Color and orientation are jointly coded and spatially organized in primate primary visual cortex

ARViS: a bleed-free multi-site automated injection robot for accurate, fast, and dense delivery of virus to mouse and marmoset cerebral cortex

Genetically encoded fluorescent sensors continue to be developed and improved. If they could be expressed across multiple cortical areas in non-human primates, it would be possible to measure a variety of spatiotemporal dynamics of primate-specific cortical activity. Here, we develop an Automated Robotic Virus injection System (ARViS) for broad expression of a biosensor. ARViS consists of two technologies: image recognition of vasculature structures on the cortical surface to determine multiple injection sites without hitting them, and robotic control of micropipette insertion perpendicular to the cortical surface with 50 μm precision. In mouse cortex, ARViS sequentially injected virus solution into 100 sites over a duration of 100 min with a bleeding probability of only 0.1% per site. Furthermore, ARViS successfully achieved 266-site injections over the frontoparietal cortex of a female common marmoset. We demonstrate one-photon and two-photon calcium imaging in the marmoset frontoparietal cortex, illustrating the effective expression of biosensors delivered by ARViS.

Asymmetric distribution of color-opponent response types across mouse visual cortex supports superior color vision in the sky

Color is an important visual feature that informs behavior, and the retinal basis for color vision has been studied across various vertebrate species. While many studies have investigated how color information is processed in visual brain areas of primate species, we have limited understanding of how it is organized beyond the retina in other species, including most dichromatic mammals. In this study, we systematically characterized how color is represented in the primary visual cortex (V1) of mice. Using large-scale neuronal recordings and a luminance and color noise stimulus, we found that more than a third of neurons in mouse V1 are color-opponent in their receptive field center, while the receptive field surround predominantly captures luminance contrast. Furthermore, we found that color-opponency is especially pronounced in posterior V1 that encodes the sky, matching the statistics of natural scenes experienced by mice. Using unsupervised clustering, we demonstrate that the asymmetry in color representations across cortex can be explained by an uneven distribution of green-On/UV-Off color-opponent response types that are represented in the upper visual field. Finally, a simple model with natural scene-inspired parametric stimuli shows that green-On/UV-Off color-opponent response types may enhance the detection of 'predatory'-like dark UV-objects in noisy daylight scenes. The results from this study highlight the relevance of color processing in the mouse visual system and contribute to our understanding of how color information is organized in the visual hierarchy across species.

Hue and orientation pinwheels in macaque area V4

Area V4 is an intermediate-level area of the macaque visual cortical hierarchy that serves key functions in visual processing by integrating inputs from lower areas such as V1 and V2 and providing feedforward inputs to many higher cortical areas. Previous V4 imaging studies have focused on differential responses to color, orientation, disparity, and motion stimuli, but many details of the spatial organization of significant hue and orientation tuning have not been fully described. We used support vector machine (SVM) decoding of intrinsic cortical single-condition responses to generate high-resolution maps of hue and orientation tuning and to describe the organization of hue and orientation pinwheels in V4. Like V1 and V2, V4 contains maps of orientation that are organized as pinwheels. V4 also contains maps of hue that are organized as pinwheels, whose circular organization more closely represents the perception of hue than is observed in antecedent cortical areas. Unlike V1, where orientation is continuously mapped across the surface, V4 hue and orientation pinwheels are organized in limited numbers of pinwheel sequences. The organization of these sequences and the distance between pinwheels may provide insight into the functional organization of V4. Regions significantly tuned for hue occupy roughly four times that of the orientation, are largely separated from each other, and overlap by roughly 5%. This spatial organization is largely consistent with segregated inputs arising from V2 thin and interstripes. This modular organization of V4 suggests that further integration of color and shape might occur in higher areas in inferotemporal cortical.NEW & NOTEWORTHY The representation of hue and orientation in macaque monkey area V4 was determined by intrinsic cortical imaging of responses to isoluminant hues and achromatic grating stimuli. Vector summation of support vector machine (SVM) decoded single-condition responses was used to generate hue and orientation maps that, like V1 orientation maps, were both characterized by distinct pinwheel patterns. These data suggest that pinwheels are an important structure to represent different stimulus features across multiple visual cortical areas.

A unifying framework for functional organization in early and higher ventral visual cortex

A key feature of cortical systems is functional organization: the arrangement of functionally distinct neurons in characteristic spatial patterns. However, the principles underlying the emergence of functional organization in the cortex are poorly understood. Here, we develop the topographic deep artificial neural network (TDANN), the first model to predict several aspects of the functional organization of multiple cortical areas in the primate visual system. We analyze the factors driving the TDANN's success and find that it balances two objectives: learning a task-general sensory representation and maximizing the spatial smoothness of responses according to a metric that scales with cortical surface area. In turn, the representations learned by the TDANN are more brain-like than in spatially unconstrained models. Finally, we provide evidence that the TDANN's functional organization balances performance with between-area connection length. Our results offer a unified principle for understanding the functional organization of the primate ventral visual system.

Orientation selectivity mapping in the visual cortex

The orientation map is one of the most well-studied functional maps of the visual cortex. However, results from the literature are of different qualities. Clear boundaries among different orientation domains and blurred uncertain distinctions were shown in different studies. These unclear imaging results will lead to an inaccuracy in depicting cortical structures, and the lack of consideration in experimental design will also lead to biased depictions of the cortical features. How we accurately define orientation domains will impact the entire field of research. In this study, we test how spatial frequency (SF), stimulus size, location, chromatic, and data processing methods affect the orientation functional maps (including a large area of dorsal V4, and parts of dorsal V1) acquired by intrinsic signal optical imaging. Our results indicate that, for large imaging fields, large grating stimuli with mixed SF components should be considered to acquire the orientation map. A diffusion model image enhancement based on the difference map could further improve the map quality. In addition, the similar outcomes of achromatic and chromatic gratings indicate two alternative types of afferents from LGN, pooling in V1 to generate cue-invariant orientation selectivity.

Development of ocular dominance columns across rodents and other species: revisiting the concept of critical period plasticity

The existence of cortical columns, regarded as computational units underlying both lower and higher-order information processing, has long been associated with highly evolved brains, and previous studies suggested their absence in rodents. However, recent discoveries have unveiled the presence of ocular dominance columns (ODCs) in the primary visual cortex (V1) of Long-Evans rats. These domains exhibit continuity from layer 2 through layer 6, confirming their identity as genuine ODCs. Notably, ODCs are also observed in Brown Norway rats, a strain closely related to wild rats, suggesting the physiological relevance of ODCs in natural survival contexts, although they are lacking in albino rats. This discovery has enabled researchers to explore the development and plasticity of cortical columns using a multidisciplinary approach, leveraging studies involving hundreds of individuals-an endeavor challenging in carnivore and primate species. Notably, developmental trajectories differ depending on the aspect under examination: while the distribution of geniculo-cortical afferent terminals indicates matured ODCs even before eye-opening, consistent with prevailing theories in carnivore/primate studies, examination of cortical neuron spiking activities reveals immature ODCs until postnatal day 35, suggesting delayed maturation of functional synapses which is dependent on visual experience. This developmental gap might be recognized as 'critical period' for ocular dominance plasticity in previous studies. In this article, I summarize cross-species differences in ODCs and geniculo-cortical network, followed by a discussion on the development, plasticity, and evolutionary significance of rat ODCs. I discuss classical and recent studies on critical period plasticity in the venue where critical period plasticity might be a component of experience-dependent development. Consequently, this series of studies prompts a paradigm shift in our understanding of species conservation of cortical columns and the nature of plasticity during the classical critical period.

Gamma Responses to Colored Natural Stimuli Can Be Predicted from Local Low-Level Stimulus Features

The role of gamma rhythm (30-80 Hz) in visual processing is debated; stimuli like gratings and hue patches generate strong gamma, but many natural images do not. Could image gamma responses be predicted by approximating images as gratings or hue patches? Surprisingly, this question remains unanswered, since the joint dependence of gamma on multiple features is poorly understood. We recorded local field potentials and electrocorticogram from two female monkeys while presenting natural images and parametric stimuli varying along several feature dimensions. Gamma responses to different grating/hue features were separable, allowing for a multiplicative model based on individual features. By fitting a hue patch to the image around the receptive field, this simple model could predict gamma responses to chromatic images across scales with reasonably high accuracy. Our results provide a simple "baseline" model to predict gamma from local image properties, against which more complex models of natural vision can be tested.

Low luminance contrast's effect on the color appearance of S-cone patterns

There is a surprisingly strong effect on color appearance when low levels of luminance contrast are added to visual targets in which only S-cones are modulated. This phenomenon can be studied with checkerboard patterns composed of alternating S-cone-modulated checks and gray checks. + S checks look purple when surrounded by slightly brighter gray checks but look highly desaturated (lavender, almost white) when surrounded by darker gray checks. -S checks change in hue with luminance contrast; they look yellow when surrounded by darker gray checks but are greener when surrounded by lighter checks. Psychophysical paired comparisons confirm these perceptions. Furthermore, visual evoked potentials (VEPs) recorded from human posterior cortex indicate that signals evoked by low luminance contrast interact nonlinearly with S-cone-evoked signals in early cortical color processing. Our new psychophysics and electrophysiology results prove that human perception of color appearance is not based on neural computations within a separate, isolated color system. Rather, signals evoked by color contrast and luminance contrast interact to produce the colors we see.

Asymmetric distribution of color-opponent response types across mouse visual cortex supports superior color vision in the sky

Color is an important visual feature that informs behavior, and the retinal basis for color vision has been studied across various vertebrate species. While many studies have investigated how color information is processed in visual brain areas of primate species, we have limited understanding of how it is organized beyond the retina in other species, including most dichromatic mammals. In this study, we systematically characterized how color is represented in the primary visual cortex (V1) of mice. Using large-scale neuronal recordings and a luminance and color noise stimulus, we found that more than a third of neurons in mouse V1 are color-opponent in their receptive field center, while the receptive field surround predominantly captures luminance contrast. Furthermore, we found that color-opponency is especially pronounced in posterior V1 that encodes the sky, matching the statistics of natural scenes experienced by mice. Using unsupervised clustering, we demonstrate that the asymmetry in color representations across cortex can be explained by an uneven distribution of green-On/UV-Off color-opponent response types that are represented in the upper visual field. Finally, a simple model with natural scene-inspired parametric stimuli shows that green-On/UV-Off color-opponent response types may enhance the detection of "predatory"-like dark UV-objects in noisy daylight scenes. The results from this study highlight the relevance of color processing in the mouse visual system and contribute to our understanding of how color information is organized in the visual hierarchy across species.

An analysis of information segregation in parallel streams of a multi-stream convolutional neural network

Visual information is processed in hierarchically organized parallel streams in the primate brain. In the present study, information segregation in parallel streams was examined by constructing a convolutional neural network with parallel architecture in all of the convolutional layers. Although filter weights for convolution were initially set to random values, color information was segregated from shape information in most model instances after training. Deletion of the color-related stream decreased recognition accuracy of animate images, whereas deletion of the shape-related stream decreased recognition accuracy of both animate and inanimate images. The results suggest that properties of filters and functions of a stream are spontaneously segregated in parallel streams of neural networks.

Visual perceptual learning of feature conjunctions leverages non-linear mixed selectivity

Visual objects are often defined by multiple features. Therefore, learning novel objects entails learning feature conjunctions. Visual cortex is organized into distinct anatomical compartments, each of which is devoted to processing a single feature. A prime example are neurons purely selective to color and orientation, respectively. However, neurons that jointly encode multiple features (mixed selectivity) also exist across the brain and play critical roles in a multitude of tasks. Here, we sought to uncover the optimal policy that our brain adapts to achieve conjunction learning using these available resources. 59 human subjects practiced orientation-color conjunction learning in four psychophysical experiments designed to nudge the visual system towards using one or the other resource. We find that conjunction learning is possible by linear mixing of pure color and orientation information, but that more and faster learning takes place when both pure and mixed selectivity representations are involved. We also find that learning with mixed selectivity confers advantages in performing an untrained "exclusive or" (XOR) task several months after learning the original conjunction task. This study sheds light on possible mechanisms underlying conjunction learning and highlights the importance of learning by mixed selectivity.

High-Resolution Laminar Identification in Macaque Primary Visual Cortex Using Neuropixels Probes

Laminar electrode arrays allow simultaneous recording of activity of many cortical neurons and assignment to correct layers using current source density (CSD) analyses. Electrode arrays with 100-micron contact spacing can estimate borders between layer 4 versus superficial or deep layers, but in macaque primary visual cortex (V1) there are far more layers, such as 4A which is only 50-100 microns thick. Neuropixels electrode arrays have 20-micron spacing, and thus could potentially discern thinner layers and more precisely identify laminar borders. Here we show that CSD signals lack the spatial resolution required to take advantage of high density Neuropixels arrays and describe the development of approaches based on higher resolution electrical signals and analyses, including spike waveforms and spatial spread, unit density, high-frequency action potential (AP) power spectrum, temporal power change, and coherence spectrum, that afford far higher resolution of laminar distinctions, including the ability to precisely detect the borders of even the thinnest layers of V1.

