Optogenetics provides a unique approach to remotely manipulate brain activity with light. Reaching the degree of spatiotemporal control necessary to dissect the role of individual cells in neuronal networks, some of which reside deep in the brain, requires joint progress in opsin engineering and light sculpting methods. Here we investigate for the first time two-photon stimulation of the red-shifted opsin ReaChR. We use two-photon (2P) holographic illumination to control the activation of individually chosen neurons expressing ReaChR in acute brain slices. We demonstrated reliable action potential generation in ReaChR-expressing neurons and studied holographic 2P-evoked spiking performances depending on illumination power and pulse width using an amplified laser and a standard femtosecond Ti:Sapphire oscillator laser. These findings provide detailed knowledge of ReaChR's behavior under 2P illumination paving the way for achieving in depth remote control of multiple cells with high spatiotemporal resolution deep within scattering tissue.

The biophysical properties of existing optogenetic tools constrain the scale, speed, and fidelity of precise optogenetic control. Here, we use structure-guided mutagenesis to engineer opsins that exhibit very high potency while retaining fast kinetics. These new opsins enable large-scale, temporally and spatially precise control of population neural activity. We extensively benchmark these new opsins against existing optogenetic tools and provide a detailed biophysical characterization of a diverse family of opsins under two-photon illumination. This establishes a resource for matching the optimal opsin to the goals and constraints of patterned optogenetics experiments. Finally, by combining these new opsins with optimized procedures for holographic photostimulation, we demonstrate the simultaneous coactivation of several hundred spatially defined neurons with a single hologram and nearly double that number by temporally interleaving holograms at fast rates. These newly engineered opsins substantially extend the capabilities of patterned illumination optogenetic paradigms for addressing neural circuits and behavior.

Patterned optogenetic activation of defined neuronal populations in the intact brain can reveal fundamental aspects of the neural codes of perception and behavior. The biophysical properties of existing optogenetic tools, however, constrain the scale, speed, and fidelity of precise optical control. Here we use structure-guided mutagenesis to engineer opsins that exhibit very high potency while retaining fast kinetics. These new opsins enable large-scale, temporally and spatially precise control of population neural activity in vivo and in vitro. We benchmark these new opsins against existing optogenetics tools with whole-cell electrophysiology and all-optical physiology and provide a detailed biophysical characterization of a diverse family of microbial opsins under two-photon illumination. This establishes a toolkit and a resource for matching the optimal opsin to the goals and constraints of patterned optogenetics experiments. Finally, by combining these new opsins with optimized procedures for cell-specific holographic photo-stimulation, we demonstrate the simultaneous co-activation of several hundred spatially defined neurons with a single hologram, and nearly double that number by temporally interleaving holograms at fast rates. These newly engineered opsins substantially extend the capabilities of patterned illumination optogenetic paradigms for addressing neural circuits and behavior.

Discovering how neural computations are implemented in the cortex at the level of monosynaptic connectivity requires probing for the existence of synapses from possibly thousands of presynaptic candidate neurons. Two-photon optogenetics has been shown to be a promising technology for mapping such monosynaptic connections via serial stimulation of neurons with single-cell resolution. However, this approach is limited in its ability to uncover connectivity at large scales because stimulating neurons one-by-one requires prohibitively long experiments. Here we developed novel computational tools that, when combined, enable learning of monosynaptic connectivity from high-speed holographic neural ensemble stimulation. First, we developed a model-based compressed sensing algorithm that identifies connections from postsynaptic responses evoked by stimulation of many neurons at once, considerably increasing the rate at which the existence and strength of synapses are screened. Second, we developed a deep learning method that isolates the postsynaptic response evoked by each stimulus, allowing stimulation to rapidly switch between ensembles without waiting for the postsynaptic response to return to baseline. Together, our system increases the throughput of monosynaptic connectivity mapping by an order of magnitude over existing approaches, enabling the acquisition of connectivity maps at speeds needed to discover the synaptic circuitry implementing neural computations.

Causally relating the detailed structure and function of neural circuits to behavior requires the ability to precisely and simultaneously write-in and read-out neural activity. All optical systems that combine two photon (2p) calcium imaging and targeted photostimulation provide such an approach, but require co-expression of an activity indicator, such as GCaMP, and an optogenetic actuator, ideally a potent soma-targeted opsin. In the mammalian brain, such co-expression has so far been achieved by viral transduction, which is invasive and can produce variable, focal, and sometimes toxic overexpression. To overcome this challenge, we developed and validated a Cre-reporter mouse ("Ai203") that conditionally expresses a soma-targeted opsin, ChroME, fused to GCaMP7s. 1p or 2p illumination of expressing neurons in vitro and in vivo produces powerful, precise activation comparable to viral expression of ChroME. The soma-targeted GCaMP7s provides sensitive activity measurements for tracking physiological activity, and the soma-targeted ChroME provides powerful control over neural ensemble activity with holographic optogenetics. We further demonstrate the use of the Ai203 reporter line in 1p optogenetic manipulation of performance on a cortex-dependent visual task and in 2p synaptic connectivity mapping. This new transgenic line could thus greatly facilitate the study of neural circuits by providing a flexible, convenient, and stable tool for all-optical access to large, cell-type specific neural populations throughout the nervous system.

Light patterning through spatial light modulators, whether they modulate amplitude or phase, is gaining an important place within optical methods used in neuroscience, especially for manipulating neuronal activity with optogenetics. The ability to selectively direct light in specific neurons expressing an optogenetic actuator, rather than in a large neuronal population within the microscope field of view, is now becoming attractive for studies that require high spatiotemporal precision for perturbing neuronal activity in a microcircuit. Computer-generated holography is a phase-modulation light patterning method providing significant advantages in terms of spatial and temporal resolution of photostimulation. It provides flexible three-dimensional light illumination schemes, easily reconfigurable, able to address a significant excitation field simultaneously, and applicable to both visible or infrared light excitation. Its implementation complexity depends on the level of accuracy that a certain application demands: Computer-generated holography can stand alone or be combined with temporal focusing in two-photon excitation schemes, producing depth-resolved excitation patterns robust to scattering. In this chapter, we present an overview of computer-generated holography properties regarding spatiotemporal resolution and penetration depth, and particularly focusing on its applications in optogenetics.

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Two-photon optogenetics has transformed our ability to probe the structure and function of neural circuits. However, achieving precise optogenetic control of neural ensemble activity has remained fundamentally constrained by the problem of off-target stimulation (OTS): the inadvertent activation of nearby non-target neurons due to imperfect confinement of light onto target neurons. Here we propose a novel computational approach to this problem called Bayesian target optimisation. Our approach uses nonparametric Bayesian inference to model neural responses to optogenetic stimulation, and then optimises the laser powers and optical target locations needed to achieve a desired activity pattern with minimal OTS. We validate our approach in simulations and using data fromin vitroexperiments, showing that Bayesian target optimisation substantially reduces OTS across all conditions we test. Together, these results establish our ability to overcome OTS, enabling optogenetic stimulation with significantly improved precision.