations commonly used in object priming studies that showed rapid response learning. Therefore, in Experiment 2, we investigated whether multiple study presentations will induce decision/action binding.

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Figure 2. Priming effects in Experiments 1–4 as a function of priming condition. Error bars represent standard errors.

EXPERIMENT 2 In Experiment 2, we tested decision/action binding for person recognition priming in the same design used in Experiment 1 with an occupation judgment task and two study phases, followed by an object-orientation distracter task and a single test phase. Again, the task instructions were identical for one of the study and the test phase and reversed for the other study phase. Because rapid response learning is usually measured after multiple study presentation, faces in study phases were presented three times.

Materials and methods Experiment 2 was identical to Experiment 1 with the following exceptions.

Participants From forty-seven adults participating in the experiment, the data of seven participants were discarded because the overall accuracy was below 60% (chance performance is 50%) or the wrong task instruction was performed in one of the study phases. The mean age of the remaining 40 participants (21 females, 3 left-handed) was 21 years (range 18–43).

Procedure The procedure was identical to that of Experiment 1, with the exception that faces in study phases were presented three times in semi-random order: the second (third) presentation of a face could start only after all the faces had been presented once (twice), and immediate stimulus repetition was avoided.

Results Missing and early responses accounted for 0.8% of trials. The accuracies for primed identical and primed reversed faces were significantly higher than the accuracy for

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British Journal of Psychology (2014) © 2014 The British Psychological Society www.wileyonlinelibrary.com

Dissociation of rapid response learning and facilitation in perceptual and conceptual networks of person recognition Christian Valt1, Christoph Klein1,2 and Stephan G. Boehm1* 1

Wolfson Centre for Clinical and Cognitive Neuroscience, School of Psychology, Bangor University, Bangor, UK 2 Department of Child and Adolescent Psychiatry, Psychotherapy and Psychosomatics, University of Freiburg, Germany Repetition priming is a prominent example of non-declarative memory, and it increases the accuracy and speed of responses to repeatedly processed stimuli. Major long-hold memory theories posit that repetition priming results from facilitation within perceptual and conceptual networks for stimulus recognition and categorization. Stimuli can also be bound to particular responses, and it has recently been suggested that this rapid response learning, not network facilitation, provides a sound theory of priming of object recognition. Here, we addressed the relevance of network facilitation and rapid response learning for priming of person recognition with a view to advance general theories of priming. In four experiments, participants performed conceptual decisions like occupation or nationality judgments for famous faces. The magnitude of rapid response learning varied across experiments, and rapid response learning co-occurred and interacted with facilitation in perceptual and conceptual networks. These findings indicate that rapid response learning and facilitation in perceptual and conceptual networks are complementary rather than competing theories of priming. Thus, future memory theories need to incorporate both rapid response learning and network facilitation as individual facets of priming.

Repetition priming is a prominent example of non-declarative memory; like all forms of non-declarative memory, it does not rely on the integrity of the medial temporal lobe (Squire & Zola, 1996) and is, accordingly, preserved in amnesia (Graf, Squire, & Mandler, 1984). Repetition priming is mainly demonstrated by faster and more accurate responses when information is processed repeatedly (Richardson-Klavehn & Bjork, 1988; Roediger & McDermott, 1993). At present, there are two contrasting theoretical views about the mechanisms underlying repetition priming. Most memory theories assume that priming is the result of facilitation in perceptual and conceptual networks (Bruce & Young, 1986, 2012; Burton, 1998; Humphreys, Lamonte, & Lloyd-Jones, 1995; Morton, 1969; Moscovitch, 1992; Richardson-Klavehn & Bjork, 1988; Roediger & McDermott, 1993; Squire, 2004; Tulving & Schacter, 1990). Alternatively, theories of rapid response learning argue that priming results from bindings between stimuli and responses (Horner & Henson, 2008; Schacter, Dobbins, & Schnyer, 2004). In the present paper, we

