The time course of explicit and implicit categorization (original) (raw)
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The cognitive neuroscience of implicit category learning
Advances in consciousness research, 2003
There is much recent interest in the question of whether people have available a single category learning system or a number of qualitatively different systems. Most proponents of multiple systems have hypothesized an explicit, rule-based system and some type of implicit system. Although there has been general agreement about the nature of the explicit system, there has been disagreement about the exact nature of the implicit system. This chapter explores the question of whether there is implicit category learning, and if there is, what form it might take. First, we examine what the word "implicit" means in the categorization literature. Next, we review some of the evidence that supports the notion that people have available one or more implicit categorization systems. Finally, we consider the nature of implicit categorization by focusing on three alternatives: an exemplar memory-based system, a procedural memory system, and an implicit system that uses the perceptual representation memory system.
On the nature of implicit categorization
Psychonomic Bulletin & Review, 1999
Current categorization models disagree about whether people make a priori assumptions about the structure of unfamiliar categories. Data from two experiments provided strong evidence that people do not make such assumptions. These results rule out prototype models and many decision bound models of categorization. We review previously published neuropsychological results that favor the assumption that category learning relies on a procedural-memory-based system, rather than on an instance-based system (as is assumed by exemplar models). On the basis ofthese results, a new categorylearning model is proposed that makes no a priori assumptions about category structure and that relies on procedural learning and memory. There is much recent evidence that human category learning relies on multiple systems (e.g.
A neuropsychological theory of multiple systems in category learning
Psychological Review, 1998
A neuropsychological theory is proposed that assumes category learning is a competition between separate verbal and implicit (i.e., procedural-learning-based) categorization systems. The theory assumes that the caudate nucleus is an important component of the implicit system and that the anterior cingulate and prefrontal cortices are critical to the verbal system. In addition to making predictions for normal human adults, the theory makes specific predictions for children, elderly people, and patients suffering from Parkinson's disease, Huntington's disease, major depression, amnesia, or lesions of the prefrontal cortex. Two separate formal descriptions of the theory are also provided. One describes trial-by-trial learning, and the other describes global dynamics. The theory is tested on published neuropsychological data and on category learning data with normal adults. Humans are remarkably adept at categorizing objects and events in their environment. In fact, it is now well established that humans can learn some extremely complex (i.e., nonlinear) categorization rules (e.g., Ashby & Maddox, 1992; McKinley & Nosofsky, 1995; Medin& Schwanenfiugel, 1981). One characteristic of demanding categorization problems is that experts use rules that are often difficult or impossible to describe verbally. For example, it is difficult to verbalize the decision rules used by farmers to sex chicks, those used by wine tasters to determine that a certain wine is a Zinfandel or a Cabernet Sanvignon, or those used by artists to categorize unfamiliar paintings according to the Renaissance master who created them. On the other hand, in many cases, contrasting categories are separated perfectly (or nearly so) by some decision rule that can be described verbally. For example, a simple verbal rule separates triangles from rectangles, oranges from lemons, and evergreens from deciduous trees. Current theories of category learning do not discriminate between these two kinds of tasks. Rather, they assume that all rules, whether verbal or nonverbal, are learned by using the same basic processes. Nevertheless, growing evidence indicates a qualitative difference in performance depending on whether the optimal decision rule-that is, the rule that maximizes categorization accuracy-can be described verbally. For example,
Dissociating explicit and procedural-learning based systems of perceptual category learning
Behavioural Processes, 2004
A fundamental question is whether people have available one category learning system, or many. Most multiple systems advocates postulate one explicit and one implicit system. Although there is much agreement about the nature of the explicit system, there is less agreement about the nature of the implicit system. In this article, we review a dual systems theory of category learning called competition between verbal and implicit systems (COVIS) developed by Ashby et al. (1998). The explicit system dominates the learning of verbalizable, rule-based category structures and is mediated by frontal brain areas such as the anterior cingulate, prefrontal cortex (PFC), and head of the caudate nucleus. The implicit system, which uses procedural learning, dominates the learning of non-verbalizable, information-integration category structures, and is mediated by the tail of the caudate nucleus and a dopamine-mediated reward signal. We review nine studies that test six a priori predictions from COVIS, each of which is supported by the data.
The neurobiology of category learning
Behavioral and cognitive neuroscience reviews, 2004
Many recent studies have examined the neural basis of category learning. Behavioral neuroscience results suggest that both the prefrontal cortex and the basal ganglia play important category-learning roles; neurons that develop category-specific firing properties are found in both regions, and lesions to both areas cause category-learning deficits. Similar studies indicate that the inferotemporal cortex does not mediate the learning of new categories. The cognitive neuroscience literature on category learning appears contradictory until the results are partitioned according to the type of category-learning task that was used. Three major tasks can be identified: rule based, information-integration, and prototype-distortion. Recent results are consistent with the hypotheses that (a) learning in rule-based tasks requires working memory and executive attention and is mediated by frontal-striatal circuits, (b) learning in information-integration tasks requires procedural memory and is m...
Learning and transfer of category knowledge in an indirect categorization task
Psychological Research, 2012
Knowledge representations acquired during category learning experiments are 'tuned' to the task goal. A useful paradigm to study category representations is indirect category learning. In the present article, we propose a new indirect categorization task called the "Same"-"Different" categorization task. The same-different categorization task is a regular same-different task, but the question asked to the participants is about the stimulus category membership instead of stimulus identity. Experiment 1 explores the possibility of indirectly learning rule-based and information-integration category structures using the new paradigm. The results suggest that there is little learning about the category structures resulting from an indirect categorization task unless the categories can be separated by a one-dimensional rule. Experiment 2 explores whether a category representation learned indirectly can be used in a direct classification task (and viceversa). The results suggest that previous categorical knowledge acquired during a direct classification task can be expressed in the same-different categorization task only when the categories can be separated by a rule that is easily verbalized. Implications of these results for categorization research are discussed.
Journal of Neuroimmunology, 2009
The timing of activating memory about visual objects is important for theories of human cognition but largely unknown, especially for tasks like entry level categorization that activate semantic memory. We tested an implicit memory-categorization “equivalence” hypothesis of multiple memory systems theory that a cortical system that stores structural knowledge to support entry level categorization also stores long-term, perceptual implicit memory, resulting in priming of this knowledge. Event-related brain potentials (ERPs) were recorded to impoverished pictures of new and repeated objects that were similar in perceptual properties but differed in categorization success. The cortical dynamics of object knowledge were defined using categorization ratings and naming. As predicted, rating, naming, and repetition effects on a frontocentral N350 show that implicit memory modifies the object knowledge network supporting categorization. This ERP is a complex of components between 200 and 500 ms indexing temporally overlapping substates from more perceptual to more conceptual knowledge. A frontopolar N350 subcomponent defines the first substate of a process of object model selection from occipitotemporal cortex based on shape similarity, and indicates that implicit memory in this system is greater with better categorization success. Afterwards, parietal positivity and a slow wave index secondary, post-model selection processes, like evaluating the success of a decision or memory match, and working memory for overt report, respectively. Altogether, ERP findings support the equivalence hypothesis and a two-state interactive account of visual object knowledge, and delineate the timing of multiple memory systems.
Temporal dynamics of categorization: forgetting as the basis of abstraction and generalization
Frontiers in Psychology, 2014
Historically, models of categorization have focused on how learners track frequencies and co-occurrence information to abstract relevant category features for generalization. The current study takes a different approach by examining how the temporal dynamics of categorization affect abstraction and generalization. In the learning phase of the experiment, all relevant category features were presented an equal number of times across category exemplars. However, the relevant features were presented on one of two learning schedules: massed or interleaved. At a series of immediate and delayed tests, learners were asked to generalize to novel exemplars that contained massed features, interleaved features, or all novel features. The results of this experiment revealed that, at an immediate test, learners more readily generalized based upon features presented on a massed schedule. Conversely, at a delayed test, learners more readily generalized based upon features presented on an interleaved schedule, until information was no longer readily retrievable from memory. These findings suggest that forgetting and retrieval processes engendered by the temporal dynamics of learning are used as a basis of abstraction, implicating forgetting as a central mechanism of generalization.
Category label and response location shifts in category learning
Psychological Research Psychologische Forschung, 2010
The category shift literature suggests that rulebased classiWcation, an important form of explicit learning, is mediated by two separate learned associations: a stimulus-to-label association that associates stimuli and category labels, and a label-to-response association that associates category labels and responses. Three experiments investigate whether information-integration classiWcation, an important form of implicit learning, is also mediated by two separate learned associations. Participants were trained on a rule-based or an information-integration categorization task and then the association between stimulus and category label, or between category label and response location was altered. For rule-based categories, and in line with previous research, breaking the association between stimulus and category label caused more interference than breaking the association between category label and response location. However, no diVerences in recovery rate emerged. For information-integration categories, breaking the association between stimulus and category label caused more interference and led to greater recovery than breaking the association between category label and response location. These results provide evidence that information-integration category learning is mediated by separate stimulus-to-label and label-to-response associations. Implications for the neurobiological basis of these two learned associations are discussed.
Multiple stages of learning in perceptual categorization: evidence and neurocomputational theory
Psychonomic Bulletin & Review, 2015
Virtually all current theories of category learning assume that humans learn new categories by gradually forming associations directly between stimuli and responses. In information-integration category-learning tasks, this purported process is thought to depend on procedural learning implemented via dopamine-dependent cortical-striatal synaptic plasticity. This article proposes a new, neurobiologically detailed model of procedural category learning that, unlike previous models, does not assume associations are made directly from stimulus to response. Rather, the traditional stimulus-response (S-R) models are replaced with a two-stage learning process. Multiple streams of evidence (behavioral, as well as anatomical and fMRI) are used as inspiration for the new model, which synthesizes evidence of multiple distinct cortical-striatal loops into a neurocomputational theory. An experiment is reported to test a priori predictions of the new model that: (1) recovery from a full reversal should be easier than learning new categories equated for difficulty, and (2) reversal learning in procedural tasks is mediated within the striatum via dopamine-dependent synaptic plasticity. The results confirm the predictions of the new two-stage model and are incompatible with existing S-R models.