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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.

Neuroscientists rely on targeted perturbations and lesions to causally map functions in the brain1. Yet, since the brain is highly interconnected, manipulation of one area can impact behavior through indirect effects on many other brain regions, complicating the interpretation of such results2,3. On the other hand, the often-observed recovery of behavior performance after lesion can cast doubt on whether the lesioned area was ever directly involved4,5. Recent studies have highlighted how the results of acute and irreversible inactivation can directly conflict4-6, making it unclear whether a brain area is instructive or merely permissive in a specific brain function. To overcome this challenge, we developed a three-stage optogenetic approach which leverages the ability to precisely control the temporal period of regional inactivation with either brief or sustained illumination. Using a visual detection task, we found that acute optogenetic inactivation of the primary visual cortex (V1) suppressed task performance if cortical inactivation was intermittent across trials within each behavioral session. However, when we inactivated V1 for entire behavioral sessions, animals quickly recovered performance in just one to two days. Most importantly, after returning these recovered animals to intermittent cortical inactivation, they quickly reverted to failing on optogenetic inactivation trials. These data support a revised model where the cortex is the default circuit that instructs perceptual performance in basic sensory tasks. More generally, this novel, temporally controllable optogenetic perturbation paradigm can be broadly applied to brain circuits and specific cell types to assess whether they are instructive or merely permissive in a brain function or behavior.

SummaryBrain computation depends on intricately connected yet highly distributed neural networks. Due to the absence of the requisite technologies, causally testing fundamental hypotheses on the nature of inter-areal processing have remained largely out-of-each. Here we developed the first two photon holographic mesoscope, a system capable of simultaneously reading and writing neural activity patterns with single cell resolution across large regions of the brain. We demonstrate the precise photo-activation of spatial and temporal sequences of neurons in one brain area while reading out the downstream effect in several other regions. Investigators can use this new platform to understand feed-forward and feed-back processing in distributed neural circuits with single cell precision for the first time.

We describe the design, synthesis, and application of voltage-sensitive silicon rhodamines. Based on the Berkeley Red Sensor of Transmembrane potential, or BeRST, scaffold, the new dyes possess an isomeric molecular wire for improved alignment in the plasma membrane and 2′ carboxylic acids for ready functionalization. The new isoBeRST dyes have a voltage sensitivity of 24% ΔF/F per 100 mV. Combined with a flexible polyethyleneglycol (PEG) linker and a chloroalkane HaloTag ligand, isoBeRST dyes enable voltage imaging from genetically defined cells and neurons and provide improved labeling over previous, rhodamine-based hybrid strategies. isoBeRST-Halo hybrid indicators achieve single-trial voltage imaging of membrane potential dynamics from cultured hippocampal neurons or cortical neurons in brain slices. With far-red/near infrared excitation and emission, turn-on response to action potentials, and effective cell labeling in thick tissue, the new isoBeRST-Halo derivatives provide an important complement to voltage imaging in neurobiology., Small-molecule enzyme hybrids pair a far-red voltage-sensitive fluorophore with a cell-surface expressed HaloTag enzyme via a flexible linker to enable voltage imaging from genetically defined neurons in culture and brain slice.

Recurrent cortical activity sculpts visual perception by refining, amplifying, or suppressing incoming visual signals. Despite the importance of recurrent circuits for cortical processing, the basic rules that govern how nearby cortical neurons influence each other remains enigmatic. We used two-photon holographic optogenetics to activate ensembles of neurons in Layer 2/3 of the primary visual cortex (V1) in the absence of external stimuli to isolate the impact of local recurrence from external inputs. We find that the spatial arrangement and the stimulus feature preference of both the stimulated and the target ensemble jointly determine the net effect of recurrent activity, defining the cortical activity patterns that drive competition versus facilitation in L2/3 circuits. Computational modeling suggests that a combination of highly local recurrent excitatory connectivity and selective convergence onto inhibitory neurons give rise to these principles of recurrent activity. Our data and modeling reveal that recurrent activity can have varied impact, but a logic emerges through an understanding of the precise spatial distribution and feature preference of the multicellular pattern of activity.

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.

