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Learning and Motivation 37 (2006) 230–246 www.elsevier.com/locate/l&m Second-order conditioning of human causal learning 夽 Elvia Jara a, Javier Vila a,¤, Antonio Maldonado b a Universidad Nacional Autónoma de México, F.E.S. Iztacala, México b University of Granada, Spain Received 11 March 2005; received in revised form 30 November 2005 Available online 17 February 2006 Abstract This article provides the Wrst demonstration of a reliable second-order conditioning (SOC) eVect in human causal learning tasks. It demonstrates the human ability to infer relationships between a cause and an eVect that were never paired together during training. Experiments 1a and 1b showed a clear and reliable SOC eVect, while Experiments 2a and 2b demonstrated that Wrst-order extinction did not aVect SOC. These results were similar to those found in animal and human conditioning and suggested that a similar associative mechanism could explain these eVects. However, they can also be used to look into the underlying causal mental model people build and store while they are learning this task. From a cognitive view, overall results suggest that an independent rather than a chain causal mental model is stored after second-order learning in human causal tasks. © 2005 Elsevier Inc. All rights reserved. Keywords: Pavlovian conditioning; Second-order conditioning; Extinction; Causal learning Second-order conditioning (SOC) has been a widely studied topic of associative learning, because it allows the study of an emergent relationship between two events that were never presented together (Pavlov, 1927; Rizley & Rescorla, 1972). In the SOC procedure, there are three phases. In the Wrst training phase, a conditioned stimulus 夽 This research was supported by founds from DGAPA-UNAM (IN302605) and CONACYT (34843-H) and by BSO2003-03723 Spanish research project, granted by MCYT (Ministerio de Ciencia y Tecnología). We gratefully acknowledge the helpful comments of Bruce Overmier. * Corresponding author. E-mail address: [email protected] (J. Vila). 0023-9690/$ - see front matter © 2005 Elsevier Inc. All rights reserved. doi:10.1016/j.lmot.2005.12.001 E. Jara et al. / Learning and Motivation 37 (2006) 230–246 231 (CS1) is followed by an unconditioned stimulus (US). In the second phase, a secondorder conditioned stimulus (CS2) is presented along with CS1. Finally, in the test phase, CS2 is presented alone to the subjects while their responses are recorded. The results have commonly shown that CS2 evokes the same conditioned response (CR) as does CS1, even though CS2 was never directly paired with the US (Pavlov, 1927). SOC has been studied in animals employing diVerent types of US and responses. For instance, it has been demonstrated in aversive conditioning (Bevins, Delzer, & Bardo, 1996; Cheatle & Rudy, 1979; Rescorla, 1976), in autoshaping of keypecking (Rashotte, GriYn, & Sisk, 1977; Rescorla & Cunningham, 1979) and in sexual behavior (Crawford & Domjan, 1995). Also, there have been demonstrations in humans using non-verbal stimuli in aversive electrodermal conditioning (Davey & McKenna, 1983; Davey & Arulampalan, 1982). Many theoretical models have been oVered, in an attempt to explain SOC; most of them are derived from associative learning theories. These models can be grouped into four diVerent types based on the diVerent possible kinds of associations that could be formed during SOC, as shown in Fig. 1 (Barnet, Cole, & Miller, 1997). The most traditional model, which is based upon the S-R model, as well as the Rescorla and Wagner (1972) model (Rashotte, 1981; Rizley & Rescorla, 1972), proposed the acquisition of a direct connection between CS2 and CR reinforced by the presence of CS1, due to temporal contiguity between them during second-order training. A second type of model, the CS2–CS1–US– CR model, suggests the existence of a chain of associative representations in such a way that CS2 will evoke a representation of CS1 which will evoke the US representation that in turn elicits CR (Hall, 1996; Mackintosh, 1974). A third type of model assumes the establishment of a direct association between CS2 and the US representation, because during the second phase the US representation could be activated in the presence of CS2 by CS1; due to this association, CS2 can evoke the CR (Barnet & Miller, 1996; Miller & Barnet, 1993). The fourth type of model considers the existence of an association between CS2 and CS1 where CR emission is only due to the CS1 representation evoked by CS2 (Miller & Escobar, 2002). (1) CS2 CS1 CR (2) CS2 CS1 US CR (3) CS2 CS1 US CR (4) CS2 CS1 US CR Fig. 1. DiVerent hypotheses about the associations established during SOC, derived from associative learning theories. Letters represent: CS1, Wrst-order stimulus; CS2, second-order stimulus; US, unconditioned stimulus; CR, conditioned response. 232 E. Jara et al. / Learning and Motivation 37 (2006) 230–246 To evaluate the nature of the learned associations during SOC, several post-conditioning revaluation techniques have been used, such as CS1 extinction (Rescorla, 1980; Rizley & Rescorla, 1972), US devaluation (Crawford & Domjan, 1995; Holland & Rescorla, 1975), as well as instructions and habituation in humans (Davey & McKenna, 1983). Among these, CS Wrst-order extinction had been the most used one, in which, after SOC had been established, CS1 is presented without being followed by the US during a third phase. The most frequent results, both in animals (Fujii, 1981; Rescorla, 1980; Rizley & Rescorla, 1972) and humans (Davey & McKenna, 1983; Davey & Arulampalan, 1982), have been that the CR evoked by CS2 persists more or less at the same magnitude, in spite of the fact that the CR evoked by CS1 has been extinguished. The Wnding that CS2 still evokes CR even after extinction of CS1 appears to suggest that the associations and the contents of learning during a second-order