Neuroscience, Motor cortex, Artificial neural network, Control theory and Basal ganglia are his primary areas of study. His Cerebellum, Purkinje cell, Saccadic masking and Saccade study in the realm of Neuroscience interacts with subjects such as Long-term depression. His Motor cortex research incorporates themes from Adaptive control, Neural coding and Posterior parietal cortex.
His Artificial neural network study combines topics in areas such as Cognitive psychology, Recall, Sequence learning and Working memory, Cognition. His work in the fields of Linearization and Motor control overlaps with other areas such as Invariant. Daniel Bullock has researched Basal ganglia in several fields, including Dopaminergic, Frontal eye fields, Eye movement and Thalamus.
His scientific interests lie mostly in Artificial neural network, Neuroscience, Artificial intelligence, Control theory and Basal ganglia. His Artificial neural network research includes elements of Cerebellum, Trajectory and Motion control. He interconnects Communication, Motor control and Computer vision in the investigation of issues within Artificial intelligence.
His studies in Communication integrate themes in fields like Color vision, Local field potential, Coordinate system and Pattern recognition. His research in Control theory intersects with topics in Motor cortex, Tonic, Simulation and Postural control. The various areas that Daniel Bullock examines in his Basal ganglia study include Neurophysiology, Cognitive science, Set, Frontal cortex and Reinforcement learning.
The scientist’s investigation covers issues in Neuroscience, Basal ganglia, Artificial intelligence, Striatum and Dopamine. He combines subjects such as Forebrain, Cognitive science, Cognition and Speech recognition with his study of Basal ganglia. His Forebrain research integrates issues from Neurophysiology, Frontal lobe and Frontal cortex.
His biological study spans a wide range of topics, including Local field potential and Computer vision. In his research on the topic of Neuron, Motor cortex is strongly related with Torque. His Thalamus research is multidisciplinary, relying on both Speech production, Inhibitory postsynaptic potential and Motor program.
His main research concerns Neuroscience, Basal ganglia, Prefrontal cortex, Striatum and Dopamine. Many of his studies on Neuroscience apply to Torque as well. His Basal ganglia research includes elements of Frontal eye fields, Recall, Supplementary eye field, Superior colliculus and Ventral striatum.
His research integrates issues of Orientation, Linear model and Communication in his study of Prefrontal cortex. The study incorporates disciplines such as Tonic and Cholinergic in addition to Dopamine. Daniel Bullock works mostly in the field of Motor cortex, limiting it down to concerns involving Thalamus and, occasionally, Speech production.
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.
Neural dynamics of planned arm movements: emergent invariants and speed-accuracy properties during trajectory formation
D. Bullock;S. Grossberg.
Psychological Review (1988)
HOW THE BASAL GANGLIA USE PARALLEL EXCITATORY AND INHIBITORY LEARNING PATHWAYS TO SELECTIVELY RESPOND TO UNEXPECTED REWARDING CUES
Joshua Brown;Daniel Bullock;Stephen Grossberg.
The Journal of Neuroscience (1999)
A self-organizing neural model of motor equivalent reaching and tool use by a multijoint arm
Daniel Bullock;Stephen Grossberg;Frank H. Guenther.
Journal of Cognitive Neuroscience (1993)
Metabotropic Glutamate Receptor Activation in Cerebellar Purkinje Cells as Substrate for Adaptive Timing of the Classically Conditioned Eye-Blink Response
John C. Fiala;Stephen Grossberg;Daniel Bullock.
The Journal of Neuroscience (1996)
Synchronous Oscillatory Neural Ensembles for Rules in the Prefrontal Cortex
Timothy J. Buschman;Eric L. Denovellis;Eric L. Denovellis;Cinira Diogo;Cinira Diogo;Daniel Bullock;Daniel Bullock.
How laminar frontal cortex and basal ganglia circuits interact to control planned and reactive saccades
Joshua W. Brown;Daniel Bullock;Stephen Grossberg.
Neural Networks (2004)
Learning and production of movement sequences: Behavioral, neurophysiological, and modeling perspectives
Bradley J. Rhodes;Daniel Bullock;Willem B. Verwey;Bruno B. Averbeck.
Human Movement Science (2004)
Neural representations and mechanisms for the performance of simple speech sequences
Jason W. Bohland;Daniel Bullock;Frank H. Guenther.
Journal of Cognitive Neuroscience (2010)
Adaptive neural networks for control of movement trajectories invariant under speed and force rescaling
Daniel Bullock;Stephen Grossberg.
Human Movement Science (1991)
Cortical networks for control of voluntary arm movements under variable force conditions.
Daniel Bullock;Paul Cisek;Stephen Grossberg.
Cerebral Cortex (1998)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: