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The Cognitive Neuroscience of Category Learning

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The Cognitive Neuroscience of Category Learning ARTICLE IN PRESS Neuroscience and Biobehavioral Reviews 32 (2008) 193–196 www.elsevier.com/locate/neubiorev Editorial The cognitive neuroscience of category learning The study of category learning has been a central Work on the cognitive neuroscience of category learning paradigm within cognitive psychology for over 25 years. has already yielded many informative results. For example, Cognitive neuroscientists have been drawn to this para- neuropsychology studies have shown that many forms of digm for several reasons: first, there is a large body category learning are impaired in patients with dysfunc- of pre-existing empirical and theoretical analyses of tional basal ganglia or frontal lobes. This pattern of data, category learning. Neuropsychological studies of clinical mimicking what is often found with motor skills, provides populations and neuroimaging of healthy subjects provide some support for viewing some category learning as a insights into the cognitive neuroscience of category cognitive skill. Other recent and ongoing neuropsycholo- learning. Second, category learning has aspects of both gical studies are examining how category learning is elementary associative learning as well as higher-order affected by schizophrenia, obsessive–compulsive disorder cognition. On one hand, category learning can be viewed (OCD), attention deficit disorder (ADD), and a host of as a ‘‘cognitive skill’’ that shares behavioral properties, other mental health disorders. Parallel to these neuropsy- and possibly some neural substrates, with motor-skill chological studies, human brain imaging studies of learning and conditioning. On the other hand, categoriza- category learning have identified several key brain regions tion underlies many higher-order cognitive abilities. critical to category learning, including the medial temporal When a connoisseur distinguishes a cabernet from a lobes, basal ganglia, and prefrontal cortex. merlot, when a doctor recognizes that a patient’s symptoms Mathematical models provide a third line of research. are due to a particular disease, or when a weather Some researchers have used these models to analyze the forecaster uses today’s barometric pressure to predict nature of the underlying deficits in category learning to tomorrow’s weather, they are all doing complex categor- develop detailed hypotheses about the functional role of ization. It is this dual nature—part elementary skill, part the basal ganglia and medial temporal lobes. Other higher cognition—which helps make category learning a researchers have used neural network models of these valuable paradigm for studying the fundamental aspects of brain structures to begin to understand their contribution human learning at both the behavioral and neural levels of to category learning. analysis. The cognitive neuroscience of category learning is a new In a typical category learning experiment, subjects are and exciting interdisciplinary field with the potential to presented with stimuli that vary along several different meld theoretical and behavioral analyses from cognitive dimensions. Subjects are usually required to classify each psychology with techniques from cognitive neuroscience. item into one of a number of contrasting categories. For example, based on a list of symptoms (features) a subject The Cognitive Neuroscience of Category Learning may be asked to make a disease diagnosis (categorization). Collaborative Consortium Although subjects may initially have to guess, they can eventually learn which features and patterns are more In the spring of 2002, the J.S. McDonnell Foundation likely to fall into one category versus another based on awarded Rutgers University—Newark a three-year grant trial-by-trial feedback. Building on an extensive base of to create a multidisciplinary collaborative consortium of empirical data from psychological studies of category researchers working in the Cognitive Neuroscience of learning over the last 30 years, mathematical modelers Category Learning. The consortium was directed by an have developed rigorous quantitative models of category Executive Committee, which included Robert Nosofsky learning that account for a wide range of behavioral (Indiana), Paul Reber (Northwestern), Russell Poldrack phenomena and predict novel psychological phenomena. (UCLA), and Mark Gluck (Rutgers-Newark), the principal Building on these behavioral models, cognitive neuroscien- investigator. The consortium hosted three annual two-day tists have begun to explore and exploit the richness of workshops on the Cognitive Neuroscience of Category category learning as a tool for increasing our under- Learning, each of which was attended by approximately standing of the brain mechanisms of cognition. 50–70 people. Proceedings from the meetings, including 0149-7634/$ - see front matter r 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.neubiorev.2007.11.002 ARTICLE IN PRESS 194 Editorial / Neuroscience and Biobehavioral Reviews 32 (2008) 193–196 copies of all talks and posters, were distributed each year to declarative knowledge, whereas single-system theorists workshop attendees and to approximately 150 additional have argued that their approach is more parsimonious researchers and students in the field. In addition to the because it only postulates a single form of memory annual workshops, the consortium supported interdisci- representation. They argue that the multiple-memory plinary summer rotations of students between laboratories, systems approach is superior in its ability to account for pilot collaborative projects, shared neuropsychological a broad range of data from psychology and neuroscience. patient access, and collaborative travel expenses. The Szabolcs Ke´ri, in his article on ‘‘Interactive memory conference and other programs were expanded through systems and category learning in schizophrenia,’’ reviews supplemental matching support from the National Science evidence suggesting that information is processed and Foundation and the National Institute of Mental Health. represented by multiple-interacting-memory systems in the With the conclusion of this three-year consortium, this brain, including prefrontal cortex, basal ganglia, and special issue of Neuroscience and Biobehavioral Reviews medial temporal lobe, all of which are implicated in the seeks to present the broader scientific community with a pathophysiology of schizophrenia. Executive and declara- collection of its highlights, emphasizing new multidisci- tive memory dysfunctions are well known in schizophrenia. plinary collaborations and research which emerged from However, there are also habit-learning deficits in schizo- this three-year program. phrenia which, Keri argues, suggest that dopaminergic and Our annual workshops provided a unique venue for other neurochemical processes in the basal ganglia may bringing together researchers with a broad range of play a crucial role in the pathophysiology and pharmacol- approaches, including animal and human researchers, ogy of schizophrenia. In this article, Keri shows how the clinical and experimental researchers, and psychologists investigation of different classification learning functions, and cognitive neuroscientists. What made these meetings including reward- and feedback-guided learning and unique was not just the broad interdisciplinary back- acquired equivalence learning, may shed light on the grounds of the participants, but the narrow and clear focus neuropsychology, pathophysiology, pharmacology, and of the behavioral paradigms which they are studying—this behavioral genetics of schizophrenia. combination of divergent methods and convergent para- In ‘‘Basal ganglia and dopamine contributions to digms—made these meetings especially valuable in moving probabilistic category learning,’’ Daphna Shohamy, forward research on the cognitive neuroscience of learning Catherine Myers, Jeevan Kalanithi, and Mark Gluck and memory. review behavioral, neuropsychological, functional neuroi- maging, and computational studies of basal ganglia and Overview of this special issue dopamine contributions to learning in humans. The authors argue that, collectively, these studies implicate the The nine articles included in this issue were selected to basal ganglia in incremental, feedback-based learning that represent a broad swath of multidisciplinary approaches involves integrating information across multiple experi- including both animal and human research, theoretical and ences. The medial temporal lobes, by contrast, contribute empirical studies, drawing on data from behavioral, to rapid encoding of relations between stimuli and support clinical, and brain imaging studies. Given the size and flexible generalization of learning to novel contexts and page limits of the journal, it is not possible to include a stimuli. Shohamy and colleagues argue that by breaking comprehensive survey of the state-of-field nor to include down our understanding of the cognitive and neural everyone who has made important contributions to the mechanisms contributing to different aspects of learning, field over the last years. For this reason, we have to use the new studies are providing insight into how, and when, these issue to highlight ‘‘selected topics’’ in the Cognitive different processes support learning, how they may interact Neuroscience of Category Learning, particularly projects with each other, and the consequence of different forms of involving new collaborations that emerged during the learning for the representation of knowledge. three-year
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