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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.

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.

Analogical transfer has been previously reported to occur between rule-based, but not information-integration, perceptual category structures (Casale, Roeder, & Ashby, 2012). The current study investigated whether a similar pattern of results would be observed in cross-modality transfer. Participants were trained on either a rule-based structure, or an information-integration structure, using visual stimuli. They were then tested on auditory stimuli that had the same underlying abstract category structure. Transfer performance was assessed relative to a control group who did not receive training on the visual stimuli. No cross-modality transfer was found, irrespective of the category structure employed.

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).

The Inverse Base Rate effect (IBRE; Medin & Edelson, 1988) is a non-rational behavioural 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. An error-driven learning account (Kruschke, 2001b) is the leading current explanation of the IBRE. 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. Analysing 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.

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 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.

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).

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.

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.

Comparative and cognitive psychologists interpret performance in different ways. Animal researchers invoke a dominant construct of associative learning. Human researchers acknowledge humans’ capacity for explicit-declarative cognition. This article offers a way to bridge a divide that defeats productive cross-talk. We show that animals often challenge the associative-learning construct, and that it does not work to try to stretch the associative-learning construct to encompass these performances. This approach thins and impoverishes that important construct. We describe an alternative approach that restrains the construct of associative learning by giving it a clear operational definition. We apply this approach in several comparative domains to show that different task variants change—in concert—the level of awareness, the declarative nature of knowledge, the dimensional breadth of knowledge, and the brain systems that organize learning. These changes reveal dissociable learning processes that a unitary associative construct cannot explain but a neural-systems framework can explain. These changes define the limit of associative learning and the threshold of explicit cognition. The neural-systems framework can broaden empirical horizons in comparative psychology. It can offer animal models of explicit cognition to cognitive researchers and neuroscientists. It can offer simple behavioral paradigms for exploring explicit cognition to developmental researchers. It can enliven the synergy between human and animal research, promising a productive future for both.

Two experiments are reported that demonstrate rate of learning in an allergy prediction task can b e a ffected b y the predictive history of the c ues involved, even if that history relates to ou tcomes different t o those being currently learned about. Predictive history is defined here as a cue’s prior status as either a good or a poor predictor of outcomes. Our r esults are problematic for commonly employed associative theories of human contingency learning but also p rovide e vidence for the sort of associability-change process envisaged by the Mackintosh (1975) theory.

publisher: Elsevier articletitle: In Defence of Effect-Centric Research journaltitle: Journal of Applied Research in Memory and Cognition articlelink: http://dx.doi.org/10.1016/j.jarmac.2016.10.005 content_type: simple-article copyright: © 2016 Society for Applied Research in Memory and Cognition. Published by Elsevier Inc. All rights reserved.

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.

OBJECTIVE Generalization is the application of existing knowledge to novel situations. Questions remain about the precise role of the hippocampus in this facet of learning, but a connectionist model by Gluck and Myers (1993) predicts that generalization should be enhanced following hippocampal damage. METHOD In a two-category learning task, a group of amnesic patients (n = 9) learned the training items to a similar level of accuracy as matched controls (n = 9). Both groups then classified new items at various levels of distortion. RESULTS The amnesic group showed significantly more accurate generalization to high-distortion novel items, a difference also present compared to a larger group of unmatched controls (n = 33). CONCLUSIONS The model prediction of a broadening of generalization gradients in amnesia, at least for items near category boundaries, was supported by the results. Our study shows for the first time that amnesia can sometimes improve generalization. (PsycINFO Database Record

This article presents a comprehensive survey of research concerning interactions between associative learning and attention in humans. Four main findings are described. First, attention is biased toward stimuli that predict their consequences reliably (learned predictiveness). This finding is consistent with the approach taken by Mackintosh (1975) in his attentional model of associative learning in nonhuman animals. Second, the strength of this attentional bias is modulated by the value of the outcome (learned value). That is, predictors of high-value outcomes receive especially high levels of attention. Third, the related but opposing idea that uncertainty may result in increased attention to stimuli (Pearce & Hall, 1980), receives less support. This suggests that hybrid models of associative learning, incorporating the mechanisms of both the Mackintosh and Pearce-Hall theories, may not be required to explain data from human participants. Rather, a simpler model, in which attention to stimuli is determined by how strongly they are associated with significant outcomes, goes a long way to account for the data on human attentional learning. The last main finding, and an exciting area for future research and theorizing, is that learned predictiveness and learned value modulate both deliberate attentional focus, and more automatic attentional capture. The automatic influence of learning on attention does not appear to fit the traditional view of attention as being either goal-directed or stimulus-driven. Rather, it suggests a new kind of “derived” attention.