The neural origin for asymmetric coding of surface color in the primate visual cortex

The coding privilege of end-spectral hues (red and blue) in the early visual cortex has been reported in primates. However, the origin of such bias remains unclear. Here, we provide a complete picture of the end-spectral bias in visual system by measuring fMRI signals and spiking activities in macaques. The correlated end-spectral biases between the LGN and V1 suggest a subcortical source for asymmetric coding. Along the ventral pathway from V1 to V4, red bias against green peaked in V1 and then declined, whereas blue bias against yellow showed an increasing trend. The feedforward and recurrent modifications of end-spectral bias were further revealed by dynamic causal modeling analysis. Moreover, we found that the strongest end-spectral bias in V1 was in layer 4C[Formula: see text]. Our results suggest that end-spectral bias already exists in the LGN and is transmitted to V1 mainly through the parvocellular pathway, then embellished by cortical processing.

A deep new look at color

Bowers et al. counter deep neural networks (DNNs) as good models of human visual perception. From our color perspective we feel their view is based on three misconceptions: A misrepresentation of the state-of-the-art of color perception; the type of model required to move the field forward; and the attribution of shortcomings to DNN research that are already being resolved.

Clarifying status of DNNs as models of human vision

On several key issues we agree with the commentators. Perhaps most importantly, everyone seems to agree that psychology has an important role to play in building better models of human vision, and (most) everyone agrees (including us) that deep neural networks (DNNs) will play an important role in modelling human vision going forward. But there are also disagreements about what models are for, how DNN-human correspondences should be evaluated, the value of alternative modelling approaches, and impact of marketing hype in the literature. In our view, these latter issues are contributing to many unjustified claims regarding DNN-human correspondences in vision and other domains of cognition. We explore all these issues in this response.

The influence of stereopsis on visual saliency in a proto-object based model of selective attention

Some animals including humans use stereoscopic vision which reconstructs spatial information about the environment from the disparity between images captured by eyes in two separate adjacent locations. Like other sensory information, such stereoscopic information is expected to influence attentional selection. We develop a biologically plausible model of binocular vision to study its effect on bottom-up visual attention, i.e., visual saliency. In our model, the scene is organized in terms of proto-objects on which attention acts, rather than on unbound sets of elementary features. We show that taking into account the stereoscopic information improves the performance of the model in the prediction of human eye movements with statistically significant differences.

Distinct Patterns of Connectivity between Brain Regions Underlie the Intra-Modal and Cross-Modal Value-Driven Modulations of the Visual Cortex

Past reward associations may be signaled from different sensory modalities; however, it remains unclear how different types of reward-associated stimuli modulate sensory perception. In this human fMRI study (female and male participants), a visual target was simultaneously presented with either an intra- (visual) or a cross-modal (auditory) cue that was previously associated with rewards. We hypothesized that, depending on the sensory modality of the cues, distinct neural mechanisms underlie the value-driven modulation of visual processing. Using a multivariate approach, we confirmed that reward-associated cues enhanced the target representation in early visual areas and identified the brain valuation regions. Then, using an effective connectivity analysis, we tested three possible patterns of connectivity that could underlie the modulation of the visual cortex: a direct pathway from the frontal valuation areas to the visual areas, a mediated pathway through the attention-related areas, and a mediated pathway that additionally involved sensory association areas. We found evidence for the third model demonstrating that the reward-related information in both sensory modalities is communicated across the valuation and attention-related brain regions. Additionally, the superior temporal areas were recruited when reward was cued cross-modally. The strongest dissociation between the intra- and cross-modal reward-driven effects was observed at the level of the feedforward and feedback connections of the visual cortex estimated from the winning model. These results suggest that, in the presence of previously rewarded stimuli from different sensory modalities, a combination of domain-general and domain-specific mechanisms are recruited across the brain to adjust the visual perception.SIGNIFICANCE STATEMENT Reward has a profound effect on perception, but it is not known whether shared or disparate mechanisms underlie the reward-driven effects across sensory modalities. In this human fMRI study, we examined the reward-driven modulation of the visual cortex by visual (intra-modal) and auditory (cross-modal) reward-associated cues. Using a model-based approach to identify the most plausible pattern of inter-regional effective connectivity, we found that higher-order areas involved in the valuation and attentional processing were recruited by both types of rewards. However, the pattern of connectivity between these areas and the early visual cortex was distinct between the intra- and cross-modal rewards. This evidence suggests that, to effectively adapt to the environment, reward signals may recruit both domain-general and domain-specific mechanisms.

Color appearance and the end of Hering's Opponent-Colors Theory

Hering's Opponent-Colors Theory has been central to understanding color appearance for 150 years. It aims to explain the phenomenology of colors with two linked propositions. First, a psychological hypothesis stipulates that any color is described necessarily and sufficiently by the extent to which it appears reddish-versus-greenish, bluish-versus-yellowish, and blackish-versus-whitish. Second, a physiological hypothesis stipulates that these perceptual mechanisms are encoded by three innate brain mechanisms. We review the evidence and conclude that neither side of the linking proposition is accurate: the theory is wrong. We sketch out an alternative, Utility-Based Coding, by which the known retinal cone-opponent mechanisms represent optimal encoding of spectral information given competing selective pressure to extract high-acuity spatial information; and phenomenological color categories represent an adaptive, efficient, output of the brain governed by behavioral demands.

Foramen lacerum impingement of trigeminal nerve root as a rodent model for trigeminal neuralgia

Trigeminal neuralgia (TN) is a classic neuralgic pain condition with distinct clinical characteristics. Modeling TN in rodents is challenging. Recently, we found that a foramen in the rodent skull base, the foramen lacerum, provides direct access to the trigeminal nerve root. Using this access, we developed a foramen lacerum impingement of trigeminal nerve root (FLIT) model and observed distinct pain-like behaviors in rodents, including paroxysmal asymmetric facial grimaces, head tilt when eating, avoidance of solid chow, and lack of wood chewing. The FLIT model recapitulated key clinical features of TN, including lancinating pain-like behavior and dental pain-like behavior. Importantly, when compared with a trigeminal neuropathic pain model (infraorbital nerve chronic constriction injury [IoN-CCI]), the FLIT model was associated with significantly higher numbers of c-Fos-positive cells in the primary somatosensory cortex (S1), unraveling robust cortical activation in the FLIT model. On intravital 2-photon calcium imaging, synchronized S1 neural dynamics were present in the FLIT but not the IoN-CCI model, revealing differential implication of cortical activation in different pain models. Taken together, our results indicate that FLIT is a clinically relevant rodent model of TN that could facilitate pain research and therapeutics development.