Microbial channelrhodopsins are light-gated ion channels widely used for optogenetic manipulation of neuronal activity. ChRmine is a bacteriorhodopsin-like cation channelrhodopsin (BCCR) more closely related to ion pump rhodopsins than other channelrhodopsins. ChRmine displays unique properties favorable for optogenetics including high light sensitivity, a broad, red-shifted activation spectrum, cation selectivity, and large photocurrents, while its slow closing kinetics impedes some applications. The structural basis for ChRmine function, or that of any other BCCR, is unknown. Here, we present cryo-EM structures of ChRmine in lipid nanodiscs in apo (opsin) and retinal-bound (rhodopsin) forms. The structures reveal an unprecedented trimeric architecture with a lipid filled central pore. Large electronegative cavities on either side of the membrane facilitate high conductance and selectivity for cations over protons. The retinal binding pocket structure suggests channel properties could be tuned with mutations and we identify ChRmine variants with ten-fold decreased and two-fold increased closing rates. A T119A mutant shows favorable properties relative to wild-type and previously reported ChRmine variants for optogenetics. These results provide insight into structural features that generate an ultra-potent microbial opsin and provide a platform for rational engineering of channelrhodopsins with improved properties that could expand the scale, depth, and precision of optogenetic experiments.

Divisive normalization, a prominent descriptive model of neural activity, plays a key role in influential theories of neural coding. Yet, the relationship between normalization and the statistics of neural activity beyond single neurons remains largely unexplored. Here we focus on noise correlations, a widely studied pairwise statistic, because its stimulus and state dependence plays a central role in neural coding. Existing models of covariability typically ignore normalization despite empirical evidence suggesting it contributes to modulations of covariability. We therefore propose a pairwise stochastic divisive normalization model that accounts for the effects of normalization and other factors on covariability. We first show that normalization modulates noise correlations in qualitatively different ways depending on whether normalization is shared between neurons, and we outline the data regime in which the corresponding model parameter is identifiable. We then apply our model to calcium imaging data from mouse primary visual cortex (V1), and find that it accurately fits the data, often outperforming a popular alternative model of correlations. Our analysis indicates that normalization signals are often shared between V1 neurons in this dataset, corresponding to a specific relation between normalization strength, stimulus contrast, and noise correlations for those pairs. Our model will enable estimation of the parameters relating normalization and covariability in a broad range of neural systems, which could provide new constraints on circuit mechanisms of normalization and their role in information transmission and representation.Author SummaryCortical responses are often variable across identical experimental conditions, and this variability is shared between neurons (noise correlations). These noise correlations have been studied extensively to understand how they impact neural coding and what mechanisms determine their properties. Here we show how correlations relate to divisive normalization, a widespread mathematical operation that describes how the activity of a neuron is modulated by other neurons via divisive gain control. We introduce the first statistical model of this relation. We extensively validate the model and characterize the regime of parameter identifiability in synthetic data. We find that our model, when applied to data from mouse visual cortex, outperforms a popular model of noise correlations that does not include normalization, and it reveals diverse influences of normalization on correlations. Our work demonstrates a framework to measure the relation between noise correlations and the parameters of the normalization model, which could become an indispensable tool for quantitative investigations of noise correlations in the wide range of neural systems that exhibit normalization.

Neurons in sensory cortices are more naturally and deeply integrated than any current neural population recording tools (e.g. electrode arrays, fluorescence imaging). Two concepts facilitate efforts to observe population neural code with single-cell recordings. First, even the highest quality single-cell recording studies find a fraction of the stimulus information in high-dimensional population recordings. Finding any of this missing information provides proof of principle. Second, neurons and neural populations are understood as coupled nonlinear differential equations. Therefore, fitted ordinary differential equations provide a basis for single-trial single-cell stimulus decoding. We obtained intracellular recordings of fluctuating transmembrane current and potential in mouse visual cortex during stimulation with drifting gratings. We use mean deflection from baseline when comparing to prior single-cell studies because action potentials are too sparse and the deflection response to drifting grating stimuli (e.g. tuning curves) are well studied. Equation-based decoders allowed more precise single-trial stimulus discrimination than tuning-curve-base decoders. Performance varied across recorded signal types in a manner consistent with population recording studies and both classification bases evinced distinct stimulus-evoked phases of population dynamics, providing further corroboration. Naturally and deeply integrated observations of population dynamics would be invaluable. We offer proof of principle and a versatile framework.

