Response latency of macaque area MT/V5 neurons and its relationship to stimulus parameters

Characterizing Spatiotemporal Population Receptive Fields in Human Visual Cortex with fMRI

The use of fMRI and computational modeling has advanced understanding of spatial characteristics of population receptive fields (pRFs) in human visual cortex. However, we know relatively little about the spatiotemporal characteristics of pRFs because neurons' temporal properties are one to two orders of magnitude faster than fMRI BOLD responses. Here, we developed an image-computable framework to estimate spatiotemporal pRFs from fMRI data. First, we developed a simulation software that predicts fMRI responses to a time-varying visual input given a spatiotemporal pRF model and solves the model parameters. The simulator revealed that ground-truth spatiotemporal parameters can be accurately recovered at the millisecond resolution from synthesized fMRI responses. Then, using fMRI and a novel stimulus paradigm, we mapped spatiotemporal pRFs in individual voxels across human visual cortex in 10 participants (both females and males). We find that a compressive spatiotemporal (CST) pRF model better explains fMRI responses than a conventional spatial pRF model across visual areas spanning the dorsal, lateral, and ventral streams. Further, we find three organizational principles of spatiotemporal pRFs: (1) from early to later areas within a visual stream, spatial and temporal windows of pRFs progressively increase in size and show greater compressive nonlinearities, (2) later visual areas show diverging spatial and temporal windows across streams, and (3) within early visual areas (V1-V3), both spatial and temporal windows systematically increase with eccentricity. Together, this computational framework and empirical results open exciting new possibilities for modeling and measuring fine-grained spatiotemporal dynamics of neural responses using fMRI.

Characterizing spatiotemporal population receptive fields in human visual cortex with fMRI

The use of fMRI and computational modeling has advanced understanding of spatial characteristics of population receptive fields (pRFs) in human visual cortex. However, we know relatively little about the spatiotemporal characteristics of pRFs because neurons' temporal properties are one to two orders of magnitude faster than fMRI BOLD responses. Here, we developed an image-computable framework to estimate spatiotemporal pRFs from fMRI data. First, we developed a simulation software that predicts fMRI responses to a time varying visual input given a spatiotemporal pRF model and solves the model parameters. The simulator revealed that ground-truth spatiotemporal parameters can be accurately recovered at the millisecond resolution from synthesized fMRI responses. Then, using fMRI and a novel stimulus paradigm, we mapped spatiotemporal pRFs in individual voxels across human visual cortex in 10 participants. We find that a compressive spatiotemporal (CST) pRF model better explains fMRI responses than a conventional spatial pRF model across visual areas spanning the dorsal, lateral, and ventral streams. Further, we find three organizational principles of spatiotemporal pRFs: (i) from early to later areas within a visual stream, spatial and temporal integration windows of pRFs progressively increase in size and show greater compressive nonlinearities, (ii) later visual areas show diverging spatial and temporal integration windows across streams, and (iii) within early visual areas (V1-V3), both spatial and temporal integration windows systematically increase with eccentricity. Together, this computational framework and empirical results open exciting new possibilities for modeling and measuring fine-grained spatiotemporal dynamics of neural responses in the human brain using fMRI.

Deeper neural network models better reflect how humans cope with contrast variation in object recognition

Visual inputs are far from ideal in everyday situations such as in the fog where the contrasts of input stimuli are low. However, human perception remains relatively robust to contrast variations. To provide insights about the underlying mechanisms of contrast invariance, we addressed two questions. Do contrast effects disappear along the visual hierarchy? Do later stages of the visual hierarchy contribute to contrast invariance? We ran a behavioral experiment where we manipulated the level of stimulus contrast and the involvement of higher-level visual areas through immediate and delayed backward masking of the stimulus. Backward masking led to significant drop in performance in our visual categorization task, supporting the role of higher-level visual areas in contrast invariance. To obtain mechanistic insights, we ran the same categorization task on three state-of the-art computational models of human vision each with a different depth in visual hierarchy. We found contrast effects all along the visual hierarchy, no matter how far into the hierarchy. Moreover, that final layers of deeper hierarchical models, which had been shown to be best models of final stages of the visual system, coped with contrast effects more effectively. These results suggest that, while contrast effects reach the final stages of the hierarchy, those stages play a significant role in compensating for contrast variations in the visual system.

Perceptual Weighting of V1 Spikes Revealed by Optogenetic White Noise Stimulation

During visually guided behaviors, mere hundreds of milliseconds can elapse between a sensory input and its associated behavioral response. How spikes occurring at different times are integrated to drive perception and action remains poorly understood. We delivered random trains of optogenetic stimulation (white noise) to excite inhibitory interneurons in V1 of mice of both sexes while they performed a visual detection task. We then performed a reverse correlation analysis on the optogenetic stimuli to generate a neuronal-behavioral kernel, an unbiased, temporally precise estimate of how suppression of V1 spiking at different moments around the onset of a visual stimulus affects detection of that stimulus. Electrophysiological recordings enabled us to capture the effects of optogenetic stimuli on V1 responsivity and revealed that the earliest stimulus-evoked spikes are preferentially weighted for guiding behavior. These data demonstrate that white noise optogenetic stimulation is a powerful tool for understanding how patterns of spiking in neuronal populations are decoded in generating perception and action.SIGNIFICANCE STATEMENT During visually guided actions, continuous chains of neurons connect our retinas to our motoneurons. To unravel circuit contributions to behavior, it is crucial to establish the relative functional position(s) that different neural structures occupy in processing and relaying the signals that support rapid, precise responses. To address this question, we randomly inhibited activity in mouse V1 throughout the stimulus-response cycle while the animals did many repetitions of a visual task. The period that led to impaired performance corresponded to the earliest stimulus-driven response in V1, with no effect of inhibition immediately before or during late stages of the stimulus-driven response. This approach offers experimenters a powerful method for uncovering the temporal weighting of spikes from stimulus to response.

