Inserting a Neuropixels probe into awake monkey cortex: two probes, two methods.

BACKGROUND: Neuropixels probes have revolutionized neurophysiological studies in the rodent, but inserting these probes through the much thicker primate dura remains a challenge. NEW METHODS: Here we describe two methods we have developed for the insertion of two types of Neuropixels probes acutely into the awake macaque monkey cortex. For the fine rodent probe (Neuropixels 1.0, IMEC), which is unable to pierce native primate dura, we developed a dural-eyelet method to insert the probe repeatedly without breakage. For the thicker short NHP probe (Neuropixels NP1010), we developed an artificial dura system to insert the probe. RESULTS AND COMPARISON WITH EXISTING METHODS: We have now conducted successful experiments in 3 animals across 7 recording chambers with the procedures described here and have achieved recordings with similar yields over several months in each case. CONCLUSION: We hope that our hardware, surgical preparation, methods for insertion and methods for removal of broken probe parts are of value to primate physiologists everywhere.

High-density recording reveals sparse clusters (but not columns) for shape and texture encoding in macaque V4.

Macaque area V4 includes neurons that exhibit exquisite selectivity for visual form and surface texture, but their functional organization across laminae is unknown. We used high-density Neuropixels probes in two awake monkeys to characterize shape and texture tuning of dozens of neurons simultaneously across layers. We found sporadic clusters of neurons that exhibit similar tuning for shape and texture: ~20% exhibited similar tuning with their neighbors. Importantly, these clusters were confined to a few layers, seldom 'columnar' in structure. This was the case even when neurons were strongly driven, and exhibited robust contrast invariance for shape and texture tuning. We conclude that functional organization in area V4 is not columnar for shape and texture stimulus features and in general organization maybe at a coarse scale (e.g. encoding of 2D vs 3D shape) rather than at a fine scale in terms of similarity in tuning for specific features (as in the orientation columns in V1). We speculate that this may be a direct consequence of the great diversity of inputs integrated by V4 neurons to build variegated tuning manifolds in a high-dimensional space.

Neural correlates of crowding in macaque area V4.

Visual crowding refers to the phenomenon where a target object that is easily identifiable in isolation becomes difficult to recognize when surrounded by other stimuli (distractors). Extensive psychophysical studies support two alternative possibilities for the underlying mechanisms. One hypothesis suggests that crowding results from the loss of visual information due to pooled encoding of multiple nearby stimuli in the mid-level processing stages along the ventral visual pathway. Alternatively, crowding may arise from limited resolution in decoding object information during recognition and the encoded information may remain inaccessible unless it is salient. To rigorously test these alternatives, we studied the responses of single neurons in macaque area V4, an intermediate stage of the ventral, object-processing pathway, to parametrically designed crowded displays and their texture-statistics matched metameric counterparts. Our investigations reveal striking parallels between how crowding parameters, e.g., number, distance, and position of distractors, influence human psychophysical performance and V4 shape selectivity. Importantly, we found that enhancing the salience of a target stimulus could reverse crowding effects even in highly cluttered scenes and such reversals could be protracted reflecting a dynamical process. Overall, we conclude that a pooled encoding of nearby stimuli cannot explain the observed responses and we propose an alternative model where V4 neurons preferentially encode salient stimuli in crowded displays.

Ultra-high density electrodes improve detection, yield, and cell type specificity of brain recordings.

To study the neural basis of behavior, we require methods to sensitively and accurately measure neural activity at single neuron and single spike resolution. Extracellular electrophysiology is a principal method for achieving this, but it has biases in the neurons it detects and it imperfectly resolves their action potentials. To overcome these limitations, we developed a silicon probe with significantly smaller and denser recording sites than previous designs, called Neuropixels Ultra (NP Ultra). This device measures neuronal activity at ultra-high densities (>1300 sites per mm, 10 times higher than previous probes), with 6 µm center-to-center spacing and low noise. This device effectively comprises an implantable voltage-sensing camera that captures a planar image of a neuron's electrical field. We introduce a new spike sorting algorithm optimized for these probes and use it to find that the yield of visually-responsive neurons in recordings from mouse visual cortex improves ~3-fold. Recordings across multiple brain regions and four species revealed a subset of unexpectedly small extracellular action potentials not previously reported. Further experiments determined that, in visual cortex, these do not correspond to major subclasses of interneurons and instead likely reflect recordings from axons. Finally, using ground-truth identification of cortical inhibitory cell types with optotagging, we found that cell type was discriminable with approximately 75% success among three types, a significant improvement over lower-resolution recordings. NP Ultra improves spike sorting performance, sampling bias, and cell type classification.