Gamma band synchronization can facilitate local and long-range communication in neural circuits. In the primary visual cortex (V1) the strength of synchronization on the local level is strongly tuned to the contrast, size and center/surround orientation of grating stimuli. On the global level, the synchronization of gamma oscillations across the retinotopic map crucially depends on matched stimulus properties in the corresponding locations in the visual field. Although these features of V1 gamma rhythms are likely to be crucial for how they might support cortico-cortical communication and visual perception, their neural basis remains largely unknown. We hypothesized VIP disinhibitory interneurons, which shape other tuning properties in V1 by inhibiting SST neurons, may be responsible for tuning local gamma band power and global gamma synchronization. To test these ideas, we combined multi-electrode electrophysiology, cell-type specific optogenetic suppression of VIP neurons and computational modeling. Contrary to expectations, our data show that on the local level, VIP activity has no role in tuning gamma power to stimulus properties; rather, it scales the gain of gamma oscillations linearly across stimulus space and across behavioral state. Conversely, on the global level, VIP neurons specifically suppress gamma synchronization (as measured by spectral coherence) between spatially separated cortical ensembles when they are processing non-matched stimulus features. A straightforward computational model of V1 shows that like-to-like connectivity across retinotopic space, and specific, but powerful VIP➔SST inhibition are sufficient to capture these seemingly opposed effects. These data demonstrate how VIP neurons differentially impact local and global properties of gamma rhythms depending on the global statistics of the retinal image. VIP neurons may thus construct temporal filters in the gamma band for spatially continuous image features, such as contours, to facilitate the downstream generation of coherent visual percepts.

We describe the design, synthesis, and application of voltage-sensitive silicon rhodamines. Based on the Berkeley Red Sensor of Transmembrane potential, or BeRST, scaffold, the new dyes possess an isomeric molecular wire for improved alignment in the plasma membrane and contain 2' carboxylic acids for ready functionalization. Conjugation with secondary amines affords tertiary amides that localize to cellular membranes and respond to voltage changes with a 24% ΔF/F per 100 mV. When combined with a flexible polyethyleneglycol (PEG) linker and a chloroalkane HaloTag ligand, the new indicators, or isoBeRST dyes, enable voltage imaging from genetically defined cells and neurons. Covalent ligation of isoBeRST to cell surface-expressed HaloTag enzymes provides up to 3-fold improved labeling over previous, rhodamine-based hybrid strategies. We show that isoBeRST-Halo hybrid indicators achieve single-trial voltage imaging of membrane potential dynamics from dissociated rat hippocampal neurons or mouse cortical neurons in brain slices. With far-red/near infrared excitation and emission, turn-on response to action potentials, effective cell labeling in thick tissue, and excellent photostability, the new isoBeRST-Halo derivatives provide an important complement to voltage imaging in neurobiology.

How cortical circuits build representations of complex objects is poorly understood. Individual neurons must integrate broadly over space, yet simultaneously obtain sharp tuning to specific global stimulus features. Groups of neurons identifying different global features must then assemble into a population that forms a comprehensive code for these global stimulus properties. Although the logic for how single neurons summate over their spatial inputs has been well explored in anesthetized animals, how large groups of neurons compose a flexible population code of higher-order features in awake animals is not known. To address this question, we probed the integration and population coding of higher-order stimuli in the somatosensory and visual cortices of awake mice using two-photon calcium imaging across cortical layers. We developed a novel tactile stimulator that allowed the precise measurement of spatial summation even in actively whisking mice. Using this system, we found a sparse but comprehensive population code for higher-order tactile features that depends on a heterogeneous and neuron-specific logic of spatial summation beyond the receptive field. Different somatosensory cortical neurons summed specific combinations of sensory inputs supra-linearly, but integrated other inputs sub-linearly, leading to selective responses to higher-order features. Visual cortical populations employed a nearly identical scheme to generate a comprehensive population code for contextual stimuli. These results suggest that a heterogeneous logic of input-specific supra-linear summation may represent a widespread cortical mechanism for the synthesis of sparse higher-order feature codes in neural populations. This may explain how the brain exploits the thalamocortical expansion of dimensionality to encode arbitrary complex features of sensory stimuli.

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.

Optogenetics ushered in a revolution in how neuroscientists interrogate brain function. Due to technical limitations, the majority of optogenetic studies have employed low spatial resolution activation schemes that limit the types of perturbations that could be made. Yet, neural activity manipulations at finer spatial scales are likely to be important to more fully understand neural computation. Spatially precise multiphoton holographic optogenetics promises to address this challenge and opens up many new classes of experiments that were not previously possible. More specifically, by offering the ability to recreate extremely specific neural activity patterns in both space and time in functionally defined ensembles of neurons, multiphoton holographic optogenetics could allow neuroscientists to reveal fundamental aspects of the neural codes for sensation, cognition, and behavior that have been beyond reach. This review summarizes recent advances in multiphoton holographic optogenetics that substantially expand its capabilities, highlights outstanding technical challenges, and provides an overview of the classes of experiments it can execute in order to test and validate key theoretical models of brain function. Multiphoton holographic optogenetics could significantly accelerate the pace of neuroscience discovery by helping to close the loop between experimental and theoretical neuroscience, leading to fundamental new insights into nervous system function and disorder.

NDNF selectively labels neurogliaform inhibitory interneurons of layer 1. In this issue of Neuron, Cohen-Kashi Malina et al. (2021) show that NDNF activity is highly correlated with arousal level. During high arousal state, NDNF inhibits the dendrites while disinhibiting the soma of nearby pyramidal neurons.

Voltage-sensitive fluorophores enable the direct visualization of membrane potential changes in living systems. To pair the speed and sensitivity of chemical synthesized fluorescent indicators with cell-type specific genetic methods, we here develop Rhodamine-based Voltage Reporters (RhoVR) that can be covalently tethered to genetically-encoded, self-labeling enzymes. These chemical-genetic hybrids feature a photoinduced electron transfer (PeT) triggered RhoVR voltage-sensitive indicator coupled to a chloroalkane HaloTag ligand through a long, water-soluble polyethyleneglycol (PEG) linker (RhoVR-Halos). When applied to cells, RhoVR-Halos selectively and covalently bind to surface-expressed HaloTag enzyme on genetically modified cells. RhoVR-Halos maintain high voltage sensitivities—up to 34% ΔF/F per 100 mV—and fast response times typical of untargeted RhoVRs, while gaining the selectivity typical of genetically encodable voltage indicators. We show that RhoVR-Halos can record action potentials in single trials from cultured rat hippocampal neurons and can be used in concert with green-fluorescent Ca2+ indicators like GCaMP to provide simultaneous voltage and Ca2+ imaging. In brain slice, RhoVR-Halos provide exquisite labeling of defined cells and can be imaged using epifluorescence, confocal, or two-photon microscopy. Using high-speed epifluorescence microscopy, RhoVR-Halos provide a read out of action potentials from labeled cortical neurons in rat brain slice, without the need for trial averaging. These results demonstrate the potential of hybrid chemical-genetic voltage indicators to combine the optical performance of small-molecule chromophores with the inherent selectivity of genetically-encodable systems, permitting imaging modalities inaccessible to either technique individually.

SummaryPatterned 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.

The cortical microcircuit can dynamically adjust to dramatic changes in the strength, scale, and complexity of its input. In the primary visual cortex (V1), pyramidal cells (PCs) integrate widely across space when signals are weak, but narrowly when signals are strong, a phenomenon known as contrast-dependent surround suppression. Theoretical work has proposed that local interneurons could mediate a shift from cooperation to competition of PCs across cortical space, underlying this computation. We combined calcium imaging and electrophysiology to constrain a stabilized supralinear network model that explains how the four principal cell types in layer 2/3 (L2/3) of mouse V1– somatostatin (SST), parvalbumin (PV), and vasoactive intestinal peptide (VIP) interneurons, and PCs– transform inputs from layer 4 (L4) PCs to encode drifting gratings of varying size and contrast. Using bidirectional optogenetic perturbations, we confirmed key predictions of the model. Our data and modeling showed that recurrent amplification drives a transition from a positive PC→VIP⊣SST⊣PC feedback loop at small size and low contrast to a negative PC→SST⊣PC feedback loop at large size and high contrast to contribute to this flexible computation. This may represent a widespread mechanism for gating competition across cortical space to optimally meet task demands.