A Unifying Principle for the Functional Organization of Visual Cortex

A key feature of many cortical systems is functional organization: the arrangement of neurons with specific functional properties in characteristic spatial patterns across the cortical surface. However, the principles underlying the emergence and utility of functional organization are poorly understood. Here we develop the Topographic Deep Artificial Neural Network (TDANN), the first unified model to accurately predict the functional organization of multiple cortical areas in the primate visual system. We analyze the key factors responsible for the TDANN's success and find that it strikes a balance between two specific objectives: achieving a task-general sensory representation that is self-supervised, and maximizing the smoothness of responses across the cortical sheet according to a metric that scales relative to cortical surface area. In turn, the representations learned by the TDANN are lower dimensional and more brain-like than those in models that lack a spatial smoothness constraint. Finally, we provide evidence that the TDANN's functional organization balances performance with inter-area connection length, and use the resulting models for a proof-of-principle optimization of cortical prosthetic design. Our results thus offer a unified principle for understanding functional organization and a novel view of the functional role of the visual system in particular.

Why do children with autism spectrum disorder have abnormal visual perception?

Autism spectrum disorder (ASD) is associated with severe impairment in social functioning. Visual information processing provides nonverbal cues that support social interactions. ASD children exhibit abnormalities in visual orientation, continuous visual exploration, and visual-spatial perception, causing social dysfunction, and mechanisms underlying these abnormalities remain unclear. Transmission of visual information depends on the retina-lateral geniculate nucleus-visual cortex pathway. In ASD, developmental abnormalities occur in rapid expansion of the visual cortex surface area with constant thickness during early life, causing abnormal transmission of the peak of the visual evoked potential (P100). We hypothesized that abnormal visual perception in ASD are related to the abnormal visual information transmission and abnormal development of visual cortex in early life, what's more, explored the mechanisms of abnormal visual symptoms to provide suggestions for future research.

Functional ultrasound imaging reveals 3D structure of orientation domains in ferret primary visual cortex

BACKGROUND AND PURPOSE

The sensory cortex is organized into "maps" that represent sensory space across cortical space. In primary visual cortex (V1) of highly visual mammals, multiple visual feature maps are organized into a functional architecture anchored by orientation domains: regions containing neurons preferring the same stimulus orientation. Although the pinwheel-like structure of orientation domains is well-characterized in the superficial cortical layers in dorsal regions of V1, the 3D shape of orientation domains spanning all 6 cortical layers and across dorsal and ventral regions of V1 has never been revealed.

METHODS

We utilized an emerging research method in neuroscience, functional ultrasound imaging (fUS), to resolve the 3D structure of orientation domains throughout V1 in anesthetized female ferrets. fUS measures blood flow from which neuronal population activity is inferred with improved spatial resolution over fMRI.

RESULTS

fUS activations in response to drifting gratings placed at multiple locations in visual space generated unique activation patterns in V1 and visual thalamus, confirming prior observations that fUS can resolve retinotopy. Iso-orientation domains, determined from clusters of activations driven by large oriented gratings, were cone-shaped and present in both dorsal and ventral regions of V1. The spacing between iso-orientation domains was consistent with spacing measured previously using optical imaging methods.

CONCLUSIONS

Orientation domains are cones rather than columns. Their width and intra-domain distances may vary across dorsal and ventral regions of V1. These findings demonstrate the power of fUS at revealing 3D functional architecture in cortical regions not accessible to traditional surface imaging methods.

Perception of color in primates: A conceptual color neurons hypothesis

Perception of color by humans and other primates is a complex problem, studied by neurophysiology, psychophysiology, psycholinguistics, and even philosophy. Being mostly trichromats, simian primates have three types of opsin proteins, expressed in cone neurons in the eye, which allow for the sensing of color as the physical wavelength of light. Further, in neural networks of the retina, the coding principle changes from three types of sensor proteins to two opponent channels: activity of one type of neuron encode the evolutionarily ancient blue-yellow axis of color stimuli, and another more recent evolutionary channel, encoding the axis of red-green color stimuli. Both color channels are distinctive in neural organization at all levels from the eye to the neocortex, where it is thought that the perception of color (as philosophical qualia) emerges from the activity of some neuron ensembles. Here, using data from neurophysiology as a starting point, we propose a hypothesis on how the perception of color can be encoded in the activity of certain neurons in the neocortex. These conceptual neurons, herein referred to as 'color neurons', code only the hue of the color of visual stimulus, similar to place cells and number neurons, already described in primate brains. A case study with preliminary, but direct, evidence for existing conceptual color neurons in the human brain was published in 2008. We predict that the upcoming studies in non-human primates will be more extensive and provide a more detailed description of conceptual color neurons.

Adaptive coding across visual features during free-viewing and fixation conditions

Theoretical studies have long proposed that adaptation allows the brain to effectively use the limited response range of sensory neurons to encode widely varying natural inputs. However, despite this influential view, experimental studies have exclusively focused on how the neural code adapts to a range of stimuli lying along a single feature axis, such as orientation or contrast. Here, we performed electrical recordings in macaque visual cortex (area V4) to reveal significant adaptive changes in the neural code of single cells and populations across multiple feature axes. Both during free viewing and passive fixation, populations of cells improved their ability to encode image features after rapid exposure to stimuli lying on orthogonal feature axes even in the absence of initial tuning to these stimuli. These results reveal a remarkable adaptive capacity of visual cortical populations to improve network computations relevant for natural viewing despite the modularity of the functional cortical architecture.

Daily two-photon neuronal population imaging with targeted single-cell electrophysiology and subcellular imaging in auditory cortex of behaving mice

Quantitative and mechanistic understanding of learning and long-term memory at the level of single neurons in living brains require highly demanding techniques. A specific need is to precisely label one cell whose firing output property is pinpointed amidst a functionally characterized large population of neurons through the learning process and then investigate the distribution and properties of dendritic inputs. Here, we disseminate an integrated method of daily two-photon neuronal population Ca²⁺ imaging through an auditory associative learning course, followed by targeted single-cell loose-patch recording and electroporation of plasmid for enhanced chronic Ca²⁺ imaging of dendritic spines in the targeted cell. Our method provides a unique solution to the demand, opening a solid path toward the hard-cores of how learning and long-term memory are physiologically carried out at the level of single neurons and synapses.

Identification of visual cortex cell types and species differences using single-cell RNA sequencing

The primate neocortex exerts high cognitive ability and strong information processing capacity. Here, we establish a single-cell RNA sequencing dataset of 133,454 macaque visual cortical cells. It covers major cortical cell classes including 25 excitatory neuron types, 37 inhibitory neuron types and all glial cell types. We identified layer-specific markers including HPCAL1 and NXPH4, and also identified two cell types, an NPY-expressing excitatory neuron type that expresses the dopamine receptor D3 gene; and a primate specific activity-dependent OSTN + sensory neuron type. Comparisons of our dataset with humans and mice show that the gene expression profiles differ between species in relation to genes that are implicated in the synaptic plasticity and neuromodulation of excitatory neurons. The comparisons also revealed that glutamatergic neurons may be more diverse across species than GABAergic neurons and non-neuronal cells. These findings pave the way for understanding how the primary cortex fulfills the high-cognitive functions.

Wide-Field Calcium Imaging of Neuronal Network Dynamics In Vivo

A central tenet of neuroscience is that sensory, motor, and cognitive behaviors are generated by the communications and interactions among neurons, distributed within and across anatomically and functionally distinct brain regions. Therefore, to decipher how the brain plans, learns, and executes behaviors requires characterizing neuronal activity at multiple spatial and temporal scales. This includes simultaneously recording neuronal dynamics at the mesoscale level to understand the interactions among brain regions during different behavioral and brain states. Wide-field Ca2+ imaging, which uses single photon excitation and improved genetically encoded Ca2+ indicators, allows for simultaneous recordings of large brain areas and is proving to be a powerful tool to study neuronal activity at the mesoscopic scale in behaving animals. This review details the techniques used for wide-field Ca2+ imaging and the various approaches employed for the analyses of the rich neuronal-behavioral data sets obtained. Also discussed is how wide-field Ca2+ imaging is providing novel insights into both normal and altered neural processing in disease. Finally, we examine the limitations of the approach and new developments in wide-field Ca2+ imaging that are bringing new capabilities to this important technique for investigating large-scale neuronal dynamics.

Mapping the Function of Whole-Brain Projection at the Single Neuron Level

Axonal projection conveys neural information. The divergent and diverse projections of individual neurons imply the complexity of information flow. It is necessary to investigate the relationship between the projection and functional information at the single neuron level for understanding the rules of neural circuit assembly, but a gap remains due to a lack of methods to map the function to whole-brain projection. Here an approach is developed to bridge two-photon calcium imaging in vivo with high-resolution whole-brain imaging based on sparse labeling with the genetically encoded calcium indicator GCaMP6. Reliable whole-brain projections are captured by the high-definition fluorescent micro-optical sectioning tomography (HD-fMOST). A cross-modality cell matching is performed and the functional annotation of whole-brain projection at the single-neuron level (FAWPS) is obtained. Applying it to the layer 2/3 (L2/3) neurons in mouse visual cortex, the relationship is investigated between functional preferences and axonal projection features. The functional preference of projection motifs and the correlation between axonal length in MOs and neuronal orientation selectivity, suggest that projection motif-defined neurons form a functionally specific information flow, and the projection strength in specific targets relates to the information clarity. This pipeline provides a new way to understand the principle of neuronal information transmission.

Cone opponent functional domains in primary visual cortex combine signals for color appearance mechanisms

Studies of color perception have led to mechanistic models of how cone-opponent signals from retinal ganglion cells are integrated to generate color appearance. But it is unknown how this hypothesized integration occurs in the brain. Here we show that cone-opponent signals transmitted from retina to primary visual cortex (V1) are integrated through highly organized circuits within V1 to implement the color opponent interactions required for color appearance. Combining intrinsic signal optical imaging (ISI) and 2-photon calcium imaging (2PCI) at single cell resolution, we demonstrate cone-opponent functional domains (COFDs) that combine L/M cone-opponent and S/L + M cone-opponent signals following the rules predicted from psychophysical studies of color perception. These give rise to an orderly organization of hue preferences of the neurons within the COFDs and the generation of hue "pinwheels". Thus, spatially organized neural circuits mediate an orderly transition from cone-opponency to color appearance that begins in V1.

A brainstem map for visceral sensations

The nervous system uses various coding strategies to process sensory inputs. For example, the olfactory system uses large receptor repertoires and is wired to recognize diverse odours, whereas the visual system provides high acuity of object position, form and movement^1-5. Compared to external sensory systems, principles that underlie sensory processing by the interoceptive nervous system remain poorly defined. Here we developed a two-photon calcium imaging preparation to understand internal organ representations in the nucleus of the solitary tract (NTS), a sensory gateway in the brainstem that receives vagal and other inputs from the body. Focusing on gut and upper airway stimuli, we observed that individual NTS neurons are tuned to detect signals from particular organs and are topographically organized on the basis of body position. Moreover, some mechanosensory and chemosensory inputs from the same organ converge centrally. Sensory inputs engage specific NTS domains with defined locations, each containing heterogeneous cell types. Spatial representations of different organs are further sharpened in the NTS beyond what is achieved by vagal axon sorting alone, as blockade of brainstem inhibition broadens neural tuning and disorganizes visceral representations. These findings reveal basic organizational features used by the brain to process interoceptive inputs.

Fractional neural sampling as a theory of spatiotemporal probabilistic computations in neural circuits

A range of perceptual and cognitive processes have been characterized from the perspective of probabilistic representations and inference. To understand the neural circuit mechanism underlying these probabilistic computations, we develop a theory based on complex spatiotemporal dynamics of neural population activity. We first implement and explore this theory in a biophysically realistic, spiking neural circuit. Population activity patterns emerging from the circuit capture realistic variability or fluctuations of neural dynamics both in time and in space. These activity patterns implement a type of probabilistic computations that we name fractional neural sampling (FNS). We further develop a mathematical model to reveal the algorithmic nature of FNS and its computational advantages for representing multimodal distributions, a major challenge faced by existing theories. We demonstrate that FNS provides a unified account of a diversity of experimental observations of neural spatiotemporal dynamics and perceptual processes such as visual perception inference, and that FNS makes experimentally testable predictions.

Representation of Cone-Opponent Color Space in Macaque Early Visual Cortices

In primate vision, the encoding of color perception arises from three types of retinal cone cells (L, M, and S cones). The inputs from these cones are linearly integrated into two cone-opponent channels (cardinal axes) before the lateral geniculate nucleus. In subsequent visual cortical stages, color-preferring neurons cluster into functional domains within "blobs" in V1, "thin/color stripes" in V2, and "color bands" in V4. Here, we hypothesize that, with increasing cortical hierarchy, the functional organization of hue representation becomes more balanced and less dependent on cone opponency. To address this question, we used intrinsic signal optical imaging in macaque V1, V2, and V4 cortices to examine the domain-based representation of specific hues (here referred to as "hue domains") in cone-opponent color space (4 cardinal and 4 intermediate hues). Interestingly, we found that in V1, the relative size of S-cone hue preference domain was significantly smaller than that for other hues. This notable difference was less prominent in V2, and, in V4 was virtually absent, resulting in a more balanced representation of hues. In V2, hue clusters contained sequences of shifting preference, while in V4 the organization of hue clusters was more complex. Pattern classification analysis of these hue maps showed that accuracy of hue classification improved from V1 to V2 to V4. These results suggest that hue representation by domains in the early cortical hierarchy reflects a transformation away from cone-opponency and toward a full-coverage representation of hue.