Inserting a Neuropixels probe into awake monkey cortex: two probes, two methods.

Neuropixels probes have revolutionized neurophysiological studies in the rodent, but inserting these probes through the much thicker primate dura remains a challenge. Here we describe two methods we have developed for the insertion of two types of Neuropixels probes acutely into the awake monkey cortex. For the fine rodent probe, which is unable to pierce native primate dura, we developed a dural-eyelet method to insert the probe repeatedly without breakage. For the thicker NHP probe, we developed an artificial dura system to insert the probe. We have now conducted successful experiments in 3 animals across 7 recording chambers with the procedures described here and have achieved stable recordings over several months in each case. Here we describe our hardware, surgical preparation, methods for insertion and methods for removal of broken probe parts. We hope that our methods are of value to primate physiologists everywhere.

Dissociation in neuronal encoding of object versus surface motion in the primate brain.

A paradox exists in our understanding of motion processing in the primate visual system: neurons in the dorsal motion processing stream often strikingly fail to encode long-range and perceptually salient jumps of a moving stimulus. Psychophysical studies suggest that such long-range motion, which requires integration over more distant parts of the visual field, may be based on higher-order motion processing mechanisms that rely on feature or object tracking. Here, we demonstrate that ventral visual area V4, long recognized as critical for processing static scenes, includes neurons that maintain direction selectivity for long-range motion, even when conflicting local motion is present. These V4 neurons exhibit specific selectivity for the motion of objects, i.e., targets with defined boundaries, rather than the motion of surfaces behind apertures, and are selective for direction of motion over a broad range of spatial displacements and defined by a variety of features. Motion direction at a range of speeds can be accurately decoded on single trials from the activity of just a few V4 neurons. Thus, our results identify a novel motion computation in the ventral stream that is strikingly different from, and complementary to, the well-established system in the dorsal stream, and they support the hypothesis that the ventral stream system interacts with the dorsal stream to achieve the higher level of abstraction critical for tracking dynamic objects.

Task Context Modulates Feature-Selective Responses in Area V4.

Feature selectivity of visual cortical responses measured during passive fixation provides only a partial view of selectivity because it does not account for the influence of cognitive factors. Here we focus on primate area V4 and ask how neuronal tuning is modulated by task engagement. We investigated whether responses to colored shapes during active shape discrimination are simple, stimulus-agnostic, scaled versions of responses during passive fixation, akin to results from attentional studies. Alternatively, responses could be subject to stimulus-specific scaling, that is, responses to different stimuli are modulated differently, resulting in changes in underlying shape/color selectivity. Among 83 well-isolated V4 neurons in two male macaques, only a minority (16 of 83), which were weakly tuned to both shape and color, displayed responses during fixation and discrimination tasks that could be related by stimulus-agnostic scaling. The majority (67 of 83), which were strongly tuned to shape, color, or both, displayed stimulus-dependent response changes during discrimination. For some of these neurons (39 of 83), the shape or color of the stimulus dictated the magnitude of the change, and for others (28 of 83) it was the combination of stimulus shape and color. Importantly, for neurons with one strong and one weak tuning dimension, stimulus-dependent response changes during discrimination were associated with a relative increase in selectivity along the stronger tuning dimension, without changes in tuning peak. These results reveal that more strongly tuned V4 neurons may also be more flexible in their selectivity, and imbalances in selectivity are amplified during active task contexts.SIGNIFICANCE STATEMENT Tuning for stimulus features is typically characterized by recording responses during passive fixation, but cognitive factors, including attention, influence responses in visual cortex. To determine how behavioral engagement influences neuronal responses in area V4, we compared responses to colored shapes during passive fixation and active behavior. For a large fraction of neurons, differences in responses between passive fixation and active behavior depended on the identity of the visual stimulus. For a subgroup of strongly feature-selective neurons, this response modulation was associated with enhanced selectivity for one feature at the expense of selectivity for the other. Such flexibility in tuning strength could improve performance in tasks requiring active judgment of stimuli.