Significance Ultrasound stimulation modulates the electrical activity of excitable cells, including in neurons of the brain and central nervous system. Compared to other neuromodulatory techniques, ultrasound offers several advantages; for example, it can be noninvasively transmitted through the skull and focused to deep brain regions. However, the molecular basis underlying the effects of ultrasound on neural activity is not known. Here, we show that ultrasound activates the mechanosensitive ion channel TRAAK through the membrane in a manner analogous to canonical mechanical activation, likely by increasing membrane tension to promote channel opening. These results suggest mechanosensitive channels underlie physiological responses to ultrasound and could serve as tools for acoustic neuromodulation of genetically targeted cells., Ultrasound modulates the electrical activity of excitable cells and offers advantages over other neuromodulatory techniques; for example, it can be noninvasively transmitted through the skull and focused to deep brain regions. However, the fundamental cellular, molecular, and mechanistic bases of ultrasonic neuromodulation are largely unknown. Here, we demonstrate ultrasound activation of the mechanosensitive K+ channel TRAAK with submillisecond kinetics to an extent comparable to canonical mechanical activation. Single-channel recordings reveal a common basis for ultrasonic and mechanical activation with stimulus-graded destabilization of long-duration closures and promotion of full conductance openings. Ultrasonic energy is transduced to TRAAK through the membrane in the absence of other cellular components, likely increasing membrane tension to promote channel opening. We further demonstrate ultrasonic modulation of neuronally expressed TRAAK. These results suggest mechanosensitive channels underlie physiological responses to ultrasound and could serve as sonogenetic actuators for acoustic neuromodulation of genetically targeted cells.

Primary motor cortex consists of a stack of interconnected but distinct layers, and plays a prominent role in motor control through large-scale networks. However, differential effects of M1 layer-specific functional pathways remain elusive, especially at the macroscopic and mesoscopic scales. Here, we combined layer-specific Cre-driver mouse lines, optogenetics, and fMRI with electrophysiological recordings to identify distinct M1 layer-specific networks. Neuronal activities initiated in L2/3 were mainly confined within M1, while stimulation of L4, L5, and L6 evoked distinct responses in M1 and motor-related subcortical regions, including the striatum and motor thalamus. Although motor cortex has long been considered agranular (without L4), our results structurally, functionally, and neurovascularly confirm the presence of L4. We also find that layer-specific fMRI responses closely couple with laminar electrophysiological recordings. Overall, our results elucidate distinct brain-wide neural archetypes of M1 layer-specific cortical circuits that provide important insights in uncovering the motor system architecture.

Predicting the response of the cortical microcircuit to perturbations is a prerequisite to determine the mechanisms that mediate its response to stimulus; yet, an encompassing perspective that describes the full ensemble of the network’s response in models that accurately recapitulate recorded data is still lacking. Here we develop a class of mathematically tractable models that exactly describe the modulation of the distribution of cell-type-specific calcium-imaging activity with the contrast of a visual stimulus. The inferred parameters recover signatures of the connectivity structure found in mouse visual cortex. Analysis of this structure subsequently reveals parameter-independent relations between the responses of different cell types to perturbations and each interneuron’s role in circuit-stabilization. Leveraging recent theoretical approaches, we derive explicit expressions for the distribution of responses to partial perturbations which reveal a novel, counter intuitive effect in the sign of response functions. Finally applying the theory to inferring feedback to V1 during locomotion, we find that it is predominantly mediated by both SOM and VIP modulation.