conditioning could be diVerent from those of Wrst-order learning. Although Wrst-order learning is aVected by CS1 extinction, by US devaluation, by US habituation or instructions, SOC is not subsequently inXuenced by any of these factors (Davey, 1983; Holland & Rescorla, 1975; Rizley & Rescorla, 1972). These results suggest that the types of associations formed during second-order conditioning are not mediated by CS1. However, the debate still continues whether associations are between CS2 and CR or are mediated by the US representation. Recent research into human learning using causal learning tasks could clarify this issue. The interest in studying associative learning phenomena in humans led Dickinson, Shanks, and Evenden (1984) to suggest that causal or contingency learning tasks could be considered similar to animal conditioning procedures. Contingency learning tasks consist in presenting a series of trials in which a cue (CS) and an outcome (US) may or may not be presented together. After several trials, the participants are asked to give a judgment about the degree of association between cues and outcomes (Dickinson et al., 1984). In a causal learning task, causes are considered formally equivalent to CSs and, in consequence, the eVects equivalent to USs in such a way that causal judgment can reXect the degree of association between them. Contingency, as well as causal learning tasks, have allowed the replication of diverse eVects of associative learning in humans, which were originally studied in animals, enlarging the Weld of knowledge on explanatory models of learning (Shanks, 1995). Although second-order conditioning has not yet been directly studied in humans using causal learning tasks, Perales, Catena, and Maldonado (2004) have recently shown how people are able to infer a relationship between two diVerent cues (C1, C2), even when causes and eVects were never presented together, based on two diVerent and independent experiences where each cue was paired with the same consequence. They also showed that the most frequent assumption during the causal inference process was an independent causal mental model. In their experiment, when the two cues were causes, (C1, C2) almost all participants used a common eVect (E) mental model in which each cause could inXuence independently the same eVect, i.e., a C1–E and C2–E mental model. In second-order causal learning, however, the Wrst phase C1 produces a given eVect and during the second phase another cause, C2, produces C1 as an eVect, this arrangement could give rise to an inference process in which people learn that the second-order cause is the cause of the Wrst-order one, which in turn produces the common eVect (i.e., C2–C1–E). In this type of procedure, the normative causal mental model should be a chained one, being more compatible with a CS2–CS1–US associative model. This chained mental model could easily explain second-order conditioning in learning tasks as a process of transitive E. Jara et al. / Learning and Motivation 37 (2006) 230–246 233 inference, but it has been shown that after extinction of the Wrst component in animal and human second-order conditioning tasks, CS2 still elicits CR. Such results argue against a chained causal mental model because a post-conditioning extinction procedure, in which people learn that the C1 does not produce the eVect, should also produce a disruption of the causal relationships between C1 and the same eVect. Therefore, the use of such a procedure might reveal whether the results are or not the same in a causal learning and a conditioning task and might also clarify whether a chained mental model underlies causal attributions during SOC. In summary, Experiments 1a and 1b aimed to show the existence of SOC in humans using causal learning tasks, in a similar way to that in which SOC was shown in classical conditioning studies. The experimental task consisted of a series of trials presented to the participants. In the Wrst phase, a cause C1 was followed by an eVect E1. In the second phase, a diVerent cause C2 produced the cause C1. In the testing phase, the participants were asked to judge to what degree C2 will cause the appearance of the eVect E1. The inference of a causal relationship between a second-order cause (C2) and an eVect (E) that were never presented together would also bear out those associative models proposing a direct connection between causes (CS) and eVects (US), independently of any CR elicitation that could also be inXuenced by other factors, such as context, memory, and emotion. The second and more important objective was to evaluate the associative structure of SOC in causal learning tasks by the subsequent extinction of the Wrst-order relationship (C1–E1). Consequently, Experiments 2a and 2b used the same experimental task, but after SOC training the participants experienced a third phase of extinction where C1 no longer produced E1. Then, they were asked about C2–E1 to Wnd out if SOC was or was not extinguished as well. The use of this extinction technique had two goals. First of all, the results will show whether or not the same eVects happen in conditioning and causal learning tasks and, second, the results can permit us to clarify whether or not a chained causal mental model underlies SOC in human learning tasks. Experiment 1a The main objective of Experiment 1a was to demonstrate a second-order conditioning phenomenon within human causal learning. To this end, a similar experimental design as the one used by Rizley and Rescorla (1972) in animals was employed. In a Wctitious situation, all participants learned during the Wrst phase that a disease (C1) caused the appearance of a substance in the blood (E1) in several patients. In the second phase, a chemical substance (C2) consumed by the patients caused the disease presented in the Wrst phase (C1). At the end of both training phases, the participants were asked to make