Corticostriatal Networks In Human Categorization
Carol A Seger, Associate Professor
Colorado State University-fort Collins Fort Collins, Co 80523
Grant 1R01MH079182-01A1 from National Institute Of Mental Health IRG: CP
Abstract: 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 is 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 is to investigate how the body and tail of the caudate interacts with visual cortex during learning. The third aim is to distinguish between the roles of the body and tail of the caudate and putamen in categorization. The fourth aim is 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.
Keywords: caudate nucleus, executive function, learning, neural information processing, neuropsychology, putamen, auditory feedback, reinforcer, temporal lobe /cortex, visual cortex, behavioral /social science research tag, clinical research, functional magnetic resonance imaging, human subject
Project start date: 2007-07-03
Project end date: 2012-05-31
1R01MH079182-01A1 (2007): $220500
Sponsored Links Excellgen http://Excellgen.com
Grants awarded to Carol A Seger
Neural Substrates Of Concept Learning
Carol A Seger
Psychologycolorado State University-fort Collins
fort Collins, Co 80523
Grant 1R03MH063784-01 from National Institute Of Mental Health IRG: ZMH1
Abstract: Concept learning is learning about the regularities or patterns that separate stimuli into different groups, or concepts. The overall aim of this project is to differentiate between forms of concept learning and their constituent subprocesses through the identification of participating neural systems using functional Magnetic Resonance Imaging (fMRI). The first aim is to dissociate the neural substrates of rule learning (classifying on the basis of a verbalizable rule, such as "always choose the blue stimulus") from exemplar learning (classifying on the basis of similarity to previously learned stimuli), and to compare the brain activity of learners with persons who fail to learn. The second aim is to dissociate the neural systems underlying rule formation from rule application. Rule learning is dependent on executive functions subserved by the frontal lobes, and thus these studies have the potential to elucidate the pattern of deficits seen in patients with frontal lobe damage due to stroke or traumatic brain injury. The third aim is to related recruitment of striatal brain structures in concept learning to the degree that a probabilistic relationship exists between a stimulus and its concept membership. Because the striatum is damaged in disorders such as Parkinson´s and Huntington´s diseases, this study may provide insight into the types of learning problems seen in patients with these diseases
Keywords: brain metabolism, concept, corpus striatum, learning psychological model behavioral /social science research tag, clinical research, functional magnetic resonance imaging, human subject
Project start date: 2001-09-01
Project end date: 2003-12-31
1R03MH063784-01 (2001): $72500
CORTICOSTRIATAL NETWORKS IN HUMAN CATEGORIZATION
Carol A Seger
Colorado State University-fort Collins, Fort Collins, Co 80523
Grant 5R01MH079182-04 from National Institute Of Mental Health
Abstract: 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 is 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 is to investigate how the body and tail of the caudate interacts with visual cortex during learning. The third aim is to distinguish between the roles of the body and tail of the caudate and putamen in categorization. The fourth aim is 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
Keywords: AD/HD; ADHD; Accounting; Affect; Area; Attention deficit hyperactivity disorder; Attention-Deficit Disorder, Predominantly Hyperactive-Impulsive Type; Basal Ganglia Diseases; Basal Ganglia Disorders; Behavior; Behavioral; Body Regions; Brain imaging; Categories; Cerebral cortex; Classification; Computer Simulation; Computerized Models; Corpus Striatum; Corpus striatum structure; Disease; Disorder; Environment; Event; Feedback; Functional Imaging; Functional Magnetic Resonance Imaging; Gilles de la Tourette syndrome; Gilles de la Tourette`s Disease; Goals; Guinon`s disease; Head; Human; Human, General; Huntington Chorea; Huntington Disease; Huntington`s; Huntington`s Disease; Huntington`s Disease Pathway; Huntingtons Disease; Hyperactivity Disorder NOS; Hyperactivity Disorder, Predominantly Hyperactive-Impulsive Type; Hyperkinetic Syndrome; Idiopathic Parkinson Disease; Image; Impairment; Individual; Investigators; Knowledge; Learning; Lewy Body Parkinson Disease; Link; Location; MRI, Functional; Magnetic Resonance Imaging, Functional; Man (Taxonomy); Man, Modern; Mathematical Model Simulation; Mathematical Models and Simulations; Medial; Medical; Memory; Models, Computer; Motor; Outcome; Paralysis Agitans; Parkinson; Parkinson Disease; Parkinson`s; Parkinson`s disease; Parkinsons disease; Patients; Pharmaceutical Agent; Pharmaceuticals; Pharmacologic Substance; Pharmacological Substance; Physical Health Services / Rehabilitation; Physiologic Imaging; Play; Prefrontal Cortex; Primary Parkinsonism; Procedures; Process; Progressive Chorea, Hereditary, Chronic (Huntington); Putamen; Recruitment Activity; Rehabilitation; Rehabilitation therapy; Rehabilitation, Medical; Relative; Relative (related person); Reliance; Research; Research Personnel; Researchers; Rewards; Role; Schizophrenia; Schizophrenic Disorders; Simulation, Computer based; Stimulus; Striate Body; Striatum; Structure; Structure of putamen; System; System, LOINC Axis 4; Systematics; Tail; Temporal Lobe; Testing; Tic Disorder, Combined Vocal and Multiple Motor; Time; Time Factors; Tourette Syndrome; Tourette`s; Tourette`s Disease; Tourette`s Disorder; Tourette`s Syndrome; Variant; Variation; Ventral Striatum; Visual; Visual Cortex; addiction; attention deficit hyperactive disorder; base; brain visualization; cognitive neuroscience; computational modeling; computational models; computational simulation; computer based models; computerized modeling; computerized simulation; dementia praecox; disease/disorder; executive control; executive function; expectation; fMRI; frontal cortex; frontal lobe; fusiform face area; imaging; in silico; insight; interest; maladie des tics; member; prototype; putamen; recruit; rehabilitative; response; reward processing; schizophrenic; social role; striatal; temporal cortex; temporal lobe/cortex; tic de Guinon; virtual simulation; visual cortical; visual process; visual processing
Project start date: 2007-07-03
Project end date: 2012-05-31
Budget start date: 1-JUN-2010
Budget end date: 31-MAY-2011
5R01MH079182-04 (2010): $220500
5R01MH079182-03 (2009): $220500
COGNITIVE NEUROPSYCHOLOGY OF IMPLICIT LEARNING
Carol A Seger
Stanford University Stanford, Ca 94305
Grant 5F32MH010925-03 from National Institute Of Mental Health IRG: SRCM
5F32MH010925-03 (1996): $28600
1F32MH010925-01 (1994): $22608