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Models of Information Processing in the Basal Ganglia
Abstract
This book brings together the biology and computational features of the basal ganglia and their related cortical areas along with select examples of how this knowledge can be integrated into neural network models. Recent years have seen a remarkable expansion of knowledge about the anatomical organization of the part of the brain known as the basal ganglia, the signal processing that occurs in these structures, and the many relations both to molecular mechanisms and to cognitive functions. This book brings together the biology and computational features of the basal ganglia and their related cortical areas along with select examples of how this knowledge can be integrated into neural network models. Organized in four parts - fundamentals, motor functions and working memories, reward mechanisms, and cognitive and memory operations - the chapters present a unique admixture of theory, cognitive psychology, anatomy, and both cellular- and systems- level physiology written by experts in each of these areas. The editors have provided commentaries as a helpful guide to each part. Many new discoveries about the biology of the basal ganglia are summarized, and their impact on the computational role of the forebrain in the planning and control of complex motor behaviors discussed. The various findings point toward an unexpected role for the basal ganglia in the contextual analysis of the environment and in the adaptive use of this information for the planning and execution of intelligent behaviors. Parallels are explored between these findings and new connectionist approaches to difficult control problems in robotics and engineering. Contributors James L. Adams, P. Apicella, Michael Arbib, Dana H. Ballard, Andrew G. Barto, J. Brian Burns, Christopher I. Connolly, Peter F. Dominey, Richard P. Dum, John Gabrieli, M. Garcia-Munoz, Patricia S. Goldman-Rakic, Ann M. Graybiel, P. M. Groves, Mary M. Hayhoe, J. R. Hollerman, George Houghton, James C. Houk, Stephen Jackson, Minoru Kimura, A. B. Kirillov, Rolf Kotter, J. C. Linder, T. Ljungberg, M. S. Manley, M. E. Martone, J. Mirenowicz, C. D. Myre, Jeff Pelz, Nathalie Picard, R. Romo, S. F. Sawyer, E Scarnat, Wolfram Schultz, Peter L. Strick, Charles J. Wilson, Jeff Wickens, Donald J. Woodward, S. J. Young Bradford Books imprint
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“Actor-critic models145-147 operate within the evaluation system”
From Resolving the neural circuits of anxiety (2015) · cites this paper as [145]
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“dopamine inputs to the striatum push the animal toward obtaining maximum reward, a process that must take into account possible dangers.”
From Resolving the neural circuits of anxiety (2015) · cites this paper as [145]
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Sorted by citations
A neural substrate of prediction and reward
Schultz, W., Dayan, P., & Montague, P. R. (1997) · Science · doi:10.1126/science.275.5306.1593 · Cited by 9,388
Rao, R. P. N., & Ballard, D. H. (1999) · Nature Neuroscience · doi:10.1038/4580 · Cited by 5,483
Holroyd, C. B., & Coles, M. G. H. (2002) · Psychological Review · doi:10.1037/0033-295x.109.4.679 · Cited by 4,027
An Integrated Theory of the Mind.
Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C. J., & Qin, Y. (2004) · Psychological Review · doi:10.1037/0033-295x.111.4.1036 · Cited by 3,153
Getting formal with dopamine and reward
Schultz, W. (2002) · Neuron · doi:10.1016/s0896-6273(02)00967-4 · Cited by 2,574
Metadata
- Venue
- The MIT Press eBooks
- Publisher
- The MIT Press
- Published
- 1994-11-07
- OpenAlex
- W1607052939
- Cited by
- 1,190
- References
- 0
- Citations by year
- 2026: 4 · 2025: 12 · 2024: 9 · 2023: 38 · 2022: 14 · 2021: 13 · 2020: 47 · 2019: 21 · 2018: 16 · 2017: 17 · 2016: 26 · 2015: 29 · 2014: 28 · 2013: 46 · 2012: 33
- FWCI
- 16.11
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- The MIT Press eBooks (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Keywords
- basal ganglia, information processing, neural network model, motor control, working memory, reward processing, cognitive function, memory, cortical regions, forebrain, robot control, computational neuroscience
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