Abstract Groundbreaking work within the NIH BRAIN Initiative has revealed many new types of neurons and their genetic signatures. The dividends from this research will include sophisticated tools allowing selective genetic access to these cell-types, such as for imaging, optogenetic or tracing studies. To complement these powerful genetic tools, it will be equally important to have new imaging techniques that can reveal how multiple neuron- types work together in the live brain to support information-processing and construct different brain states. To address this challenge, Stanford University and The John B. Pierce Laboratory at Yale University will create optical techniques for imaging the concurrent voltage dynamics of up to 4 separate neuron-types in behaving animals. First, we will combine machine learning methods and an automated, high-throughput protein screening platform to engineer 4 different categories of genetically encoded fluorescent optical indicators of neuronal transmembrane voltage. We will then innovate several types of optical instruments tailored to work in conjunction with the new voltage indicators. These instruments will enable unprecedented studies of voltage rhythms and spiking dynamics in 2–4 genetically identified neuron-types in superficial and deep brain areas of awake behaving animals. One instrument will allow us to track the concurrent, population voltage oscillations of 2 neuron-types in freely behaving rodents. Another instrument, an optical mesoscope, will enable imaging studies of voltage waves and oscillations across the entire neocortical surface of behaving mice. A third device will be a high-speed miniature microscope for tracking neural dynamics at single cell-, single spike-resolution in freely behaving mice. Lastly, we will develop the capability to image with millisecond-scale precision the simultaneous spiking dynamics of 4 targeted neuron-types in either cortical or deep brain areas. Five external beta-tester labs will evaluate all these innovations in live mice and flies and provide critical user-feedback. If our work succeeds, it will be a ‘game-changer’ for studies of brain dynamics, yielding vital knowledge about how different neuron-types synergize their dynamics to shape animal behavior and the brain’s global states in health and disease. To facilitate this outcome, we plan a 5-fold strategy for resource sharing: (i) All voltage-indicator constructs, viral vectors, transgenic flies, software and screening data will be deposited at public repositories for open distribution; (ii) All instrument designs will be published in extensive detail to facilitate replication; (iii) Our novel imaging devices will be integrated into an existing NIH-supported, publicly accessible facility for brain-imaging in rodents; (iv) In project years 2–4, we will conduct 4 training workshops for 40 visiting scientists per year (120 in total) to learn the new technologies firsthand. These visitors will also provide extensive user-feedback; (v) We will license our imaging instruments for commercial distribution. Overall, we expect our project will lead to major conceptual advances in brain science and multiple new technologies that will reshape the practice of mammalian brain imaging.

Project Narrative Prominent successes of the NIH BRAIN Initiative to date include the identification of many new types of neurons, but to understand how these cell-types work together in the live brain it will be crucial to have techniques that can record the coordinated voltage dynamics of multiple classes of identified neurons simultaneously. To create such techniques, we will engineer four novel fluorescent indicators of neuronal trans-membrane voltage and three new optical instruments tailored to use these indicators to image either the spiking or oscillatory voltage dynamics of up to four neuron-types concurrently in the brains of awake behaving animals. These innovations will reveal how multiple neuron-types act concertedly at the millisecond-scale to support information-processing and shape a wide range of neurophysiologic states.