SummaryUltrasound modulates the electrical activity of excitable cells and offers advantages over other neuromodulatory techniques; for example, it can be non-invasively transmitted through skull and focused to deep brain regions. However, the fundamental cellular, molecular, and mechanistic bases of ultrasonic neuromodulation are largely unknown. Here, we demonstrate ultrasound activation of the mechanosensitive K+ channel TRAAK with sub-millisecond kinetics to an extent comparable to canonical mechanical activation. Single channel recordings reveal a common basis for ultrasonic and mechanical activation with stimulus-graded destabilization of long-duration closures and promotion of full conductance openings. Ultrasonic energy is transduced to TRAAK directly through the membrane in the absence of other cellular components, likely increasing membrane tension to promote channel opening. We further demonstrate ultrasonic modulation of neuronally expressed TRAAK. These results suggest mechanosensitive channels underlie physiological responses to ultrasound and provides a framework for developing channel-based sonogentic actuators for acoustic neuromodulation of genetically targeted cells.

The combination of electrophysiology and optogenetics enables the exploration of how the brain operates down to a single neuron and its network activity. Neural probes are in vivo invasive devices that integrate sensors and stimulation sites to record and manipulate neuronal activity with high spatiotemporal resolution. State-of-the-art probes are limited by tradeoffs involving their lateral dimension, number of sensors, and ability to access independent stimulation sites. Here, we realize a highly scalable probe that features three-dimensional integration of small-footprint arrays of sensors and nanophotonic circuits to scale the density of sensors per cross-section by one order of magnitude with respect to state-of-the-art devices. For the first time, we overcome the spatial limit of the nanophotonic circuit by coupling only one waveguide to numerous optical ring resonators as passive nanophotonic switches. With this strategy, we achieve accurate on-demand light localization while avoiding spatially demanding bundles of waveguides and demonstrate the feasibility with a proof-of-concept device and its scalability towards high-resolution and low-damage neural optoelectrodes.

How cortical circuits build representations of complex objects is poorly understood. The massive dimensional expansion from the thalamus to the primary sensory cortex may enable sparse, comprehensive representations of higher order features to facilitate object identification. To generate such a code, cortical neurons must integrate broadly over space, yet simultaneously obtain sharp tuning to specific stimulus features. The logic of cortical integration that may synthesize such a sparse, high dimensional code for complex features is not known. To address this question, we probed the integration and population coding of higher order stimuli in the somatosensory and visual cortices of awake mice using two-photon calcium imaging across cortical layers. We found that somatosensory and visual cortical neurons sum highly specific combinations of sensory inputs supra-linearly, but integrate other inputs sub-linearly, leading to selective responses to higher order features. This integrative process generates a sparse, but comprehensive code for complex stimuli from the earliest stages of cortical processing. These results from multiple sensory modalities imply that input-specific supra-linear summation may represent a widespread cortical mechanism for the synthesis of higher order feature codes. This new mechanism may explain how the brain exploits the thalamocortical expansion of dimensionality to encode arbitrary complex features of sensory stimuli.

SummaryActive haptic sensation is critical for object identification and manipulation, such as for tool use in humans, or prey capture in rodents. The neural circuit basis for recognizing objects through active touch alone is poorly understood. To address this gap, we combined optogenetics, two photon imaging, and high-speed behavioral tracking in mice solving a novel surface orientation discrimination task with their whiskers. We found that orientation discrimination required animals to summate input from multiple whiskers specifically along the whisker arc. Many animals discriminated the orientation of the stimulus per se, as their performance was invariant to the specific location of the presented stimulus. Two photon imaging showed that populations of neurons in the barrel cortex encoded each of the discriminated orientations, and this coding depended on integration over the whisker array. Finally, acute optogenetic inactivation of the barrel cortex strongly impaired surface orientation discrimination, and even cell-type specific optogenetic suppression of layer 4 excitatory neurons degraded performance, implying a role for superficial layers in this computation. These data suggest a model in which spatial summation over an active haptic array generates representations of an object’s surface orientations. These computations may facilitate the encoding of complex three-dimensional objects during active exploration.

