Category learning and multiple memory systems (original) (raw)
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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,
A role for the perceptual representation memory system in category learning
Perception & Psychophysics, 2008
There is growing evidence and theoretical speculation that all major memory systems contribute to category learning (Ashby & O'Brien, 2005). For example, empirical evidence suggests that at least some types of category learning are mediated by working memory (DeCaro,
Multiple Systems of Perceptual Category Learning
Handbook of Categorization in Cognitive Science, 2005
There is widespread agreement that multiple qualitatively different category learning systems mediate the learning of different category structures. Two systems that have received support are (1) a frontal-based explicit system that uses logical reasoning, depends on working memory and executive attention, and is mediated primarily by the anterior cingulated, the prefrontal cortex, and the head of the caudate, and (2) a basal ganglia-mediated implicit system that uses procedural learning and requires a dopamine reward signal. This chapter reviews a large body of work conducted in our laboratories that examines the details of the two proposed systems using neurological patients as experimental participants. Collectively the studies suggest little involvement of the medial temporal lobes in category learning with large categories. They also suggest that, in striatal-damaged patients, the need to ignore irrelevant information is predictive of a rule-based category learning deficit, whereas the complexity of the rule is predictive of an information-integration category learning deficit.
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...
Journal of Experimental Psychology: Learning, Memory, and Cognition, 2012
This special section brings together behavioral, computational, mathematical, and neuroimaging approaches to understand the processes underlying category learning. Over the past decade, there has been growing convergence in research on categorization, with computational-mathematical models influencing the interpretation of brain imaging and neuropsychological data, and with cognitive neuroscience findings influencing the development and refinement of models. Classic debates between single-system and multiple-memory-system theories have become more nuanced and focused. Multiple brain areas and cognitive processes contribute to categorization, but theories differ markedly in whether and when those neurocognitive components are recruited for different aspects of categorization. The articles in this special section approach this issue from several diverse angles.
A role for the medial temporal lobes in category learning
Learning & Memory
Despite much research, the role of the medial temporal lobes (MTL) in category learning is unclear. Two unstructured categorization experiments explored conditions that might recruit MTL category learning and memory systems—namely, whether the stimulus display includes one or two stimuli, and whether category membership depends on configural properties of the stimulus features. The results supported three conclusions. First, in agreement with prior research, learning with single stimulus displays depended on striatal-mediated procedural learning. Second, and most important, learning with pair displays was mediated by MTL declarative memory systems. Third, the use of stimuli in which category membership depends on configural properties of the stimulus features made MTL learning slightly more likely. Overall, the results suggested that the MTL are most likely to mediate learning when the participant must decide which of two configural stimuli belongs to a selected category.
Category learning in the brain
2010
The ability to group items and events into functional categories is a fundamental characteristic of sophisticated thought. It is subserved by plasticity in many neural systems, including neocortical regions (sensory, prefrontal, parietal, and motor cortex), the medial temporal lobe, the basal ganglia, and midbrain dopaminergic systems. These systems interact during category learning.
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.
The contribution of temporary storage and executive processes to category learning
Acta psychologica, 2015
Three distinctly different working memory processes, temporary storage, mental shifting and inhibition, were proposed to account for individual differences in category learning. A sample of 213 participants completed a classic category learning task and two working memory tasks that were experimentally manipulated for tapping specific working memory processes. Fixed-links models were used to decompose data of the category learning task into two independent components representing basic performance and improvement in performance in category learning. Processes of working memory were also represented by fixed-links models. In a next step the three working memory processes were linked to components of category learning. Results from modeling analyses indicated that temporary storage had a significant effect on basic performance and shifting had a moderate effect on improvement in performance. In contrast, inhibition showed no effect on any component of the category learning task. These...
Memory, reasoning, and categorization: parallels and common mechanisms
Frontiers in Psychology, 2014
Traditionally, memory, reasoning, and categorization have been treated as separate components of human cognition. We challenge this distinction, arguing that there is broad scope for crossover between the methods and theories developed for each task. The links between memory and reasoning are illustrated in a review of two lines of research. The first takes theoretical ideas (two-process accounts) and methodological tools (signal detection analysis, receiver operating characteristic curves) from memory research and applies them to important issues in reasoning research: relations between induction and deduction, and the belief bias effect. The second line of research introduces a task in which subjects make either memory or reasoning judgments for the same set of stimuli. Other than broader generalization for reasoning than memory, the results were similar for the two tasks, across a variety of experimental stimuli and manipulations. It was possible to simultaneously explain performance on both tasks within a single cognitive architecture, based on exemplar-based comparisons of similarity. The final sections explore evidence for empirical and processing links between inductive reasoning and categorization and between categorization and recognition. An important implication is that progress in all three of these fields will be expedited by further investigation of the many commonalities between these tasks.