Removing direct photocurrent artifacts in optogenetic connectivity mapping data via constrained matrix factorization.

Monosynaptic connectivity mapping is crucial for building circuit-level models of neural computation. Two-photon optogenetic stimulation, when combined with whole-cell recording, enables large-scale mapping of physiological circuit parameters. In this experimental setup, recorded postsynaptic currents are used to infer the presence and strength of connections. For many cell types, nearby connections are those we expect to be strongest. However, when the postsynaptic cell expresses opsin, optical excitation of nearby cells can induce direct photocurrents in the postsynaptic cell. These photocurrent artifacts contaminate synaptic currents, making it difficult or impossible to probe connectivity for nearby cells. To overcome this problem, we developed a computational tool, Photocurrent Removal with Constraints (PhoRC). Our method is based on a constrained matrix factorization model which leverages the fact that photocurrent kinetics are less variable than those of synaptic currents. We demonstrate on real and simulated data that PhoRC consistently removes photocurrents while preserving synaptic currents, despite variations in photocurrent kinetics across datasets. Our method allows the discovery of synaptic connections which would have been otherwise obscured by photocurrent artifacts, and may thus reveal a more complete picture of synaptic connectivity. PhoRC runs faster than real time and is available as open source software.

Modeling the diverse effects of divisive normalization on noise correlations.

Divisive normalization, a prominent descriptive model of neural activity, is employed by theories of neural coding across many different brain areas. Yet, the relationship between normalization and the statistics of neural responses 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 affects correlation structure in neural populations. 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 discuss how to infer when normalization signals are shared. 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. Our model will enable quantifying the relation between 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.

Ultrasound activates mechanosensitive TRAAK K+ channels through the lipid membrane.

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.

Distinct local and brain-wide networks are activated by optogenetic stimulation of neurons specific to each layer of motor cortex.

Primary motor cortex (M1) consists of a stack of interconnected but distinct layers (L1-L6) which affect motor control through large-scale networks. However, the brain-wide functional influence of each layer is poorly understood. We sought to expand our knowledge of these layers' circuitry by combining Cre-driver mouse lines, optogenetics, fMRI, and electrophysiology. Neuronal activities initiated in Drd3 neurons (within L2/3) were mainly confined within M1, while stimulation of Scnn1a, Rbp4, and Ntsr1 neurons (within L4, L5, and L6, respectively) evoked distinct responses in M1 and motor-related subcortical regions, including striatum and motor thalamus. We also found that fMRI responses from targeted stimulations correlated with both local field potentials (LFPs) and spike changes. This study represents a step forward in our understanding of how different layers of primary motor cortex are embedded in brain-wide circuitry.

Superficial Layers Suppress the Deep Layers to Fine-tune Cortical Coding.

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 STATEMENT The 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 extensively in vitro, functional relationships in 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.

Covalently Tethered Rhodamine Voltage Reporters for High Speed Functional Imaging in Brain Tissue.

Voltage-sensitive fluorophores enable the direct visualization of membrane potential changes in living systems. To pair the speed and sensitivity of chemically 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 triggered RhoVR voltage-sensitive indicator coupled to a chloroalkane HaloTag ligand through a long, water-soluble polyethylene glycol linker (RhoVR-Halo). When applied to cells, RhoVR-Halo dyes selectively and covalently bind to surface-expressed HaloTag enzyme on genetically modified cells. RhoVR-Halo dyes maintain high voltage sensitivities-up to 34% ΔF/F per 100 mV-and fast response times typical of untargeted RhoVRs, while gaining the selectivity 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 a 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 a 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.

Layer-specific excitation/inhibition balances during neuronal synchronization in the visual cortex.

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.

Gain control by layer six in cortical circuits of vision.

After entering the cerebral cortex, sensory information spreads through six different horizontal neuronal layers that are interconnected by vertical axonal projections. It is believed that through these projections layers can influence each other's response to sensory stimuli, but the specific role that each layer has in cortical processing is still poorly understood. Here we show that layer six in the primary visual cortex of the mouse has a crucial role in controlling the gain of visually evoked activity in neurons of the upper layers without changing their tuning to orientation. This gain modulation results from the coordinated action of layer six intracortical projections to superficial layers and deep projections to the thalamus, with a substantial role of the intracortical circuit. This study establishes layer six as a major mediator of cortical gain modulation and suggests that it could be a node through which convergent inputs from several brain areas can regulate the earliest steps of cortical visual processing.

A neural circuit for spatial summation in visual cortex.

