Optimization of genetically encoded voltage and neurotransmitter indicators for multiwavelength in vivo analysis of brain circuits - The brain is remarkably dynamic, adaptive, and flexible in response to environmental changes. These capacities are enabled by diverse cell types which communicate with an array of chemical neurotransmitters (NTs) or neuromodulators (NMs) and receptors. Neurochemical inputs have a wide-ranging and dramatic influence on neuronal activity and circuit dynamics. To understand the logic by which multiple convergent inputs shape neuronal activity, it is essential to record the timing and location of NT and NM release and the dynamic changes in membrane voltage that result. Our team has developed genetically encoded indicators, as well as high-speed and resolution microscopy, to allow simultaneous optical measurement of various NT/NM release and diffusion and post-synaptic activity in vivo with cell-type and circuit specificity. Broad applications of these technologies have started to reveal how neuromodulators collectively manipulate brain-wide states. Despite these successes, significant headroom exists to optimize these indicators to enable sensitive imaging in small structures, higher throughput, and measurements in sparsely-innervated brain areas. Moreover, existing NT and voltage indicators are nearly all green in color, and optimization of other colors is needed to enable multiplexing, along with hardware to perform such recordings and algorithms to process them. Finally, these new tools must be rigorously and systematically benchmarked in vivo to allow the large community of users to better design and interpret measurements in behavioral experiments. With available technology, we have yet to address the diversity of chemical neurotransmission at scales crucial to understanding brain circuit function. Therefore the overarching goal of this UM1 proposal is to establish a multidisciplinary, multi-investigator, and multi-institution program focusing on developing tools for measuring molecular inputs to neurons and resulting activity, including: Engineering optimized and multi-color FP-based indicators for NT/NM and voltage (Aim 1); detailed characterization and benchmarking of indicators in vivo (Aim 2); disseminating vetted, best-of-class reagents and related testing data (Aim 3). Our effort will provide the foundation for unraveling the logic of input-output transformation in defined cell types in vivo, which underlie information processing, brain states, circuit plasticity, and (ultimately) behavior.
