Using Neuroimaging and Optogenetics to Better Understand the Neural Circuit Basis of Major Depression.
Abstract/Contents
- Abstract
- Depression is a leading global health problem that affects hundreds of millions of people. Though the psychiatric disorder has been known to exist for centuries, its treatment still has yet to be perfected. The inability to clearly define the neurobiological mechanism of depression results in the lack of precise tools for the diagnosis and treatment of depressed patients. Advances in neuroscience research are working towards redefining depression in the language of brain circuits by characterizing the disease's structural, functional, and electrochemical profile. In the pioneering work of Helen Mayberg, one promising brain region that has been shown to be metabolically overactive in depression and therapeutically receptive via deep brain stimulation is the subgenual cingulate cortex. In this thesis, I describe the use of graph theoretical analysis of structural imaging data from depressed humans and optogenetic fMRI in the rat to evaluate the changes in whole-brain connectivity associated with depression, especially with respect to the subgenual cingulate and its associated brain regions. In the graph analysis, it was found that the structural correlation brain network in depressed patients was inefficient and less densely connected than in healthy controls. However, some regions, such as the amygdala and ventral frontal cortex, were found to be hyperconnected. In the optogenetic fMRI study, ventromedial prefrontal cortex (the rodent analog to the subgenual cingulate gyrus) stimulation was able to drive behaviors associated with depression and alter the functional connectivity of the region to other areas in the brain, such as the anterior prefrontal cortices, striatum and amygdala. Together, these studies indicate structural and functional abnormalities of the circuitry between the frontal cortices and subcortical limbic system, a collection of brain regions that control emotion, behavior, and reward processing. The presented data supports and expands upon Helen Mayberg’s hypothesis of an overactive subgenual cingulate cortex in depression. Both graph analysis and optogenetic fMRI require further research and development, but they have the potential to be useful tools in the deciphering of the neural circuit basis of depression and in the creation of impactful clinical tools to help manage the debilitating disorder.
Description
| Type of resource | text |
|---|---|
| Date created | May 12, 2014 |
Creators/Contributors
| Author | Amatya, Debha |
|---|---|
| Advisor | Deisseroth, Karl |
| Advisor | Singh, Manpreet |
| Editor | Ferenczi, Emily |
| Degree granting institution | Stanford University. Department of Bioengineering. |
Subjects
| Subject | bioengineering |
|---|---|
| Subject | neuroscience |
| Subject | psychiatric disease |
| Subject | depression |
| Subject | neural circuits |
| Subject | optogenetics |
| Subject | functional magnetic resonance imaging |
| Subject | fMRI |
| Subject | graph theoretical analysis |
| Genre | Thesis |
Bibliographic information
| Related Publication | Singh, Manpreet K., Shelli R. Kesler, S.m. Hadi Hosseini, Ryan G. Kelley, Debha Amatya, J. Paul Hamilton, Michael C. Chen, and Ian H. Gotlib. "Anomalous Gray Matter Structural Networks in Major Depressive Disorder." Biological Psychiatry 74.10 (2013): 777-85. Print. |
|---|---|
| Location | https://purl.stanford.edu/yr868vr4727 |
Access conditions
- Use and reproduction
- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Preferred citation
- Preferred Citation
- Amatya, Debha (2014). Using Neuroimaging and Optogenetics to Better Understand the Neural Circuit Basis of Major Depression. Stanford Digital Repository. Available at: http://purl.stanford.edu/yr868vr4727
Collection
Undergraduate Theses, School of Engineering
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- Contact
- amatya.debha@gmail.com
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