Key points Understanding the balance between synaptic excitation and inhibition in cortical circuits in the brain, and how this contributes to cortical rhythms, is fundamental to explaining information processing in the cortex. This study used cortical layer-specific optogenetic activation in mouse cortex to show that excitatory neurons in any cortical layer can drive powerful gamma rhythms, while inhibition balances excitation. The net impact of this is to keep activity within each layer in check, but simultaneously to promote the propagation of activity to downstream layers. The data show that rhythm-generating circuits exist in all principle layers of the cortex, and provide layer-specific balances of excitation and inhibition that affect the flow of information across the layers. Abstract Rhythmic activity can synchronize neural ensembles within and across cortical layers. While gamma band rhythmicity has been observed in all layers, the laminar sources and functional impacts of neuronal synchronization in the cortex remain incompletely understood. Here, layer-specific optogenetic stimulation demonstrates that populations of excitatory neurons in any cortical layer of the mouse's primary visual cortex are sufficient to powerfully entrain neuronal oscillations in the gamma band. Within each layer, inhibition balances excitation and keeps activity in check. Across layers, translaminar output overcomes inhibition and drives downstream firing. These data establish that rhythm-generating circuits exist in all principle layers of the cortex, but provide layer-specific balances of excitation and inhibition that may dynamically shape the flow of information through cortical circuits. These data might help explain how excitation/inhibition (E/I) balances across cortical layers shape information processing, and shed light on the diverse nature and functional impacts of cortical gamma rhythms.

Voltage-sensitive fluorophores enable the direct visualization of membrane potential changes in living systems. To pair the speed and sensitivity of chemical synthesized fluorescent indicators with cell-type specific genetic methods, we here develop Rhodamine-based Voltage Reporters (RhoVR) that can be covalently tethered to genetically-encoded, self-labeling enzymes. These chemical-genetic hybrids feature a photoinduced electron transfer (PeT) triggered RhoVR voltage-sensitive indicator coupled to a chloroalkane HaloTag ligand through a long, water-soluble polyethyleneglycol (PEG) linker (RhoVR-Halos). When applied to cells, RhoVR-Halos selectively and covalently bind to surface-expressed HaloTag enzyme on genetically modified cells. RhoVR-Halos maintain high voltage sensitivities—up to 34% ΔF/F per 100 mV—and fast response times typical of untargeted RhoVRs, while gaining the selectivity typical of genetically encodable voltage indicators. We show that RhoVR-Halos can record action potentials in single trials from cultured rat hippocampal neurons and can be used in concert with green-fluorescent Ca2+ indicators like GCaMP to provide simultaneous voltage and Ca2+ imaging. In brain slice, RhoVR-Halos provide exquisite labeling of defined cells and can be imaged using epifluorescence, confocal, or two-photon microscopy. Using high-speed epifluorescence microscopy, RhoVR-Halos provide a read out of action potentials from labeled cortical neurons in rat brain slice, without the need for trial averaging. These results demonstrate the potential of hybrid chemical-genetic voltage indicators to combine the optical performance of small-molecule chromophores with the inherent selectivity of genetically-encodable systems, permitting imaging modalities inaccessible to either technique individually.

The neocortex is functionally organized into layers. Layer four receives the densest bottom up sensory inputs, while layers 2/3 and 5 receive top down inputs that may convey predictive information. A subset of cortical somatostatin (SST) neurons, the Martinotti cells, gate top down input by inhibiting the apical dendrites of pyramidal cells in layers 2/3 and 5, but it is unknown whether an analogous inhibitory mechanism controls activity in layer 4. Using high precision circuit mapping, in vivo optogenetic perturbations, and single cell transcriptional profiling, we reveal complementary circuits in the mouse barrel cortex involving genetically distinct SST subtypes that specifically and reciprocally interconnect with excitatory cells in different layers: Martinotti cells connect with layers 2/3 and 5, whereas non-Martinotti cells connect with layer 4. By enforcing layer-specific inhibition, these parallel SST subnetworks could independently regulate the balance between bottom up and top down input.

We synthesize custom light fields by simultaneously modulating light in the spatial and angular domain. Experimental results show new applications for high-resolution 3D displays and for high-speed sculpted illumination with enhanced depth selectivity.

