Transfer of strategic task components across unique tasks that share some common structures.

Flexible, adaptive behaviour depends on the application of prior learning to novel contexts (transfer). Transfer can take many forms, but the focus of the present study was on "task schemas"-learning strategies that guide the earliest stages of engaging in a novel task. The central aim was to examine the architecture of task schemas and determine whether strategic task components can expedite learning novel tasks that share some structural components with the training tasks. Groups of participants across two experiments were exposed to different training regimes centred around multiple unique tasks that shared some/all/none of the structural task components (the kinds of stimuli, classifications, and/or responses) but none of the surface features (the specific stimuli, classifications, and/or responses) with the test task (a dot-pattern classification task). Initial test performance was improved (to a degree) in all groups relative to a control group whose training did not include any of the structural components relevant to the test task. The strongest evidence of transfer was found in the motoric, perceptual + categorization, and full schema training groups. This observation indicates that training with some (or all) strategic task components expedited learning of a novel task that shared those components. That is, task schemas were found to be componential and were able to expedite learning a novel task where similar (learning) strategies could be applied to specific elements of the test task.

Theory protection: Do humans protect existing associative links?

Theories of associative learning often propose that learning is proportional to prediction error, or the difference between expected events and those that occur. Spicer et al. (2020) suggested an alternative, that humans might instead selectively attribute surprising outcomes to cues that they are not confident about, to maintain cue-outcome associations about which they are more confident. Spicer et al. reported three predictive learning experiments, the results of which were consistent with their proposal ("theory protection") rather than a prediction error account (Rescorla, 2001). The four experiments reported here further test theory protection against a prediction error account. Experiments 3 and 4 also test the proposals of Holmes et al. (2019), who suggested a function mapping learning to performance that can explain Spicer et al.'s results using a prediction-error framework. In contrast to the previous study, these experiments were based on inhibition rather than excitation. Participants were trained with a set of cues (represented by letters), each of which was followed by the presence or absence of an outcome (represented by + or -). Following this, a cue that previously caused the outcome (A+) was placed in compound with another cue (B) with an ambiguous causal status (e.g., a novel cue in Experiment 1). This compound (AB-) did not cause the outcome. Participants always learned more about B in the second training phase, despite A always having the greater prediction error. In Experiments 3 and 4, a cue with no apparent prediction error was learned about more than a cue with a large prediction error. Experiment 4 tested participants' relative confidence about the causal status of cues A and B prior to the AB- stage, producing findings that are consistent with theory protection and inconsistent with the predictions of Rescorla, and Holmes et al. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The benefits of impossible tests: Assessing the role of error-correction in the pretesting effect.

Relative to studying alone, guessing the meanings of unknown words can improve later recognition of their meanings, even if those guesses were incorrect - the pretesting effect (PTE). The error-correction hypothesis suggests that incorrect guesses produce error signals that promote memory for the meanings when they are revealed. The current research sought to test the error-correction explanation of the PTE. In three experiments, participants studied unfamiliar Finnish-English word pairs by either studying each complete pair or by guessing the English translation before its presentation. In the latter case, the participants also guessed which of two categories the word belonged to. Hence, guesses from the correct category were semantically closer to the true translation than guesses from the incorrect category. In Experiment 1, guessing increased subsequent recognition of the English translations, especially for translations that were presented on trials in which the participants' guesses were from the correct category. Experiment 2 replicated these target recognition effects while also demonstrating that they do not extend to associative recognition performance. Experiment 3 again replicated the target recognition pattern, while also examining participants' metacognitive recognition judgments. Participants correctly judged that their memory would be better after small than after large errors, but incorrectly believed that making any errors would be detrimental, relative to study-only. Overall, the data are inconsistent with the error-correction hypothesis; small, within-category errors produced better recognition than large, cross-category errors. Alternative theories, based on elaborative encoding and motivated learning, are considered.

A cognitive category-learning model of rule abstraction, attention learning, and contextual modulation.

