Explicit Category Learning Research Articles

Discrimination sensitivity of visual shapes sharpens in autistic adults but only after explicit category learning

BackgroundCategorization and its influence on perceptual discrimination are essential processes to organize information efficiently. Individuals with Autism Spectrum Condition (ASC) are suggested to display enhanced discrimination on the one hand, but also to experience difficulties with generalization and ignoring irrelevant differences on the other, which underlie categorization. Studies on categorization and discrimination in ASC have mainly focused on one process at a time, however, and typically only used either behavioral or neural measures in isolation. Here, we aim to investigate the interrelationships between these perceptual processes using novel stimuli sampled from a well-controlled artificial stimulus space. In addition, we complement standard behavioral psychophysical tasks with frequency-tagging EEG (FT-EEG) to obtain a direct, non-task related neural index of discrimination and categorization.MethodsThe study was completed by 38 adults with ASC and 38 matched neurotypical (NT) individuals. First, we assessed baseline discrimination sensitivity by administering FT-EEG measures and a complementary behavioral task. Second, participants were trained to categorize the stimuli into two groups. Finally, participants again completed the neural and behavioral discrimination sensitivity measures.ResultsBefore training, NT participants immediately revealed a categorical tuning of discrimination, unlike ASC participants who showed largely similar discrimination sensitivity across the stimuli. During training, both autistic and non-autistic participants were able to categorize the stimuli into two groups. However, in the initial training phase, ASC participants were less accurate and showed more variability, as compared to their non-autistic peers. After training, ASC participants showed significantly enhanced neural and behavioral discrimination sensitivity across the category boundary. Behavioral indices of a reduced categorical processing and perception were related to the presence of more severe autistic traits. Bayesian analyses confirmed overall results.LimitationsData-collection occurred during the COVID-19 pandemic.ConclusionsOur behavioral and neural findings indicate that adults with and without ASC are able to categorize highly similar stimuli. However, while categorical tuning of discrimination sensitivity was spontaneously present in the NT group, it only emerged in the autistic group after explicit categorization training. Additionally, during training, adults with autism were slower at category learning. Finally, this multi-level approach sheds light on the mechanisms underlying sensory and information processing issues in ASC.

Explicit and implicit category learning in categorical visual search.

Categorical search has been heavily investigated over the past decade, mostly using natural categories that leave the underlying category mental representation unknown. The categorization literature offers several theoretical accounts of category mental representations. One prominent account is that separate learning systems account for classification: an explicit learning system that relies on easily verbalized rules and an implicit learning system that relies on an associatively learned (nonverbalizable) information integration strategy. The current study assessed the contributions of these separate category learning systems in the context of categorical search using simple stimuli. Participants learned to classify sinusoidal grating stimuli according to explicit or implicit categorization strategies, followed by a categorical search task using these same stimulus categories. Computational modeling determined which participants used the appropriate classification strategy during training and search, and eye movements collected during categorical search were assessed. We found that the trained categorization strategies overwhelmingly transferred to the verification (classification response) phase of search. Implicit category learning led to faster search response and shorter target dwell times relative to explicit category learning, consistent with the notion that explicit rule classification relies on a more deliberative response strategy. Participants who transferred the correct category learning strategy to the search guidance phase produced stronger search guidance (defined as the proportion of trials on which the target was the first item fixated) with evidence of greater guidance in implicit-strategy learners. This demonstrates that both implicit and explicit categorization systems contribute to categorical search and produce dissociable patterns of data.

Multisensory transfer effects in implicit and explicit category learning.

In category learning, transfer emerges when individuals apply the knowledge or strategy learned with one set of stimuli to a novel set. Under multisensory circumstances, it remains unclear whether the transfer occurs differently in implicit and explicit category learning, as it remains controversial whether explicit knowledge is indispensable for transfer. To address this issue, we adopted multisensory stimuli in implicit (i.e., information integration, II) and explicit (i.e., conjunctive rule-based, RB) category learning tasks. Experiment 1 showed that when training and novel sets shared the same feature modalities, spontaneous transfer without feedback was perfect in the II condition but impaired in the RB condition. However, with feedback, the dependent transfer occurred equally between conditions. Experiment 2 revealed that when across different feature modalities, no spontaneous transfer was observed in any of the two conditions. A dependent transfer occurred in the RB but not in the II condition. Experiment 3 found that delayed feedback disrupted II task performance but not RB task performance, indicating that people did not learn the II task using an explicit rule. The current study demonstrated that transfer to novel stimuli could emerge in explicit and implicit category learning within feature modalities. However, the transfer across feature modalities could only arise with feedback in explicit learning. We further discuss these findings' meaning with the current category learning theory.

A dissociation between conceptual prominence and explicit category learning: Evidence from agent and patient event roles.

We investigate whether linguistic categories have the same structure as categories used to conceptualize the world outside of language. We focus on the event roles Agent and Patient (in the sentence Murray ate the ice cream, Murray is the Agent and the ice cream is the Patient). These categories appear to be tightly linked across language and cognition: they are encoded robustly in the world's languages and have been argued to be highly prominent conceptually, even part of innate core knowledge. This view predicts (a) that Agent and Patient categories will be readily accessible to adults in explicit categorization tasks and (b) that these categories have similar structure across semantic and conceptual domains. We tested these predictions across four experiments in which adult speakers of English had to induce Agent and Patient categories from visual illustrations of events (e.g., one figure kicking another). We found that 25% to 40% of participants failed to induce the categories, suggesting that prominent concepts are not always easily accessed for conscious reasoning. At the same time, for those participants who did induce the categories, they generalized these categories in ways predicted by previous analyses of English syntax. This finding supports the view that Agent and Patient are domain-general, spanning both conceptual and linguistic representation, though not necessarily used by participants in explicit categorization tasks. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Conceptual anchoring dissociates implicit and explicit category learning.

Categorization researchers have long debated the possibility of multiple category-learning systems. The need persists for paradigms that dissociate explicit-declarative category-learning processes (featuring verbalizable category rules) from implicit-procedural processes (featuring stimulus-response associations lying beneath declarative cognition). The authors contribute a new paradigm, using perfectly matched exclusive-or (XOR) category tasks differing only in the availability or absence of easily verbalizable conceptual content. This manipulation transformed learning. The conceptual task alone was learned suddenly, by insightful rule discovery, producing explicit-declarative XOR knowledge. The perceptual task was learned more gradually, consistent with associative-learning processes, producing impoverished declarative knowledge. We also tested participants under regimens of immediate and deferred reinforcement. The conceptual task alone was learned through processes that survive the loss of trial-by-trial reinforcement. All results support the idea that humans have perceptual-associative processes for implicit learning, but also an overlain conceptual system that under the right circumstances constitutes a parallel explicit-declarative category-learning system. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Supplemental Material for Conceptual Anchoring Dissociates Implicit and Explicit Category Learning

Supplemental Material for Conceptual Anchoring Dissociates Implicit and Explicit Category Learning

Simulating category learning and set shifting deficits in patients weight-restored from anorexia nervosa.

To examine set shifting in a group of women previously diagnosed with anorexia nervosa who are now weight-restored (AN-WR) and then apply a biologically based computational model (Competition between Verbal and Implicit Systems [COVIS]) to simulate the pattern of category learning and set shifting performances observed. Nineteen AN-WR women and 35 control women (CW) were administered an explicit category learning task that required rule acquisition and then a set shift following a rule change. COVIS was first fit to the behavioral results of the controls and then parameters of the model theoretically relevant to AN were altered to mimic the behavioral results. Relative to CW, the AN-WR group displayed steeper learning curves (i.e., hyper learning) before the rule shift, but greater difficulty in learning the new categories after the rule shift (i.e., a deficit in set shifting). Hyper learning and set shifting deficits in the AN-WR group were not associated and differentially correlated with clinical measures. Hyper learning in the AN-WR group was simulated by increasing the model parameter that represents sensitivity to negative feedback (δ parameter), whereas the deficit in set shifting was simulated by altering the parameters that represent changes in rule selection and flexibility (λ and γ parameters, respectively). These simulations suggest that multiple factors can impact category learning and set shifting in AN-WR individuals (e.g., alterations in sensitivity to negative feedback, rule selection deficits, and inflexibility) and provide an important starting point to further investigate this pervasive deficit in adult AN.