*Correspondence should be addressed to Stephan G. Boehm, Wales Institute of Cognitive Neuroscience, School of Psychology, Bangor University, Brigantia Building, Penrallt Road, Bangor LL57 2AS, UK (email: [email protected]). DOI:10.1111/bjop.12095

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EXPERIMENT 3 In Experiment 3, we tested decision/action binding in person recognition priming in an occupation judgment task and, in contrast to Experiments 1 and 2, changed from a single test phase to study–test cycles. Each study phase was followed immediately by a test phase; the task instructions were identical for faces in one study–test cycle and reversed between study and test phase for faces in the other study–test cycle. In addition, we removed the distracter task from the experiment, which reduces the lag between study and test exposure of faces and eliminates the disguising effect of the distracter phase on the link between study and test phases.

Materials and methods Experiment 3 was identical to Experiment 2 with the following exceptions.

Participants Forty-three adults took part in the experiment. The data from three participants were discarded because the overall accuracy was below 60% (chance performance is 50%); the mean age of the remaining 40 participants (25 females, 3 left-handed) was 21 years (range 18–37). Stimuli The stimulus set was enlarged to 208 grey-scale facial images of celebrities by incorporating four additional stimuli of similar properties.

Procedure The experiment consisted of an initial practice plus two study–test cycles. In study phases, 52 faces were presented in semi-random order three times. In test phases, 104 faces were presented in random order; half of them were repeated from the preceding study phase as primed faces, the other half were not presented in the experiment before and served as unprimed faces. For each participant, the faces were randomly split into four sets of 52 faces for the four conditions (unprimed identical, unprimed reversed, primed identical, primed reversed) with the constraint that each set contained 13 faces of each category of male actor, male non-actor, female actor, and female non-actor.

Data analyses Priming in accuracy and response times was assessed by comparing accuracy rates and response times of correct trials for the two primed conditions with the respective unprimed conditions of the same study–test cycle. Decision/action binding was assessed by comparing the two priming differences (unprimed–primed).

Results Missing and early responses accounted for 0.4% of trials. The accuracy for primed identical faces was significantly higher than the accuracy for unprimed identical faces, z = 4.54,

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Figure 4. Response times in Experiment 3 as a function of priming condition. Error bars represent standard errors.

p < .001 (Table 1). The accuracy for primed reversed faces again was significantly higher than the accuracy for unprimed reversed faces, z = 3.27, p = .01. Priming resulted in a larger accuracy gain of 4.2% for identical compared to reversed faces, z = 2.12, p = .034. Priming resulted in significant shorter response times for both primed identical, t (39) = 12.08, p < .001, and primed reversed faces, t(39) = 10.25, p < .001 (see Figure 4). Priming was significantly larger for identical than reversed faces (M = 33 ms, SE = 14), t(39) = 2.37, p = .023, indicating decision/action binding (Figure 2).

Discussion The results again show that decision/action binding was present. Although the experimental setup was closely matched to object recognition priming studies that have shown a dominance of decision/action binding by employing multiple study presentations and study–test cycles, decision/action binding still does not dominate priming of person recognition. This leaves the classification as remaining issue, which is investigated in Experiment 4.

EXPERIMENT 4 In Experiment 4, we investigated classification binding of person recognition. In experiments using the shoebox task, classification binding is investigated by changing the referent against which the size of the object is compared. The critical comparison takes place between objects primed with identical classifications for both referents versus objects primed with different classifications for the two referents, while keeping decisions and actions either identical or reversed. This approach cannot be taken with more conventional tasks that do not require a referent, for example, tasks using manmade/natural judgments for objects or occupation judgements for people. Here, classification binding might be investigated by employing orthogonal-task, such as nationality and occupation judgments. Priming from an orthogonal-task eliminates classification binding, whereas priming within the same task

