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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.

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.

SummaryDetermining which features of the neural code drive perception and behavior requires the ability to simultaneous read out and write in neural activity patterns with high precision across many neurons. All-optical systems that combine two photon (2p) calcium imaging and targeted 2p photostimulation enable the activation of specific, functionally defined groups of neurons in behaving animals. However, these techniques do not yet have the ability to reveal how the specific distribution of firing rates across a relevant neural population mediates neural computation and behavior. The key technical obstacle is the inability to transform single-cell calcium signals into accurate estimates of firing rate changes and then write in these cell-specific firing rate changes to each individual neuron in a targeted population. To overcome this challenge, we made two advances: first we introduce a new genetic line of mice for robust Cre-dependent co-expression of a high-performance calcium indicator and a potent soma-targeted microbial opsin. Second, using this line, we developed a pipeline that enables the read-out and write-in of precise population vectors of neural activity across a targeted group of neurons. The combination of the new multifunctional transgenic line and the photostimulation paradigm offer a powerful and convenient platform for investigating the neural codes of computation and behavior. It may prove particularly useful for probing causal features of the geometry of neural representations where the ability to directly control the topology of population activity is essential.