Columnar processing of border ownership in primate visual cortex

To understand a visual scene, the brain segregates figures from background by assigning borders to foreground objects. Neurons in primate visual cortex encode which object owns a border (border ownership), but the underlying circuitry is not understood. Here, we used multielectrode probes to record from border ownership-selective units in different layers in macaque visual area V4 to study the laminar organization and timing of border ownership selectivity. We find that border ownership selectivity occurs first in deep layer units, in contrast to spike latency for small stimuli in the classical receptive field. Units on the same penetration typically share the preferred side of border ownership, also across layers, similar to orientation preference. Units are often border ownership-selective for a range of border orientations, where the preferred sides of border ownership are systematically organized in visual space. Together our data reveal a columnar organization of border ownership in V4 where the earliest border ownership signals are not simply inherited from upstream areas, but computed by neurons in deep layers, and may thus be part of signals fed back to upstream cortical areas or the oculomotor system early after stimulus onset. The finding that preferred border ownership is clustered and can cover a wide range of spatially contiguous locations suggests that the asymmetric context integrated by these neurons is provided in a systematically clustered manner, possibly through corticocortical feedback and horizontal connections.

To understand a visual scene, the brain needs to identify objects and distinguish them from background. A border marks the transition from object to background, but to differentiate which side of the border belongs to the object and which to background, the brain must integrate information across space. An early signature of this computation is that brain cells signal which side of a border is ‘owned’ by an object, also known as border ownership. But how the brain computes border ownership remains unknown.

The optic nerve is a cable-like group of nerve cells that transmits information from the eye to the brain’s visual processing areas and into the visual cortex. This flow of information is often described as traveling in a feedforward direction, away from the eyes to progressively more specialized areas in the visual cortex. However, there are also numerous feedback connections in the brain, running backward from more specialized to less specialized cortical areas.

To better understand the role of these feedforward and feedback circuits in the visual processing of object borders, Franken and Reynolds made use of their stereotyped projection patterns across the cortex layers. Feedforward connections terminate in the middle layers of a cortical area, whereas feedback connections terminate in upper and lower layers. Since time is required for information to traverse the cortical layers, dissecting the timing of border ownership signals may reveal if border ownership is computed in a feedforward or feedback manner. To find out more, electrodes were used to record neural activity in the upper, middle and lower layers of the visual cortex of two rhesus monkeys as they were presented with a set of abstract scenes composed of simple shapes on a background.

This revealed that cells signaling border ownership in deep layers of the cortex did so before the signals appeared in the middle layer. This suggests that feedback rather than feedforward is required to compute border ownership. Moreover, Franken and Reynolds found evidence that cells that prefer the same side of border ownership are clustered in columns, showing how these neural circuits are organized within the visual cortex.

In summary, Franken and Reynolds found that the circuits of the primate brain that compute border ownership occur as columns, in which cells in deep layers signal border ownership first, suggesting that border ownership relies on feedback from more specialized areas. A better understanding of how feedback in the brain works to process visual information helps us appreciate what happens when these systems are impaired.

Dynamic divisive normalization circuits explain and predict change detection in monkey area MT

Sudden changes in visual scenes often indicate important events for behavior. For their quick and reliable detection, the brain must be capable to process these changes as independently as possible from its current activation state. In motion-selective area MT, neurons respond to instantaneous speed changes with pronounced transients, often far exceeding the expected response as derived from their speed tuning profile. We here show that this complex, non-linear behavior emerges from the combined temporal dynamics of excitation and divisive inhibition, and provide a comprehensive mathematical analysis. A central prediction derived from this investigation is that attention increases the steepness of the transient response irrespective of the activation state prior to a stimulus change, and irrespective of the sign of the change (i.e. irrespective of whether the stimulus is accelerating or decelerating). Extracellular recordings of attention-dependent representation of both speed increments and decrements confirmed this prediction and suggest that improved change detection derives from basic computations in a canonical cortical circuitry.

Early recurrence enables figure border ownership

Rubin's face-vase illusion demonstrates how one can switch back and forth between two different interpretations depending on how the figure outlines are assigned. In the primate visual system, assigning ownership along figure borders is encoded by neurons called the border ownership (BO) cells. Studies show that the responses of these neurons not only depend on the local features within their receptive fields, but also on contextual information. Despite two decades of studies on BO neurons, the ownership assignment mechanism in the brain is still unknown. Here, we propose a hierarchical recurrent model grounded on the hypothesis that neurons in the dorsal stream provide the context required for ownership assignment. Our proposed model incorporates early recurrence from the dorsal pathway as well as lateral modulations within the ventral stream. While dorsal modulations initiate the response difference to figure on either side of the border, lateral modulations enhance the difference. We found responses of our dorsally-modulated BO cells, similar to their biological counterparts, are invariant to size, position and solid/outlined figures. Moreover, our model BO cells exhibit comparable levels of reliability in the ownership signal to biological BO neurons. We found dorsal modulations result in high levels of accuracy and robustness for BO assignments in complex scenes compared to previous models based on ventral feedback. Finally, our experiments with illusory contours suggest that BO encoding could explain the perception of such contours in higher processing stages in the brain.

Neural Selectivity for Visual Motion in Macaque Area V3A

The processing of visual motion is conducted by dedicated pathways in the primate brain. These pathways originate with populations of direction-selective neurons in the primary visual cortex, which projects to dorsal structures like the middle temporal (MT) and medial superior temporal (MST) areas. Anatomical and imaging studies have suggested that area V3A might also be specialized for motion processing, but there have been very few studies of single-neuron direction selectivity in this area. We have therefore performed electrophysiological recordings from V3A neurons in two macaque monkeys (one male and one female) and measured responses to a large battery of motion stimuli that includes translation motion, as well as more complex optic flow patterns. For comparison, we simultaneously recorded the responses of MT neurons to the same stimuli. Surprisingly, we find that overall levels of direction selectivity are similar in V3A and MT and moreover that the population of V3A neurons exhibits somewhat greater selectivity for optic flow patterns. These results suggest that V3A should be considered as part of the motion processing machinery of the visual cortex, in both human and non-human primates.

Excitation-Inhibition Balanced Neural Networks for Fast Signal Detection

Excitation-inhibition (E-I) balanced neural networks are a classic model for modeling neural activities and functions in the cortex. The present study investigates the potential application of E-I balanced neural networks for fast signal detection in brain-inspired computation. We first theoretically analyze the response property of an E-I balanced network, and find that the asynchronous firing state of the network generates an optimal noise structure enabling the network to track input changes rapidly. We then extend the homogeneous connectivity of an E-I balanced neural network to include local neuronal connections, so that the network can still achieve fast response and meanwhile maintain spatial information in the face of spatially heterogeneous signal. Finally, we carry out simulations to demonstrate that our model works well.

Attention amplifies neural representations of changes in sensory input at the expense of perceptual accuracy

Attention enhances the neural representations of behaviorally relevant stimuli, typically by a push-pull increase of the neuronal response gain to attended vs. unattended stimuli. This selectively improves perception and consequently behavioral performance. However, to enhance the detectability of stimulus changes, attention might also distort neural representations, compromising accurate stimulus representation. We test this hypothesis by recording neural responses in the visual cortex of rhesus monkeys during a motion direction change detection task. We find that attention indeed amplifies the neural representation of direction changes, beyond a similar effect of adaptation. We further show that humans overestimate such direction changes, providing a perceptual correlate of our neurophysiological observations. Our results demonstrate that attention distorts the neural representations of abrupt sensory changes and consequently perceptual accuracy. This likely represents an evolutionary adaptive mechanism that allows sensory systems to flexibly forgo accurate representation of stimulus features to improve the encoding of stimulus change.

Visual Motion Processing in Macaque V2

In the primate visual system, direction-selective (DS) neurons are critical for visual motion perception. While DS neurons in the dorsal visual pathway have been well characterized, the response properties of DS neurons in other major visual areas are largely unexplored. Recent optical imaging studies in monkey visual cortex area 2 (V2) revealed clusters of DS neurons. This imaging method facilitates targeted recordings from these neurons. Using optical imaging and single-cell recording, we characterized detailed response properties of DS neurons in macaque V2. Compared with DS neurons in the dorsal areas (e.g., middle temporal area [MT]), V2 DS neurons have a smaller receptive field and a stronger antagonistic surround. They do not code speed or plaid motion but are sensitive to motion contrast. Our results suggest that V2 DS neurons play an important role in figure-ground segregation. The clusters of V2 DS neurons are likely specialized functional systems for detecting motion contrast.

Going with the Flow: The Neural Mechanisms Underlying Illusions of Complex-Flow Motion

Studying the mismatch between perception and reality helps us better understand the constructive nature of the visual brain. The Pinna-Brelstaff motion illusion is a compelling example illustrating how a complex moving pattern can generate an illusory motion perception. When an observer moves toward (expansion) or away (contraction) from the Pinna-Brelstaff figure, the figure appears to rotate. The neural mechanisms underlying the illusory complex-flow motion of rotation, expansion, and contraction remain unknown. We studied this question at both perceptual and neuronal levels in behaving male macaques by using carefully parametrized Pinna-Brelstaff figures that induce the above motion illusions. We first demonstrate that macaques perceive illusory motion in a manner similar to that of human observers. Neurophysiological recordings were subsequently performed in the middle temporal area (MT) and the dorsal portion of the medial superior temporal area (MSTd). We find that subgroups of MSTd neurons encoding a particular global pattern of real complex-flow motion (rotation, expansion, contraction) also represent illusory motion patterns of the same class. They require an extra 15 ms to reliably discriminate the illusion. In contrast, MT neurons encode both real and illusory local motions with similar temporal delays. These findings reveal that illusory complex-flow motion is first represented in MSTd by the same neurons that normally encode real complex-flow motion. However, the extraction of global illusory motion in MSTd from other classes of real complex-flow motion requires extra processing time. Our study illustrates a cascaded integration mechanism from MT to MSTd underlying the transformation from external physical to internal nonveridical flow-motion perception.SIGNIFICANCE STATEMENT The neural basis of the transformation from objective reality to illusory percepts of rotation, expansion, and contraction remains unknown. We demonstrate psychophysically that macaques perceive these illusory complex-flow motions in a manner similar to that of human observers. At the neural level, we show that medial superior temporal (MSTd) neurons represent illusory flow motions as if they were real by globally integrating middle temporal area (MT) local motion signals. Furthermore, while MT neurons reliably encode real and illusory local motions with similar temporal delays, MSTd neurons take a significantly longer time to process the signals associated with illusory percepts. Our work extends previous complex-flow motion studies by providing the first detailed analysis of the neuron-specific mechanisms underlying complex forms of illusory motion integration from MT to MSTd.

Prefrontal Contributions to Attention and Working Memory

The processes of attention and working memory are conspicuously interlinked, suggesting that they may involve overlapping neural mechanisms. Working memory (WM) is the ability to maintain information in the absence of sensory input. Attention is the process by which a specific target is selected for further processing, and neural resources directed toward that target. The content of WM can be used to direct attention, and attention can in turn determine which information is encoded into WM. Here we discuss the similarities between attention and WM and the role prefrontal cortex (PFC) plays in each. First, at the theoretical level, we describe how attention and WM can both rely on models based on attractor states. Then we review the evidence for an overlap between the areas involved in both functions, especially the frontal eye field (FEF) portion of the prefrontal cortex. We also discuss similarities between the neural changes in visual areas observed during attention and WM. At the cellular level, we review the literature on the role of prefrontal DA in both attention and WM at the behavioral and neural levels. Finally, we summarize the anatomical evidence for an overlap between prefrontal mechanisms involved in attention and WM. Altogether, a summary of pharmacological, electrophysiological, behavioral, and anatomical evidence for a contribution of the FEF part of prefrontal cortex to attention and WM is provided.