The influential competition between verbal and implicit systems (COVIS) model proposes that category learning is driven by two competing neural systems-an explicit, verbal, system, and a procedural-based, implicit, system. In the current fMRI study, participants learned either a conjunctive, rule-based (RB), category structure that is believed to engage the explicit system, or an information-integration category structure that is thought to preferentially recruit the implicit system. The RB and information-integration category structures were matched for participant error rate, the number of relevant stimulus dimensions, and category separation. Under these conditions, considerable overlap in brain activation, including the prefrontal cortex, basal ganglia, and the hippocampus, was found between the RB and information-integration category structures. Contrary to the predictions of COVIS, the medial temporal lobes and in particular the hippocampus, key regions for explicit memory, were found to be more active in the information-integration condition than in the RB condition. No regions were more activated in RB than information-integration category learning. The implications of these results for theories of category learning are discussed. Hum Brain Mapp 37:3557-3574, 2016. © 2016 Wiley Periodicals, Inc.

Inhibitory processes have been implicated in depressive rumination. Inhibitory deficits may cause difficulties in disengaging from ruminative content (e.g., Joormann, 2005), or rumination may constitute a working memory load, causing deficits in inhibitory control (e.g., Hertel, 2004). These hypotheses have different implications for the treatment of depression. We conducted a systematic review of existing evidence, and conclude that most studies do not unambiguously measure inhibition. The majority of published evidence is correlational, and thus supports neither causal direction. No published experimental studies have investigated the inhibitory deficit -? rumination causal direction, and only six have investigated the rumination -? inhibitory deficit hypothesis. In two of these studies the dependent variable has low construct validity. One study reported no effect of rumination on interference, and three did not control for mood effects. There is need for carefully designed experimental research that has the potential to investigate these proposed causal mechanisms.

Potts and Shanks (2014) recently reported that making mistakes improved the encoding of novel information compared with simply studying. This benefit of generating errors is counterintuitive, since it resulted in less study time and more opportunity for proactive interference. Five experiments examined the effect of generating errors versus studying on item recognition, cued recall, associative recognition, two-alternative forced choice and multiple-choice performance. Following Potts and Shanks (2014), participants first attempted to learn the English definitions of either very rare English words or Euskara nouns. During encoding, participants either guessed the definition (and almost always made an error) before the correct definition was revealed, or simply studied the words for an equivalent period. Experiments 1–4 used rare English words. In these experiments, generating errors led to better subsequent recognition of both the cues and targets compared with studying (Experiments 1 and 3). Tests of cued recall and associative recognition, by contrast, revealed no significant benefit of generating errors over studying (Experiments 1–3). Generating errors during encoding also improved performance on a two-alternative forced choice test when the correct target was presented with a novel foil, but not when the familiarity of the target and the foil was matched (Experiment 4). In Experiment 5, a different set of materials – Euskara nouns – and a different (intermixed) encoding procedure was adopted. Here, guessing improved target recognition (performance was improved on a multiple-choice test with unfamiliar foils), but impaired cued recall performance. These results suggest that, when learning word pairs that do not have a pre-existing semantic association, generating errors strengthens the cues and targets in isolation, but does not strengthen the cue-target associations.

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.

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

Does cognition begin with an undifferentiated stimulus whole, which can be divided into distinct attributes if time and cognitive resources allow (Differentiation Theory)? Or does it begin with the attributes, which are combined if time and cognitive resources allow (Combination Theory)? Across psychology, use of the terms analytic and non-analytic imply that Differentiation Theory is correct—if cognition begins with the attributes, then synthesis, rather than analysis, is the more appropriate chemical analogy. We re-examined four classic studies of the effects of time pressure, incidental training, and concurrent load on classification and category learning (Kemler Nelson, 1984; Smith & Kemler Nelson, 1984; Smith & Shapiro, 1989; Ward, 1983). These studies are typically interpreted as supporting Differentiation Theory over Combination Theory, while more recent work in classification (Milton et al., 2008, et seq.) supports the opposite conclusion. Across seven experiments, replication and re-analysis of the four classic studies revealed that they do not support Differentiation Theory over Combination Theory—two experiments support Combination Theory over Differentiation Theory, and the remainder are compatible with both accounts. We conclude that Combination Theory provides a parsimonious account of both classic and more recent work in this area. The presented data do not require Differentiation Theory, nor a Combination–Differentiation hybrid account.

The effects of two different types of training on rule-based and information-integration category learning were investigated in two experiments. In observational training, a category label is presented, followed by an example of that category and the participant's response. In feedback training, the stimulus is presented, and the participant assigns it to a category and then receives feedback about the accuracy of that decision. Ashby, Maddox, and Bohil (2002. Observational versus feedback training in rule-based and information-integration category learning. Memory & Cognition, 30, 666–677) reported that feedback training was superior to observational training when learning information-integration category structures, but that training type had little effect on the acquisition of rule-based category structures. These results were argued to support the COVIS (competition between verbal and implicit systems) dual-process account of category learning. However, a number of nonessential differences between their rule-based and information-integration conditions complicate interpretation of these findings. Experiment 1 controlled between-category structures for participant error rates, category separation, and the number of stimulus dimensions relevant to the categorization. Under these more controlled conditions, rule-based and information-integration category structures both benefited from feedback training to a similar degree. Experiment 2 maintained this difference in training type when learning a rule-based category that had otherwise been matched, in terms of category overlap and overall performance, with the rule-based categories used in Ashby et al. These results indicate that differences in dimensionality between the category structures in Ashby et al. is a more likely explanation for the interaction between training type and category structure than the dual-system explanation that they offered.

We report the first electrophysiological investigation of the inverse base-rate effect (IBRE), a robust non-rational bias in predictive learning. In the IBRE, participants learn that one pair of symptoms (AB) predicts a frequently occurring disease, whilst an overlapping pair of symptoms (AC) predicts a rarely occurring disease. Participants subsequently infer that BC predicts the rare disease, a non-rational decision made in opposition to the underlying base rates of the two diseases. Error-driven attention theories of learning state that the IBRE occurs because C attracts more attention than B. On the basis of this account we predicted and observed the occurrence of brain potentials associated with visual attention: a posterior Selection Negativity, and a concurrent anterior Selection Positivity, for C vs. B in a post-training test phase. Error-driven attention theories further predict no Selection Negativity, Selection Positivity or IBRE, for control symptoms matched on frequency to B and C, but for which there was no shared symptom (A) during training. These predictions were also confirmed, and this confirmation discounts alternative explanations of the IBRE based on the relative novelty of B and C. Further, we observed higher response accuracy for B alone than for C alone; this dissociation of response accuracy (B > C) from attentional allocation (C > B) discounts the possibility that the observed attentional difference was caused by the difference in response accuracy.

Background and Objectives Control theory predicts that the detection of goal discrepancies initiates ruminative self-focus ( Martin & Tesser, 1996 ). Despite the breadth of applications and interest in control theory, there is a lack of experimental evidence evaluating this prediction. The present study provided the first experimental test of this prediction. Methods We examined uninstructed state rumination in response to the cueing of resolved and unresolved goals in a non-clinical population using a novel measure of online rumination. Results Consistent with control theory, cueing an unresolved goal resulted in significantly greater recurrent intrusive ruminative thoughts than cueing a resolved goal. Individual differences in trait rumination moderated the impact of the goal cueing task on the extent of state rumination: individuals who had a stronger tendency to habitually ruminate were more susceptible to the effects of cueing goal discrepancies. Limitations The findings await replication in a clinically depressed sample where there is greater variability and higher levels of trait rumination. Conclusions These results indicate that control theories of goal pursuit provide a valuable framework for understanding the circumstances that trigger state rumination. Additionally, our measure of uninstructed online state rumination was found to be a valid and sensitive index of the extent and temporal course of state rumination, indicating its value for further investigating the proximal causes of state rumination.

It is sometimes argued that the implementation of an overall similarity classification is less effortful than the implementation of a single-dimension classification. In the current article, we argue that the evidence securely in support of this view is limited, and report additional evidence in support of the opposite proposition—overall similarity classification is more effortful than single-dimension classification. Using a match-to-standards procedure, Experiments 1A, 1B and 2 demonstrate that concurrent load reduces the prevalence of overall similarity classification, and that this effect is robust to changes in the concurrent load task employed, the level of time pressure experienced, and the short-term memory requirements of the classification task. Experiment 3 demonstrates that participants who produced overall similarity classifications from the outset have larger working memory capacities than those who produced single-dimension classifications initially, and Experiment 4 demonstrates that instructions to respond meticulously increase the prevalence of overall similarity classification.

This research explored the role that associative learning may play in human sequence learning. Two-choice serial reaction time tasks were performed under incidental conditions using 2 different sequences. In both cases, an experimental group was trained on 4 subsequences: LLL, LRL, RLR, and RRR for Group "Same" and LLR, LRR, RLL, and RRL for Group "Different," with left and right counterbalanced across participants. To control for sequential effects, we assayed sequence learning by comparing their performance with that of a control group, which had been trained on a pseudorandom ordering, during a test phase in which both experimental and control groups experienced the same subsequences. Participants in both groups showed sequence learning, but the group trained on "different" learned more and more rapidly. This result is the opposite that predicted by the augmented simple recurrent network used by F. W. Jones and I. P. L. McLaren (2009, Human sequence learning under incidental and intentional conditions, Journal of Experimental Psychology: Animal Behavior Processes, Vol. 35, pp. 538-553), but can be modeled using a reparameterized version of this network that also includes a more realistic representation of the stimulus array, suggesting that the latter may be a better model of human sequence learning under incidental conditions.

Demonstrations of retrospective revaluation suggest that remembered stimuli undergo a reduction in association with the unconditioned stimulus (US) present during learning. Conversely, demonstrations of mediated conditioning in flavor-conditioning experiments with rats suggest that remembered stimuli undergo an increase in association with the US present during learning. In a food allergy prediction task with 23 undergraduates, we demonstrated simultaneous backward conditioned inhibition and mediated conditioning effects. These results are compatible with the hypothesis that the direction of change (decrease or increase) in associative strength depends on whether the remembered stimulus was of a different category (conditioned stimulus/antecedent) or the same category (US/outcome) as the presented US.

The effect of concurrent load on generalization performance in human contingency learning was examined in 2 experiments that employed the combined positive and negative patterning procedure of Shanks and Darby (1998). In Experiment 1, we tested 32 undergraduates and found that participants who were trained and tested under full attention showed generalization consistent with the application of an opposites rule (i.e., single cues signal the opposite outcome to their compound), whereas participants trained and tested under a concurrent cognitive load showed generalization consistent with surface similarity. In Experiment 2, we replicated the effect with 148 undergraduates and provided evidence that it was the presence of concurrent load during training, rather than during testing, that was critical. Implications for associative, inferential, and dual-process accounts of human learning are discussed.

In an artificial grammar learning (AGL) experiment, participants were trained with instances of one grammatical structure before completing a test phase in which they were required to discriminate grammatical from randomly created strings. Importantly, the underlying structure used to generate test strings was different from that used to generate the training strings. Despite the fact that grammatical training strings were more similar to nongrammatical test strings than they were to grammatical test strings, this manipulation resulted in a positive transfer effect, as compared with controls trained with nongrammatical strings. It is suggested that training with grammatical strings leads to an appreciation of set variance that aids the detection of grammatical test strings in AGL tasks. The analysis presented demonstrates that it is useful to conceptualize test performance in AGL as a form of unsupervised category learning.

The ability to group stimuli into meaningful categories is fundamental to natural behavior. Raw perceptions would be useless without an ability to classify items as, for example, threat or food. Previous work suggests that people have a tendency to group stimuli either on the basis of a single dimension or by overall similarity (e.g., Milton, F.N., Longmore, C.A., and Wills, A.J. (2008). Processes of overall similarity sorting in free classification. J. Exp. Psychol. Hum. Percept. Perform, 34, 676–692.). It has recently been suggested that overall similarity sorting can engage similar rule-based processes to single-dimension sorting and, in addition, requires greater use of working memory (Milton, F.N., and Wills, A.J. (2004). The influences of stimulus properties on category construction. J. Exp. Psychol. Learn. Mem. Cogn, 30, 407–415.). These predictions were tested in an event-related fMRI study of spontaneous categorization. Results showed a striking overlap of activation between overall similarity and single-dimension sorting indicating engagement of common neural processes. Furthermore, overall similarity sorting recruited additional activity in bilateral precuneus, right cuneus, left cerebellum, left postcentral gyrus, right thalamus and right ventrolateral frontal cortex (VLFC). Our findings suggest that overall similarity sorting can be the result of rule-based processes and highlight a potential role for right VLFC in integrating multi-dimensional sensory information to form conceptual categories.

Contemporary theories of learning typically assume that learning is driven by prediction errors—in other words, that we learn more when our predictions turn out to be incorrect than we do when our predictions are correct. Results from the recording of electrical brain activity suggest one mechanism by which this might happen; we seem to direct visual attention toward the likely causes of previous prediction errors. This can happen very rapidly—within less than 200 milliseconds of the error-causing object being presented. It is tempting to infer that if learning is driven by prediction errors, then little can be learned in the absence of feedback. Such a conclusion is unwarranted. In fact, the substantial learning that is sometimes the result of simple exposure to objects can also be explained by processes of directing attention toward the likely causes of previous prediction errors.

The processes of overall similarity sorting were investigated in 5 free classification experiments. Experiments 1 and 2 demonstrated that increasing time pressure can reduce the likelihood of overall similarity categorization. Experiment 3 showed that a concurrent load also reduced overall similarity sorting. These findings suggest that overall similarity sorting can be a time-consuming analytic process. Such results appear contrary to the idea that overall similarity is a nonanalytic process (e.g., T. B. Ward, 1983) but are in line with F. N. Milton and A. J. Wills's (2004) dimensional summation hypothesis and with the stochastic sampling assumptions of the extended generalized context model (K. Lamberts, 2000). Experiments 4 and 5 demonstrated that the relationship between stimulus presentation time and overall similarity sorting is nonmonotonic, and the shape of the function is consistent with the idea that the three aforementioned processes operate over different parts of the time course.

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.

When humans process visual stimuli, global information often takes precedence over local information. In contrast, some recent studies have pointed to a local precedence effect in both pigeons and nonhuman primates. In the experiment reported here, we compared the speed of acquisition of two different categorizations of the same four geometric figures. One categorization was on the basis of a local feature, the other on the basis of a readily apparent global feature. For both humans and pigeons, the global-feature categorization was acquired more rapidly. This result reinforces the conclusion that local information does not always take precedence over global information in nonhuman animals.

It has been demonstrated that when people free classify stimuli presented simultaneously in an array, they have a preference to categorize by a single dimension. However, when people are encouraged to categorize items sequentially, they sort by “family resemblance,” grouping by overall similarity. The present studies extended this research, producing 3 main findings. First, the sequential procedure introduced by G. Regehr and L. R. Brooks (1995) does not always produce a preference for family resemblance sorts. Second, sort strategy in a sequential procedure is sensitive to subtle variations in stimulus properties. Third, spatially separable stimuli evoked more family resemblance sorts than stimuli of greater spatial integration. It is suggested that the family resemblance sorting observed is due to an analytic strategy. Categorization is a fundamental building block of everyday cognition; it is hard to imagine how people would function effectively without it. Categorization enables one to react to different objects in the same way and to make inferences about how novel objects should be treated. For instance, when a person sees a novel object, classifying it as a “dog” allows the person to deal with it in an appropriate manner. Because of the immense variety of discriminable objects that people encounter in the natural environment, it is necessary that this categorization process should be highly constrained, as there are virtually limitless numbers of ways in which objects can be partitioned. It is therefore of fundamental importance to understand the principles that underlie the categories that people have. Traditional categorization experiments give the participant itemby-item specific feedback about category membership. While such an approach is undoubtedly useful in examining category learning, it seems extremely unlikely that people receive this level of feedback anywhere other than in the laboratory. One way of addressing this issue is to examine how people spontaneously categorize a group of objects. This can be done by providing them with a group of stimuli and asking them to categorize them in the way that they think is most appropriate. No feedback, or other information, is given by the experimenter. Such an approach has variously been called category construction (e.g., Medin, Wattenmaker, & Hampson, 1987), free sorting (e.g., Bersted, Brown, & Evans, 1969), and free classification (e.g., Handel & Imai, 1972). It seems reasonable to assume that the categories we prefer to create would reflect the underlying structure of objects we encounter outside the laboratory. Over the years, there have been several

What are the effects of preexposure of stimuli on participants’ subsequent ability to categorize them accurately? An experiment employing artificial, abstract, visual stimuli confirms that, for adult humans, the effect of preexposure is dependent upon category structure. Whether preexposure has beneficial or detrimental effects is shown to be dependent on the way category examples are generated from the category base patterns. The results are predicted by salience reduction accounts of perceptual learning but may be problematic for stimulus differentiation accounts.

Humans can spontaneously create rules that allow them to efficiently generalize what they have learned to novel situations. An enduring question is whether rule-based generalization is uniquely human or whether other animals can also abstract rules and apply them to novel situations. In recent years, there have been a number of high-profile claims that animals such as rats can learn rules. Most of those claims are quite weak because it is possible to demonstrate that simple associative systems (which do not learn rules) can account for the behavior in those tasks. Using a procedure that allows us to clearly distinguish feature-based from rule-based generalization (the Shanks–Darby procedure), we demonstrate that adult humans show rule-based generalization in this task, while generalization in rats and pigeons was based on featural overlap between stimuli. In brief, when learning that a stimulus made of two components (“AB”) predicts a different outcome than its elements (“A” and “B”), people spontaneously abstract an opposites rule and apply it to new stimuli (e.g., knowing that “C” and “D” predict one outcome, they will predict that “CD” predicts the opposite outcome). Rats and pigeons show the reverse behavior—they generalize what they have learned, but on the basis of similarity (e.g., “CD” is similar to “C” and “D”, so the same outcome is predicted for the compound stimulus as for the components). Genuinely rule-based behavior is observed in humans, but not in rats and pigeons, in the current procedure. Electronic supplementary material The online version of this article (doi:10.1007/s10071-015-0895-8) contains supplementary material, which is available to authorized users.

Two experiments are reported that investigate the difference in gradient of generalization observed between one-category (non-discriminative) and two-category (discriminative) training. Extrapolating from the results of a number of animal learning studies, it was predicted that the gradient should be steeper under discriminative training. The first experiment confirms this basic prediction for the stimuli used, which were novel, prototype-structured, and constructed from 12 symbols positioned on a grid. An explanation for the effect, based on the Rescorla-Wagner theory of Pavlovian conditioning (Rescorla & Wagner, 1972), is that under non-discriminative training “incidental stimuli” have significant control over responding, whereas under discriminative training they do not. Incidental stimuli are those aspects of the stimulus, or the surrounding context, that are not differentially reinforced under discriminative training. This explanation leads to the prediction that a comparable effect of blocked versus intermixed discriminative training should also be found. This prediction is disconfirmed by the second experiment. An alternative model, still based on the Rescorla Wagner theory but with the addition of a decision mechanism comprising a threshold unit and a competitive network system, is proposed, and its ability to predict both the choice probabilities and the pattern of response times found is evaluated via simulation.

The present study examined the impact of engaging frontal-mediated, working memory processes on implicit and explicit category learning. Two stimulus dimensions were relevant to categorization, but in some conditions a third irrelevant dimension was also presented. Results indicated that, in both implicit and explicit conditions, the inclusion of the irrelevant dimension impaired performance by increasing the reliance on sub-optimal unidimensional strategies. With three-dimension stimuli a striking dissociation was observed between implicit and explicit category learning when participants performed the sequential working memory task. With explicit category learning, performance was impaired further and there was an increased use of sub-optimal unidimensional strategies. However, with implicit category learning, the performance impairment decreased and there was an increased use of optimal strategies. These findings demonstrate the paradoxical situation in which learning can be improved under sequential-task conditions and have important implications for training, decision making, and understanding interactive memory systems.

