Dynamic navigational coding in an unchanging environment
Abstract/Contents
- Abstract
- In order to support complex behavior in a dynamic world, the brain must integrate internal conditions with external context. For example, during navigation an animal must combine its internal goals with sensory information to choose the appropriate actions and delineate con-textual episodes from continuous experience. The medial entorhinal cortex, a key navigational brain region, may support such dynamic integration through activity changes in single neurons, a phenomenon known as remapping. But previous studies have yet to uncover the specific impact of internal factors on remapping. Furthermore, successful integration of different internal and external factors likely relies on the coordination of many neurons, but it is not known how large populations of entorhinal neurons transition between different activity patterns together. I describe our discovery of dynamic, reversible, and population-wide remapping of spatial representations in the medial entorhinal cortex in an unchanging virtual environment. These remapping events were synchronized across hundreds of neurons, differentially impacted navigational cell types, and correlated with changes in running speed. I show that the neural population maintains a stable position estimate—despite widespread changes in spatial coding—through geometric alignment of the neural activity manifolds. I also discuss extensions of my primary work, including an exploration of within versus across environment remapping and preliminary modeling results indicating that geometrically aligned manifolds are a general solution to the challenge of simultaneous navigation and context discrimination. Together my findings reveal the incredible capacity of higher-order cortex to rapidly reconfigure largescale neural representations in response to behavioral state changes, tying into a larger body of emerging studies of dynamic neural coding and laying the groundwork for future research directions.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2022; ©2022 |
| Publication date | 2022; 2022 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Low, Isabel Iselin Cusick |
|---|---|
| Degree supervisor | Giocomo, Lisa |
| Thesis advisor | Giocomo, Lisa |
| Thesis advisor | Druckmann, Shaul |
| Thesis advisor | Hestrin, Shaul |
| Thesis advisor | Shah, Nirao |
| Degree committee member | Druckmann, Shaul |
| Degree committee member | Hestrin, Shaul |
| Degree committee member | Shah, Nirao |
| Associated with | Stanford University, Neurosciences Program |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Isabel Iselin Cusick Low. |
|---|---|
| Note | Submitted to the Neurosciences Program. |
| Thesis | Thesis Ph.D. Stanford University 2022. |
| Location | https://purl.stanford.edu/zm618mg9039 |
Access conditions
- Copyright
- © 2022 by Isabel Iselin Cusick Low
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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