Human posterior parietal cortex responds to visual stimuli as early as peristriate occipital cortex

Much of what is known about the timing of visual processing in the brain is inferred from intracranial studies in monkeys, with human data limited to mainly noninvasive methods with lower spatial resolution. Here, we estimated visual onset latencies from electrocorticographic (ECoG) recordings in a patient who was implanted with 112 subdural electrodes, distributed across the posterior cortex of the right hemisphere, for presurgical evaluation of intractable epilepsy. Functional MRI prior to surgery was used to determine boundaries of visual areas. The patient was presented with images of objects from several categories. Event-related potentials (ERPs) were calculated across all categories excluding targets, and statistically reliable onset latencies were determined, using a bootstrapping procedure over the single trial baseline activity in individual electrodes. The distribution of onset latencies broadly reflected the known hierarchy of visual areas, with the earliest cortical responses in primary visual cortex, and higher areas showing later responses. A clear exception to this pattern was a robust, statistically reliable and spatially localized, very early response, on the bank of the posterior intraparietal sulcus (IPS). The response in the IPS started nearly simultaneously with responses detected in peristriate visual areas, around 60 ms poststimulus onset. Our results support the notion of early visual processing in the posterior parietal lobe, not respecting traditional hierarchies, and give direct evidence for onset times of visual responses across the human cortex.

State dependence of stimulus-induced variability tuning in macaque MT

Behavioral states marked by varying levels of arousal and attention modulate some properties of cortical responses (e.g. average firing rates or pairwise correlations), yet it is not fully understood what drives these response changes and how they might affect downstream stimulus decoding. Here we show that changes in state modulate the tuning of response variance-to-mean ratios (Fano factors) in a fashion that is neither predicted by a Poisson spiking model nor changes in the mean firing rate, with a substantial effect on stimulus discriminability. We recorded motion-sensitive neurons in middle temporal cortex (MT) in two states: alert fixation and light, opioid anesthesia. Anesthesia tended to lower average spike counts, without decreasing trial-to-trial variability compared to the alert state. Under anesthesia, within-trial fluctuations in excitability were correlated over longer time scales compared to the alert state, creating supra-Poisson Fano factors. In contrast, alert-state MT neurons have higher mean firing rates and largely sub-Poisson variability that is stimulus-dependent and cannot be explained by firing rate differences alone. The absence of such stimulus-induced variability tuning in the anesthetized state suggests different sources of variability between states. A simple model explains state-dependent shifts in the distribution of observed Fano factors via a suppression in the variance of gain fluctuations in the alert state. A population model with stimulus-induced variability tuning and behaviorally constrained information-limiting correlations explores the potential enhancement in stimulus discriminability by the cortical population in the alert state.

The brain controls behavior fluidly in a wide variety of cognitive contexts that alter the precision of neural responses. We examine how neural variability changes versus the mean response as a function of the stimulus and the behavioral state. We show that this scaled variability can have qualitatively different stimulus tuning in different behavioral contexts. In alert primates, scaled variability is tuned to the direction of motion of a visual stimulus and decreases around the preferred direction of each neuron. Under anesthesia, neurons show flat scaled variability tuning and, overall, responses are significantly more variable. We develop a simple model that includes a parameter describing firing rate gain fluctuations that can explain these changes. Our results suggest that tuned decreases in scaled variability during wakefulness may be mediated by an active process that suppresses synchronization and makes information transmission more reliable.

Distinct Laminar Processing of Local and Global Context in Primate Primary Visual Cortex

Visual perception is affected by spatial context. In visual cortex, neuronal responses to stimuli inside the receptive field (RF) are suppressed by stimuli in the RF surround. To understand the circuits and cortical layers processing spatial context, we simultaneously recorded across all layers of macaque primary visual cortex while presenting stimuli at increasing distances from the recorded cells' RF. We find that near versus far-surround stimuli activate distinct layers, thus revealing unique laminar contributions to the processing of local and global spatial context. Stimuli in the near-surround evoke the earliest subthreshold responses in superficial and upper-deep layers, and earliest suppression of spiking responses in superficial layers. Conversely, far-surround stimuli evoke the earliest subthreshold responses in feedback-recipient layer 1 and lower-deep layers, and earliest suppression of spiking responses almost simultaneously in all layers, except 4C, where suppression emerges last. Our results suggest distinct circuits for local and global signal integration.

Visual motion serves but is not under the purview of the dorsal pathway

Visual motion processing is often attributed to the dorsal visual pathway despite visual motion's involvement in almost all visual functions. Furthermore, some visual motion tasks critically depend on the structural integrity of regions outside the dorsal pathway. Here, based on numerous studies, I propose that visual motion signals are swiftly transmitted via multiple non-hierarchical routes to primary motion-dedicated processing regions (MT/V5 and MST) that are not part of the dorsal pathway, and then propagated to a multiplicity of brain areas according to task demands, reaching these regions earlier than the dorsal/ventral hierarchical flow. This not only places MT/V5 at the same or even earlier visual processing stage as that of V1, but can also elucidate many findings with implications to visual awareness. While the integrity of the non-hierarchical motion pathway is necessary for all visual motion perception, it is insufficient on its own, and the transfer of visual motion signals to additional brain areas is crucial to allow the different motion perception tasks (e.g. optic flow, visuo-vestibular balance, movement observation, dynamic form detection and perception, and even reading). I argue that this lateral visual motion pathway can be distinguished from the dorsal pathway not only based on faster response latencies and distinct anatomical connections, but also based on its full field representation. I also distinguish between this primary lateral visual motion pathway sensitive to all motion in the visual field, and a much less investigated optic flow sensitive medial processing pathway (from V1 to V6 and V6A) that appears to be part of the dorsal pathway. Multiple additional predictions are provided that allow testing this proposal and distinguishing between the visual pathways.