Davida's deficits: weak encoding of impoverished stimuli or faulty egocentric representation?

Vannuscorps and colleagues present the fascinating case of Davida, a young person who makes systematic errors in judgments related to orientations of sharp or high-contrast visual stimuli. In this commentary, we discuss the findings in the context of observations from mid-level ventral visual stream physiology. We propose two additional interpretations for the specificity of the behavioural deficits: the observed impairments in orientation judgments may be consistent with a system that is not able to unambiguously represent certain impoverished stimuli, or with a system that is not able to translate visual input into head- or body-centered coordinates. Davida's case offers a unique glimpse into the complex cascade of transformations that enable accurate orientation judgments, and sparks curiosity about which mechanistic disruptions can produce such specific unstable percepts.

Perceptual Texture Dimensions Modulate Neuronal Response Dynamics in Visual Cortical Area V4.

Texture is an important visual attribute for surface pattern discrimination and therefore object segmentation, but the neural bases of texture perception are largely unknown. Previously, we demonstrated that the responses of V4 neurons to naturalistic texture patches are sensitive to four key features of human texture perception: coarseness, directionality, regularity, and contrast. To begin to understand how distinct texture perception emerges from the dynamics of neuronal responses, in 2 macaque monkeys (1 male, 1 female), we investigated the relative contribution of the four texture attributes to V4 responses in terms of the strength and timing of response modulation. We found that the different feature dimensions are associated with different temporal dynamics. Specifically, the response modulation associated with directionality and regularity was significantly delayed relative to that associated with coarseness and contrast, suggesting that the latter are fundamentally simpler feature dimensions. The population of texture-selective neurons could be grouped into multiple clusters based on the combination of feature dimensions encoded, and those subpopulations displayed distinct temporal dynamics characterized by the weighted combinations of multiple features. Finally, we applied a population decoding approach to demonstrate that texture category information can be obtained from short temporal windows across time. These results demonstrate that the representation of different perceptually relevant texture features emerge over time in the responses of V4 neurons. The observed temporal organization provides a framework to interpret how the processing of surface features unfolds in early and midlevel cortical stages, and could ultimately inform the interpretation of perceptual texture dynamics.SIGNIFICANCE STATEMENT To delineate how neuronal responses underlie our ability to perceive visual textures, we related four key perceptual dimensions (coarseness, directionality, regularity, and contrast) of naturalistic textures to the strength and timing of modulation of neuronal responses in area V4, an intermediate stage in the form-processing, ventral visual pathway. Our results provide the first characterization of V4 temporal dynamics for texture encoding along perceptually defined axes.

Encoding of Partially Occluded and Occluding Objects in Primate Inferior Temporal Cortex.

Object segmentation-the process of parsing visual scenes-is essential for object recognition and scene understanding. We investigated how responses of neurons in macaque inferior temporal (IT) cortex contribute to object segmentation under partial occlusion. Specifically, we asked whether IT responses to occluding and occluded objects are bound together as in the visual image or linearly separable reflecting their segmentation. We recorded the activity of 121 IT neurons while two male animals performed a shape discrimination task under partial occlusion. We found that for a majority (60%) of neurons, responses were enhanced by partial occlusion, but they were only weakly shape selective for the discriminanda at all levels of occlusion. Enhancement of IT responses in these neurons depended largely on the area of occlusion but only minimally on the color and shape of the occluding dots. In contrast to the above group of neurons, a sizable minority responded best to the unoccluded stimulus and showed strong selectivity for the shape of the discriminanda. In these neurons, response magnitude and shape selectivity declined with increasing levels of occlusion. Simulations revealed that the response characteristics of both classes of neurons were consistent with a model in which the responses to the occluded shape and the occluders are weighted separately and linearly combined. Overall, our results support the hypothesis that information about occluded and occluding stimuli are linearly separable and easily decodable from IT responses and that IT neurons encode a segmented representation of the visual scene.SIGNIFICANCE STATEMENT Recognizing partially occluded objects can be challenging, yet the primate visual system achieves it rapidly and effortlessly. For successful recognition in the face of occlusion, segmentation of the occluded and occluding objects is a critical first step. Using a combination of experimental data and simulations, here we demonstrate that responses of neurons in macaque IT cortex, the highest stage of the form processing pathway, reflect occluded and occluding stimuli as segmented components and are not bound together as they appear in the visual image. These results support the idea that segmentation and perception of occluded and occluding stimuli are directly mirrored in the responses of neurons in the highest form processing stages.

