Optogenetics is a set of technologies that enable optically triggered gain or loss of function in genetically specified populations of cells. Optogenetic methods have revolutionized experimental neuroscience by allowing precise excitation or inhibition of firing in specified neuronal populations embedded within complex, heterogeneous tissue. Although optogenetic tools have greatly improved our ability manipulate neural activity, they do not offer control of neural firing in the face of ongoing changes in network activity, plasticity, or sensory input. In this thesis, I develop a feedback control technology that automatically adjusts optical stimulation in real-time to precisely control network activity levels. I describe hardware and software tools, modes of optogenetic stimulation, and control algorithms required to achieve robust neural control over timescales ranging from seconds to days. I then demonstrate the scientific utility of these technologies in several experimental contexts. First, I investigate the role of connectivity in shaping the network encoding process using continuously-varying optical stimulation. I show that synaptic connectivity linearizes the neuronal response, verifying previous theoretical predictions. Next, I use long-term optogenetic feedback control to show that reductions in excitatory neurotransmission directly trigger homeostatic increases in synaptic strength. This result opposes a large body of literature on the subject and has significant implications for memory formation and maintenance. The technology presented in this thesis greatly enhances the precision with which optical stimulation can control neural activity, and allows causally related variables within neural circuits to be studied independently.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/52973 |
| Date | 12 January 2015 |
| Creators | Newman, Jonathan P. |
| Contributors | Potter, Steve M. |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
Page generated in 0.0022 seconds