NSF Award
1533534
ECCS- Prop. No. 1533598<br/><br/>PI: Gong, Yiyang <br/>Institute: Duke University<br/>Title: NCS-FO: Real-time optical readout and control of population neural activity with cellular resolution<br/>Objective: <br/>This project will develop a mechanism for simultaneously controlling and reading out neural activity when being activated by optogenetic techniques; this capability will surpass a previous limitation in neural studies. The proposal is separated into three aims: 1) develop calcium sensors and optogenetic channels active on different wavelength ranges to allow simultaneous readout and control, 2) develop a dual-beam two photon microscope, and 3) develop imaging software that can process neural activity in real-time. <br/><br/>Nontechnical abstract<br/>Understanding neural function requires examining specific subsets of the vast numbers of neurons in the brain. Recently developed optogenetics tools, such as optogenetic stimulation and calcium imaging, have partially fulfilled the need to target these specific sets of neurons and study their function. These techniques deliver engineered genes to targeted neural populations, and use light to manipulate or measure neural activity. Current optogenetic tools lack the spatiotemporal resolution to causally study many individual neurons in parallel on fast time scales; they only make broad conclusions either on near-millimeter sized brain regions, or over the timescale of many action potentials. We propose to integrate the design and implementation of optical and genetic tools to greatly refine the scale of investigating neural activity. Specifically, we will create two optically independent channels: one channel for fast, spatially precise optical patterning to control individual neurons; and one channel for independent recording of neural activity from individual neurons. We will then integrate these two channels by creating software that instantaneously patterns optical excitation based on the optical recording. Integrative design and engineering of this expansive set of tools will enable neuroscientists to quickly manipulate and control large populations of single neurons, a capability that does not exist presently. Our technology will allow the community to directly explore how neural activity patterns of many individual neurons in one brain region drive downstream neural activity. This novel probing of functional connectivity is exactly the type of study needed to better understand the coordination of neural activity in healthy and diseased brains. Beyond the specific application of neuroscience, training students within our multidisciplinary setting will create the next generation of scientists capable of tackling the broad set of technical challenges facing society today. <br/><br/><br/>Technical Abstract<br/>Optical imaging of brain activity has steadily developed into a staple technique within neuroscience labs over the past decade. In combination with genetically encoded sensors of neural activity, optical methods enable genetic targeting and chronic, simultaneous imaging of many individual neurons. One significant weakness of existing optical techniques when compared to electrophysiology is the inability to simultaneously measure and control the activity of a neuron in real time. We propose to address this shortcoming by developing an optical imaging system and data processing software suite that will enable real-time optical readout of neural activity and real-time neural feedback via optical excitation, all with cellular level specificity and in parallel over a large population of neurons. This new ability to optically record and manipulate many genetically or functionally specified neurons individually will augment current studies using bulk neural activation or inhibition; the fine scale perturbations of neurons will tease apart the details of neural circuits. Specifically, we will engineer a set of optogenetic actuators, fluorescent sensors, and microscopy tools that will enable optical readout and control of neurons in different wavelength channels. We will also develop fast image processing algorithms that quickly convert images to neural activity of individual neurons, thereby enabling real-time control of neural activity based on the optical readout. Recently, improvements to these tools occurred independently. Our proposal will address the integrated development of the tool set, and effectively employ trade-offs between the individual components. For example, simultaneous engineering of the protein sensor, imaging processing software, and optical imaging hardware will optimize the readout fidelity. Similarly, joint design of the genetic tools? spectral separation and the optical spatiotemporal resolution will extend optical control precision. Integration of these developments to examine neural function at the cellular level is unprecedented: successful advancement of this research will enable novel examination of the brain and help guide targeted biomedical therapies.