Cyclic reactivation of distinct feature dimensions in human visual working memory

Several recent behavioral studies have observed 4-10 Hz rhythmic fluctuations in attention-related performance over time. So far, this rhythmic attentional sampling has predominantly been demonstrated with regards to external visual attention, directed toward one single feature dimension. Whether and how attention might sample from concurrent internal representations of different feature dimensions held in working memory (WM) is currently largely unknown. To elucidate this issue, we conducted a human behavioral dense-sampling experiment, in which participants had to hold representations of two distinct feature dimensions (color and orientation) in WM. By querying the contents of WM at 72 time-points after encoding, we estimated the activity time course of the individual feature representations. Our results demonstrate an oscillatory component at 9.4 Hz in the joint time courses of both representations, presumably reflecting a common early perceptual sampling process in the alpha-frequency range. Furthermore, we observed an oscillatory component at 3.5 Hz in the time course difference between the two representations. This likely corresponds to a later attentional sampling process and indicates that internal representations of distinct features are activated in alteration. In summary, we demonstrate the cyclic reactivation of internal WM representations of distinct feature dimensions, as well as the co-occurrence of behavioral fluctuations at distinct frequencies, presumably associated to internal perceptual- and attentional rhythms. In addition, our findings also challenge a model of strict parallel processing in visual search, thus, providing novel input to the ongoing debate on whether search for more than one target feature constitutes a parallel- or a sequential mechanism.

Signals from Single-Opponent Cortical Cells in the Human cVEP

We used the chromatic visual evoked potential (cVEP) to study responses in human visual cortex evoked by equiluminant color stimuli for 6 male and 11 female observers. Large-area, colored squares were used to stimulate Single-Opponent cells preferentially, and fine color-checkerboard stimuli were used to activate Double-Opponent responses preferentially. Stimuli were modulated along the following two directions in color space: (1) the cardinal direction, L-M or M-L of DKL (Derrington, Krauskopf, and Lennie) space; and (2) the line from the white point to the color of the Red LED in the display screen, which was approximately intermediate between the L-M and -S directions in DKL space in cone-contrast coordinates. The amplitudes of cVEPs to large squares were smaller than those to checkerboards, and the latency of the cVEP response to squares was significantly less than the checkerboard latency. The latency of cVEP responses to the squares varied little with cone-contrast unlike the steep reduction of latency with cone-contrast observed in responses to color checkerboard patterns. The dynamic differences between cVEPs to squares and checkerboards support the hypothesis that a distinct neuronal mechanism responded to squares: Single-Opponent cells. Response amplitude, latency, and transientness-and their dependence on cone-contrast-were similar in the responses in the L-M and Red color directions. The similarity supports the hypothesis that the Single-Opponent signals in the cVEP come from a distinct population of cells that receives subtractive inputs from L and M cones, either L-M or M-L.SIGNIFICANCE STATEMENT This article is about characterizing the visual behavior of a distinct population of neurons in the human visual cortex, the Single-Opponent color cells. Based on single-cell results in the visual cortex of macaque monkeys, we used large uniformly colored stimuli to isolate the responses of Single-Opponent cells in the chromatic visual evoked potential (cVEP) recorded on the scalp of human observers. VEP signals recorded under conditions believed to reveal Single-Opponent responses are small and transient. Their time course is relatively unaffected by cone-contrast, and they are relatively insensitive to stimulus modulation of short wavelength-sensitive S cones. Because Single-Opponent cells convey signals that can be used to judge the color of scene illumination, knowing their visual properties is important for understanding color vision.

Human visual gamma for color stimuli

Strong gamma-band oscillations in primate early visual cortex can be induced by homogeneous color surfaces (Peter et al., 2019; Shirhatti and Ray, 2018). Compared to other hues, particularly strong gamma oscillations have been reported for red stimuli. However, precortical color processing and the resultant strength of input to V1 have often not been fully controlled for. Therefore, stronger responses to red might be due to differences in V1 input strength. We presented stimuli that had equal luminance and cone contrast levels in a color coordinate system based on responses of the lateral geniculate nucleus, the main input source for area V1. With these stimuli, we recorded magnetoencephalography in 30 human participants. We found gamma oscillations in early visual cortex which, contrary to previous reports, did not differ between red and green stimuli of equal L-M cone contrast. Notably, blue stimuli with contrast exclusively on the S-cone axis induced very weak gamma responses, as well as smaller event-related fields and poorer change-detection performance. The strength of human color gamma responses for stimuli on the L-M axis could be well explained by L-M cone contrast and did not show a clear red bias when L-M cone contrast was properly equalized.

Artificial Visual System for Orientation Detection Based on Hubel–Wiesel Model

The Hubel–Wiesel (HW) model is a classical neurobiological model for explaining the orientation selectivity of cortical cells. However, the HW model still has not been fully proved physiologically, and there are few concise but efficient systems to quantify and simulate the HW model and can be used for object orientation detection applications. To realize a straightforward and efficient quantitive method and validate the HW model’s reasonability and practicality, we use McCulloch-Pitts (MP) neuron model to simulate simple cells and complex cells and implement an artificial visual system (AVS) for two-dimensional object orientation detection. First, we realize four types of simple cells that are only responsible for detecting a specific orientation angle locally. Complex cells are realized with the sum function. Every local orientation information of an object is collected by simple cells and subsequently converged to the corresponding same type complex cells for computing global activation degree. Finally, the global orientation is obtained according to the activation degree of each type of complex cell. Based on this scheme, an AVS for global orientation detection is constructed. We conducted computer simulations to prove the feasibility and effectiveness of our scheme and the AVS. Computer simulations show that the mechanism-based AVS can make accurate orientation discrimination and shows striking biological similarities with the natural visual system, which indirectly proves the rationality of the Hubel–Wiesel model. Furthermore, compared with traditional CNN, we find that our AVS beats CNN on orientation detection tasks in identification accuracy, noise resistance, computation and learning cost, hardware implementation, and reasonability.