a causal judgment about the relationship between the second-order cause (C2, the chemical substance) and the eVect (E1, appearance of a substance in the blood). As a control, another cause (C3) and a second eVect (E2) were also presented during the Wrst phase and another new cause (C4) and C3 were presented during the second-order phase. For half of the participants, C3 and the eVect (E2) were paired during the Wrst phase, but C3 and C4 were never paired during the second phase. For the other half of the participants, C3 and E2 were not paired during the Wrst phase, while C4 and C3 were presented together during the second phase. In both cases, participants should infer the existence of causal relationships between the second-order cause (C2) and the Wrst eVect (E1), while they should infer the non-existence of causal relationships between the other cause (C4) and the second eVect (E2). 234 E. Jara et al. / Learning and Motivation 37 (2006) 230–246 Method Participants The participants were 24 undergraduate students of psychology between 18- and 25years-old who volunteered to take part in the experiment as part of their course requirements. The participants were randomly divided into two groups (12 participants in each condition). Apparatus and stimuli An IBM compatible computer and a projector were used in the experiment. The Super Lab Pro v 2.1 software for Windows (Cedrus Co.) was used to show the cues. Cues C1 and C3 were names of two diVerent diseases (Midiasis or Xeritis), the eVects E1 and E2 were blood substances (Alpha or Beta), and Wnally C2 and C4 were chemical substances (Neocina or Licaina). All of them were used in this experiment as stimuli, and they were counterbalanced across the participants. Procedure The experiment was conducted in a dark room, with half of the participants tested at each of two sessions (because of counterbalance). They were seated in a chair facing a screen, to which slides of the stimuli were to be projected. Paper and pencil were provided to register their prediction and their judgment. The experiment was conducted in Spanish; instructions translated into English were as follows: Two new diVerent diseases were found in ‘Gersy Laboratories’ in The Netherlands, and these diseases are known as Midiasis and Xeritis. These diseases are transmitted quickly. You should identify whether these diseases are related to the substances Alpha and Beta that are found in the blood of patients. Also, you will see that patients ate sausages which contain the substances Neocina and Licaina, and you should identify if theses chemical substances, used in food preservation, are related to these diseases. By pressing keys, you will Wnd out whether they have some relation. At the beginning, your answer will be uncertain, but little by little you will become an expert. If you detect some changes in the experiment you should continue. Remember that you can take as much time as you need to complete the experiment. Press any key to continue. After the participants read the instructions, the training phase began. The training screen was present as follows (relations could change because of the counterbalance). At the top of the screen was centered the laboratory name “Gersy Laboratories,” in pink capital letters. Below the laboratory name, and depending on the counterbalancing, a sentence such as the following appeared in purple color: “The patient has Midiasis. Does this disease cause the appearance of the blood substance Alpha?” Under the question, the name of the two blood substances appeared in blue color each one associated with a key number, Alpha with the number three and Beta with the number Wve. On each trial, the participants had to give a prediction; for instance, if participants considered that Midiasis would cause Alpha, they had to write the number three on a sheet of paper; on the contrary, if they considered that the disease would cause Beta, they had to write the number Wve. Once the prediction was made, the participants were given the correct feedback (1200 ms duration). E. Jara et al. / Learning and Motivation 37 (2006) 230–246 235 Experiment 1a employed both between and within design variables. Table 1 summarizes the design of this experiment. For all participants, the experiment had two diVerent phases of training; each phase consisted of two blocks of 12 diVerent trials, Paired (P) or nonpaired (N) presented randomly and intermixed. In each one of the two groups (PP/PN and PP/NP), the causes C1 and C2 were always followed by their eVects (E1 or C1) in 12 trials during each phase (the SOC or paired PP condition). In the non-paired PN or NP second condition, the causes (C3 and C4) were followed (P) or not (N) by their eVects (E2 or C3) in another 12 trials during the Wrst and the second phases. After both training phases, all participants were asked for causal judgments about the relationship between both the second-order paired cause and its possible eVect (C2–E1) and the non-paired cause and its possible eVect (C4–E2). The participants were asked to make causal judgments according to the following instructions, “To what degree do you believe Neocina causes the blood substance Alpha to appear? You must use a 0–100 scale, where 0 represents that it never produced the substance and 100 that it always produces the substance.” Below the instructions, the stimulus name was written on the left and a little square was drawn on the right; Wnally, a numerical scale from 0 to 100 appeared with marks at 0, 25, 50, 75, and 100%. The participants had to give their judgments on a sheet of paper. Results and discussion The upper in Fig. 2 panel shows the mean judgments for the SOC test phase. Participants estimated a higher relationship in SOC (C2–E1) type of causes than in the nonpaired (C4–E2) ones. A 2 £ 2 analysis of variance (ANOVA), with the Wrst factor being the two Groups (PP/NP vs. PP/PN) and the second factor the two Types of Cause (C2 and C4) was performed on the participants’ judgments. The results revealed only a main eVect of on Type of Cause, F (1, 22) D 11.43, p < .01, MSE D 1714.67, because in both groups, causal judgments about the relationships between the second-order cause and the eVect, C2–E1 Table 1 Experimental designs Experiment Group (n D 12) Phase 1 1a PP/NP C1–E1 C3–No E2 C1–E1 C3–E2 PP/PN 1b PP/NP PP/PN C1–E1 C3–No E2 C1–E1 C3–E2 2a C1–E1 C3–E2 2b C1–E1 C3–E2 Test Phase 2 Test Phase 3 Test C2–C1 C4–C3 C2–C1 C4–No C3 C1–E1? C3–E2? C1–E1? C3–E2? C2–C1 C4–C3 C2–C1 C4–No C3 C2–E1? C4–E2? C2–E1? C4–E2? C2–C1? C4–C3? C2–C1? C4–C3? C2–C1 C4–C3 C1–E1? C3–E2? C2–C1 C4–C3 SOC Test C2–E1? C4–E2? C2–E1? C4–E2? C1–No E1 C5–No E2 C2–C1? C4–C3? C1–No E1 C5–No E2 C2–E1? C4–E2? C1–E1? C5–E2? C2–E1? C4–E2? Note. PP represents Paired type of causes. NP and PN represent Non-paired. The Wrst letter represent Wrst phase, and the second letter represents the second phase, with the slash dividing the type of causes. The rest of the letters represents the diVerent stimuli presented counterbalanced along training. C1, C3, and C5: diseases Midiasis, Xeritis or Zatuba. E1 and E2: blood substances Alpha or Beta. C2 and C4: chemical substances Neocina or Licaina. 236 E. Jara et al. / Learning and Motivation 37 (2006) 230–246 100 EXPERIMENT 1a 80 60 40 Mean Judgment 20 0 100 EXPERIMENT 1b 80 60 40 20 C2-E1 C4-E2 0 PP / NP GROUP PP / PN GROUP Fig. 2. Mean judgments for the SOC test. Open bars represent SOC Type of Cause, and hatched bars represent Non-paired Type of Cause. Error bars denote standard errors of the mean. (the paired PP conditions, i.e., SOC) were signiWcantly higher than those about C4–E2 (the non-paired NP or PN conditions). These results are the Wrst demonstration of SOC in human causal learning tasks, and they also show that SOC in causal learning tasks, as well as in conditioning tasks, depends on paired presentations in both training phases. These Wndings revealed a SOC eVect similar to that commonly observed in animals using appetitive and aversive conditioning (Crawford & Domjan, 1995, Rizley & Rescorla, 1972; Rescorla, 1980) as well as in humans using electrodermal associative conditioning (Davey & McKenna, 1983; Davey & Arulampalan, 1982). The results showed that people are able to infer a causal relationship between a second-order cause (C2) and an eVect (E1) that were never presented together. This inference comes from independent experiences, Wrst, from whether the eVect was related to a primary cause (C1) and, second, whether this cause was also an “eVect” of the second- E. Jara et al. / Learning and Motivation 37 (2006) 230–246 237 order cause (C2). The control for the type of causes showed the need for a positive correlation between elements in both phases to get such a second-order eVect, just as is the case in associative conditioning procedures. The next experiment aimed to replicate these Wndings while providing evidence for the existence of causal learning during each phase. Experiment 1b Although Experiment 1a showed SOC occurs in causal learning tasks, it had only a Wnal test at the end of all training phases. This fact allows for the possibility that the results were not based on learned relations in the training phases. To prove that phases 1 and 2 did produce causal learning, the Experiment 1b objective was to replicate the SOC eVect, while investigating whether the participants accurately detected the contingent relationships established among causes and eVects in each experimental phase. In this experiment, participants were asked to make a causal judgment not only at the end of training, but also after each experimental training phase. Method Participants Twenty-four undergraduate students of psychology participated in this experiment for course credits. Their ages varied between 18 and 24, and they were randomly divided into two groups (12 participants in each condition). Procedure The procedure and design were identical to those described in Experiment 1a, the only diVerence being that the participants were requested to estimate the relationships between causes and eVects at the end of each training phase. Finally, to assess the SOC association, the participants were asked to judge the relationships between C2–E1 and C4–E2 as in the previous experiment. Results and discussion Table 2 shows the mean judgment for each relationship after each experimental phase. Participants were able to accurately detect both the relationship between causes and their contingent eVects and the lack of relationships between non-paired causes and eVects. Table 2 Mean judgment after each experimental phase for Experiments 1b and 2b Experiment Group Type of Cause First phase Second phase 1b PP/NP SOC UNP SOC UNP 91.66 4.16 86.25 83.75 97.91 95.83 84.16 20.83 EXT SOC 89.58 89.58 91.25 87.91 PP/PN 2b Third phase SOC Test 79.16 18.33 72.91 33.33 4.16 8.3 66.16 67.91 Note. Types of causes are represented by: SOC Second-order, UNP Non-paired, and EXT Extinction. Types of causes in Experiment 1b are represented by PP: Paired and NP: Non-paired. 238 E. Jara et al. / Learning and Motivation 37 (2006) 230–246 Higher causal judgments were obtained when causes were followed by their eVects than when they were not. The 2 £ 2 £ 2 ANOVA (Groups £ Type of Cause £ Training phase) performed upon causal judgments yielded a signiWcant interaction between the three factors, F (1, 22) D 53.12, p < .01, MSE D 456.4, as well as the interaction between Type of Cause £ Training phase, F (1, 22) D 28.30, p < .01, MSE D 456.4. A posteriori analyses revealed that between-judgments diVerences were only signiWcant when the causes were not followed by their eVects, as in the Wrst phase of the PP/NP group (paired C1–E1 versus non-paired C3–E2) and the second phase of the PP/PN group (paired C2–C1 vs nonpaired C4–C3). These results always showed accurate judgments, higher when the causes were followed by their eVects and lower when the causes were not followed by them. The lower panel of Fig. 2 shows the mean judgment for C2–E1 and C4–E2 relationships. The 2 £ 2 ANOVA (Groups x Type of Cause) showed only a main eVect for Type of Cause, F (1, 22) D 13.99, p D .01, MSE D 2161.7, as in Experiment 1. Participants’ causal judgments were higher about SOC or paired type of causes (C2) than about non-paired ones (C4). These results replicated the novel Wnding of SOC in Experiment 1a. In general, the results of Experiments 1a and 1b have shown that the procedure was appropriate to study SOC in causal learning tasks and that the development of SOC depends on the relationships between causes and eVects in both training phases. These results are similar to those found in animal conditioning. Although Experiments 1a and 1b results were expected, they are important because they are the Wrst demonstrations of SOC in human causal learning tasks. Moreover, they also showed that participants were able to infer the absence of relationships between a secondorder cause and the Wrst-order eVect, when causes and eVects were not paired in either of the two phases. Experiments 2a and 2b extend our analysis of SOC in causal learning by showing the eVect of the Wrst-order extinction relationships upon SOC. Experiment 2a The previous experiments identiWed necessary and suYcient conditions for secondorder conditioning (SOC) in a causal learning task. However, they left open the question of the nature of the learned associations underlying SOC. The main goal of Experiments 2a and 2b was to evaluate, Wrst, the nature of the second-order association in human causal learning using post-conditioning extinction and, second, the generality of such eVects by showing whether SOC in causal learning is aVected by the same variables that aVect associative conditioning tasks. The experimental design was similar to the previous ones, but with a third phase that included extinguishing the Wrst-order relationship learned during the Wrst phase. The common Wnding in animal and human learning associative conditioning tasks has been that SOC is not inXuenced by extinction of Wrst-order conditioning (Davey & McKenna, 1983; Davey, 1987; Holland & Rescorla, 1975; Rescorla, 1980; Rizley & Rescorla, 1972). The conditioned response continues to be elicited by the second-order CS after extinction of the Wrst-order relationship, indicating that the SOC response is not mediated by some association between CS2 and CS1. These results suggested the formation of a direct link between CS2 and CR (Rizley & Rescorla, 1972), or possibly between CS2 and US (see Barnet, Arnold, & Miller, 1991; Miller & Barnet, 1993). The use of a causal learning task could clarify this issue, while, at the same time, the eVect of extinction upon E. Jara et al. / Learning and Motivation 37 (2006) 230–246 239 second-order causal learning could also reveal the causal mental model people build when they learn such causal relationships. In previous experiments, Perales et al. (2004) employed a mediated learning procedure, where two cues were subsequently linked to the same eVect in two diVerent phases. After the training, they found that participants were able to establish an emergent relationship between the two cues that were never presented together, while, at the same time, they showed that participants used an independent cause mental model rather than a chained cause mental model. Assuming that during a second-order causal learning task, people form an association between “causes and eVects” (i.e., the CS and the US in a conditioning procedure), the normative and rational causal model should be chained (C2–C1–E), as they have learned that the Wrst-order cause (C1) produces the eVect (E) and, subsequently, that the second-order cause (C2) produces the Wrst one (C1). Accordingly, the extinction of the relationship between the Wrst-order cause and the eVect should aVect the perceived relationship between the second-order cause and the same eVect, if participants have formed such a chained mental model, i.e., if there is a mediation of the Wrst cause (the CS1 in conditioning procedures). However, if the extinction of the relationship between the Wrst-order cause and the eVect did not have any inXuence on the second-order relationship, this would imply the formation of a diVerent mental model in which each cause could be directly and independently linked with the same eVect, as seems to happen in animal and human associative conditioning procedures. Method Participants Twelve undergraduate students of psychology participated in this experiment for course credits. Their ages varied from 19 to 24. Procedure The experimental design is summarized in Table 1. The presentation of trials on the screen was identical to that described in previous experiments. This experiment had two diVerent types of causes, SOC and EXT, and they only diVered during the third extinction phase. First and second-order training phases were similar to those described in previous experiments with the diVerence that in both phases the contingency established among the causes and the eVects was always 1.0. The third phase consisted in two intermixed counterbalanced blocks of 12 trials. In the EXT type of cause condition, the Wrstorder cause (C1) was presented without being followed by the eVect (E1). Depending on the counterbalancing, the information given in these trials was for example: “The patient has Midiasis.” Under this sentence, the next question that appeared was “Does this disease cause the appearance of the substance Alpha in the blood? Again, the participants had to give an answer indicating “Yes” with the number three and,“No”with the number Wve. After their response, feedback was presented in the sentence “Midiasis does not cause Alpha” (1200 ms duration). In the SOC type of cause condition, the only diVerence was that a novel cause, for example Zatuba (C5) and a second eVect (Beta, E2) were presented. After the participant responded, the feedback indicated that “Zatuba does not cause Beta.” In the test phase, the participants were required to judge the relationships between the second-order causes and eVects, C2–E1 and C4–E2, using a scale from 0 to 100. 