Browse
Search
Explore more content
Fleischer PhD 2018.
pdf
(1.73 MB)
File info
Download file
Fullscreen
A Unified Model of Rule-Set Learning and Selection
Cite
Download
(1.73 MB)
Share
Embed
thesis
posted on 2019-01-16, 19:48
authored by
Pierson J. Fleischer
Pierson J. Fleischer
A new, biologically plausible model of task-set learning that reproduces effects from both rule-learning experiments and task-switching experiments.
Funding
Award #2R01MH063760-09A1 from the National Institute of Health
History
Degree Type
Doctor of Philosophy
Department
Psychological Sciences
Campus location
West Lafayette
Advisor/Supervisor/Committee Chair
Sébastien Hélie
Additional Committee Member 2
Greg Francis
Additional Committee Member 3
Richard Schweickert
Additional Committee Member 4
Shawn Ell
Usage metrics
Categories
Cognitive neuroscience
Keywords
learning model
rule sets
basal ganglia
prefrontal cortex
presynaptic inhibition
task set switching
Neurocognitive Patterns and Neural Networks
Licence
CC BY 4.0
Exports
Select an option
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC