Title |
Learning to Select Actions with Spiking Neurons in the Basal Ganglia
|
---|---|
Published in |
Frontiers in Neuroscience, January 2012
|
DOI | 10.3389/fnins.2012.00002 |
Pubmed ID | |
Authors |
Terrence C. Stewart, Trevor Bekolay, Chris Eliasmith |
Abstract |
We expand our existing spiking neuron model of decision making in the cortex and basal ganglia to include local learning on the synaptic connections between the cortex and striatum, modulated by a dopaminergic reward signal. We then compare this model to animal data in the bandit task, which is used to test rodent learning in conditions involving forced choice under rewards. Our results indicate a good match in terms of both behavioral learning results and spike patterns in the ventral striatum. The model successfully generalizes to learning the utilities of multiple actions, and can learn to choose different actions in different states. The purpose of our model is to provide both high-level behavioral predictions and low-level spike timing predictions while respecting known neurophysiology and neuroanatomy. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Canada | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Canada | 4 | 3% |
United States | 4 | 3% |
United Kingdom | 4 | 3% |
Germany | 2 | 2% |
Switzerland | 2 | 2% |
Russia | 1 | <1% |
Sweden | 1 | <1% |
Unknown | 114 | 86% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 35 | 27% |
Student > Master | 27 | 20% |
Researcher | 23 | 17% |
Professor | 9 | 7% |
Professor > Associate Professor | 9 | 7% |
Other | 18 | 14% |
Unknown | 11 | 8% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 23 | 17% |
Computer Science | 23 | 17% |
Neuroscience | 21 | 16% |
Engineering | 17 | 13% |
Agricultural and Biological Sciences | 15 | 11% |
Other | 13 | 10% |
Unknown | 20 | 15% |