240 E. Jara et al. / Learning and Motivation 37 (2006) 230–246 Results and discussion The left panel of Fig. 3 displays the mean judgment given during the test phase. No diVerences appear between the SOC and EXT types of causes, showing that the extinction of C1–E1 relationships did not aVect the second-order causal judgments. A one-way ANOVA performed on the participant judgments did not reveal any signiWcant eVect for Type of cause F (1, 11) D .09, p D .759, MSE D 187.0. These results suggest that although the C1–E1 relationships are a necessary condition to form a SOC association, once learned, the C2–E1 association seems independent of the C1–E1 association. Revaluation of C1–E1 association had no eVect on responding to C2. These results replicated those obtained in animal conditioning experiments (Fujii, 1981; Holland & Rescorla, 1975; Rizley & Rescorla, 1972) and those observed in electrodermal associative conditioning with human participants (Davey & McKenna, 1983). However, before further discussing this issue, it seems important to be sure that the participants had actually extinguished the Wrst-order relationship. Experiment 2b In Experiment 2b, the participants were required to estimate the causal relationships after each training phase, to determine whether they in fact learned the contingencies presented in each phase. In the previous Experiment 2a, the Wrst-order relationship was extinguished after second-order learning. The results showed that such extinction did not have any eVect on the second-order causal learning, as was also found in animal conditioning (Rizley & Rescorla, 1972) and human aversive conditioning (Davey & McKenna, 1983). Experiment 2b attempted to replicate the same eVect and, in addition, assessed whether the participants had learned the relations presented in each phase, especially in extinction. 100 Mean Judgment 80 60 40 20 C2-E1 C4-E2 0 EXPERIMENT 2a EXPERIMENT 2b Fig. 3. Mean judgments for SOC test. Open bars represent Extinction Type of Cause, and hatched bars represent SOC Type of Cause. Error bars denote standard errors of the mean. E. Jara et al. / Learning and Motivation 37 (2006) 230–246 241 Consequently, the participants were asked to estimate the causal relationships between each cause and its eVect after each experimental phase. Method Participants Twelve undergraduate students of psychology, 19- to 24-year-old, participated in this experiment for course credits. Procedure The procedure and experimental design were identical to those one used in Experiment 2a and are summarized in Table 1; the only diVerence was that the participants were requested to estimate the relationships between causes and eVects at the end of each training phase. Finally, at the end of training phases, the participants had to give a judgment about C2–E1 and C4–E2 relationships to show the level of SOC. Results and discussion The participants accurately detected the contingencies between causes and eVects programmed in each experimental phase, as can be observed in Table 2. Participant causal judgments were similarly higher after the Wrst and second-order phases and lower after the extinction phase. These impressions were corroborated by a 3 £ 2 (Phases £ Type of Cause) ANOVA which yielded a signiWcant eVect of Phases, F (2, 22) D 70.96, p < .001, MSE D 782.83. LSD Post Hoc tests did not reveal signiWcant diVerences between the Wrst and the second phase judgments (p > .05), but diVerences were signiWcant between each of these phases and the third phase (p < .05). This pattern of results is important because it permits us to conWrm the extinction of the Wrst-order relationship. The right panel of Fig. 3 displays the mean judgment given on the SOC test and reveals that the judgments remained high despite extinction of the Wrst-order relationship. A oneway ANOVA, F (1, 11) D .02, p D .88, MSE D 46.5, indicated that there was no diVerence between SOC and EXT type of causes during the test phase. However, a second 2 £ 2 ANOVA was carried out to compare Type of Cause during the third phase and the Wnal test. This analysis revealed diVerences between phases but not between type of causes, F (1, 33) D 39.60, p D .01, MSE D 584.86. This last result further demonstrated that SOC was not aVected by extinction of the Wrst-order relationship, because judgments about the second-order causes were signiWcantly diVerent from judgments about the Wrst-order extinguished causes. In general, the results of Experiment 2b showed a similar eVect to the one found in Experiment 2a, because no diVerences appeared between SOC and EXT conditions. In summary, the main Wnding of both Experiment 2a and 2b was that extinction of the Wrst-order relationship did not aVect the second-order relationship. This Wnding is similar to those found in conditioning experiments carried out with animals and humans (Davey & McKenna, 1983). Overall results suggest that the structure which mediates the secondorder learning is based on an independent causal relationship between C2 and the EVect without any mediation by C1. This conclusion is parallel to the original Wnding of Rizley and Rescorla (1972) with the classical conditioning paradigm. 