We introduce the Category Abstraction Learning (CAL) model, a cognitive framework formally describing category learning built on similarity-based generalization, dissimilarity-based abstraction, two attention learning mechanisms, error-driven knowledge structuring, and stimulus memorization. Our hypotheses draw on an array of empirical and theoretical insights connecting reinforcement and category learning. The key novelty of the model is its explanation of how rules are learned from scratch based on three central assumptions. (a) Category rules emerge from two processes of stimulus generalization (similarity) and its direct inverse (category contrast) on independent dimensions. (b) Two attention mechanisms guide learning by focusing on rules, or on the contexts in which they produce errors. (c) Knowing about these contexts inhibits executing the rule, without correcting it, and consequently leads to applying partial rules in different situations. The model is designed to capture both systematic and individual differences in a broad range of learning paradigms. We illustrate the model's explanatory scope by simulating several benchmarks, including the classic Six Problems, the 5-4 problem, and linear separability. Beyond the common approach of predicting average response probabilities, we also propose explanations for more recently studied phenomena that challenge existing learning accounts, regarding task instructions, individual differences in rule extrapolation in three different tasks, individual attention shifts to stimulus features during learning, and other phenomena. We discuss CAL's relation to different models, and its potential to measure the cognitive processes regarding attention, abstraction, error detection, and memorization from multiple psychological perspectives. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Neural correlates of the inverse base rate effect.

The inverse base rate effect (IBRE) is a nonrational behavioral phenomenon in predictive learning. Canonically, participants learn that the AB stimulus compound leads to one outcome and that AC leads to another outcome, with AB being presented three times as often as AC. When subsequently presented with BC, the outcome associated with AC is preferentially selected, in opposition to the underlying base rates of the outcomes. The current leading explanation is based on error-driven learning. A key component of this account is prediction error, a concept previously linked to a number of brain areas including the anterior cingulate, the striatum, and the dorsolateral prefrontal cortex. The present work is the first fMRI study to directly examine the IBRE. Activations were noted in brain areas linked to prediction error, including the caudate body, the anterior cingulate, the ventromedial prefrontal cortex, and the right dorsolateral prefrontal cortex. Analyzing the difference in activations for singular key stimuli (B and C), as well as frequency matched controls, supports the predictions made by the error-driven learning account.

Similarities and differences: Comment on Chan et al. (2021).

Spicer et al. (2020) reported a series of causal learning experiments in which participants appeared to learn most readily about cues when they were not certain of their causal status and proposed that their results were a consequence of participants' use of theory protection. In the present issue, Chan et al. (2021) present an alternative view, using a modification of Rescorla and Wagner's (1972) influential model of learning. Although the explanation offered by Chan et al. appears very different from that suggested by Spicer et al., there are conceptual commonalities. Here we briefly discuss the similarities and differences of the 2 approaches and agree with Chan et al.'s proposal that the best way to advance the debate will be to test situations in which the 2 theories make differing predictions. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Pretesting boosts recognition, but not cued recall, of targets from unrelated word pairs.

Attempting to retrieve the answer to a question on an initial test can improve memory for that answer on a subsequent test, relative to an equivalent study period. Such retrieval attempts can be beneficial even when they are unsuccessful, although this benefit is usually only seen with related word pairs. Three experiments examined the effects of pretesting for both related (e.g., pond-frog) and unrelated (e.g., pillow-leaf) word pairs on cued recall and target recognition. Pretesting improved subsequent cued recall performance for related but not for unrelated word pairs, relative to simply studying the word pairs. Tests of target recognition, by contrast, revealed benefits of pretesting for memory of targets from both related and unrelated word pairs. These data challenge popular theories that suggest that the pretesting effect depends on partial activation of the target during the pretesting phase.

A dimensional summation account of polymorphous category learning.

Polymorphous concepts are hard to learn, and this is perhaps surprising because they, like many natural concepts, have an overall similarity structure. However, the dimensional summation hypothesis (Milton and Wills Journal of Experimental Psychology: Learning, Memory and Cognition, 30, 407-415 2004) predicts this difficulty. It also makes a number of other predictions about polymorphous concept formation, which are tested here. In Experiment 4, we confirm the theory's prediction that polymorphous concept formation should be facilitated by deterministic pretraining on the constituent features of the stimulus. This facilitation is relative to an equivalent amount of training on the polymorphous concept itself. In further experiments, we compare the predictions of the dimensional summation hypothesis with a more general strategic account (Experiment 2), a seriality of training account (Experiment 3), a stimulus decomposition account (also Experiment 3), and an error-based account (Experiment 4). The dimensional summation hypothesis provides the best account of these data. In Experiment 5, a further prediction is confirmed-the single feature pretraining effect is eliminated by a concurrent counting task. The current experiments suggest the hypothesis that natural concepts might be acquired by the deliberate serial summation of evidence. This idea has testable implications for classroom learning.

The effect of preexposure on overall similarity categorization.

This article examines the effect that prior exposure to perceptual stimuli has on the prevalence of overall similarity (family resemblance) categorization. Experiment 1 demonstrated that participants who had previously encountered stimuli produced more overall similarity sorting when asked to free classify them than participants who were preexposed to different stimuli to those they later classified. Experiments 2a and 2b showed that this effect is modulated by the perceptual difficulty of the stimuli-preexposure statistically increased overall similarity sorting for perceptually easy stimuli but not for perceptually difficult stimuli. Overall similarity sorting was also significantly higher for perceptually easy stimuli than for perceptually difficult stimuli. Experiment 2b additionally showed that preexposure increased the discriminability of the perceptually easy stimuli but this effect was not statistically detectable for perceptually difficult stimuli. Experiment 3 established that the preexposure effect is also influenced by the spatial separateness of the stimulus dimensions-preexposure significantly elevated overall similarity sorting when the dimensions were integrated into a coherent object but not when they were spatially separated. Similarly, there was a statistically significant increase in the perceptual discriminability of the spatially integrated stimuli after preexposure but not for the spatially separate stimuli. Taken together, these results demonstrate that preexposure can elevate overall similarity sorting and provide insight into the conditions under which the effect will occur. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Theory protection in associative learning: Humans maintain certain beliefs in a manner that violates prediction error.

Three experiments were conducted to investigate a possible role for certainty in human causal learning. In these experiments, human participants were initially trained with a set of cues, each of which was followed by the presence or absence of an outcome. In a subsequent training stage, 2 of these cues were trained in a causal compound, and the change in associative strength for each of the cues was compared, using a procedure based on Rescorla (2001). In each experiment, the cues differed in both their causal certainty (on the part of participants) and size of their prediction error (with respect to the outcome). The cue with the larger prediction error was always the cue with the more certain causal status. According to established prediction error models (Bush & Mosteller, 1951; Rescorla, 2001; Rescorla & Wagner, 1972), a larger prediction error should result in a greater updating of associative strength. However, the opposite was observed, as participants always learned more about the cue with the smaller prediction error. A plausible explanation is that participants engaged in a form of theory protection, in which they were resistant to updating their existing beliefs about cues with a certain causal status. Instead, participants appeared to attribute outcomes to cues with a comparatively uncertain causal status, in an apparent violation of prediction error. The potential role of attentional processes (Mackintosh, 1975; Pearce & Hall, 1980) in explaining these results is also discussed. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Selective effects of errorful generation on recognition memory: the role of motivation and surprise.

The current research examined the effects of errorful generation on memory, focusing particularly on the roles of motivation and surprise. In two experiments, participants were first presented with photographs of faces and were asked to associate four facts with each photograph. On Generate trials, the participants guessed two of the facts (Guess targets) before those correct facts, and another two correct facts (Study targets), were revealed. On the remaining Read trials, all four facts were presented without a guessing stage. In Experiment 1, participants also ranked their motivation to know the answers before they were revealed, or their surprise on learning the true answers. Guess targets were subsequently better recognised than the concurrently presented, non-guessed Study targets. Guess targets were also better recognised than Read targets, and recognition of Study and Read targets did not differ. Errorful generation also increased self-reported motivation, but not surprise. Experiment 2 showed that the results of Experiment 1 can outlive a 20-minute delay, and that they generalise to a more challenging recognition test. Together, the results suggest that errorful generation improves memory specifically for the guessed fact, and this may be linked to an increase in motivation to learn that fact.

Dissociable learning processes, associative theory, and testimonial reviews: A comment on Smith and Church (2018).

Smith and Church (Psychonomic Bulletin & Review, 25, 1565-1584 2018) present a "testimonial" review of dissociable learning processes in comparative and cognitive psychology, by which we mean they include only the portion of the available evidence that is consistent with their conclusions. For example, they conclude that learning the information-integration category-learning task with immediate feedback is implicit, but do not consider the evidence that people readily report explicit strategies in this task, nor that this task can be accommodated by accounts that make no distinction between implicit and explicit processes. They also consider some of the neuroscience relating to information-integration category learning, but do not report those aspects that are more consistent with an explicit than an implicit account. They further conclude that delay conditioning in humans is implicit, but do not report evidence that delay conditioning requires awareness; nor do they present the evidence that conditioned taste aversion, which should be explicit under their account, can be implicit. We agree with Smith and Church that it is helpful to have a clear definition of associative theory, but suggest that their definition may be unnecessarily restrictive. We propose an alternative definition of associative theory and briefly describe an experimental procedure that we think may better distinguish between associative and non-associative processes.

