New methods and models for interrogating cell assembly, projection, and whole brain functional data during motivated behavior
Abstract/Contents
- Abstract
- While it is accepted that coordinated activity among populations of neurons in three-dimensional brain structures is critical to animal behavior, our understanding of such systems and their dynamics is circumscribed by available recording and intervention technologies. In particular, the ability to optically record and perturb dynamics in long-range, connectivity- and genetically-specified projections is needed to understand the roles that such inter-regional projections play in behavior, and fast methods to record and perturb population dynamics at cellular resolution across brain volumes are necessary to understand how cell assemblies coordinate across areas to encode and generate behavior. Finally, interpretable statistical techniques able to accurately capture the trends and dynamics in these complex data are required to turn observations into comprehensible descriptions, models, and theories. This work seeks to address these needs by developing (1) fiber photometry, a minimally-invasive method for recording bulk activity in connectivity-targeted and genetically-targeted cell bodies and projections during behavior, (2) SWIFT volume imaging, a method for synchronous recording and identification of cell assemblies across large volumes of tissue at high frame rates during behavior, and (3) interpretable statistical methods appropriate for high dimensional, potentially nonlinear neuroimaging data including those that are produced by SWIFT but also applicable to other whole-brain imaging data such as those generated by functional magnetic resonance imaging (fMRI). These approaches are applied and validated in several examples of motivated behavior including social approach behavior in mice, prey approach behavior in zebrafish, reward-based learning in mice, modulation of reward-seeking behavior by prefrontal cortex in rats, and incentivized decision making in humans.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2015 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Grosenick, Logan | |
|---|---|---|
| Associated with | Stanford University, Department of Neurosciences. | |
| Primary advisor | Deisseroth, Karl | |
| Thesis advisor | Deisseroth, Karl | |
| Thesis advisor | Boyd, Stephen P | |
| Thesis advisor | Newsome, William T | |
| Thesis advisor | Shenoy, Krishna V. (Krishna Vaughn) | |
| Advisor | Boyd, Stephen P | |
| Advisor | Newsome, William T | |
| Advisor | Shenoy, Krishna V. (Krishna Vaughn) |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Logan Grosenick. |
|---|---|
| Note | Submitted to the Department of Neurosciences. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2015. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2015 by Logan Micail Grosenick
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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