242 E. Jara et al. / Learning and Motivation 37 (2006) 230–246 General discussion The primary novel Wnding of this research was a reliable second-order conditioning eVect in human causal learning tasks in two independent experiments. It is important because it suggests people are able to infer a causal relationship between causes and eVects that were never experienced together. Experiments 1a and 1b also showed that the main determinant of SOC is the prior correlation between cause and eVect. The additional and most important Wnding of Experiments 2a and 2b was that extinction of the Wrst-order causal relationship (C1–E) did not inXuence the acquired second-order relationship (C2– E). This last result suggests that causal learning and conditioning tasks probably are mediated, at least in part, by similar learning mechanisms (Dickinson et al., 1984). A theoretical beneWt of Experiments 2a and 2b was the information about association types that are learned during SOC. At the same time, the results could clarify the type of causal mental model participants may be using to establish the emergent relationship between C2 and the EVect. Until now, the only explanations of SOC have been derived from associative views based upon the four types of possible learned associations (Fig. 1) during second-order conditioning. The usual Wnding had been that extinction of Wrst-order conditioning did not reduce the conditioned response to the second-order stimulus (CS2), suggesting the absence of any CS1 mediation in the elicitation of the second-order response. However, there still remained two possible associations responsible for the eVect. There could be a direct connection between CS2 and the conditioned response itself, as suggested by S-R theory (cf. Rizley & Rescorla, 1972), or the response could be dependent on a direct link between CS2 and the US, as suggested by more recent theories (Barnet et al., 1991). The results obtained using causal learning tasks suggested that there could be such a direct link between the CS (the cause) and US (the eVect) because the participants were able to infer the existence of a causal relationship between them, without any conditioned response, unless such causal judgment is considered a conditioned response. In addition, these results seem compatible with those found in animal and human sensory-preconditioning experiments, where if CS2 and CS1 are paired in a Wrst training phase and, subsequently, CS1 is paired with the US, an emergent CS2–CR association is formed even though CS2 and the US were never presented together (Brogden, 1939). When using such a sensory-preconditioning procedure in humans, White and Davey (1989) found that they still showed a strong relationship between CS2 and CR, even after post-conditioning inXation of US. These results bear out Rizley and Rescorla’s (1972) proposals that SOC and sensory-preconditioning may be products of diVerent underlying associative structures. Therefore, whether the type of associations formed during sensory-preconditioning and SOC are the same and similarly aVected by extinction of C1–US, remains an open question for future research into human causal learning. To summarize, the overall results showed that second-order causal learning, as well as the perception of a relationship between C2 and E1, is dependent on the strength of the contingent acquisition relationship between the Wrst-order cause and the eVect (C1–E1). Accordingly, the successive cue-outcome pairings progressively strengthen the connection between the mental representation of the cue and the outcome giving rise to the CR (Allan, 1993). In the absence of such contingent pairings, as happened in the non-paired conditions, SOC does not develop. But, once the second-order association is established, then it seems no longer dependent on the Wrst-order association. This view is entirely consistent E. Jara et al. / Learning and Motivation 37 (2006) 230–246 243 with those associative theories that assume a direct CS2–US link formed during SOC, giving rise to the conditioned response without the need of any CS1 mediation (Barnet et al., 1991). However, the results might also be explained from more recent causal learning theories, as the result of a process of causal inference (Johnson-Laird, 1983). From this perspective, the Wnding that SOC happens in human causal learning is not at all surprising. If participants are taught by means of instructions or by direct experience that a cause (C1) produces an eVect (E1) and that another cause (C2) produces this Wrst cause, it seems very easy to infer the existence of a causal relationship between all components as a causal chain, C2–C1–E1. In agreement with these experimental results on human reasoning (Goldvarg & Johnson-Laird, 2001), our results could be seen as a product of simple deductive reasoning in the form of “axioms or inference rules,” such as “If C1 causes E1, and C2 causes C1, then C2 causes E1.” Moreover, participants were also able to infer the absence of relationships when one of the conditions was preventative, as also happened in human reasoning experiments (Goldvarg & Johnson-Laird, 2001) and as Experiment 1b convincingly showed. When learning was that “C3 causes E2, and C4 prevents C3” or “C3 prevents E2, and C4 causes C3,” then participants logically inferred that C4 did not cause E2. By contrast, the lack of inXuence of extinction of the Wrst-order relationships upon the second-order causal relationship was an unexpected and important result. It was unexpected, because it is normatively inaccurate. According to logical inference rules and the results obtained in human deductive reasoning (Goldvarg & Johnson-Laird, 2001), “if C2 causes C1, and C1 prevents E1, then C2 should also prevent E1.” However, Experiments 2a and 2b showed that participants were unable to make such a logical inference, suggesting that once the causal link between C2 and the eVect is formed, this new knowledge seems to be rather independent of the previous knowledge about the relationship between C1 and the same eVect. These results are important, because they could allow a reinterpretation of the nature of the causal relationship learned during second-order conditioning tasks and the type of causal mental models naïve participants built during such a learning experience. Recent developments in the Weld