Visual Functions of Primate Area V4.

Area V4-the focus of this review-is a mid-level processing stage along the ventral visual pathway of the macaque monkey. V4 is extensively interconnected with other visual cortical areas along the ventral and dorsal visual streams, with frontal cortical areas, and with several subcortical structures. Thus, it is well poised to play a broad and integrative role in visual perception and recognition-the functional domain of the ventral pathway. Neurophysiological studies in monkeys engaged in passive fixation and behavioral tasks suggest that V4 responses are dictated by tuning in a high-dimensional stimulus space defined by form, texture, color, depth, and other attributes of visual stimuli. This high-dimensional tuning may underlie the development of object-based representations in the visual cortex that are critical for tracking, recognizing, and interacting with objects. Neurophysiological and lesion studies also suggest that V4 responses are important for guiding perceptual decisions and higher-order behavior.

Timing of response onset and offset in macaque V4: stimulus and task dependence.

In the primate visual cortex, both the magnitude of the neuronal response and its timing can carry important information about the visual world, but studies typically focus only on response magnitude. Here, we examine the onset and offset latency of the responses of neurons in area V4 of awake, behaving macaques across several experiments in the context of a variety of stimuli and task paradigms. Our results highlight distinct contributions of stimuli and tasks to V4 response latency. We found that response onset latencies are shorter than typically cited (median = 75.5 ms), supporting a role for V4 neurons in rapid object and scene recognition functions. Moreover, onset latencies are longer for smaller stimuli and stimulus outlines, consistent with the hypothesis that longer latencies are associated with higher spatial frequency content. Strikingly, we found that onset latencies showed no significant dependence on stimulus occlusion, unlike in inferotemporal cortex, nor on task demands. Across the V4 population, onset latencies had a broad distribution, reflecting the diversity of feedforward, recurrent, and feedback connections that inform the responses of individual neurons. Response offset latencies, on the other hand, displayed the opposite tendency in their relationship to stimulus and task attributes: they are less influenced by stimulus appearance but are shorter in guided saccade tasks compared with fixation tasks. The observation that response latency is influenced by stimulus- and task-associated factors emphasizes a need to examine response timing alongside firing rate in determining the functional role of area V4.NEW & NOTEWORTHY Onset and offset timing of neuronal responses can provide information about visual environment and neuron's role in visual processing and its anatomical connectivity. In the first comprehensive examination of onset and offset latencies in the intermediate visual cortical area V4, we find neurons respond faster than previously reported, making them ideally suited to contribute to rapid object and scene recognition. While response onset reflects stimulus characteristics, timing of response offset is influenced more by behavioral task.

Object shape and surface properties are jointly encoded in mid-level ventral visual cortex.

Recognizing a myriad visual objects rapidly is a hallmark of the primate visual system. Traditional theories of object recognition have focused on how crucial form features, for example, the orientation of edges, may be extracted in early visual cortex and utilized to recognize objects. An alternative view argues that much of early and mid-level visual processing focuses on encoding surface characteristics, for example, texture. Neurophysiological evidence from primate area V4 supports a third alternative - the joint, but independent, encoding of form and texture - that would be advantageous for segmenting objects from the background in natural scenes and for object recognition that is independent of surface texture. Future studies that leverage deep convolutional network models, especially focusing on network failures to match biology and behavior, can advance our insights into how such a joint representation of form and surface properties might emerge in visual cortex.

