Closed-Loop Systems for Large Scale Spatiotemporal Imaging and Actuation of Neural Activity in Freely Behaving Animals
- Institution
- UNIVERSITY OF CALIFORNIA LOS ANGELES, CA
- Principal investigator
- Daniel Aharoni
- Funding
- $611K
- Duration
- 2022–2026
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Abstract
ABSTRACT A major challenge in neuroscience is to uncover how defined neural circuits in the brain encode, store, modify, and retrieve information. Adding to this challenge is the fact that neural function does not operate in isolation but rather within living, behaving animals. Great technological advances over the past decades have allowed researchers to begin to optically measure and modulate neural activity but these approaches are often limited to head-fix animals when studying neural function at spatial and temporal scales relevant to internal neural circuit dynamics. While a great deal of scientific and technological progress has been made, there is still much to learn concerning complex neural function, especially within the context of natural behavior. This knowledge gap, at least in part, is due to a lack of accessible tools for simultaneously modulating and observing large-scale neural circuits with single-cell precision in freely behaving animals. This project will fill this gap by developing open-source, head-mounted miniature microscopes with spatiotemporal illumination capabilities for both patterned photo-stimulation and improved neural imaging in freely behaving animals. We will develop a modular control and acquisition platform for native integration of neural and behavioral equipment to facilitate neural-behavioral experiments. Finally, this platform will be driven by a novel, automated, closed-loop processing framework for detecting, decoding, and manipulating neural and behavioral dynamics in real-time. The goal of this platform is to 1) significantly extend and improve upon current freely behaving neural imaging and modulation techniques and 2) provide an integrated framework for observing, controlling, and manipulating neural dynamics within the context of behavior. This approach has the potential to simultaneously “read” from and “write” into, potentially, any area of the brain, enabling fine-grained investigation of the causal role between neural activity and behavior. Our development will be guided by concurrent benchtop and in vivo testing at every stage of the development and optimization process. To maximize the impact of our efforts, all tools and technologies developed for this proposal will be open-source and shared widely with the scientific community through online resources and technical workshops.
Research team
- Daniel AharoniPI
- Hugh T BlairPI
- Peyman GolshaniPI
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