The importance of decision onset

The neural mechanisms of decision making are thought to require the integration of evidence over time until a response threshold is reached. Much work suggests that response threshold can be adjusted via top-down control as a function of speed or accuracy requirements. In contrast, the time of integration onset has received less attention and is believed to be determined mostly by afferent or preprocessing delays. However, a number of influential studies over the past decade challenge this assumption and begin to paint a multifaceted view of the phenomenology of decision onset. This review highlights the challenges involved in initiating the integration of evidence at the optimal time and the potential benefits of adjusting integration onset to task demands. The review outlines behavioral and electrophysiolgical studies suggesting that the onset of the integration process may depend on properties of the stimulus, the task, attention, and response strategy. Most importantly, the aggregate findings in the literature suggest that integration onset may be amenable to top-down regulation, and may be adjusted much like response threshold to exert cognitive control and strategically optimize the decision process to fit immediate behavioral requirements.

Visual attention: Linking prefrontal sources to neuronal and behavioral correlates

Attention is a means of flexibly selecting and enhancing a subset of sensory input based on the current behavioral goals. Numerous signatures of attention have been identified throughout the brain, and now experimenters are seeking to determine which of these signatures are causally related to the behavioral benefits of attention, and the source of these modulations within the brain. Here, we review the neural signatures of attention throughout the brain, their theoretical benefits for visual processing, and their experimental correlations with behavioral performance. We discuss the importance of measuring cue benefits as a way to distinguish between impairments on an attention task, which may instead be visual or motor impairments, and true attentional deficits. We examine evidence for various areas proposed as sources of attentional modulation within the brain, with a focus on the prefrontal cortex. Lastly, we look at studies that aim to link sources of attention to its neuronal signatures elsewhere in the brain.

Transient activity in monkey area MT represents speed changes and is correlated with human behavioral performance

Neurons in the middle temporal area (MT) respond to motion onsets and speed changes with a transient-sustained firing pattern. The latency of the transient response has recently been shown to correlate with reaction time in a speed change detection task, but it is not known how the sign, the amplitude, and the latency of this response depend on the sign and the magnitude of a speed change, and whether these transients can be decoded to explain speed change detection behavior. To investigate this issue, we measured the neuronal representation of a wide range of positive and negative speed changes in area MT of fixating macaques and obtained three major findings. First, speed change transients not only reflect a neuron's absolute speed tuning but are shaped by an additional gain that scales the tuned response according to the magnitude of a relative speed change. Second, by means of a threshold model positive and negative population transients of a moderate number of MT neurons explain detection of both positive and negative speed changes, respectively, at a level comparable to human detection rates under identical visual stimulation. Third, like reaction times in a psychophysical model of velocity detection, speed change response latencies follow a power-law function of the absolute difference of a speed change. Both this neuronal representation and its close correlation with behavioral measures of speed change detection suggest that neuronal transients in area MT facilitate the detection of rapid changes in visual input.

Why is "blindsight" blind? A new perspective on primary visual cortex, recurrent activity and visual awareness

The neuropsychological phenomenon of blindsight has been taken to suggest that the primary visual cortex (V1) plays a unique role in visual awareness, and that extrastriate activation needs to be fed back to V1 in order for the content of that activation to be consciously perceived. The aim of this review is to evaluate this theoretical framework and to revisit its key tenets. Firstly, is blindsight truly a dissociation of awareness and visual detection? Secondly, is there sufficient evidence to rule out the possibility that the loss of awareness resulting from a V1 lesion simply reflects reduced extrastriate responsiveness, rather than a unique role of V1 in conscious experience? Evaluation of these arguments and the empirical evidence leads to the conclusion that the loss of phenomenal awareness in blindsight may not be due to feedback activity in V1 being the hallmark awareness. On the basis of existing literature, an alternative explanation of blindsight is proposed. In this view, visual awareness is a "global" cognitive function as its hallmark is the availability of information to a large number of perceptual and cognitive systems; this requires inter-areal long-range synchronous oscillatory activity. For these oscillations to arise, a specific temporal profile of neuronal activity is required, which is established through recurrent feedback activity involving V1 and the extrastriate cortex. When V1 is lesioned, the loss of recurrent activity prevents inter-areal networks on the basis of oscillatory activity. However, as limited amount of input can reach extrastriate cortex and some extrastriate neuronal selectivity is preserved, computations involving comparison of neural firing rates within a cortical area remain possible. This enables "local" read-out from specific brain regions, allowing for the detection and discrimination of basic visual attributes. Thus blindsight is blind due to lack of "global" long-range synchrony, and it functions via "local" neural readout from extrastriate areas.

Microcircuitry of agranular frontal cortex: testing the generality of the canonical cortical microcircuit

We investigated whether a frontal area that lacks granular layer IV, supplementary eye field, exhibits features of laminar circuitry similar to those observed in primary sensory areas. We report, for the first time, visually evoked local field potentials (LFPs) and spiking activity recorded simultaneously across all layers of agranular frontal cortex using linear electrode arrays. We calculated current source density from the LFPs and compared the laminar organization of evolving sinks to those reported in sensory areas. Simultaneous, transient synaptic current sinks appeared first in layers III and V followed by more prolonged current sinks in layers I/II and VI. We also found no variation of single- or multi-unit visual response latency across layers, and putative pyramidal neurons and interneurons displayed similar response latencies. Many units exhibited pronounced discharge suppression that was strongest in superficial relative to deep layers. Maximum discharge suppression also occurred later in superficial than in deep layers. These results are discussed in the context of the canonical cortical microcircuit model originally formulated to describe early sensory cortex. The data indicate that agranular cortex resembles sensory areas in certain respects, but the cortical microcircuit is modified in nontrivial ways.

Bifurcation study of a neural field competition model with an application to perceptual switching in motion integration

Perceptual multistability is a phenomenon in which alternate interpretations of a fixed stimulus are perceived intermittently. Although correlates between activity in specific cortical areas and perception have been found, the complex patterns of activity and the underlying mechanisms that gate multistable perception are little understood. Here, we present a neural field competition model in which competing states are represented in a continuous feature space. Bifurcation analysis is used to describe the different types of complex spatio-temporal dynamics produced by the model in terms of several parameters and for different inputs. The dynamics of the model was then compared to human perception investigated psychophysically during long presentations of an ambiguous, multistable motion pattern known as the barberpole illusion. In order to do this, the model is operated in a parameter range where known physiological response properties are reproduced whilst also working close to bifurcation. The model accounts for characteristic behaviour from the psychophysical experiments in terms of the type of switching observed and changes in the rate of switching with respect to contrast. In this way, the modelling study sheds light on the underlying mechanisms that drive perceptual switching in different contrast regimes. The general approach presented is applicable to a broad range of perceptual competition problems in which spatial interactions play a role.

Neural mechanisms of speed perception: transparent motion

Visual motion on the macaque retina is processed by direction- and speed-selective neurons in extrastriate middle temporal cortex (MT). There is strong evidence for a link between the activity of these neurons and direction perception. However, there is conflicting evidence for a link between speed selectivity of MT neurons and speed perception. Here we study this relationship by using a strong perceptual illusion in speed perception: when two transparently superimposed dot patterns move in opposite directions, their apparent speed is much larger than the perceived speed of a single pattern moving at that physical speed. Moreover, the sensitivity for speed discrimination is reduced for such bidirectional patterns. We first confirmed these behavioral findings in human subjects and extended them to a monkey subject. Second, we determined speed tuning curves of MT neurons to bidirectional motion and compared these to speed tuning curves for unidirectional motion. Consistent with previous reports, the response to bidirectional motion was often reduced compared with unidirectional motion at the preferred speed. In addition, we found that tuning curves for bidirectional motion were shifted to lower preferred speeds. As a consequence, bidirectional motion of some speeds typically evoked larger responses than unidirectional motion. Third, we showed that these changes in neural responses could explain changes in speed perception with a simple labeled line decoder. These data provide new insight into the encoding of transparent motion patterns and provide support for the hypothesis that MT activity can be decoded for speed perception with a labeled line model.

Relationship between size summation properties, contrast sensitivity and response latency in the dorsomedial and middle temporal areas of the primate extrastriate cortex

Analysis of the physiological properties of single neurons in visual cortex has demonstrated that both the extent of their receptive fields and the latency of their responses depend on stimulus contrast. Here, we explore the question of whether there are also systematic relationships between these response properties across different cells in a neuronal population. Single unit recordings were obtained from the middle temporal (MT) and dorsomedial (DM) extrastriate areas of anaesthetized marmoset monkeys. For each cell, spatial integration properties (length and width summation, as well as the presence of end- and side-inhibition within 15° of the receptive field centre) were determined using gratings of optimal direction of motion and spatial and temporal frequencies, at 60% contrast. Following this, contrast sensitivity was assessed using gratings of near-optimal length and width. In both areas, we found a relationship between spatial integration and contrast sensitivity properties: cells that summated over smaller areas of the visual field, and cells that displayed response inhibition at larger stimulus sizes, tended to show higher contrast sensitivity. In a sample of MT neurons, we found that cells showing longer latency responses also tended to summate over larger expanses of visual space in comparison with neurons that had shorter latencies. In addition, longer-latency neurons also tended to show less obvious surround inhibition. Interestingly, all of these effects were stronger and more consistent with respect to the selectivity for stimulus width and strength of side-inhibition than for length selectivity and end-inhibition. The results are partially consistent with a hierarchical model whereby more extensive receptive fields require convergence of information from larger pools of “feedforward” afferent neurons to reach near-optimal responses. They also suggest that a common gain normalization mechanism within MT and DM is involved, the spatial extent of which is more evident along the cell’s preferred axis of motion.

Neural correlates and neural computations in posterior parietal cortex during perceptual decision-making

A recent line of work has found remarkable success in relating perceptual decision-making and the spiking activity in the macaque lateral intraparietal area (LIP). In this review, we focus on questions about the neural computations in LIP that are not answered by demonstrations of neural correlates of psychological processes. We highlight three areas of limitations in our current understanding of the precise neural computations that might underlie neural correlates of decisions: (1) empirical questions not yet answered by existing data; (2) implementation issues related to how neural circuits could actually implement the mechanisms suggested by both extracellular neurophysiology and psychophysics; and (3) ecological constraints related to the use of well-controlled laboratory tasks and whether they provide an accurate window on sensorimotor computation. These issues motivate the adoption of a more general "encoding-decoding framework" that will be fruitful for more detailed contemplation of how neural computations in LIP relate to the formation of perceptual decisions.

Evidence of a direct influence between the thalamus and hMT+ independent of V1 in the human brain as measured by fMRI

In the present study we employed Conditional Granger Causality (CGC) and Coherence analysis to investigate whether visual motion-related information reaches the human middle temporal complex (hMT+) directly from the Lateral Geniculate Nucleus (LGN) of the thalamus, by-passing the primary visual cortex (V1). Ten healthy human volunteers underwent brain scan examinations by functional magnetic resonance imaging (fMRI) during two optic flow experiments. In addition to the classical LGN-V1-hMT+ pathway, our results showed a significant direct influence of the blood oxygenation level dependent (BOLD) signal recorded in LGN over that in hMT+, not mediated by V1 activity, which strongly supports the existence of a bilateral pathway that connects LGN directly to hMT+ and serves visual motion processing. Furthermore, we evaluated the relative latencies among areas functionally connected in the processing of visual motion. Using LGN as a reference region, hMT+ exhibited a statistically significant earlier peak of activation as compared to V1. In conclusion, our findings suggest the co-existence of an alternative route that directly links LGN to hMT+, bypassing V1. This direct pathway may play a significant functional role for the faster detection of motion and may contribute to explain persistence of unconscious motion detection in individuals with severe destruction of primary visual cortex (blindsight).

The functional link between area MT neural fluctuations and detection of a brief motion stimulus

Fluctuations of neural firing rates in visual cortex are known to be correlated with variations in perceptual performance. It is important to know whether these fluctuations are functionally linked to perception in a causal manner or instead reflect non-causal processes that arise after the perceptual decision is made. We recorded from middle temporal (MT) neurons from monkey subjects while they detected the random occurrence of a brief 50 ms motion pulse that occurred in either of two (or simultaneously in both) random dot patches located in the same hemisphere. The receptive field parameters of the motion pulse were matched to that preferred by each MT neuron under study. This task contained uncertainty in both space and time because, on any given trial, the subjects did not know which patch would contain the motion pulse or when the motion pulse would occur. Covariations between MT activity and behavior began just before the motion pulse onset and peaked at the maximum neural response. These neural-behavioral covariations were strongest when only one patch contained the motion pulse and were still weakly present when a patch did not contain a motion pulse. A feedforward temporal integration model with two independent detector channels captured both the detection performance and evolution of the neural-behavior covariations over time and stimulus condition. The results suggest that, when detecting a brief visual stimulus, there is a causal relationship between fluctuations in neural activity and variations in behavior across trials.

Visual feature-tolerance in the reading network

A century of neurology and neuroscience shows that seeing words depends on ventral occipital-temporal (VOT) circuitry. Typically, reading is learned using high-contrast line-contour words. We explored whether a specific VOT region, the visual word form area (VWFA), learns to see only these words or recognizes words independent of the specific shape-defining visual features. Word forms were created using atypical features (motion-dots, luminance-dots) whose statistical properties control word-visibility. We measured fMRI responses as word form visibility varied, and we used TMS to interfere with neural processing in specific cortical circuits, while subjects performed a lexical decision task. For all features, VWFA responses increased with word-visibility and correlated with performance. TMS applied to motion-specialized area hMT+ disrupted reading performance for motion-dots, but not line-contours or luminance-dots. A quantitative model describes feature-convergence in the VWFA and relates VWFA responses to behavioral performance. These findings suggest how visual feature-tolerance in the reading network arises through signal convergence from feature-specialized cortical areas.

Reference frames for spatial frequency in face representation differ in the temporal visual cortex and amygdala

Social communication in nonhuman primates and humans is strongly affected by facial information from other individuals. Many cortical and subcortical brain areas are known to be involved in processing facial information. However, how the neural representation of faces differs across different brain areas remains unclear. Here, we demonstrate that the reference frame for spatial frequency (SF) tuning of face-responsive neurons differs in the temporal visual cortex and amygdala in monkeys. Consistent with psychophysical properties for face recognition, temporal cortex neurons were tuned to image-based SFs (cycles/image) and showed viewing distance-invariant representation of face patterns. On the other hand, many amygdala neurons were influenced by retina-based SFs (cycles/degree), a characteristic that is useful for social distance computation. The two brain areas also differed in the luminance contrast sensitivity of face-responsive neurons; amygdala neurons sharply reduced their responses to low luminance contrast images, while temporal cortex neurons maintained the level of their responses. From these results, we conclude that different types of visual processing in the temporal visual cortex and the amygdala contribute to the construction of the neural representations of faces.

Neural correlates of subsecond time distortion in the middle temporal area of visual cortex

How does the brain represent the passage of time at the subsecond scale? Although different conceptual models for time perception have been proposed, its neurophysiological basis remains unknown. We took advantage of a visual duration illusion produced by stimulus novelty to link changes in cortical activity in monkeys with distortions of duration perception in humans. We found that human subjects perceived the duration of a subsecond motion pulse with a novel direction longer than a motion pulse with a repeated direction. Recording from monkeys viewing identical motion stimuli but performing a different behavioral task, we found that both the duration and amplitude of the neural response in the middle temporal area of visual cortex were positively correlated with the degree of novelty of the motion direction. In contrast to previous accounts that attribute distortions in duration perception to changes in the speed of a putative internal clock, our results suggest that the known adaptive properties of neural activity in visual cortex contributes to subsecond temporal distortions.

Impact of noise structure and network topology on tracking speed of neural networks

Understanding why neural systems can process information extremely fast is a fundamental question in theoretical neuroscience. The present study investigates the effect of noise on accelerating neural computation. To evaluate the speed of network response, we consider a computational task in which the network tracks time-varying stimuli. Two noise structures are compared, namely, the stimulus-dependent and stimulus-independent noises. Based on a simple linear integrate-and-fire model, we theoretically analyze the network dynamics, and find that the stimulus-dependent noise, whose variance is proportional to the mean of external inputs, has better effect on speeding up network computation. This is due to two good properties in the transient network dynamics: (1) the instant firing rate of the network is proportional to the mean of external inputs, and (2) the stationary state of the network is robust to stimulus changes. We investigate two network models with varying recurrent interactions, and find that recurrent interactions tend to slow down the tracking speed of the network. When the biologically plausible Hodgkin-Huxley model is considered, we also observe that the stimulus-dependent noise accelerates neural computation, although the improvement is smaller than that in the case of linear integrate-and-fire model.