of human causal learning (Cheng, 1997; Waldmann & Hagmayer, 2001) emphasize that causal relationships can not be reduced to covariation between the events or to mere associations, because they are a product of top–down higher cognitive processes. In this way, people are able to accurately detect true causal relationships and diVerentiate them from spurious correlations. Accordingly, it is assumed that causal relationships are learned within a “causal mental model” by encoding assumptions about the causal status of the events (causes and eVects, as shown by the eVects of causal directionality in cue competition, see Waldmann, 2000, 2001), or in mediated learning eVects, see also Perales et al. (2004) and about hypothetical direct and indirect causal relationships. Non-observed relationships between a cause and an eVect can then be inferred from such mental models built either by the integration of the information provided via instructions or by the knowledge acquired during the task. Assuming that a causal mental model is a working memory representation of real (or imaginary) related events (JohnsonLaird, 1983), its structure being isomorphic to that provided by the situation, at least two diVerent causal models could be built during SOC training. The most obvious one should be a chained cause mental model in which C2 produce C1 which in turn cause E1 (i.e., C2– C1–E1), allowing the inference that C2 also causes E1. If this was the model built by the participants, we should expect that extinction of the Wrst link, i.e., C1 no longer produces E1, should lead to disruption of the causal link between C2 and the same eVect. The 244 E. Jara et al. / Learning and Motivation 37 (2006) 230–246 absence of inXuence of this new knowledge upon the relationship between C2 and E1 suggests that participants build or store a diVerent causal model during such training. In accordance with related research on mediated learning and emergent causal relationships between events never experienced together (Perales et al., 2004), there are at least two diVerent possibilities. The Wrst one proposed by Perales et al. (2004) is that once the causal relationship between C2 and the eVect is formed, both C1–E1 and C2–E1 relationships are stored as an independent causal mental model. It seems that once the between-events relationship is stored, the causal chain is no longer necessary, as the data of Experiment 1b and 2b convincingly show. It is also important to acknowledge that it is not necessary to express a causal judgment of each relationship, as Experiment 2a clearly suggests; participants were aware of all the relationships, as Experiment 2b demonstrated. A second possibility, however, also reviewed in Perales et al. (2004) and proposed by an anonymous reviewer, could be that participants adopted a “common-cause mental model” in which they saw C2 as a common cause of C1 and E1. In other words, they stored a “causal mental model” in which they saw C1 and E1 as independent eVects of C2. The results of experiment 2b are not clearly compatible with this view, because participants had indicated that they considered C1 a cause of E1 rather than an independent eVect of C2. The exact nature of the mental model people build and store during SOC remains a question for future research. According to the actual results, it is proposed that during the second-order conditioning task naïve people built an “independent causal mental model” of the situation. According to this model, each cause can produce the eVect in an independent way, explaining the emergence of the second-order relationship between the second-order cause and the eVect, as well as the absence of inXuence of extinction of the Wrst causal component upon the second one. Whether other factors, such as instructions, additivity or cause directionality, could also inXuence extinction and the building and storing of the underlying causal mental model in human second-order causal learning, as has happened with other well established associative eVects like cue competition (Beckers, De Houwer, Pineño, & Miller, 2005; Waldmann, 2000, 2001), remains an open question for further research. In summary, this work provides the Wrst demonstration of a reliable second-order conditioning eVect in human causal learning and shows that this second-order learning is independent of the degree of relationships between the Wrst-order cause and the eVect. These Wndings match Wndings from animal and human conditioning tasks and emphasize that similar learning mechanisms are probably at work. From an associative point of view, the learning mechanism in causal learning tasks would be the formation of a direct association between the mental representations of CS2 (Cause) and the US (EVect), giving rise to the conditioned response. From a cognitive causal theory point of view, this association reXects the inference of a direct causal relationship between C2 and the EVect, as a product of an underlying stored independent cause mental model. Moreover, the results of this research bear out previous Wndings using a mediated learning task (Perales et al., 2004) and agree with those causal theories (Waldmann & Martignon, 1998) which assume that in a causal scenario where diVerent causes can produce the same eVect, people use by default an independent model rather than a cause chained one, even though the latter would be more rational. This independent causal mental model means that the perceived causal power of each cause to inXuence the eVect seems to be independent of the causal power of the other causes. It is important to acknowledge that an independent and additive causal model seems to be a necessary condition to Wnd and explain others eVects, similarly obtained both E. Jara et al. / Learning and Motivation 37 (2006) 230–246 245 in causal and conditioning tasks, such as blocking (Beckers et al., 2005). 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