Categorization is one of the fundamental building blocks of cognition, and the study of categorization is notable for the extent to which formal modeling has been a central and influential component of research. However, the field has seen a proliferation of noncomplementary models with little consensus on the relative adequacy of these accounts. Progress in assessing the relative adequacy of formal categorization models has, to date, been limited because (a) formal model comparisons are narrow in the number of models and phenomena considered and (b) models do not often clearly define their explanatory scope. Progress is further hampered by the practice of fitting models with arbitrarily variable parameters to each data set independently. Reviewing examples of good practice in the literature, we conclude that model comparisons are most fruitful when relative adequacy is assessed by comparing well-defined models on the basis of the number and proportion of irreversible, ordinal, penetrable successes (principles of minimal flexibility, breadth, good-enough precision, maximal simplicity, and psychological focus).

Unitization, the creation of new stimulus features by the fusion of preexisting features, is one of the hypothesized processes of perceptual learning (Goldstone Annual Review of Psychology, 49:585–612, 1998). Some argue that unitization occurs to the extent that it is required for successful task performance (e.g., Shiffrin & Lightfoot, 1997), while others argue that unitization is largely independent of functionality (e.g., McLaren & Mackintosh Animal Learning & Behavior, 30:177–200, 2000). Across three experiments, employing supervised category learning and unsupervised exposure, we investigated three predictions of the McLaren and Mackintosh (Animal Learning & Behavior, 30:177–200, 2000) model: (1) Unitization is accompanied by an initial increase in the subjective similarity of stimuli sharing a unitized component; (2) unitization of a configuration occurs through exposure to its components, even when the task does not require it; (3) as unitization approaches completion, salience of the unitized component may be reduced. Our data supported these predictions. We also found that unitization is associated with increases in overt attention to the unitized component, as measured through eye tracking.

1. Introduction Emmanuel M. Pothos and Andy J. Wills 2. The generalized context model: an exemplar model of classification Robert M. Nosofsky 3. Prototype models of categorization: basic formulation, predictions, and limitations John Paul Minda and J. David Smith 4. COVIS F. Gregory Ashby, Erick J. Paul and W. Todd Maddox 5. Semantics without categorization Timothy T. Rogers and James L. McClelland 6. Models of attentional learning John K. Kruschke 7. An elemental model of associative learning and memory Evan Livesey and Ian McLaren 8. Nonparametric Bayesian models of categorization Thomas L. Griffiths, Adam N. Sanborn, Kevin R. Canini, Daniel J. Navarro and Joshua B. Tenenbaum 9. The simplicity model of unsupervised categorization Emmanuel M. Pothos, Nick Chater and Peter Hines 10. Adaptive clustering models of categorization John V. McDonnell and Todd M. Gureckis 11. COBWEB models of categorization and probabilistic concept formation Wayne Iba and Pat Langley 12. The knowledge and resonance (KRES) model of category learning Harlan D. Harris and Bob Rehder 13. The contribution (and drawbacks) of models to the study of concepts Gregory L. Murphy 14. Formal models of categorization: insights from cognitive neuroscience Lukas Strnad, Stefano Anzellotti and Alfonso Caramazza 15. Comments on models and categorization theories: the razor's edge Douglas Medin.

Pigeons (Columba livia), gray squirrels (Sciurus carolinensis), and undergraduates (Homo sapiens) learned discrimination tasks involving multiple mutually redundant dimensions. First, pigeons and undergraduates learned conditional discriminations between stimuli composed of three spatially separated dimensions, after first learning to discriminate the individual elements of the stimuli. When subsequently tested with stimuli in which one of the dimensions took an anomalous value, the majority of both species categorized test stimuli by their overall similarity to training stimuli. However some individuals of both species categorized them according to a single dimension. In a second set of experiments, squirrels, pigeons, and undergraduates learned go/no-go discriminations using multiple simultaneous presentations of stimuli composed of three spatially integrated, highly salient dimensions. The tendency to categorize test stimuli including anomalous dimension values unidimensionally was higher than in the first set of experiments and did not differ significantly between species. The authors conclude that unidimensional categorization of multidimensional stimuli is not diagnostic for analytic cognitive processing, and that any differences between human’s and pigeons’ behavior in such tasks are not due to special features of avian visual cognition.

