Associationism and cognition: Human contingency learning at 25

Release from response interference in color-word contingency learning

In identifying the print colors of words when some combinations of color and word occur more frequently than others, people quickly show evidence of learning these associations. This contingency learning effect is evident in faster and more accurate responses to high-contingency combinations than to low-contingency combinations. Across four experiments, we systematically varied the number of response-irrelevant word stimuli connected to response-relevant colors. In each experiment, one group experienced the typical contingency learning paradigm with three colors linked to three words; other groups saw more words (six or twelve) linked to the same three colors. All four experiments disconfirmed a central prediction derived from the Parallel Episodic Processing (PEP 2.0) model (Schmidt et al., 2016)-that the magnitude of the contingency learning effect should remain stable as more words are added to the response-irrelevant dimension, as long as the color-word contingency ratios are maintained. Responses to high-contingency items did slow down numerically as the number of words increased between groups, consistent with the prediction from PEP 2.0, but these changes were unreliable. Inconsistent with PEP 2.0, however, overall response time did not slow down and responses to low-contingency items actually sped up as the number of words increased across groups. These findings suggest that the PEP 2.0 model should be modified to incorporate response interference caused by high-probability associations when responding to low-probability combinations.

Associative interference and nonreinforcement in human contingency learning

This article reports three experiments comparing the impact on contingency assessment of associative cue interference (proactive, interspersed, and retroactive) and nonreinforcement (latent inhibition, partial reinforcement, and extinction). All three experiments used variants of the rapid trial streaming procedure developed by Allan and collaborators. Participants were exposed to stimulus streams and then asked how likely it was for a target cue to be accompanied (Experiment 1) or to be followed (Experiments 2 and 3) by a target outcome. Experiments 1 and 2 looked at interference and found that when the objective target cue-outcome contingency is positive, interspersed interference is more effective than either proactive or retroactive interference. Experiment 2 additionally showed that this conclusion was a function of the target cue-outcome contingency: when the number of cue-outcome pairings was low, retroactive interference was more efficient than interspersed interference. Experiment 3 examined nonreinforcement and found that the efficacies of latent inhibition, partial reinforcement, and extinction are also a function of the target cue-outcome contingency, but the pattern differed greatly from what was observed in Experiment 2. When the number of cue-outcome pairings was high, there was no difference between latent inhibition, partial reinforcement, and extinction. When the number of cue-outcome pairings was low, extinction did not lower the contingency judgement, whereas latent inhibition and partial reinforcement did.

Language models and psychological sciences

Large language models (LLMs) are demonstrating impressive performance on many reasoning and problem-solving tasks from cognitive psychology. When tested, their accuracy is often on par with average neurotypical adults, challenging long-standing critiques of associative models. Here we analyse recent findings at the intersection of LLMs and cognitive science. Here we discuss how modern LLMs resurrect associationist principles, with abilities like long-distance associations enabling complex reasoning. While limitations remain in areas like causal cognition and planning, phenomena like emergence suggest room for growth. Providing examples and increasing the dimensions of the network are methods that further improve LLM abilities, mirroring facilitation effects in human cognition. Analysis of LLMs errors provides insight into human cognitive biases. Overall, we argue LLMs represent a promising development for cognitive modelling, enabling new explorations of the mechanisms underlying intelligence and reasoning from an associationist point of view. Carefully evaluating LLMs with the tools of cognitive psychology will further understand the building blocks of the human mind.

Scarcity affects cognitive biases: The case of the illusion of causality

Previous research indicates that economic scarcity affects people's judgments, decisions, and cognition in a variety of contexts, and with various consequences. We hypothesized that scarcity could sometimes reduce cognitive biases. Specifically, it could reduce the causal illusion, a cognitive bias that is at the heart of superstitions and irrational thoughts, and consists of believing that two events are causally connected when they are not. In three experiments, participants played the role of doctors deciding whether to administer a drug to a series of patients. The drug was ineffective, because the percentage of patients recovering was identical regardless of whether they took the drug. We manipulated the budget available to buy the drugs, tough all participants had enough for all their patients. Even so, participants in the scarce group reduced the use of the drug and showed a lower causal illusion than participants in the wealthy group. Experiments 2 and 3 added a phase in which the budget changed. Participants who transitioned from scarcity to wealth exhibited a reduced use of resources and a lower causal illusion, whereas participants transitioning from wealth to scarcity were unaffected by their previous history.

Articulation dynamics and evaluative conditioning: investigating the boundary conditions, mental representation, and origin of the in-out effect

People prefer linguistic stimuli with an inward (e.g. BODIKA) over those with an outward articulation dynamic (e.g. KODIBA), a phenomenon known as the articulatory in-out effect. Despite its robustness across languages and contexts, the phenomenon is still poorly understood. To learn more about the effect's boundary conditions, mental representation, and origin, we crossed the in-out effect with evaluative conditioning research. In five experiments (N = 713, three experiments pre-registered), we systematically paired words containing inward versus outward dynamics with pictures of negative versus positive valence. Although this evaluative conditioning procedure reversed the preference for inward over outward words, this was the case only for words with the same consonant sequences as the conditioned words. For words with inward/outward dynamics but different consonant sequences than the conditioned ones, a regular in-out effect emerged. Also, no preference reversal at all emerged for the conditioned consonant sequences when the contingency between single consonants at specific positions and positive/negative valence was zero. Implications of these findings for the in-out effect and evaluative conditioning are discussed.