Perceptual hue, lightness, and chroma are represented in a multidimensional functional anatomical map in macaque V1

Humans perceive millions of colors along three dimensions of color space: hue, lightness, and chroma. A major gap in knowledge is where the brain represents these specific dimensions in cortex, and how they relate to each other. Previous studies have shown that brain areas V4 and the posterior inferotemporal cortex (PIT) are central to computing color dimensions. To determine the contribution of V1 to setting up these downstream processing mechanisms, we studied cortical color responses in macaques-who share color vision mechanisms with humans. We used two-photon calcium imaging at both meso- and micro-scales and found that hue and lightness are laid out in orthogonal directions on the cortical map, with chroma represented by the strength of neuronal responses, as previously shown in PIT. These findings suggest that the earliest cortical stages of vision determine the three primary dimensions of human color perception.

Biased Orientation and Color Tuning of the Human Visual Gamma Rhythm

Narrowband γ oscillations (NBG: ∼20-60 Hz) in visual cortex reflect rhythmic fluctuations in population activity generated by underlying circuits tuned for stimulus location, orientation, and color. A variety of theories posit a specific role for NBG in encoding and communicating this information within visual cortex. However, recent findings suggest a more nuanced role for NBG, given its dependence on certain stimulus feature configurations, such as coherent-oriented edges and specific hues. Motivated by these factors, we sought to quantify the independent and joint tuning properties of NBG to oriented and color stimuli using intracranial recordings from the human visual cortex (male and female). NBG was shown to display a cardinal orientation bias (horizontal) and also an end- and mid-spectral color bias (red/blue and green). When jointly probed, the cardinal bias for orientation was attenuated and an end-spectral preference for red and blue predominated. This loss of mid-spectral tuning occurred even for recording sites showing large responses to uniform green stimuli. Our results demonstrate the close, yet complex, link between the population dynamics driving NBG oscillations and known feature selectivity biases for orientation and color within visual cortex. Such a bias in stimulus tuning imposes new constraints on the functional significance of the visual γ rhythm. More generally, these biases in population electrophysiology will need to be considered in experiments using orientation or color features to examine the role of visual cortex in other domains, such as working memory and decision-making.SIGNIFICANCE STATEMENT Oscillations in electrophysiological activity occur in visual cortex in response to stimuli that strongly drive the orientation or color selectivity of visual neurons. The significance of this induced "γ rhythm" to brain function remains unclear. Answering this question requires understanding how and why some stimuli can reliably generate oscillatory γ activity while others do not. We examined how different orientations and colors independently and jointly modulate γ oscillations in the human brain. Our data show that γ oscillations are greatest for certain orientations and colors that reflect known response biases in visual cortex. Such findings complicate the functional significance of γ oscillations but open new avenues for linking circuits to population dynamics in visual cortex.

Temporal dynamics of the neural representation of hue and luminance polarity

Hue and luminance contrast are basic visual features. Here we use multivariate analyses of magnetoencephalography data to investigate the timing of the neural computations that extract them, and whether they depend on common neural circuits. We show that hue and luminance-contrast polarity can be decoded from MEG data and, with lower accuracy, both features can be decoded across changes in the other feature. These results are consistent with the existence of both common and separable neural mechanisms. The decoding time course is earlier and more temporally precise for luminance polarity than hue, a result that does not depend on task, suggesting that luminance contrast is an updating signal that separates visual events. Meanwhile, cross-temporal generalization is slightly greater for representations of hue compared to luminance polarity, providing a neural correlate of the preeminence of hue in perceptual grouping and memory. Finally, decoding of luminance polarity varies depending on the hues used to obtain training and testing data. The pattern of results is consistent with observations that luminance contrast is mediated by both L-M and S cone sub-cortical mechanisms.

Fluorescence imaging of large-scale neural ensemble dynamics

Recent progress in fluorescence imaging allows neuroscientists to observe the dynamics of thousands of individual neurons, identified genetically or by their connectivity, across multiple brain areas and for extended durations in awake behaving mammals. We discuss advances in fluorescent indicators of neural activity, viral and genetic methods to express these indicators, chronic animal preparations for long-term imaging studies, and microscopes to monitor and manipulate the activity of large neural ensembles. Ca2+ imaging studies of neural activity can track brain area interactions and distributed information processing at cellular resolution. Across smaller spatial scales, high-speed voltage imaging reveals the distinctive spiking patterns and coding properties of targeted neuron types. Collectively, these innovations will propel studies of brain function and dovetail with ongoing neuroscience initiatives to identify new neuron types and develop widely applicable, non-human primate models. The optical toolkit's growing sophistication also suggests that "brain observatory" facilities would be useful open resources for future brain-imaging studies.

Cytochrome oxidase "blobs": a call for more anatomy

An ordered relation of structure and function has been a cornerstone in thinking about brain organization. Like the brain itself, however, this is not straightforward and is confounded both by functional intricacy and structural plasticity (many routes to a given outcome). As a striking case of putative structure-function correlation, this mini-review focuses on the relatively well-characterized pattern of cytochrome oxidase (CO) blobs (aka "patches" or "puffs") in the supragranular layers of macaque monkey visual cortex. The pattern is without doubt visually compelling, and the semi-dichotomous array of CO+ blobs and CO- interblobs is consistent with multiple studies reporting compartment-specific preferential connectivity and distinctive physiological response properties. Nevertheless, as briefly reviewed here, the finer anatomical organization of this system is surprisingly under-investigated, and the relation to functional aspects, therefore, unclear. Microcircuitry, cell type, and three-dimensional spatiotemporal level investigations of the CO+ CO- pattern are needed and may open new views to structure-function organization of visual cortex, and to phylogenetic and ontogenetic comparisons across nonhuman primates (NHP), and between NHP and humans.

The Expression Patterns of Cytochrome Oxidase and Immediate-Early Genes Show Absence of Ocular Dominance Columns in the Striate Cortex of Squirrel Monkeys Following Monocular Inactivation

Because at least some squirrel monkeys lack ocular dominance columns (ODCs) in the striate cortex (V1) that are detectable by cytochrome oxidase (CO) histochemistry, the functional importance of ODCs on stereoscopic 3-D vision has been questioned. However, conventional CO histochemistry or trans-synaptic tracer study has limited capacity to reveal cortical functional architecture, whereas the expression of immediate-early genes (IEGs), c-FOS and ZIF268, is more directly responsive to neuronal activity of cortical neurons to demonstrate ocular dominance (OD)-related domains in V1 following monocular inactivation. Thus, we wondered whether IEG expression would reveal ODCs in the squirrel monkey V1. In this study, we first examined CO histochemistry in V1 of five squirrel monkeys that were subjected to monocular enucleation or tetrodotoxin (TTX) treatment to address whether there is substantial cross-individual variation as reported previously. Then, we examined the IEG expression of the same V1 tissue to address whether OD-related domains are revealed. As a result, staining patterns of CO histochemistry were relatively homogeneous throughout layer 4 of V1. IEG expression was also moderate and homogeneous throughout layer 4 of V1 in all cases. On the other hand, the IEG expression was patchy in accordance with CO blobs outside layer 4, particularly in infragranular layers, although they may not directly represent OD clusters. Squirrel monkeys remain an exceptional species among anthropoid primates with regard to OD organization, and thus are potentially good subjects to study the development and function of ODCs.