Initial training with difficult items does not facilitate category learning.

In the phenomenon of transfer along a continuum (TAC), initial training on easy items facilitates later learning of a harder discrimination. TAC is a widely replicated cross-species phenomenon that is well predicted by certain kinds of associative theory. A recent report of an approximately opposite phenomenon (i.e., facilitation by initial training on hard items) poses a puzzle for such theories, but is predicted by a dual-system model (COVIS). However, across four experiments, we present substantial evidence that this counterintuitive finding was in error. Rather, the result appears to be a false positive and, as such, should not form part of the evidence base for COVIS nor be considered as a counter-example to the pervasive TAC phenomenon.

Automaticity and cognitive control: Effects of cognitive load on cue-controlled reward choice.

The extent to which human outcome-response (O-R) priming effects are automatic or under cognitive control is currently unclear. Two experiments tested the effect of cognitive load on O-R priming to shed further light on the debate. In Experiment 1, two instrumental responses earned beer and chocolate points in an instrumental training phase. Instrumental response choice was then tested in the presence of beer, chocolate, and neutral stimuli. On test, a Reversal instruction group was told that the stimuli signalled which response would not be rewarded. The transfer test was also conducted under either minimal (No Load) or considerable (Load) cognitive load. The Non-Reversal groups showed O-R priming effects, where the reward cues increased the instrumental responses that had previously produced those outcomes, relative to the neutral stimulus. This effect was observed even under cognitive load. The Reversal No Load group demonstrated a reversed effect, where response choice was biased towards the response that was most likely to be rewarded according to the instruction. Most importantly, response choice was at chance in the Reversal Load condition. In Experiment 2, cognitive load abolished the sensitivity to outcome devaluation that was otherwise seen when multiple outcomes and responses were cued on test. Collectively, the results demonstrate that complex O-R priming effects are sensitive to cognitive load, whereas the very simple, standard O-R priming effect is more robust.

Model-free and model-based reward prediction errors in EEG.

Learning theorists posit two reinforcement learning systems: model-free and model-based. Model-based learning incorporates knowledge about structure and contingencies in the world to assign candidate actions with an expected value. Model-free learning is ignorant of the world's structure; instead, actions hold a value based on prior reinforcement, with this value updated by expectancy violation in the form of a reward prediction error. Because they use such different learning mechanisms, it has been previously assumed that model-based and model-free learning are computationally dissociated in the brain. However, recent fMRI evidence suggests that the brain may compute reward prediction errors to both model-free and model-based estimates of value, signalling the possibility that these systems interact. Because of its poor temporal resolution, fMRI risks confounding reward prediction errors with other feedback-related neural activity. In the present study, EEG was used to show the presence of both model-based and model-free reward prediction errors and their place in a temporal sequence of events including state prediction errors and action value updates. This demonstration of model-based prediction errors questions a long-held assumption that model-free and model-based learning are dissociated in the brain.

Multiple feature use in pigeons' category discrimination: The influence of stimulus set structure and the salience of stimulus differences.

Two experiments investigated what makes it more likely that pigeons' behavior will come under the control of multiple relevant visual stimulus dimensions. Experiment 1 investigated the effect of stimulus set structure, using a conditional discrimination between circles that differed in both hue and diameter. Two training conditions differed in whether hue and diameter were correlated in the same way within positive and negative stimulus sets as between sets. Transfer tests showed that all pigeons came under the control of both dimensions, regardless of stimulus set structure. Experiment 2 investigated the effect of the relative salience of the stimulus differences on three visual dimensions. Pigeons learned a multiple simultaneous discrimination between circular patches of sinusoidal gratings that differed in hue, orientation, and spatial frequency. In initial training, each stimulus only included one positive or negative feature, and the stimulus differences on the three dimensions were adjusted so that the rates of learning about the three dimensions were kept approximately equal. Transfer tests showed that all three dimensions acquired control over behavior, with no single dimension dominating consistently across pigeons. Subsequently the pigeons were trained in a polymorphous category discrimination using all three dimensions, and the level of control by the three dimensions tended to become more equal as polymorphous training continued. We conclude that the salience of the stimulus differences on different dimensions is an important factor in whether pigeons will come under the control of multiple dimensions of visual stimuli. (PsycINFO Database Record

Due Process in Dual Process: Model-Recovery Simulations of Decision-Bound Strategy Analysis in Category Learning.