Deferred Feedback Sharply Dissociates Implicit and Explicit Category Learning

The controversy over multiple category-learning systems is reminiscent of the controversy over multiple memory systems. Researchers continue to seek paradigms to sharply dissociate explicit category-learning processes (featuring category rules that can be verbalized) from implicit category-learning processes (featuring learned stimulus-response associations that lie outside declarative cognition). We contribute a new dissociative paradigm, adapting the technique of deferred-rearranged reinforcement from comparative psychology. Participants learned matched category tasks that had either a one-dimensional, rule-based solution or a multidimensional, information-integration solution. They received feedback either immediately or after each block of trials, with the feedback organized such that positive outcomes were grouped and negative outcomes were grouped (deferred-rearranged reinforcement). Deferred reinforcement qualitatively eliminated implicit, information-integration category learning. It left intact explicit, rule-based category learning. Moreover, implicit-category learners facing deferred-rearranged reinforcement turned by default and information-processing necessity to rule-based strategies that poorly suited their nominal category task. The results represent one of the strongest explicit-implicit dissociations yet seen in the categorization literature.

Re-evaluating Dissociations between Implicit and Explicit Category Learning: An Event-related fMRI Study

Recent fMRI studies have found that distinct neural systems may mediate perceptual category learning under implicit and explicit learning conditions. In these previous studies, however, different stimulus-encoding processes may have been associated with implicit versus explicit learning. The present design was aimed at decoupling the influence of these factors on the recruitment of alternate neural systems. Consistent with previous reports, following incidental learning in a dot-pattern classification task, participants showed decreased neural activity in occipital visual cortex (extrastriate region V3, BA 19) in response to novel exemplars of a studied category compared to members of a foil category, but did not show this decreased neural activity following explicit learning. Crucially, however, our results show that this pattern was primarily modulated by aspects of the stimulus-encoding instructions provided at the time of study. In particular, when participants in an implicit learning condition were encouraged to evaluate the overall shape and configuration of the stimuli during study, we failed to find the pattern of brain activity that has been taken to be a signature of implicit learning, suggesting that activity in this area does not uniquely reflect implicit memory for perceptual categories but instead may reflect aspects of processing or perceptual encoding strategies.

Development of implicit and explicit category learning

We present two studies that examined developmental differences in the implicit and explicit acquisition of category knowledge. College-attending adults consistently outperformed school-age children on two separate information-integration paradigms due to children’s more frequent use of an explicit rule-based strategy. Accuracy rates were also higher for adults on a unidimensional rule-based task due to children’s more frequent use of the irrelevant dimension to guide their behavior. Results across these two studies suggest that the ability to learn categorization structures may be dependent on a child’s ability to inhibit output from the explicit system.

Removing the Frontal Lobes

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 suboptimal unidimensional strategies. With three-dimensional stimuli, a striking dissociation was observed between implicit and explicit category learning when participants performed a sequential working memory task. With explicit category learning, performance was impaired further, and there was an increased use of suboptimal 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.

Learning rule-described and non-rule-described categories: A comparison of children and adults.

Three experiments investigated the ability of 3-, 5-, and 8-year-old children as well as adults to learn sets of perceptual categories. Adults and children performed comparably on categories that could be learned by either a single-dimensional rule or by associative learning mechanisms. However, children showed poorer performance relative to adults in learning categories defined by a disjunctive rule and categories that were nonlinearly separable. Increasing the task demands for adults resulted in child-like performance on the disjunctive categories. Decreasing the task demands for children resulted in more adult-like performance on the disjunctive categories. The authors interpret these results within a multiple-systems approach to category learning and suggest that children have not fully developed the same explicit category learning system as adults.

Explicit category learning in Parkinson's disease: Deficits related to impaired rule generation and selection processes.

The present study examined the source of explicit category learning deficits previously noted in patients with Parkinson's disease (PD). Task stimuli consisted of 4 binary-valued cues that together determined category assignment, although some cues were more important for the categorization decision. Participants verbalized the hypotheses being tested to provide several measures of the hypothesis testing. Analyses of these verbal protocols indicated that PD patients were impaired on rule generation and selection but not rule shifting. Patients had particular difficulty noting the relative importance of the cues. Specific aspects of performance were differently correlated with neuropsychological measures of working memory and hypothesis testing ability. Together, the results suggest that the cognitive processes required for explicit category learning are mediated by partially distinct neural mechanisms.

340. Implicit versus explicit category learning: an event-related functional MRI study

340. Implicit versus explicit category learning: an event-related functional MRI study