Pigeons and undergraduates learned conditional discriminations involving multiple spatially separated stimulus dimensions. Under some conditions, the dimensions were made available sequentially. In 3 experiments, the dimensions were all perfectly valid predictors of the response that would be reinforced and mutually redundant; in 2 others, they varied in validity. In tests with stimuli in which 1 of the 3 dimensions took an anomalous value, most but not all individuals of both species categorized them in terms of single dimensions. When information was delivered as a function of the passage of time, some students, but no pigeons, waited for the most useful information, especially when the cues differed in objective validity. When the subjects could control information delivery, both species obtained information selectively. When cue validities varied, almost all students tended to choose the most valid cues, and when all cues were valid, some chose the cues by which they classified test stimuli. Only a few pigeons chose the most useful information in either situation. Despite their tendency to unidimensional categorization, the pigeons showed no evidence of rule-governed behavior, but students followed a simple "take-the-best" rule.

Previous laboratory studies on social learning suggest that some animals can learn more readily if they first observe a conspecific demonstrator perform the task unsuccessfully and so fail to obtain a food reward than if they observe a successful demonstrator that obtains the food. This effect may indicate a difference in how easily animals are able to associate different outcomes with the conspecific or could simply be the result of having food present in only some of the demonstrations. To investigate we tested a scatter-hoarding mammal, the eastern grey squirrel, on its ability to learn to choose between two pots of food after watching a conspecific remove a nut from one of them on every trial. Squirrels that were rewarded for choosing the opposite pot to the conspecific chose correctly more frequently than squirrels rewarded for choosing the same pot (a feature-negative effect). Another group of squirrels was tested on their ability to choose between the two pots when the rewarded option was indicated by a piece of card. This time, squirrels showed no significant difference in their ability to learn to choose the same or the opposite pot. The results add to anecdotal reports that grey squirrels can learn by observing a conspecific and suggest that even when all subjects are provided with demonstrations with the same content, not all learning occurs equally. Prior experience or expectations of the association between a cue (a conspecific) and food influences what can be learned through observation whilst previously unfamiliar cues (the card) can be associated more readily with any outcome.

Two free classification experiments that investigate the persistence of sort strategy are reported. Participants tend to persist with their initial categorization type (family resemblance or unidimensional) for the remaining sorts, overriding the effects of otherwise influential stimulus properties. Sort type was found to persist even after a one-week delay. Stimulus-driven models of free classification (e.g., the SUSTAIN model, [Love, B. C., Medin, D. L., & Gureckis, T. M. (2004). SUSTAIN: A network model of category learning. Psychological Review, 111, 309-332]) cannot predict the sort type persistence effects we observe, but they are naturally accounted for by theories that posit strategic selection of a problem-solving strategy (e.g., Hypothesis theory, [Levine, M. (1971). Hypothesis theory and nonlearning despite ideal S-R-reinforcement contingencies. Psychological Review, 78, 130-140]).

Many naturally occurring categories vary across multiple stimulus dimensions (e.g. size, color, texture). When humans categorize multidimensional stimuli on the basis of a single dimension this has been taken to indicate use of a rule that could be verbalized. Sorting on the basis of all the stimulus dimensions (‘overall similarity’ or ‘family resemblance’) has been taken to indicate a more basic, implicit, automatic, perhaps associative process. However, a review of the literature on animal discrimination learning shows that animals often discriminate on the basis of one dominant dimension. In recent experiments, situations conducive to more complex cognitive processes have increased family resemblance sorting in humans. In an effort to resolve this apparent paradox, experiments were conducted in which humans and pigeons were exposed to multidimensional category discrimination tasks under closely similar conditions. Preliminary results show no evidence that even a non-verbal rule can be said to be involved in pigeons’ choices in these conditions, despite the fact that under some conditions a single dimension may dominate their behavior.