Neural Coding for Shape and Texture in Macaque Area V4.

The distinct visual sensations of shape and texture have been studied separately in cortex; therefore, it remains unknown whether separate neuronal populations encode each of these properties or one population carries a joint encoding. We directly compared shape and texture selectivity of individual V4 neurons in awake macaques (1 male, 1 female) and found that V4 neurons lie along a continuum from strong tuning for boundary curvature of shapes to strong tuning for perceptual dimensions of texture. Among neurons tuned to both attributes, tuning for shape and texture were largely separable, with the latter delayed by ∼30 ms. We also found that shape stimuli typically evoked stronger, more selective responses than did texture patches, regardless of whether the latter were contained within or extended beyond the receptive field. These results suggest that there are separate specializations in mid-level cortical processing for visual attributes of shape and texture.SIGNIFICANCE STATEMENT Object recognition depends on our ability to see both the shape of the boundaries of objects and properties of their surfaces. However, neuroscientists have never before examined how shape and texture are linked together in mid-level visual cortex. In this study, we used systematically designed sets of simple shapes and texture patches to probe the responses of individual neurons in the primate visual cortex. Our results provide the first evidence that some cortical neurons specialize in processing shape whereas others specialize in processing textures. Most neurons lie between the ends of this continuum, and in these neurons we find that shape and texture encoding are largely independent.

Modeling diverse responses to filled and outline shapes in macaque V4.

Visual area V4 is an important midlevel cortical processing stage that subserves object recognition in primates. Studies investigating shape coding in V4 have largely probed neuronal responses with filled shapes, i.e., shapes defined by both a boundary and an interior fill. As a result, we do not know whether form-selective V4 responses are dictated by boundary features alone or if interior fill is also important. We studied 43 V4 neurons in two male macaque monkeys ( Macaca mulatta) with a set of 362 filled shapes and their corresponding outlines to determine how interior fill modulates neuronal responses in shape-selective neurons. Only a minority of neurons exhibited similar response strength and shape preferences for filled and outline stimuli. A majority responded preferentially to one stimulus category (either filled or outline shapes) and poorly to the other. Our findings are inconsistent with predictions of the hierarchical-max (HMax) V4 model that builds form selectivity from oriented boundary features and takes little account of attributes related to object surface, such as the phase of the boundary edge. We modified the V4 HMax model to include sensitivity to interior fill by either removing phase-pooling or introducing unoriented units at the V1 level; both modifications better explained our data without increasing the number of free parameters. Overall, our results suggest that boundary orientation and interior surface information are both maintained until at least the midlevel visual representation, consistent with the idea that object fill is important for recognition and perception in natural vision. NEW & NOTEWORTHY The shape of an object's boundary is critical for identification; consistent with this idea, models of object recognition predict that filled and outline versions of a shape are encoded similarly. We report that many neurons in a midlevel visual cortical area respond differently to filled and outline shapes and modify a biologically plausible model to account for our data. Our results suggest that representations of boundary shape and surface fill are interrelated in visual cortex.

'Artiphysiology' reveals V4-like shape tuning in a deep network trained for image classification.

Deep networks provide a potentially rich interconnection between neuroscientific and artificial approaches to understanding visual intelligence, but the relationship between artificial and neural representations of complex visual form has not been elucidated at the level of single-unit selectivity. Taking the approach of an electrophysiologist to characterizing single CNN units, we found many units exhibit translation-invariant boundary curvature selectivity approaching that of exemplar neurons in the primate mid-level visual area V4. For some V4-like units, particularly in middle layers, the natural images that drove them best were qualitatively consistent with selectivity for object boundaries. Our results identify a novel image-computable model for V4 boundary curvature selectivity and suggest that such a representation may begin to emerge within an artificial network trained for image categorization, even though boundary information was not provided during training. This raises the possibility that single-unit selectivity in CNNs will become a guide for understanding sensory cortex.

Predictive Coding in Area V4: Dynamic Shape Discrimination under Partial Occlusion.