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will conserve it. A drawback of this approach is that because the primed semantic-memory information changes with tasks, this also might disrupt conceptually driven priming. The empirical evidence about such orthogonal-task conceptually driven priming is mixed with reports of preserved (Burton et al., 1998; Johnston & Barry, 2006) and interrupted priming (Johnston & Barry, 2006). The experiment was similar in design to Experiment 3, but instead employed three study–test cycles. Task instruction in test phases remained the same within participants (e.g., ‘singer?’) while the task instructions in study phases varied across study–tests cycles and were, compared to the test phase, identical (‘singer?’), reversed (actor/actress?’), or orthogonal (‘American?’). Note that in the test phase of the orthogonal cycle, half of the repeated stimuli required identical decisions and actions compared to the study phase and half required reversed decisions and actions.

Materials and methods Experiment 4 was identical to Experiment 3 with the following exceptions.

Participants One hundred young British adults took part in the experiment. Data of four participants were discarded because the wrong task instruction was performed in one of the study or test phases. The mean age of the remaining 96 participants (76 females, 8 left-handed) was 20 years (range 18–42).

Stimuli A total of 204 greyscale pictures of British and American celebrities comparable to those in Experiments 1–3 were used in the experiment with 51 (30 males) faces in each of the categories: British singers, American singers, British actors/actresses, and American actors/actresses. An additional set of 36 similar faces was used for practice runs.

Procedure Before the experiment, participants had four practice runs (nine stimuli each), one for each task instruction. The main experiment consisted of three consecutive study–test cycles, one with identical, one with reversed and one with orthogonal-task instructions in study phases compared to the instructions in the test phases (see Figure 5). Half of the participants performed occupation judgments at test and the other half nationality judgments at test. For occupation judgements, the task instruction at test was ‘singer?’ for half of the participants and ‘actor/actress?’ for the other half; similarly, for nationality judgements the task instruction at test was ‘American?’ for half of the participants and ‘British?’ for the other half. Moreover, the task instruction at study in the orthogonal-task and the order of the cycles were counterbalanced across participants. For each participant, the faces were pseudo-randomly divided into six sets of 34 faces (20 males), of which three sets were used as primed stimuli and three sets as unprimed stimuli (one primed and one unprimed set per cycle). Each set had a similar proportion of occupations and nationalities so that in all phases half of the stimuli required a positive response.

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Figure 5. Schematic experimental setup of the different cycles in Experiment 4.

Data analyses Primed faces in the orthogonal-task were divided according to whether decisions and actions required at study and test were identical or reversed. Although unprimed faces were not presented at study, for comparison purposes they were nevertheless similarly divided according to the response that would have been given had the faces been presented at study.

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Mean accuracy (which did not deviate significantly from a normal distribution) and mean response times were analysed with 2 9 2 9 2 ANOVAs with the factors priming (primed, unprimed), decision/action (identical, reversed), and classification (same, orthogonal). Only main effects and interactions of direct relevance for priming and rapid response learning will be reported. Priming would be indicated by a main effect of priming. Decision/action binding would be indicated by an interaction between decision/ action and priming, and classification binding by an interaction between classification and priming. Planned comparisons for accuracy and response times were made with one-sample two-tailed t-tests.

Results Missing and early responses accounted for 0.6% of trials. Priming increased overall accuracy as indicated by the significant main effect of priming in the ANOVA, F(1, 95) = 16.26, p < .001 (Table 1). Decision/action binding increased accuracy as indicated in the ANOVA by the significant interaction between the factors decision/action and priming, F(1, 95) = 44.26, p < .001. Classification binding increased accuracy as indicated in the ANOVA by the significant interaction between the factors classification and priming, F(1, 95) = 4.90, p = .029. Accuracy changes from priming varied with decision/action binding and classification binding as indicated in the ANOVA by the significant 3-way interaction, F(1, 95) = 6.94, p = .010. Planned contrasts revealed that with the same classification, priming increased accuracy for identical decisions/actions, t (95) = 7.26, p < .001, but did not significantly alter accuracy for reversed decisions/ actions, t(95) = 1.40, p = .166. With the orthogonal classification, priming increased accuracy for identical decisions/actions, t(95) = 5.47, p < .001, but reduced accuracy for reversed decisions/actions, t(95) = 2.69, p = .009. Priming resulted in shorter response times as indicated by the significant main effect of priming in the ANOVA, F(1, 95) = 372.97, p < 001 (see Figure 6). Decision/action binding resulted in shorter response times as indicated in the ANOVA by the significant interaction between the factors decision/action and priming, F(1, 95) = 24.71, p < .001 (see Figure 2). Classification binding resulted in shorter response times as