EXPRESS: Determinants of Extinction in a Streamed Trial Procedure

The strength of an association between a cue and its outcome is influenced by both the probability of the outcome given the cue and the probability of the outcome in the absence of the cue. Once an association has been formed, extinction is the procedure for reducing responding indicative of the association by repeated presentation of the cue without the outcome. The present experiments tested whether cumulative frequency and/or cumulative duration of these events affects associative extinction in a streamed trial extinction procedure with human participants. Experiment 1 assessed the effects of parametric manipulations of the frequency and duration of either the cue by itself or cue-outcome coabsence. In Experiment 1, participants proved relatively insensitive to manipulation of the event's duration. In contrast, judgments of the association by participants decreased when the frequency of cue-alone events was increased, even when the durations of those events were decreased so that cumulative exposure to the cue was equated. No effect of either the duration or the frequency of cue-outcome coabsence was observed. Experiment 2 demonstrated that the effect of cue-alone (i.e., extinction trial) frequency generalizes across a wide range of parameters for initial acquisition achieved by cue-outcome pairings. Experiment 3 tested for an interaction between event duration during initial learning and event duration during extinction. Collectively, these results indicate that the cumulative frequency, and not the cumulative duration, of extinction trials as well as the duration of the cue-outcome coabsences between extinction trials controls the effectiveness of an extinction procedure.

Pseudoscientific Health Beliefs and the Perceived Frequency of Causal Relationships

Beliefs about cause and effect, including health beliefs, are thought to be related to the frequency of the target outcome (e.g., health recovery) occurring when the putative cause is present and when it is absent (treatment administered vs. no treatment); this is known as contingency learning. However, it is unclear whether unvalidated health beliefs, where there is no evidence of cause–effect contingency, are also influenced by the subjective perception of a meaningful contingency between events. In a survey, respondents were asked to judge a range of health beliefs and estimate the probability of the target outcome occurring with and without the putative cause present. Overall, we found evidence that causal beliefs are related to perceived cause–effect contingency. Interestingly, beliefs that were not predicted by perceived contingency were meaningfully related to scores on the paranormal belief scale. These findings suggest heterogeneity in pseudoscientific health beliefs and the need to tailor intervention strategies according to underlying causes.

All I Need Is Two: The Clinical Potential of Adding Evaluative Pairing Procedures to Cognitive Behavioral Therapy for Changing Self-, Body- and Food-Related Evaluations

Pairing procedures are among the most frequently used paradigms for modifying evaluations of target stimuli related to oneself, an object, or a specific situation due to their repeated pairing with evaluative sources, such as positive or negative images or words. Because altered patterns of evaluations can be linked to the emergence and maintenance of disordered cognitions and behaviors, it has been suggested that pairing procedures may provide a simple yet effective means of complementing more complex intervention approaches, such as cognitive behavioral therapy (CBT). Here, we summarize recent studies that explored the clinical potential of pairing procedures for improving self-esteem, body satisfaction, and food and consumption preferences. While no study has yet combined pairing procedures with CBT, there are several successful examples of pairing procedures in clinically relevant domains and clinical populations. We discuss potential sources of heterogeneity among findings, provide methodological recommendations, and conclude that pairing procedures may bear clinical potential as an add-on to classical psychotherapy.

Controlled or automatic? Influence of congruency proportion and stimulus-onset asynchrony on the brightness-valence and spatial-valence metaphoric congruency effects

Whether a cognitive process is operated automatically or in a controlled manner has been a long-standing question in cognitive psychology. However, this issue has not been investigated in the activation of metaphoric association. A primed word valence judgement task is often used to test the activation of metaphoric association, in which participants first see a prime (bright/dark square or fixation point moving up or down from the centre of the screen) and then make a valence judgement to a target word. Metaphoric congruency effect occurs when participants make faster judgements to the target with valence being matched with the prime (good followed bright/top prime) than being mismatched with the prime (good followed dark/bottom prime). In the present two experiments, we manipulated prime-target stimulus-onset asynchrony (SOA) and proportion of metaphorically congruent trials (congruency proportion) to tease apart the effects of automatic and controlled activation of brightness-valence and spatial-valence metaphoric associations on word valence judgements. Results showed an overall effect of congruency proportion on brightness-valence and spatial-valence metaphoric congruency effect, which was independent of prime-target SOA. The effect was enhanced or reversed when congruency proportion was higher or lower than 0.5, respectively, suggesting that the activation of metaphoric association could be modulated by strategic control. The implications of these findings on the Conceptual Metaphor Theory and semantic priming theories are discussed.

Discovering skill

This paper shows how identical skills can emerge either from instruction or discovery when both result in an understanding of the causal structure of the task domain. The paper focuses on the discovery process, extending the skill acquisition model of Anderson et al. (2019) to address learning by discovery. The discovery process involves exploring the environment and developing associations between discontinuities in the task and events that precede them. The growth of associative strength in ACT-R serves to identify potential causal connections. The model can derive operators from these discovered causal relations just as does with the instructed causal information. Subjects were given a task of learning to play a video game either with a description of the game's causal structure (Instruction) or not (Discovery). The Instruction subjects learned faster, but successful Discovery subjects caught up. After 20 3-minute games the behavior of the successful subjects in the two groups was largely indistinguishable. The play of these Discovery subjects jumped in the same discrete way as did the behavior of simulated subjects in the model. These results show how implicit processes (associative learning, control tuning) and explicit processes (causal inference, planning) can combine to produce human learning in complex environments.

Five paths to personality coherence: Integrative implications of the Knowledge-and-Appraisal Personality Architecture

The study of personality coherence can be grounded in an analysis of personality architecture, that is, the overall structure and dynamics of intra-individual personality systems. A personality architecture can identify, and organize the study of, interrelated phenomena that each are instances of personality coherence. It thereby can provide an integrative framework for understanding relations among distinct lines of research. This thesis is advanced by drawing on the Knowledge-and-Appraisal Personality Architecture, or KAPA model. KAPA model principles distinguish among three classes of social-cognitive knowledge structures: beliefs, goals, and evaluative standards. These distinctions, in turn, provide a foundation for understanding five aspects of personality coherence: 1) Belief-Based Coherence, 2) Goal-Based Coherence, 3) Evaluative Standards-Based Coherence, 4) Intra-Psychic Coherence (that is, coherent functional interrelations among personality systems), and 5) Phenomenological Coherence. Research documenting each of these five paths to personality coherence is reviewed. The paper also reviews the strengths and limitations of 20th-century social-cognitive formulations that provide key foundations for the KAPA model.

Individual differences in the perception of cue-outcome contingencies: A signal detection analysis

In a signal detection theory (SDT) approach to associative learning, one assumes that, when a subject is exposed to a flow of stimuli, an association is created between the internal representations of a cue and of an outcome, allowing the representation of the cue to activate the representation of the outcome. The outcome activation is a random variable drawn from a Gaussian distribution with mean m (sensitivity to the contingency) and standard deviation d (variability in outcome activation). Depending on whether the outcome activation is above or below various decision thresholds, the participant perceives either a negative, a null, or a positive contingency between the cue and the outcome. This study presents a detailed SDT analysis of the performance of four participants on whom data in a contingency assessment task were collected almost daily during several months. Parameters from the SDT model proved relatively stable over time, except if feedback was provided to the subject. In that case, for some participants but not all, the sensitivity increased. The decision criteria were also affected. Some of these changes endured despite the discontinuation of feedback. The variability in outcome activation was not affected by the feedback.

Can We Set Aside Previous Experience in a Familiar Causal Scenario?

Causal and predictive learning research often employs intuitive and familiar hypothetical scenarios to facilitate learning novel relationships. The allergist task, in which participants are asked to diagnose the allergies of a fictitious patient, is one example of this. In such studies, it is common practice to ask participants to ignore their existing knowledge of the scenario and make judgments based only on the relationships presented within the experiment. Causal judgments appear to be sensitive to instructions that modify assumptions about the scenario. However, the extent to which prior knowledge continues to affect competition for associative learning, even after participants are instructed to disregard it, is unknown. To answer this, we created a cue competition design that capitalized on prevailing beliefs about the allergenic properties of various foods. High and low allergenic foods were paired with foods moderately associated with allergy to create two compounds; high + moderate and low + moderate. We expected high allergenic foods to produce greater competition for associative memory than low allergenic foods. High allergenic foods may affect learning either because they generate a strong memory of allergy or because they are more salient in the context of the task. We therefore also manipulated the consistency of the high allergenic cue-outcome relationship with prior beliefs about the nature of the allergies. A high allergenic food that is paired with an inconsistent allergenic outcome should generate more prediction error and thus more competition for learning, than one that is consistent with prior beliefs. Participants were instructed to either use or ignore their knowledge of food allergies to complete the task. We found that while participants were able to set aside their prior knowledge when making causal judgments about the foods in question, associative memory was weaker for the cues paired with highly allergenic foods than cues paired with low allergenic foods regardless of instructions. The consistency manipulation had little effect on this result, suggesting that the effects in associative memory are most likely driven by selective attention to highly allergenic cues. This has implications for theories of causal learning as well as the way causal learning tasks are designed.

The effect of conditioned inhibitors and preexposed cues on the outcome-specific Pavlovian-to-instrumental transfer effect in humans

Using a human Pavlovian-to-instrumental transfer (PIT) task, Alarcón and Bonardi showed that the selective elevation of instrumental responding produced by excitatory transfer cues was reduced when these cues were presented with a conditioned inhibitor (CI), relative to a control cue that was simply preexposed. However, previous research has shown that preexposed cues might also acquire inhibitor-like properties. This study aimed to contrast the inhibitory properties of CIs and preexposed cues, using novel stimuli as controls, in summation and PIT tests. Participants were trained to perform two actions, each reinforced with a distinct outcome (O₁ or O₂). Two images were trained as CIs, each signalling the absence of one of the outcomes, by presenting them with a cue that was otherwise followed by that outcome (e.g., A→O₁, AI→no O₁). In contrast, the preexposed cues were simply presented in the absence of the outcomes. In the summation test, participants rated the likelihood of the outcomes in the presence of two independently trained excitatory cues, each presented with a CI, a preexposed cue, or a novel stimulus. Similarly, in the PIT test, participants performed both actions in the presence and absence of these compounds. In the summation test, the CIs and the preexposed cues reduced participants' expectations of the outcomes more than the novel stimuli. However, in the PIT test, only the CIs reduced the selective elevation of responding produced by the transfer cues. These results might reflect distinct properties of stimuli trained as CIs and those simply preexposed.

