The scientist’s investigation covers issues in Neuroscience, Cognition, Artificial intelligence, Associative learning and Basal ganglia. Mark A. Gluck frequently studies issues relating to Parkinson's disease and Neuroscience. His Cognition research includes elements of Concept learning, Cognitive psychology, Latent inhibition and Reinforcement learning.
His Concept learning study combines topics from a wide range of disciplines, such as Discrimination learning and Stimulus generalization. The study incorporates disciplines such as Machine learning, Social psychology and Classical conditioning in addition to Artificial intelligence. His study brings together the fields of Cognitive science and Associative learning.
His primary areas of study are Neuroscience, Cognition, Associative learning, Classical conditioning and Hippocampal formation. His study ties his expertise on Parkinson's disease together with the subject of Neuroscience. The concepts of his Cognition study are interwoven with issues in Cognitive psychology, Audiology, Developmental psychology, Disease and Depression.
His biological study deals with issues like Probabilistic logic, which deal with fields such as Categorization. Mark A. Gluck has researched Associative learning in several fields, including Functional magnetic resonance imaging and Generalization. His study in Classical conditioning is interdisciplinary in nature, drawing from both Entorhinal cortex, Cognitive science and Artificial intelligence.
Mark A. Gluck mainly investigates Cognition, Disease, Neuroscience, Gerontology and Cognitive psychology. His Cognition research includes themes of Audiology, Parkinson's disease, Functional magnetic resonance imaging, Associative learning and Depression. His work carried out in the field of Parkinson's disease brings together such families of science as Developmental psychology and Reinforcement learning.
As a part of the same scientific study, Mark A. Gluck usually deals with the Associative learning, concentrating on Striatum and frequently concerns with Putamen. His study involves Hippocampus, Prefrontal cortex, Rapid eye movement sleep, Sleep in non-human animals and Stimulation, a branch of Neuroscience. His Cognitive psychology study incorporates themes from Probabilistic logic, Memory consolidation, Age related and Healthy aging.
Cognition, Neuroscience, Hippocampus, Gerontology and Sleep are his primary areas of study. He interconnects Associative learning, Apolipoprotein E, Disease and Laterality in the investigation of issues within Cognition. His biological study spans a wide range of topics, including Hippocampal formation, Neural correlates of consciousness, Disease risk and Risk factor.
His Neuroscience study frequently links to adjacent areas such as Developmental psychology. He has included themes like Resting state fMRI, Prefrontal cortex, Episodic memory and Neuropsychology in his Hippocampus study. His studies deal with areas such as Striatum, Lateralization of brain function, Audiology, Parkinson's disease and Putamen as well as Functional magnetic resonance imaging.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Interactive memory systems in the human brain.
R. A. Poldrack;J. Clark;E. J. Paré-Blagoev;D. Shohamy.
Nature (2001)
From conditioning to category learning: an adaptive network model.
Mark A. Gluck;Gordon H. Bower.
Journal of Experimental Psychology: General (1988)
Probabilistic classification learning in amnesia.
Barbara J. Knowlton;Larry R. Squire;Mark A. Gluck.
Learning & Memory (1994)
Pictures and names: Making the connection ☆
Pierre Jolicoeur;Mark A. Gluck;Stephen M. Kosslyn.
Cognitive Psychology (1984)
Hippocampal mediation of stimulus representation: A computational theory
Mark A. Gluck;Catherine E. Myers.
Hippocampus (1993)
A novelty detection approach to classification
Nathalie Japkowicz;Catherine Myers;Mark Gluck.
international joint conference on artificial intelligence (1995)
Information, Uncertainty and the Utility of Categories
M. Gluck.
Proc.of the Seventh Annual Conf.on Cognitive Science Society (1985)
Comparing modes of rule-based classification learning: A replication and extension of Shepard, Hovland, and Jenkins (1961)
Robert M. Nosofsky;Mark A. Gluck;Thomas J. Palmeri;Stephen C. Mckinley.
Memory & Cognition (1994)
Cortico‐striatal contributions to feedback‐based learning: converging data from neuroimaging and neuropsychology
Daphna Shohamy;C. E. Myers;S. Grossman;J. Sage.
Brain (2004)
Evaluating an adaptive network model of human learning
Mark A Gluck;Gordon H Bower.
Journal of Memory and Language (1988)
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