The primate visual system has an exquisite ability to discriminate partially occluded shapes. Recent electrophysiological recordings suggest that response dynamics in intermediate visual cortical area V4, shaped by feedback from prefrontal cortex (PFC), may play a key role. To probe the algorithms that may underlie these findings, we build and test a model of V4 and PFC interactions based on a hierarchical predictive coding framework. We propose that probabilistic inference occurs in two steps. Initially, V4 responses are driven solely by bottom-up sensory input and are thus strongly influenced by the level of occlusion. After a delay, V4 responses combine both feedforward input and feedback signals from the PFC; the latter reflect predictions made by PFC about the visual stimulus underlying V4 activity. We find that this model captures key features of V4 and PFC dynamics observed in experiments. Specifically, PFC responses are strongest for occluded stimuli and delayed responses in V4 are less sensitive to occlusion, supporting our hypothesis that the feedback signals from PFC underlie robust discrimination of occluded shapes. Thus, our study proposes that area V4 and PFC participate in hierarchical inference, with feedback signals encoding top-down predictions about occluded shapes.

Joint coding of shape and blur in area V4.

Edge blur, a prevalent feature of natural images, is believed to facilitate multiple visual processes including segmentation and depth perception. Furthermore, image descriptions that explicitly combine blur and shape information provide complete representations of naturalistic scenes. Here we report the first demonstration of blur encoding in primate visual cortex: neurons in macaque V4 exhibit tuning for both object shape and boundary blur, with observed blur tuning not explained by potential confounds including stimulus size, intensity, or curvature. A descriptive model wherein blur selectivity is cast as a distinct neural process that modulates the gain of shape-selective V4 neurons explains observed data, supporting the hypothesis that shape and blur are fundamental features of a sufficient neural code for natural image representation in V4.

Dynamic representation of partially occluded objects in primate prefrontal and visual cortex.

Successful recognition of partially occluded objects is presumed to involve dynamic interactions between brain areas responsible for vision and cognition, but neurophysiological evidence for the involvement of feedback signals is lacking. Here, we demonstrate that neurons in the ventrolateral prefrontal cortex (vlPFC) of monkeys performing a shape discrimination task respond more strongly to occluded than unoccluded stimuli. In contrast, neurons in visual area V4 respond more strongly to unoccluded stimuli. Analyses of V4 response dynamics reveal that many neurons exhibit two transient response peaks, the second of which emerges after vlPFC response onset and displays stronger selectivity for occluded shapes. We replicate these findings using a model of V4/vlPFC interactions in which occlusion-sensitive vlPFC neurons feed back to shape-selective V4 neurons, thereby enhancing V4 responses and selectivity to occluded shapes. These results reveal how signals from frontal and visual cortex could interact to facilitate object recognition under occlusion.

Contour Curvature As an Invariant Code for Objects in Visual Area V4.

UNLABELLED: Size-invariant object recognition-the ability to recognize objects across transformations of scale-is a fundamental feature of biological and artificial vision. To investigate its basis in the primate cerebral cortex, we measured single neuron responses to stimuli of varying size in visual area V4, a cornerstone of the object-processing pathway, in rhesus monkeys (Macaca mulatta). Leveraging two competing models for how neuronal selectivity for the bounding contours of objects may depend on stimulus size, we show that most V4 neurons (∼70%) encode objects in a size-invariant manner, consistent with selectivity for a size-independent parameter of boundary form: for these neurons, "normalized" curvature, rather than "absolute" curvature, provided a better account of responses. Our results demonstrate the suitability of contour curvature as a basis for size-invariant object representation in the visual cortex, and posit V4 as a foundation for behaviorally relevant object codes. SIGNIFICANCE STATEMENT: Size-invariant object recognition is a bedrock for many perceptual and cognitive functions. Despite growing neurophysiological evidence for invariant object representations in the primate cortex, we still lack a basic understanding of the encoding rules that govern them. Classic work in the field of visual shape theory has long postulated that a representation of objects based on information about their bounding contours is well suited to mediate such an invariant code. In this study, we provide the first empirical support for this hypothesis, and its instantiation in single neurons of visual area V4.