A hard to read font reduces the causality bias

Previous studies have demonstrated that fluency affects judgment and decision-making. The purpose of the present research was to investigate the effect of perceptual fluency in a causal learning task that usually induces an illusion of causality in non-contingent conditions. We predicted that a reduction of fluency could improve accuracy in the detection of non-contingency and, therefore, could be used to debias illusory perceptions of causality. Participants were randomly assigned to either an easy-to-read or a hard-to-read condition. Our results showed a strong bias (i.e., overestimation) of causality in those participants who performed the non-contingent task in the easy-to-read font, which replicated the standard causality bias effect. This effect was reduced when the same task was presented in a hard-to-read font. Overall, our results provide evidence for a reduction of the causality bias when presenting the problem in a hard-to-read font. This suggests that perceptual fluency affects causal judgments.

Evaluative Influences of CS-US Pairings Are Non-Reciprocal

Three experiments examined the reciprocity of evaluative effects following CS-US pairing. In all three experiments, CS evaluations were assimilated to the valence of the US they were paired with (i.e., an evaluative conditioning effect), whereas US evaluations became less extreme (i.e., a US devaluation effect). Of importance, however, US devaluation proved to be independent of CS-US pairing. Experiment 1 replicated previous evidence for US devaluation: USs were less intensely evaluated after a conditioning procedure as compared to their normative ratings. Experiment 2 controlled for the effect of CS-US pairing: A US devaluation effect of similar magnitude was observed for USs paired with the CSs or presented alone during the conditioning procedure. Experiment 3 indicated that US habituation drives US devaluation: USs presented and evaluated only once were less devalued than USs paired with CSs or USs presented alone during the conditioning procedure, with the latter two US types not differing from each other. Together, these findings suggest that US devaluation is driven by US habituation rather than by a CS-to-US influence in an associative learning procedure. The theoretical implications of these findings for associative and propositional accounts of evaluative learning are discussed.

Testing the deductive inferential account of blocking in causal learning

The sensitivity of the blocking effect to outcome additivity pretraining has been used to argue that the phenomenon is the result of deductive inference, and to draw general conclusions about the nature of human causal learning. In two experiments, we manipulated participants' assumptions about the additivity of the outcome using pretraining before a typical blocking procedure. Ratings measuring causal judgments, confidence, and expected severity of the outcome were used concurrently to investigate how pretraining affected assumptions of outcome additivity and blocking. In Experiment 1, additive pretraining led to lower causal ratings and higher confidence ratings of the blocked cue, relative to control cues, consistent with the notion that additive pretraining encourages deductive reasoning. However, Experiments 1 and 2 showed that removing additivity assumptions through nonadditive pretraining had no impact on a statistically reliable blocking effect observed in a blocking procedure with no pretraining. We found no evidence that the blocking effect in the absence of pretraining was related to the participants' assumptions about the additivity of the outcome. Although additive pretraining may enhance blocking by encouraging deductive reasoning about the blocked cue, the evidence suggests that blocking in causal learning is not reliant on this reasoning and that humans do not readily engage in deduction merely because they possess the assumptions that permit its use.

How Do Actions Influence Attitudes? An Inferential Account of the Impact of Action Performance on Stimulus Evaluation

Over the past decade, an increasing number of studies have shown that the performance of specific actions (e.g., approach and avoidance) in response to a stimulus can lead to changes in how that stimulus is evaluated. In contrast to the reigning idea that these effects are mediated by the automatic formation and activation of associations in memory, we describe an inferential account that specifies the inferences underlying the effects and how these inferences are formed. We draw on predictive processing theories to explain the basic processes underlying inferential reasoning and their main characteristics. Our inferential account accommodates past findings, is supported by new findings, and leads to novel predictions as well as concrete recommendations for how action performance can be used to influence real-world behavior.

Rule-based processes in generalisation and peak shift in human fear conditioning

Two experiments explored the role of verbalisable rules in generalisation of human differential fear conditioning with electric shock as the aversive stimulus. Two circles of different sizes served as conditioned stimuli (CS+ and CS–), before testing with a range of circle sizes. In Experiment 1, shock expectancy ratings followed a peak-shifted unimodal gradient, with maximum ratings at a test value further along the dimension from CS+ in the opposite direction to CS–. However, differentiable gradients were observed when participants were divided on the basis of the rules they reported using during the task (linear and similarity). Experiment 2 was designed to counter the contradictory feedback arising from extinction testing by removing the shock electrodes during the test phase. A more linear overall gradient was observed, and sub-groups defined by self-reported rules showed distinct gradients that were congruent with their rules. These results indicate that rule-based processes are influential in generalisation of conditioned fear along simple stimulus dimensions, and may help explain generalisation phenomena that have traditionally been attributed to automatic, similarity-based processes.

Relational information moderates approach-avoidance instruction effects on implicit evaluation

Previous research demonstrated that instructions to approach one stimulus and avoid another stimulus can result in a spontaneous or implicit preference for the former stimulus. In the current study, we tested whether the effect of approach-avoidance instructions on implicit evaluation depends on the relational information embedded in these instructions. Participants received instructions that they would move towards a certain non-existing word and move away from another non-existing word (self-agent instructions) or that one non-existing word would move towards them and the other non-existing word would move away from them (stimulus-agent instructions). Results showed that self-agent instructions produced stronger effects than stimulus-agent instructions on implicit evaluations of the non-existing words. These findings support the idea that propositional processes play an important role in effects of approach-avoidance instructions on implicit evaluation and in implicit evaluation in general.