The response of cortical neurons to a sensory stimulus is modulated by the context. In the visual cortex, for example, stimulation of a pyramidal cell's receptive-field surround can attenuate the cell's response to a stimulus in the centre of its receptive field, a phenomenon called surround suppression. Whether cortical circuits contribute to surround suppression or whether the phenomenon is entirely relayed from earlier stages of visual processing is debated. Here we show that, in contrast to pyramidal cells, the response of somatostatin-expressing inhibitory neurons (SOMs) in the superficial layers of the mouse visual cortex increases with stimulation of the receptive-field surround. This difference results from the preferential excitation of SOMs by horizontal cortical axons. By perturbing the activity of SOMs, we show that these neurons contribute to pyramidal cells' surround suppression. These results establish a cortical circuit for surround suppression and attribute a particular function to a genetically defined type of inhibitory neuron.

Lateral competition for cortical space by layer-specific horizontal circuits.

The cerebral cortex constructs a coherent representation of the world by integrating distinct features of the sensory environment. Although these features are processed vertically across cortical layers, horizontal projections interconnecting neighbouring cortical domains allow these features to be processed in a context-dependent manner. Despite the wealth of physiological and psychophysical studies addressing the function of horizontal projections, how they coordinate activity among cortical domains remains poorly understood. We addressed this question by selectively activating horizontal projection neurons in mouse somatosensory cortex, and determined how the resulting spatial pattern of excitation and inhibition affects cortical activity. We found that horizontal projections suppress superficial layers while simultaneously activating deeper cortical output layers. This layer-specific modulation does not result from a spatial separation of excitation and inhibition, but from a layer-specific ratio between these two opposing conductances. Through this mechanism, cortical domains exploit horizontal projections to compete for cortical space.

Balanced bidirectional optogenetics reveals the causal impact of cortical temporal dynamics in sensory perception.

Whether the fast temporal dynamics of neural activity in brain circuits causally drive perception and cognition remains one of most longstanding unresolved questions in neuroscience 1-6 . While some theories posit a 'timing code' in which dynamics on the millisecond timescale is central to brain function, others instead argue that mean firing rates over more extended periods (a 'rate code') carry most of the relevant information. Existing tools, such as optogenetics, can be used to alter temporal structure of neural dynamics 7 , but they invariably change mean firing rates, leaving the interpretation of such experiments ambiguous. Here we developed and validated a new approach based on balanced, bidirectional optogenetics that can alter temporal structure of neural dynamics while mitigating effects on mean activity. Using this new approach, we found that selectively altering cortical temporal dynamics substantially reduced performance in a sensory perceptual task. These results demonstrate that endogenous temporal dynamics in the cortex are causally required for perception and behavior. More generally, this new bidirectional optogenetic approach should be broadly useful for disentangling the causal impact of different timescales of neural dynamics on behavior.

The logic of recurrent circuits in the primary visual cortex.

Recurrent cortical activity sculpts visual perception by refining, amplifying or suppressing visual input. However, the rules that govern the influence of recurrent activity remain enigmatic. We used ensemble-specific two-photon optogenetics in the mouse visual cortex to isolate the impact of recurrent activity from external visual input. We found that the spatial arrangement and the visual feature preference of the stimulated ensemble and the neighboring neurons jointly determine the net effect of recurrent activity. Photoactivation of these ensembles drives suppression in all cells beyond 30 µm but uniformly drives activation in closer similarly tuned cells. In nonsimilarly tuned cells, compact, cotuned ensembles drive net suppression, while diffuse, cotuned ensembles drive activation. Computational modeling suggests that highly local recurrent excitatory connectivity and selective convergence onto inhibitory neurons explain these effects. Our findings reveal a straightforward logic in which space and feature preference of cortical ensembles determine their impact on local recurrent activity.

Bayesian target optimisation for high-precision holographic optogenetics.

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 from in vitro experiments, showing that Bayesian target optimisation considerably reduces OTS across all conditions we test. Together, these results establish our ability to overcome OTS, enabling optogenetic stimulation with substantially improved precision.

Cortical VIP neurons locally control the gain but globally control the coherence of gamma band rhythms.

Gamma band synchronization can facilitate local and long-range neural communication. In the primary visual cortex, visual stimulus properties within a specific location determine local synchronization strength, while the match of stimulus properties between distant locations controls long-range synchronization. The neural basis for the differential control of local and global gamma band synchronization is unknown. Combining electrophysiology, optogenetics, and computational modeling, we found that VIP disinhibitory interneurons in mouse cortex linearly scale gamma power locally without changing its stimulus tuning. Conversely, they suppress long-range synchronization when two regions process non-matched stimuli, tuning gamma coherence globally. Modeling shows that like-to-like connectivity across space and specific VIP→SST inhibition capture these opposing effects. VIP neurons thus differentially impact local and global properties of gamma rhythms depending on visual stimulus statistics. They may thereby construct gamma-band filters for spatially extended but continuous image features, such as contours, facilitating the downstream generation of coherent visual percepts.