Figure 6. Response times in Experiment 4 as a function of priming condition. Error bars represent standard errors.

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indicated in the ANOVA by the significant interaction between the factors classification and priming, F(1, 95) = 44.79, p < .001 (see Figure 2). Priming in response times did not significantly vary with decision/action and classification binding as indicated in the ANOVA by the non-significant 3-way interaction, F(1, 95) = 3.46, p = .066. Planned contrasts revealed shorter response times in all four conditions: ts(95) > 7.25, ps < .001.

Discussion The response time results show greater priming with the same compared to the orthogonal classification. This priming may result from either classification binding or conceptually driven priming. Importantly, priming was still significant in the orthogonaltask when all positive contributions from rapid response learning, be it from the classification, the decision or the action, were eliminated. This priming reflects data-driven and, perhaps, conceptually driven priming and it provides clear evidence for network facilitation, strongly suggesting that network facilitation and rapid response learning co-occur. Priming with the orthogonal classification resulted in higher accuracy for identical, but lower accuracy for reversed decisions and actions, while, in contrast, in both cases shorter response times occurred. Similar results have been observed in a perceptual task (Soldan et al., 2012). These results suggest that under particular circumstances response time priming may be dominated by network facilitation, resulting in response times benefits irrespective of, although modulated by, decision/action binding, whereas accuracy priming may reflect largely decision/action binding with accuracy benefits for identical and accuracy costs for reversed decisions/actions.2 The accuracy costs with the orthogonal classification for priming of reversed decisions/actions indicate an interaction between the responses derived from network processing and derived from rapid response learning. Whereas the perceptual and conceptual networks deliver the correct response, the incorrect response from rapid response learning interferes with correctly responding, increasing the error rate and possibly slowing down the response.

GENERAL DISCUSSION The present experiments investigated the relevance of rapid response learning for priming of person recognition with a view to the larger theoretical implications of rapid response learning for repetition priming theories. Rapid response learning has never been investigated in priming of person recognition before and the corresponding theories explain priming by network facilitation. Our results indicate that when rapid response learning in person recognition priming is investigated directly, it can be present, depending on the experimental setup, and co-occur with network facilitation. The vast majority of studies of rapid response learning have investigated decision/ action binding. Decision/action binding contributes the major amount of object recognition priming in conceptual tasks, compared to the small size of priming from classification binding (Horner & Henson, 2009). Although here a small, yet not significant, amount of decision/action binding was present in Experiment 1, decision/action binding reached significance only after multiple study presentations (for further support, see