Communicated beliefs about action-outcomes: The role of initial confirmation in the adoption and maintenance of unsupported beliefs

As agents seeking to learn how to successfully navigate their environments, humans can both obtain knowledge through direct experience, and second-hand through communicated beliefs. Questions remain concerning how communicated belief (or instruction) interacts with first-hand evidence integration, and how the former can bias the latter. Previous research has revealed that people are more inclined to seek out confirming evidence when they are motivated to uphold the belief, resulting in confirmation bias. The current research explores whether merely communicated beliefs affect evidence integration over time when it is not of interest to uphold the belief, and all evidence is readily available. In a novel series of on-line experiments, participants chose on each trial which of two options to play for money, being exposed to outcomes of both. Prior to this, they were exposed to favourable communicated beliefs regarding one of two options. Beliefs were either initially supported or undermined by subsequent probabilistic evidence (probabilities reversed halfway through the task, rendering the options equally profitable overall). Results showed that while communicated beliefs predicted initial choices, they only biased subsequent choices when supported by initial evidence in the first phase of the experiment. Findings were replicated across contexts, evidence sequence lengths, and probabilistic distributions. This suggests that merely communicated beliefs can prevail even when not supported by long run evidence, and in the absence of a motivation to uphold them. The implications of the interaction between communicated beliefs and initial evidence for areas including instruction effects, impression formation, and placebo effects are discussed.

Predictions and causal estimations are not supported by the same associative structure

Studies performed by different researchers have shown that judgements about cue–outcome relationships are systematically influenced by the type of question used to request those judgements. It is now recognized that judgements about the strength of the causal link between a cue and an outcome are mostly determined by the cue–outcome contingency, whereas predictions of the outcome are more influenced by the probability of the outcome given the cue. Although these results make clear that those different types of judgement are mediated by some knowledge of the normative differences between causal estimations and outcome predictions, they do not speak to the underlying processes of these effects. The experiment presented here reveals an interaction between the type of question and the order of trials that challenges standard models of causal and predictive learning that are framed exclusively in associative terms or exclusively in higher order reasoning terms. However, this evidence could be easily explained by assuming the combined intervention of both types of process.

Inferences about unobserved causes in human contingency learning

Estimates of the causal efficacy of an event need to take into account the possible presence and influence of other unobserved causes that might have contributed to the occurrence of the effect. Current theoretical approaches deal differently with this problem. Associative theories assume that at least one unobserved cause is always present. In contrast, causal Bayes net theories (including Power PC theory) hypothesize that unobserved causes may be present or absent. These theories generally assume independence of different causes of the same event, which greatly simplifies modelling learning and inference. In two experiments participants were requested to learn about the causal relation between a single cause and an effect by observing their co-occurrence (Experiment 1) or by actively intervening in the cause (Experiment 2). Participants’ assumptions about the presence of an unobserved cause were assessed either after each learning trial or at the end of the learning phase. The results show an interesting dissociation. Whereas there was a tendency to assume interdependence of the causes in the online judgements during learning, the final judgements tended to be more in the direction of an independence assumption. Possible explanations and implications of these findings are discussed.

Second-order conditioning in human predictive judgements when there is little time to think

Associative accounts uniquely predict that second-order conditioning might be observed in human predictive judgements. Such an effect was found for cue X in two experiments in which participants were required to predict the outcomes of a series of training trials that included P + and PX−, but only when training was paced by requiring participants to make a prediction within 3 s on each trial. In Experiment 1 training on P + ended before training was given on PX − . In Experiment 2 trials with P+, PX−, T + and other cues were intermixed. In the unpaced group inhibitory learning was revealed by a summation test, TX versus TM, where M was a control stimulus. These results suggest either that pacing interferes with learning successive associations more than with learning simultaneous associations or that lack of time to think interferes with inferential processes required for this type of inhibitory learning.

The blocking effect in associative learning involves learned biases in rapid attentional capture

Blocking refers to the finding that less is learned about the relationship between a stimulus and an outcome if pairings are conducted in the presence of a second stimulus that has previously been established as a reliable predictor of that outcome. Attentional models of associative learning suggest that blocking reflects a reduction in the attention paid to the blocked cue. We tested this idea in three experiments in which participants were trained in an associative learning task using a blocking procedure. Attention to stimuli was measured 250 ms after onset using an adapted version of the dot probe task. This task was presented at the beginning of each learning trial (Experiments 1 and 2) or in independent trials (Experiment 3). Results show evidence of reduced attention to blocked stimuli (i.e. “attentional blocking”). In addition, this attentional bias correlated with the magnitude of blocking in associative learning, as measured by predictive-value judgments. Moreover, Experiments 2 and 3 found evidence of an influence of learning about predictiveness on memory for episodes involving stimuli. These findings are consistent with a central role of learned attentional biases in producing the blocking effect, and in the encoding of new memories.

Previously acquired cue-outcome structural knowledge guides new learning: Evidence from the retroactive-interference-between-cues effect

The effect of retroactive interference between cues predicting the same outcome (RIBC) occurs when the behavioral expression of a cue-outcome association (e.g., A→O1) is reduced due to the later acquisition of an association between a different cue and the same outcome (e.g., B→O1). In the present experimental series, we show that this effect can be modulated by knowledge concerning the structure of these cue-outcome relationships. In Experiments 1A and 1B, a pretraining phase was included to promote the expectation of either a one-to-one (OtO) or a many-to-one (MtO) cue-outcome structure during the subsequent RIBC training phases. We hypothesized that the adoption of an OtO expectation would make participants infer that the previously learned A→O1 relationship would not hold any longer after the exposure to B→O1 trials. Alternatively, the adoption of an MtO expectation would prevent participants from making such an inference. Experiment 1B included an additional condition without pretraining, to assess whether the OtO structure was expected by default. Experiment 2 included control conditions to assess the RIBC effect and induced the expectation of an OtO or MtO structure without the addition of a pretraining phase. Overall, the results suggest that participants effectively induced structural expectations regarding the cue-outcome contingencies. In turn, these expectations may have potentiated (OtO expectation) or alleviated (MtO expectation) the RIBC effect, depending on how well these expectations could accommodate the target A→O1 test association. This pattern of results poses difficulties for current explanations of the RIBC effect, since these explanations do not consider the incidence of cue-outcome structural expectations.

Three Ways That Non-associative Knowledge May Affect Associative Learning Processes

Associative learning theories offer one account of the way animals and humans assess the relationship between events and adapt their behavior according to resulting expectations. They assume knowledge about event relations is represented in associative networks, which consist of mental representations of cues and outcomes and the associative links that connect them. However, in human causal and contingency learning, many researchers have found that variance in standard learning effects is controlled by "non-associative" factors that are not easily captured by associative models. This has given rise to accounts of learning based on higher-order cognitive processes, some of which reject altogether the notion that humans learn in the manner described by associative networks. Despite the renewed focus on this debate in recent years, few efforts have been made to consider how the operations of associative networks and other cognitive operations could potentially interact in the course of learning. This paper thus explores possible ways in which non-associative knowledge may affect associative learning processes: (1) via changes to stimulus representations, (2) via changes to the translation of the associative expectation into behavior (3) via a shared source of expectation of the outcome that is sensitive to both the strength of associative retrieval and evaluation from non-associative influences.

Global Cue Inconsistency Diminishes Learning of Cue Validity

In daily life, we make decisions that are associated with probabilistic outcomes (e.g., the chance of rain today). People search for and utilize information that validly predicts an outcome (i.e., we look for dark clouds to indicate the possibility of rain). In the current study (N = 107), we present a two-stage learning task that examines how participants learn and utilize predictive information within a probabilistic learning environment. In the first stage, participants select one of three cues that gives predictive information about the outcome of the second stage. Participants then use this information to predict the outcome in stage two, for which they receive feedback. Critically, only one of the three cues in stage one gives valid predictive information about the outcome in stage two. Participants must differentiate the valid from non-valid cues and select this cue on subsequent trials in order to inform their prediction of the outcome in stage two. The validity of this predictive information, however, is reinforced with varying levels of probabilistic feedback (i.e., 75, 85, 95, 100%). A second manipulation involved changing the consistency of the predictive information in stage one and the outcome in stage two. The results show that participants, with higher levels of probabilistic feedback, learned to utilize the valid cue. In inconsistent task conditions, however, participants were significantly less successful in utilizing higher validity cues. We interpret this result as implying that learning in probabilistic categorization is based on developing a representation of the task that allows for goal-directed action.

The influence of the number of relevant causes on the processing of covariation information in causal reasoning

Research on causal reasoning has focused on the influence of covariation between candidate causes and effects on causal judgments. We suggest that the type of covariation information to which people attend is affected by the task being performed. For this, we manipulated the test questions for the evaluation of contingency information and observed its influence on both contingency learning and subsequent causal selections. When people select one cause related to an effect, they focus on conditional contingencies assuming the absence of alternative causes. When people select two causes related to an effect, they focus on conditional contingencies assuming the presence of alternative causes. We demonstrated this use of contingency information in four experiments.

Gambling with Rose-Tinted Glasses on: Use of Emotion-Regulation Strategies Correlates with Dysfunctional Cognitions in Gambling Disorder Patients

Background and aims Existing research shows that gambling disorder patients (GDPs) process gambling outcomes abnormally when compared against healthy controls (HCs). These anomalies present the form of exaggerated or distorted beliefs regarding the expected utility of outcomes and one's ability to predict or control gains and losses, as well as retrospective reinterpretations of what caused them. This study explores the possibility that the emotional regulation strategies GDPs use to cope with aversive events are linked to these cognitions. Methods 41 GDPs and 45 HCs, matched in sociodemographic variables, were assessed in gambling severity, emotion-regulation strategies (cognitive emotion-regulation questionnaire, CERQ), and gambling-related cognitions (gambling-related cognitions scale, GRCS). Results GDPs showed higher scores in all gambling-related cognition dimensions. Regarding emotion regulation, GDPs were observed to use self-blame and catastrophizing, but also positive refocusing, more often than controls. Additionally, in GDPs, putatively adaptive CERQ strategies shared a significant portion of variance with South Oaks gambling screen severity and GRCS beliefs. Shared variability was mostly attributable to the roles of refocusing on planning and putting into perspective at positively predicting severity and the interpretative bias (GDPs propensity to reframe losses in a more benign way), respectively. Discussion and conclusions Results show links between emotion-regulation strategies and problematic gambling-related behaviors and cognitions. The pattern of those links supports the idea that GDPs use emotion-regulation strategies, customarily regarded as adaptive, to cope with negative emotions, so that the motivational and cognitive processing of gambling outcomes becomes less effective in shaping gambling-related behavior.

Changing US Attributes After CS-US Pairings Changes CS-Attribute-Assessments

Attribute Conditioning (AC) refers to people’s changed assessments of stimuli’s (CSs) attributes due to repeated pairing with stimuli (USs) possessing these attributes; for example, when an athletic person (US) is paired with a neutral person (CS), the neutral person is judged to be more athletic after the pairing. We hypothesize that this AC effect is due to CSs’ associations with USs rather than direct associations with attributes. Three experiments test this hypothesis by changing US attributes after CS-US pairings. Experiments 1 and 2 conditioned athleticism by pairing neutral men (CSs) with athletic and non-athletic USs. Post-conditioning, USs’ athleticism was reversed, which systematically influenced participants’ assessment of CS athleticism. Experiment 3 conditioned athleticism and changed USs’ musicality after CS-US pairings. This post-conditioning change affected musicality assessments of CSs but did not influence athleticism-assessments. The results indicate that AC effects are based on an associative CS-US-attribute structure.

Illusions of causality: how they bias our everyday thinking and how they could be reduced

Illusions of causality occur when people develop the belief that there is a causal connection between two events that are actually unrelated. Such illusions have been proposed to underlie pseudoscience and superstitious thinking, sometimes leading to disastrous consequences in relation to critical life areas, such as health, finances, and wellbeing. Like optical illusions, they can occur for anyone under well-known conditions. Scientific thinking is the best possible safeguard against them, but it does not come intuitively and needs to be taught. Teaching how to think scientifically should benefit from better understanding of the illusion of causality. In this article, we review experiments that our group has conducted on the illusion of causality during the last 20 years. We discuss how research on the illusion of causality can contribute to the teaching of scientific thinking and how scientific thinking can reduce illusion.

Resistance to instructed reversal of the learned predictiveness effect

The learned predictiveness effect is a widely observed bias towards previously predictive cues in novel situations. Although the effect is generally attributed to an automatic attentional shift, it has recently been explained as the product of controlled inferences about the predictive value of cues. This view is supported by the susceptibility of learned predictiveness to instruction manipulation. However, recent research has shown conflicting results. Three experiments investigated the parameters of the instructed reversal effect in a human causal learning task, to determine the relative contribution of automatic and controlled attention processes. Experiment 1 showed that reversal instructions abolished, but did not reverse, the learned predictiveness effect, although length of initial training had no effect on the extent to which predictive cues subsequently captured attention. Experiment 2 explored whether particular causal scenarios lend themselves more readily to instructed reversal, but still failed to establish a significant reversal effect. Experiment 3 demonstrated a significant reversal effect when nonpredictive cues were explicitly and individually identified as the causes of outcomes. However, this effect was considerably weaker than the learned predictiveness effect when predictive cues were identified in the same way. Taken together, the results are inconsistent with a purely controlled account of learned predictiveness and provide support for dual-process theories of learning and attention.

Illusion of control: the role of personal involvement

The illusion of control consists of overestimating the influence that our behavior exerts over uncontrollable outcomes. Available evidence suggests that an important factor in development of this illusion is the personal involvement of participants who are trying to obtain the outcome. The dominant view assumes that this is due to social motivations and self-esteem protection. We propose that this may be due to a bias in contingency detection which occurs when the probability of the action (i.e., of the potential cause) is high. Indeed, personal involvement might have been often confounded with the probability of acting, as participants who are more involved tend to act more frequently than those for whom the outcome is irrelevant and therefore become mere observers. We tested these two variables separately. In two experiments, the outcome was always uncontrollable and we used a yoked design in which the participants of one condition were actively involved in obtaining it and the participants in the other condition observed the adventitious cause-effect pairs. The results support the latter approach: Those acting more often to obtain the outcome developed stronger illusions, and so did their yoked counterparts.

Encouraging Children to Think Counterfactually Enhances Blocking in a Causal Learning Task

According to a higher order reasoning account, inferential reasoning processes underpin the widely observed cue competition effect of blocking in causal learning. The inference required for blocking has been described as modus tollens (if p then q, not q therefore not p). Young children are known to have difficulties with this type of inference, but research with adults suggests that this inference is easier if participants think counterfactually. In this study, 100 children (51 five-year-olds and 49 six- to seven-year-olds) were assigned to two types of pretraining groups. The counterfactual group observed demonstrations of cues paired with outcomes and answered questions about what the outcome would have been if the causal status of cues had been different, whereas the factual group answered factual questions about the same demonstrations. Children then completed a causal learning task. Counterfactual pretraining enhanced levels of blocking as well as modus tollens reasoning but only for the younger children. These findings provide new evidence for an important role for inferential reasoning in causal learning.

Contingency Bias in Probability Judgement May Arise from Ambiguity regarding Additional Causes

In laboratory contingency learning tasks, people usually give accurate estimates of the degree of contingency between a cue and an outcome. However, if they are asked to estimate the probability of the outcome in the presence of the cue, they tend to be biased by the probability of the outcome in the absence of the cue. This bias is often attributed to an automatic contingency detection mechanism, which is said to act via an excitatory associative link to activate the outcome representation at the time of testing. We conducted 3 experiments to test alternative accounts of contingency bias. Participants were exposed to the same outcome probability in the presence of the cue, but different outcome probabilities in the absence of the cue. Phrasing the test question in terms of frequency rather than probability and clarifying the test instructions reduced but did not eliminate contingency bias. However, removal of ambiguity regarding the presence of additional causes during the test phase did eliminate contingency bias. We conclude that contingency bias may be due to ambiguity in the test question, and therefore it does not require postulation of a separate associative link-based mechanism.

Simple minds: a qualified defence of associative learning

Using cooperation in chimpanzees as a case study, this article argues that research on animal minds needs to steer a course between 'association-blindness'--the failure to consider associative learning as a candidate explanation for complex behaviour--and 'simple-mindedness'--the assumption that associative explanations trump more cognitive hypotheses. Association-blindness is challenged by the evidence that associative learning occurs in a wide range of taxa and functional contexts, and is a major force guiding the development of complex human behaviour. Furthermore, contrary to a common view, association-blindness is not entailed by the rejection of behaviourism. Simple-mindedness is founded on Morgan's canon, a methodological principle recommending 'lower' over 'higher' explanations for animal behaviour. Studies in the history and philosophy of science show that Morgan failed to offer an adequate justification for his canon, and subsequent attempts to justify the canon using evolutionary arguments and appeals to simplicity have not been successful. The weaknesses of association-blindness and simple-mindedness imply that there are no short-cuts to finding out about animal minds. To decide between associative and yet more cognitive explanations for animal behaviour, we have to spell them out in sufficient detail to allow differential predictions, and to test these predictions through observation and experiment.

Second-order conditioning and conditioned inhibition: influences of speed versus accuracy on human causal learning

In human causal learning, excitatory and inhibitory learning effects can sometimes be found in the same paradigm by altering the learning conditions. This study aims to explore whether learning in the feature negative paradigm can be dissociated by emphasising speed over accuracy. In two causal learning experiments, participants were given a feature negative discrimination in which the outcome caused by one cue was prevented by the addition of another. Participants completed training trials either in a self-paced fashion with instructions emphasising accuracy, or under strict time constraints with instructions emphasising speed. Using summation tests in which the preventative cue was paired with another causal cue, participants in the accuracy groups correctly rated the preventative cue as if it reduced the probability of the outcome. However, participants in the speed groups rated the preventative cue as if it increased the probability of the outcome. In Experiment 1, both speed and accuracy groups later judged the same cue to be preventative in a reasoned inference task. Experiment 2 failed to find evidence of similar dissociations in retrospective revaluation (release from overshadowing vs. mediated extinction) or learning about a redundant cue (blocking vs. augmentation). However in the same experiment, the tendency for the accuracy group to show conditioned inhibition and the speed group to show second-order conditioning was consistent even across sub-sets of the speed and accuracy groups with equivalent accuracy in training, suggesting that second-order conditioning is not merely a consequence of poorer acquisition. This dissociation mirrors the trade-off between second-order conditioning and conditioned inhibition observed in animal conditioning when training is extended.

Can we dissociate contingency learning from social learning in word acquisition by 24-month-olds?

We compared 24-month-old children's learning when their exposure to words came either in an interactive (coupled) context or in a nonsocial (decoupled) context. We measured the children's learning with two different methods: one in which they were asked to point to the referent for the experimenter, and the other a preferential looking task in which they were encouraged to look to the referent. In the pointing test, children chose the correct referents for words encountered in the coupled condition but not in the decoupled condition. In the looking time test, however, they looked to the targets regardless of condition. We explore the explanations for this and propose that the different response measures are reflecting two different kinds of learning.

Similarity and rules United: similarity- and rule-based processing in a single neural network

A central controversy in cognitive science concerns the roles of rules versus similarity. To gain some leverage on this problem, we propose that rule- versus similarity-based processes can be characterized as extremes in a multidimensional space that is composed of at least two dimensions: the number of features (Pothos, 2005) and the physical presence of features. The transition of similarity- to rule-based processing is conceptualized as a transition in this space. To illustrate this, we show how a neural network model uses input features (and in this sense produces similarity-based responses) when it has a low learning rate or in the early phases of training, but it switches to using self-generated, more abstract features (and in this sense produces rule-based responses) when it has a higher learning rate or is in the later phases of training. Relations with categorization and the psychology of learning are pointed out.

Word learning emerges from the interaction of online referent selection and slow associative learning

Classic approaches to word learning emphasize referential ambiguity: In naming situations, a novel word could refer to many possible objects, properties, actions, and so forth. To solve this, researchers have posited constraints, and inference strategies, but assume that determining the referent of a novel word is isomorphic to learning. We present an alternative in which referent selection is an online process and independent of long-term learning. We illustrate this theoretical approach with a dynamic associative model in which referent selection emerges from real-time competition between referents and learning is associative (Hebbian). This model accounts for a range of findings including the differences in expressive and receptive vocabulary, cross-situational learning under high degrees of ambiguity, accelerating (vocabulary explosion) and decelerating (power law) learning, fast mapping by mutual exclusivity (and differences in bilinguals), improvements in familiar word recognition with development, and correlations between speed of processing and learning. Together it suggests that (a) association learning buttressed by dynamic competition can account for much of the literature; (b) familiar word recognition is subserved by the same processes that identify the referents of novel words (fast mapping); (c) online competition may allow the children to leverage information available in the task to augment performance despite slow learning; (d) in complex systems, associative learning is highly multifaceted; and (e) learning and referent selection, though logically distinct, can be subtly related. It suggests more sophisticated ways of describing the interaction between situation- and developmental-time processes and points to the need for considering such interactions as a primary determinant of development.