Active haptic sensation is critical for object identification, but its neural circuit basis is poorly understood. We combined optogenetics, two-photon imaging, and high-speed behavioral tracking in mice solving a whisker-based object orientation discrimination task. We found that orientation discrimination required animals to summate input from multiple whiskers specifically along the whisker arc. Animals discriminated the orientation of the stimulus per se, as their performance was invariant to the location of the presented stimulus. Populations of barrel cortex neurons summated across whiskers to encode each orientation. Finally, acute optogenetic inactivation of the barrel cortex and cell-type specific optogenetic suppression of layer 4 excitatory neurons degraded performance, implying that infragranular layers alone are not sufficient to solve the task. These data suggest that spatial summation over an active haptic array generates representations of an object’s orientations, which may facilitate the encoding of complex three-dimensional objects during active exploration.

The neocortex is organized into discrete layers of excitatory neurons: layer 4 receives the densest ‘bottom up’ projection carrying external sensory data, while layers 2/3 and 5 receive ‘top down’ inputs from higher cortical areas that may convey sensory expectations and behavioral goals. A subset of cortical somatostatin (SST) neurons gate top down input and control sensory computation by inhibiting the apical dendrites of pyramidal cells in layers 2/3 and 5. However, it is unknown whether an analogous inhibitory mechanism separately and specifically controls activity in layer 4. We hypothesized that distinct SST circuits might exist to inhibit specific cortical layers. By enforcing layer-specific inhibition, distinct SST subnetworks could mediate pathway-specific gain control, such as regulating the balance between bottom up and top down input. Employing a combination of high precision circuit mapping, in vivo optogenetic perturbations, and single cell transcriptional profiling, we reveal distinct and complementary SST circuits that specifically and reciprocally interconnect with excitatory cells in either layer 4 or layers 2/3 and 5. Our data further define a transcriptionally distinct SST neuronal sub-class that powerfully gates bottom up sensory activity during active sensation by regulating layer 4 activity. This integrated paradigm further represents a potentially generalizable approach to identify and characterize neuronal cell types and reveal their in vivo function.

The descending microcircuit from layer 2/3 (L2/3) to layer 5 (L5) is one of the strongest excitatory pathways in the cortex, presumably forming a core component of its feedforward hierarchy. To date, however, no experiments have selectively tested the impact of L2/3 activity on L5 during active sensation. We used optogenetic, cell-type-specific manipulation of L2/3 neurons in the barrel cortex of actively sensing mice (of either sex) to elucidate the significance of this pathway to sensory coding in L5. Contrary to standard models, activating L2/3 predominantly suppressed spontaneous activity in L5, whereas deactivating L2/3 mainly facilitated touch responses in L5. Somatostatin interneurons are likely important to this suppression because their optogenetic deactivation significantly altered the functional impact of L2/3 onto L5. The net effect of L2/3 was to enhance the stimulus selectivity and expand the range of L5 output. These data imply that the core cortical pathway increases the selectivity and expands the range of cortical output through feedforward inhibition.SIGNIFICANCE STATEMENTThe primary sensory cortex contains six distinct layers that interact to form the basis of our perception. While rudimentary patterns of connectivity between the layers have been outlined quite extensivelyin vitro, functional relationshipsin vivo, particularly during active sensation, remain poorly understood. We used cell-type-specific optogenetics to test the functional relationship between layer 2/3 and layer 5. Surprisingly, we discovered that L2/3 primarily suppresses cortical output from L5. The recruitment of somatostatin-positive interneurons is likely fundamental to this relationship. The net effect of this translaminar suppression is to enhance the selectivity and expand the range of receptive fields, therefore potentially sharpening the perception of space.

Understanding how cortical activity generates sensory perceptions requires a detailed dissection of the function of cortical layers. Despite our relatively extensive knowledge of their anatomy and wiring, we have a limited grasp of what each layer contributes to cortical computation. We need to develop a theory of cortical function that is rooted solidly in each layer's component cell types and fine circuit architecture and produces predictions that can be validated by specific perturbations. Here we briefly review the progress toward such a theory and suggest an experimental road map toward this goal. We discuss new methods for the all-optical interrogation of cortical layers, for correlating in vivo function with precise identification of transcriptional cell type, and for mapping local and long-range activity in vivo with synaptic resolution. The new technologies that can crack the function of cortical layers are finally on the immediate horizon.