Experience dependent neural codes in the hippocampus
Abstract/Contents
- Abstract
- As animals navigate through the world, their survival depends on their ability to maintain a memory for episodes that occurred in different locations. During such memory-guided navigation, sparse sets of neurons in the mammalian hippocampus show striking correlations with an animal's instantaneous location in an environment. These neurons, called 'place cells', are maximally active when an animal occupies one or few restricted spatial locations and collectively form a neural map of the external environment. Across distinct environments, place cells will turn on, turn off, or move their location of peak firing—a set of phenomena collectively referred to as 'remapping'. Moreover, the activity of place cells is hypothesized to provide the neural basis for episodic memory and support the ability of animals to navigate both physical and conceptual spaces. During my graduate work, I used a combination of in vivo two photon imaging, virtual reality behaviors, genetic and viral manipulations, and computational and statistical modeling to address several open questions regarding how these striking neural representations are formed and recalled. In the first set of experiments, I address how the hippocampus chooses which place cell representation to recall when entering an environment. Uniting decades of conflicting findings, I found that the hippocampus activates the representation for the most likely environment given the animal's past experience and the available sensory information. I demonstrate that the animal's prior experience with the different environments can even be reconstructed in an unsupervised manner from the neural activity alone. In the second set of experiments, I investigated the cellular mechanisms that give rise to these hippocampal computations. Surprisingly, I found that the most well studied form of synaptic plasticity in the hippocampus, long term potentiation, is not necessary for forming or maintaining contextual or spatial codes in the output region of the hippocampus, CA1. Instead, long term potentiation in CA1 is specifically involved in novelty and reward processing. These data and the associated model help to disentangle the influences of inherited neural dynamics and plasticity in driving place cell representations and behavior. In the final set of experiments, I helped develop and test a novel genetically encoded voltage indicator for use in behaving animals. We show that with minimal modifications to a commercial two photon microscope, we can record intracellular voltage fluctuations from dozens of cells simultaneously. Combined, my thesis work identified a central mnemonic computation performed by the hippocampus and began to untangle how this and other computations of the hippocampus arise from the components of the biology.
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 | Plitt, Mark Houston |
|---|---|
| Degree supervisor | Giocomo, Lisa |
| Thesis advisor | Giocomo, Lisa |
| Thesis advisor | Ding, Jun (Jun B.) |
| Thesis advisor | Ganguli, Surya, 1977- |
| Thesis advisor | Raymond, Jennifer L |
| Degree committee member | Ding, Jun (Jun B.) |
| Degree committee member | Ganguli, Surya, 1977- |
| Degree committee member | Raymond, Jennifer L |
| Associated with | Stanford University, Neurosciences Program |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Mark Houston Plitt. |
|---|---|
| Note | Submitted to the Neurosciences Program. |
| Thesis | Thesis Ph.D. Stanford University 2022. |
| Location | https://purl.stanford.edu/mg949sr8466 |
Access conditions
- Copyright
- © 2022 by Mark Houston Plitt
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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