Behavioral evidence for the COVIS dual-process model of category learning has been widely reported in over a hundred publications (Ashby & Valentin, ). It is generally accepted that the validity of such evidence depends on the accurate identification of individual participants' categorization strategies, a task that usually falls to Decision Bound analysis (Maddox & Ashby, ). Here, we examine the accuracy of this analysis in a series of model-recovery simulations. In Simulation 1, over a third of simulated participants using an Explicit (conjunctive) strategy were misidentified as using a Procedural strategy. In Simulation 2, nearly all simulated participants using a Procedural strategy were misidentified as using an Explicit strategy. In Simulation 3, we re-examined a recently reported COVIS-supporting dissociation (Smith et al., ) and found that these misidentification errors permit an alternative, single-process, explanation of the results. Implications for due process in the future evaluation of dual-process theories, including recommendations for future practice, are discussed.

Transfer of learned category-response associations is modulated by instruction.

Although instructions often emphasize categories (e.g., odd number→left hand response) rather than specific stimuli (e.g., 3→left hand response), learning is often interpreted in terms of stimulus-response (S-R) bindings or, less frequently, stimulus-classification (S-C) bindings with little attention being paid to the importance of category-response (C-R) bindings. In a training-transfer paradigm designed to investigate the early stages of category learning, participants were required to classify stimuli according to the category templates presented prior to each block (Experiments 1-4). In some transfer blocks the stimuli, categories and/or responses could be novel or repeated from the preceding training phase. Learning was assessed by comparing the transfer-training performance difference across conditions. Participants were able to rapidly transfer C-R associations to novel stimuli but evidence of S-C transfer was much weaker and S-R transfer was largely limited to conditions where the stimulus was classified under the same category. Thus, even though there was some evidence that learned S-R and S-C associations contributed to performance, learned C-R associations seemed to play a much more important role. In a final experiment (Experiment 5) the stimuli themselves were presented prior to each block, and the instructions did not mention the category structure. In this experiment, the evidence for S-R learning outweighed the evidence for C-R learning, indicating the importance of instructions in learning. The implications for these findings to the learning, cognitive control, and automaticity literatures are discussed.

The Neural Correlates of Similarity- and Rule-based Generalization.

The idea that there are multiple learning systems has become increasingly influential in recent years, with many studies providing evidence that there is both a quick, similarity-based or feature-based system and a more effortful rule-based system. A smaller number of imaging studies have also examined whether neurally dissociable learning systems are detectable. We further investigate this by employing for the first time in an imaging study a combined positive and negative patterning procedure originally developed by Shanks and Darby [Shanks, D. R., & Darby, R. J. Feature- and rule-based generalization in human associative learning. Journal of Experimental Psychology: Animal Behavior Processes, 24, 405-415, 1998]. Unlike previous related studies employing other procedures, rule generalization in the Shanks-Darby task is beyond any simple non-rule-based (e.g., associative) account. We found that rule- and similarity-based generalization evoked common activation in diverse regions including the pFC and the bilateral parietal and occipital lobes indicating that both strategies likely share a range of common processes. No differences between strategies were identified in whole-brain comparisons, but exploratory analyses indicated that rule-based generalization led to greater activation in the right middle frontal cortex than similarity-based generalization. Conversely, the similarity group activated the anterior medial frontal lobe and right inferior parietal lobes more than the rule group did. The implications of these results are discussed.

Free classification of large sets of everyday objects is more thematic than taxonomic.

Traditionally it has been thought that the overall organisation of categories in the brain is taxonomic. To examine this assumption, we had adults sort 140-150 diverse, familiar objects from different basic-level categories. Almost all the participants (80/81) sorted the objects more thematically than taxonomically. Sorting was only weakly modulated by taxonomic priming, and people still produced many thematically structured clusters when explicitly instructed to sort taxonomically. The first clusters that people produced were rated as having equal taxonomic and thematic structure. However, later clusters were rated as being increasingly thematically organised. A minority of items were consistently clustered taxonomically, but the overall dominance of thematically structured clusters suggests that people know more thematic than taxonomic relations among everyday objects. A final study showed that the semantic relations used to sort a given item in the initial studies predicted the proportion of thematic to taxonomic word associates generated to that item. However, unlike the results of the sorting task, most of these single word associates were related taxonomically. This latter difference between the results of large-scale, free sorting tasks versus single word association tasks suggests that thematic relations may be more numerous, but weaker, than taxonomic associations in our stored conceptual network. Novel statistical and numerical methods for objectively measuring sorting consistency were developed during the course of this investigation, and have been made publicly available.