Deconstructing the cerebellar learning algorithm
Abstract/Contents
- Abstract
- This thesis is composed of experimental and analytic work deconstructing the cerebellar learning algorithm. The central finding is that two parallel neural circuits, with independent instructive signals, support cerebellum-dependent learning. An analytic framework for this result, based on overcoming signal-dependent noise, is proposed.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Copyright date | 2013 |
| Publication date | 2012, c2013; 2012 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Rinaldi, Jacob | |
|---|---|---|
| Associated with | Stanford University, Neurosciences Program. | |
| Primary advisor | Raymond, Jennifer L | |
| Thesis advisor | Raymond, Jennifer L | |
| Thesis advisor | Clandinin, Thomas R. (Thomas Robert), 1970- | |
| Thesis advisor | Greicius, Michael D | |
| Thesis advisor | Moore, Tirin, 1969- | |
| Advisor | Clandinin, Thomas R. (Thomas Robert), 1970- | |
| Advisor | Greicius, Michael D | |
| Advisor | Moore, Tirin, 1969- |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Jacob Rinaldi. |
|---|---|
| Note | Submitted to the Program in Neuroscience. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2012. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2013 by Jacob Matteo Rinaldi
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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