Category learning is learning to classify stimuli into different groups, or categories. Corticostriatal networks connecting the striatum, including the caudate and putamen, with the cerebral cortex play an important role in category learning. The overall aim of this project is to differentiate between the functions that three of these networks, one linking the head of the caudate with frontal cortex, and one linking the body/tail of the caudate to visual cortex, and one linking the putamen with sensorimotor cortex, serve in classification learning using functional Magnetic Resonance Imaging (fMRI). Previous studies have linked the head of the caudate to processing feedback (i.e., being told that a classification response is correct or incorrect). The body and tail of the caudate, along with the putamen, has been linked to learning and executing associations between stimuli and categories.
The first aim i s to investigate the sensitivity of the head of the caudate to both verbal feedback and monetary reward, and compare how positive and negative associations with stimuli are represented.
The second aim i s to investigate how the body and tail of the caudate interacts with visual cortex during learning.
The third aim i s to distinguish between the roles of the body and tail of the caudate and putamen in categorization.
The fourth aim i s to separate the contributions of the striatum to categorization from those of the medial temporal lobe. The striatum is affected in many disorders, including Parkinson's disease, Huntington's disease, schizophrenia, and Tourette syndrome. Behavioral studies have shown that category learning is impaired in all of these disorders. The proposed studies may provide insight into the types of learning problems seen in patients with these diseases.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Cognition and Perception Study Section (CP)
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Rossi, Andrew
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Colorado State University-Fort Collins
Schools of Arts and Sciences
Fort Collins
United States
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Braunlich, Kurt; Seger, Carol A (2016) Categorical evidence, confidence, and urgency during probabilistic categorization. Neuroimage 125:941-952
Braunlich, Kurt; Gomez-Lavin, Javier; Seger, Carol A (2015) Frontoparietal networks involved in categorization and item working memory. Neuroimage 107:146-62
Liu, Zhiya; Song, Xiaohong; Seger, Carol A (2015) An Eye-Tracking Study of Multiple Feature Value Category Structure Learning: The Role of Unique Features. PLoS One 10:e0135729
Liu, Zhiya; Braunlich, Kurt; Wehe, Hillary S et al. (2015) Neural networks supporting switching, hypothesis testing, and rule application. Neuropsychologia 77:19-34
Seger, Carol A; Braunlich, Kurt; Wehe, Hillary S et al. (2015) Generalization in category learning: the roles of representational and decisional uncertainty. J Neurosci 35:8802-12
Peterson, Erik J; Seger, Carol A (2013) Many hats: intratrial and reward level-dependent BOLD activity in the striatum and premotor cortex. J Neurophysiol 110:1689-702
Seger, Carol A; Peterson, Erik J (2013) Categorization = decision making + generalization. Neurosci Biobehav Rev 37:1187-200
Ryals, Anthony J; Cleary, Anne M; Seger, Carol A (2013) Recall versus familiarity when recall fails for words and scenes: the differential roles of the hippocampus, perirhinal cortex, and category-specific cortical regions. Brain Res 1492:72-91
Seger, Carol A; Spiering, Brian J (2011) A critical review of habit learning and the Basal Ganglia. Front Syst Neurosci 5:66
Seger, Carol A; Dennison, Christina S; Lopez-Paniagua, Dan et al. (2011) Dissociating hippocampal and basal ganglia contributions to category learning using stimulus novelty and subjective judgments. Neuroimage 55:1739-53

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