Miniature microscopes for manipulating and recording in vivo brain activity

Here we describe the development and application of miniature integrated microscopes (miniscopes) paired with microendoscopes that allow for the visualization and manipulation of neural circuits in superficial and subcortical brain regions in freely behaving animals. Over the past decade the miniscope platform has expanded to include simultaneous optogenetic capabilities, electrically-tunable lenses that enable multi-plane imaging, color-corrected optics, and an integrated data acquisition platform that streamlines multimodal experiments. Miniscopes have given researchers an unprecedented ability to monitor hundreds to thousands of genetically-defined neurons from weeks to months in both healthy and diseased animal brains. Sophisticated algorithms that take advantage of constrained matrix factorization allow for background estimation and reliable cell identification, greatly improving the reliability and scalability of source extraction for large imaging datasets. Data generated from miniscopes have empowered researchers to investigate the neural circuit underpinnings of a wide array of behaviors that cannot be studied under head-fixed conditions, such as sleep, reward seeking, learning and memory, social behaviors, and feeding. Importantly, the miniscope has broadened our understanding of how neural circuits can go awry in animal models of progressive neurological disorders, such as Parkinson's disease. Continued miniscope development, including the ability to record from multiple populations of cells simultaneously, along with continued multimodal integration of techniques such as electrophysiology, will allow for deeper understanding into the neural circuits that underlie complex and naturalistic behavior.

Microendoscopic calcium imaging of the primary visual cortex of behaving macaques

In vivo calcium imaging with genetically encoded indicators has recently been applied to macaque brains to monitor neural activities from a large population of cells simultaneously. Microendoscopic calcium imaging combined with implantable gradient index lenses captures neural activities from deep brain areas with a compact and convenient setup; however, this has been limited to rodents and marmosets. Here, we developed miniature fluorescent microscopy to image neural activities from the primary visual cortex of behaving macaques. We found tens of clear fluorescent signals from three of the six brain hemispheres. A subset of these neurons showed clear retinotopy and orientation tuning. Moreover, we successfully decoded the stimulus orientation and tracked the cells across days. These results indicate that microendoscopic calcium imaging is feasible and reasonable for investigating neural circuits in the macaque brain by monitoring fluorescent signals from a large number of neurons.

Optical deep-cortex exploration in behaving rhesus macaques

Two papers published in June 2021 used a two-photon microscope or one-photon miniature microscope to interrogate the motor cortex in behaving macaque monkeys. The imaging was performed over several months, and the direction of natural arm reaching was decoded from the population activity.

Signals Related to Color in the Early Visual Cortex

Visual images can be described in terms of the illuminants and objects that are causal to the light reaching the eye, the retinal image, its neural representation, or how the image is perceived. Respecting the differences among these distinct levels of description can be challenging but is crucial for a clear understanding of color vision. This article approaches color by reviewing what is known about its neural representation in the early visual cortex, with a brief description of signals in the eye and the thalamus for context. The review focuses on the properties of single neurons and advances the general theme that experimental approaches based on knowledge of feedforward signals have promoted greater understanding of the neural code for color than approaches based on correlating single-unit responses with color perception. New data from area V1 illustrate the strength of the feedforward approach. Future directions for progress in color neurophysiology are discussed: techniques for improved single-neuron characterization, for investigations of neural populations and small circuits, and for the analysis of natural image statistics.

Functional visualization and manipulation in the marmoset brain using viral vectors

The common marmoset, a New World monkey, has a primate-specific cortex with approximately 40 Brodmann areas. Genetically encoded calcium indicator (GECI) techniques have been applied to study the functional organization of the marmoset cortex. The success of GCaMP (a green fluorescent of GECI) imaging and other advances, including optogenetic approaches, provide an interesting and exciting opportunity to study the primate brain at the molecular and cellular levels, leading to an understanding of primate neural circuits. These approaches will help advance our knowledge on cognition in primates, including humans, and therapy for human neurological and psychiatric disorders.

Dendritic calcium signals in rhesus macaque motor cortex drive an optical brain-computer interface

Calcium imaging is a powerful tool for recording from large populations of neurons in vivo. Imaging in rhesus macaque motor cortex can enable the discovery of fundamental principles of motor cortical function and can inform the design of next generation brain-computer interfaces (BCIs). Surface two-photon imaging, however, cannot presently access somatic calcium signals of neurons from all layers of macaque motor cortex due to photon scattering. Here, we demonstrate an implant and imaging system capable of chronic, motion-stabilized two-photon imaging of neuronal calcium signals from macaques engaged in a motor task. By imaging apical dendrites, we achieved optical access to large populations of deep and superficial cortical neurons across dorsal premotor (PMd) and gyral primary motor (M1) cortices. Dendritic signals from individual neurons displayed tuning for different directions of arm movement. Combining several technical advances, we developed an optical BCI (oBCI) driven by these dendritic signalswhich successfully decoded movement direction online. By fusing two-photon functional imaging with CLARITY volumetric imaging, we verified that many imaged dendrites which contributed to oBCI decoding originated from layer 5 output neurons, including a putative Betz cell. This approach establishes new opportunities for studying motor control and designing BCIs via two photon imaging.

Head-mounted microendoscopic calcium imaging in dorsal premotor cortex of behaving rhesus macaque

Microendoscopic calcium imaging with one-photon miniature microscopes enables unprecedented readout of neural circuit dynamics during active behavior in rodents. In this study, we describe successful application of this technology in the rhesus macaque, demonstrating plug-and-play, head-mounted recordings of cellular-resolution calcium dynamics from large populations of neurons simultaneously in bilateral dorsal premotor cortices during performance of a naturalistic motor reach task. Imaging is stable over several months, allowing us to longitudinally track individual neurons and monitor their relationship to motor behavior over time. We observe neuronal calcium dynamics selective for reach direction, which we could use to decode the animal's trial-by-trial motor behavior. This work establishes head-mounted microendoscopic calcium imaging in macaques as a powerful approach for studying the neural circuit mechanisms underlying complex and clinically relevant behaviors, and it promises to greatly advance our understanding of human brain function, as well as its dysfunction in neurological disease.