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Appendix S1). This suggests that in conventional priming experiments of person recognition with a single test phase and single study presentation, decisions/action binding may play only a marginal role. The role of classification binding in person recognition priming is somewhat less clear. In object recognition priming experiments, classification binding contributes only a small fraction of the overall priming magnitude (see Experiment 7 in Horner & Henson, 2009). Classification binding was investigated in Experiment 4 with an orthogonal-task, and the results are compatible with the idea of classification binding. On the other hand, the orthogonal-task might have disrupted conceptually driven priming. The empirical evidence about such orthogonal-task conceptually driven priming is mixed with reports of preserved (Burton et al., 1998; Johnston & Barry, 2006) and interrupted priming (Johnston & Barry, 2006). Moreover, it is unclear whether tasks such as occupation and nationality judgements do involve a classification at all. Thus, the role of classification binding for priming of person recognition warrants further investigation. This uncertainty about the role of classification binding does not detract from the main result of the present investigation concerning the co-occurrence of rapid response learning and network facilitation. In Experiment 4, where all considered issues have been included, strong network facilitation occurred after all three response bindings have been eliminated, reflecting, at least, data-driven priming. The present findings thus contrast markedly to priming of object recognition with conceptual tasks (Dobbins et al., 2004; Horner & Henson, 2009, 2011b; Race et al., 2010), which reflects (almost) exclusively rapid response learning (Horner & Henson, 2009). Hence, the one crucial factor that determines the dominance of rapid response learning appears to be the stimulus domain. At present, it is not clear why facilitation in perceptual and conceptual networks should play a much larger role in priming of person recognition than object recognition. One possible reason for this stark contrast could be that person recognition depends on individuation within the same category, in contrast to object recognition, which is based on object categories, such as chair or house. Alternatively, because objects are more action-oriented, objects may be more likely bound to responses than persons.4 The response interference in Experiment 4, indicated by reduced accuracy with the orthogonal classification and reversed decisions/actions, sheds interesting light on the possible ways rapid response learning leads to faster responses, on the magnitude of priming from network facilitation with orthogonal classifications or reversed decisions and actions, and on the interpretation of associated reduced activity in neural networks. This interference suggests that the response from network processing and from rapid response learning interact, resulting in benefits if they are congruent and costs if they are not, arguing against a horse-race model or faster responses from rapid response learning (Logan, 1990). Importantly, these costs suggest that the residual priming with orthogonal classifications or reversed decisions/actions may underestimate the actual amount of priming from network facilitation. Moreover, it has been suggested, based on reduced activity found in perceptual and conceptual network for repeated stimuli (Schacter & Buckner, 1998), that rapid response learning leads to partially bypassing these networks (Horner & Henson, 2008; Schacter et al., 2004). Although our results cannot rule out that 4 Another crucial difference between (our) person and object priming studies might be the somewhat low accuracy in the present experiments. A re-analysis of the data using only the best stimuli resulted in increased accuracy levels comparable to object priming studies and confirmed the overall priming effects in response times (see Appendix S2).

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this might be the case for priming of object recognition, the present response interference indicates that perceptual and conceptual networks of person recognition are not bypassed. Reverting back to the larger implications of the present findings for memory theories, the co-occurrence of network facilitation and rapid response learning suggests that rapid response learning (Horner & Henson, 2008; Schacter et al., 2004) and facilitation in perceptual and conceptual networks (Bruce & Young, 1986, 2012; Burton, 1998; Humphreys et al., 1995; Morton, 1969; Moscovitch, 1992; Richardson-Klavehn & Bjork, 1988; Roediger & McDermott, 1993; Squire, 2004; Tulving & Schacter, 1990) are two complementary, rather than competing theories of repetition priming. Future memory models must be adapted to incorporate these two facets of repetition priming in a hybrid model (see Horner & Henson, 2009). Conclusions Rapid response learning and facilitation in perceptual and conceptual networks are complementary rather than competing theories of priming. Thus, future memory theories need to incorporate both rapid response learning and facilitation in perceptual and conceptual networks as complementary sources of priming.

Acknowledgements This research was supported by funding from the School of Psychology, Bangor University, the Medical School, Cardiff University, by a 125th anniversary PhD bursary from Bangor University, and an RCUK Academic Fellowship to SGB. We are grateful to Mari Jones for assistance with data collection, and to Benjamin R. Dering for feedback on an earlier draft of this paper and for proofreading.

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Supporting Information The following supporting information may be found in the online edition of the article: Appendix S1. Single face presentation in study-test cycles. Appendix S2. Re-analysis of Experiments 1-3 at higher accuracy levels.

Dissociation of rapid response learning and facilitation in perceptual and conceptual networks of person recognition.

Repetition priming is a prominent example of non-declarative memory, and it increases the accuracy and speed of responses to repeatedly processed stim...
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