Probing inter-areal computations with a cellular resolution two-photon holographic mesoscope.

Brain 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.

Dissociating instructive from permissive roles of brain circuits with reversible neural activity manipulations.

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.

All-optical recreation of naturalistic neural activity with a multifunctional transgenic reporter mouse.

Determining which features of the neural code drive behavior requires the ability to simultaneously read out and write in neural activity patterns with high precision across many neurons. All-optical systems that combine two-photon calcium imaging and targeted photostimulation enable the activation of specific, functionally defined groups of neurons. However, these techniques are unable to test how patterns of activity across a population contribute to computation because of an inability to both read and write cell-specific firing rates. To overcome this challenge, we make two advances: first, we introduce a genetic line of mice for Cre-dependent co-expression of a calcium indicator and a potent soma-targeted microbial opsin. Second, using this line, we develop a method for read-out and write-in of precise population vectors of neural activity by calibrating the photostimulation to each cell. These advances offer a powerful and convenient platform for investigating the neural codes of computation and behavior.

maskNMF: A denoise-sparsen-detect approach for extracting neural signals from dense imaging data.

A number of calcium imaging methods have been developed to monitor the activity of large populations of neurons. One particularly promising approach, Bessel imaging, captures neural activity from a volume by projecting within the imaged volume onto a single imaging plane, therefore effectively mixing signals and increasing the number of neurons imaged per pixel. These signals must then be computationally demixed to recover the desired neural activity. Unfortunately, currently-available demixing methods can perform poorly in the regime of high imaging density (i.e., many neurons per pixel). In this work we introduce a new pipeline (maskNMF) for demixing dense calcium imaging data. The main idea is to first denoise and temporally sparsen the observed video; this enhances signal strength and reduces spatial overlap significantly. Next we detect neurons in the sparsened video using a neural network trained on a library of neural shapes. These shapes are derived from segmented electron microscopy images input into a Bessel imaging model; therefore no manual selection of "good" neural shapes from the functional data is required here. After cells are detected, we use a constrained non-negative matrix factorization approach to demix the activity, using the detected cells' shapes to initialize the factorization. We test the resulting pipeline on both simulated and real datasets and find that it is able to achieve accurate demixing on denser data than was previously feasible, therefore enabling faithful imaging of larger neural populations. The method also provides good results on more "standard" two-photon imaging data. Finally, because much of the pipeline operates on a significantly compressed version of the raw data and is highly parallelizable, the algorithm is fast, processing large datasets faster than real time.

Prominent in vivo influence of single interneurons in the developing barrel cortex.

Spontaneous synchronous activity is a hallmark of developing brain circuits and promotes their formation. Ex vivo, synchronous activity was shown to be orchestrated by a sparse population of highly connected GABAergic 'hub' neurons. The recent development of all-optical methods to record and manipulate neuronal activity in vivo now offers the unprecedented opportunity to probe the existence and function of hub cells in vivo. Using calcium imaging, connectivity analysis and holographic optical stimulation, we show that single GABAergic, but not glutamatergic, neurons influence population dynamics in the barrel cortex of non-anaesthetized mouse pups. Single GABAergic cells mainly exert an inhibitory influence on both spontaneous and sensory-evoked population bursts. Their network influence scales with their functional connectivity, with highly connected hub neurons displaying the strongest impact. We propose that hub neurons function in tailoring intrinsic cortical dynamics to external sensory inputs.

Recurrent pattern completion drives the neocortical representation of sensory inference.

When sensory information is incomplete or ambiguous, the brain relies on prior expectations to infer perceptual objects. Despite the centrality of this process to perception, the neural mechanism of sensory inference is not known. Illusory contours (ICs) are key tools to study sensory inference because they contain edges or objects that are implied only by their spatial context. Using cellular resolution, mesoscale two-photon calcium imaging and multi-Neuropixels recordings in the mouse visual cortex, we identified a sparse subset of neurons in the primary visual cortex (V1) and higher visual areas that respond emergently to ICs. We found that these highly selective 'IC-encoders' mediate the neural representation of IC inference. Strikingly, selective activation of these neurons using two-photon holographic optogenetics was sufficient to recreate IC representation in the rest of the V1 network, in the absence of any visual stimulus. This outlines a model in which primary sensory cortex facilitates sensory inference by selectively strengthening input patterns that match prior expectations through local, recurrent circuitry. Our data thus suggest a clear computational purpose for recurrence in the generation of holistic percepts under sensory ambiguity. More generally, selective reinforcement of top-down predictions by pattern-completing recurrent circuits in lower sensory cortices may constitute a key step in sensory inference.