Implied Motion Activation in Cortical Area MT Can Be Explained by Visual Low-level Features

To investigate form-related activity in motion-sensitive cortical areas, we recorded cell responses to animate implied motion in macaque middle temporal (MT) and medial superior temporal (MST) cortex and investigated these areas using fMRI in humans. In the single-cell studies, we compared responses with static images of human or monkey figures walking or running left or right with responses to the same human and monkey figures standing or sitting still. We also investigated whether the view of the animate figure (facing left or right) that elicited the highest response was correlated with the preferred direction for moving random dot patterns. First, figures were presented inside the cell's receptive field. Subsequently, figures were presented at the fovea while a dynamic noise pattern was presented at the cell's receptive field location. The results show that MT neurons did not discriminate between figures on the basis of the implied motion content. Instead, response preferences for implied motion correlated with preferences for low-level visual features such as orientation and size. No correlation was found between the preferred view of figures implying motion and the preferred direction for moving random dot patterns. Similar findings were obtained in a smaller population of MST cortical neurons. Testing human MT+ responses with fMRI further corroborated the notion that low-level stimulus features might explain implied motion activation in human MT+. Together, these results suggest that prior human imaging studies demonstrating animate implied motion processing in area MT+ can be best explained by sensitivity for low-level features rather than sensitivity for the motion implied by animate figures.

Testing a simplified method for measuring velocity integration in saccades using a manipulation of target contrast

A growing number of studies in vision research employ analyses of how perturbations in visual stimuli influence behavior on single trials. Recently, we have developed a method along such lines to assess the time course over which object velocity information is extracted on a trial-by-trial basis in order to produce an accurate intercepting saccade to a moving target. Here, we present a simplified version of this methodology, and use it to investigate how changes in stimulus contrast affect the temporal velocity integration window used when generating saccades to moving targets. Observers generated saccades to one of two moving targets which were presented at high (80%) or low (7.5%) contrast. In 50% of trials, target velocity stepped up or down after a variable interval after the saccadic go signal. The extent to which the saccade endpoint can be accounted for as a weighted combination of the pre- or post-step velocities allows for identification of the temporal velocity integration window. Our results show that the temporal integration window takes longer to peak in the low when compared to high contrast condition. By enabling the assessment of how information such as changes in velocity can be used in the programming of a saccadic eye movement on single trials, this study describes and tests a novel methodology with which to look at the internal processing mechanisms that transform sensory visual inputs into oculomotor outputs.

Contributions of indirect pathways to visual response properties in macaque middle temporal area MT

The primate visual cortex exhibits a remarkable degree of interconnectivity. Each visual area receives an average of 10 to 15 inputs, many of them from cortical areas with overlapping, but not identical, functional properties. In this study, we assessed the functional significance of this anatomical parallelism to the middle temporal area (MT) of the macaque visual cortex. MT receives major feedforward inputs from areas V1, V2, and V3, but little is known about the properties of each of these pathways. We previously demonstrated that reversible inactivation of V2 and V3 causes a disproportionate degradation of tuning for binocular disparity of MT neurons, relative to direction tuning (Ponce et al., 2008). Here we show that MT neurons continued to encode speed and size information during V2/3 inactivation; however, many became significantly less responsive to fast speeds and others showed a modest decrease in surround suppression. These changes resemble previously reported effects of reducing stimulus contrast (Pack et al., 2005; Krekelberg et al., 2006), but we show here that they differ in their temporal dynamics. We find no evidence that the indirect pathways selectively target different functional regions within MT. Overall, our findings suggest that the indirect pathways to MT primarily convey modality-specific information on binocular disparity, but that they also contribute to the processing of stimuli moving at fast speeds.

A metric-based analysis of the contribution of spike timing to contrast and motion direction coding by single neurons in macaque area MT

Spike timing is thought to contribute to the coding of motion direction information by neurons in macaque area MT. Here, we examined whether spike timing also contributes to the coding of stimulus contrast. We applied a metric-based approach to spike trains fired by MT neurons in response to stimuli that varied in contrast, or direction. We assessed the performance of three metrics, D(spike) and D(product) (containing spike count and timing information), and the spike count metric D(count). We analyzed responses elicited during the first 200 msec of stimulus presentation from 205 neurons. For both contrast and direction, the large majority of neurons showed the highest mutual information using D(spike), followed by D(product), and D(count). This was corroborated by the performance of a theoretical observer model at discriminating contrast and direction using the three metrics. Our results demonstrate that spike timing can contribute to contrast coding in MT neurons, and support previous reports of its potential contribution to direction coding. Furthermore, they suggest that a combination of spike count with periodic and non-periodic spike timing information (contained in D(spike), but not in D(product) and D(count) which are insensitive to spike counts and timing respectively) provides the largest coding advantage in spike trains fired by MT neurons during contrast and direction discrimination.

Misperceptions of speed are accounted for by the responses of neurons in macaque cortical area MT

In humans, the perceived speed of random dot patterns (RDP) moving within small apertures is faster than that of RDPs moving within larger apertures at the same physical speed. To investigate the neural basis of this illusion, we recorded the responses of direction- and speed-selective neurons in the middle temporal area (MT) of macaque monkeys to stimuli varying in size and speed. Our results show that the preferred speed of MT neurons is slower for smaller stimuli. This effect was larger for neurons preferring faster speeds, matching our psychophysical observation in human subjects that the magnitude of the misperception is larger at higher stimulus speeds. Our physiological data indicate that, across a population of speed-tuned neurons in MT, decreasing the size of a stimulus would shift the activity profile to neurons tuned for higher speeds. Modeling a labeled-line readout of this shifted profile, we show an increased apparent speed, in line with the psychophysical observations. This link strengthens the evidence for a causal role of area MT in speed perception. The systematic shift in tuning curves of single neurons with stimulus size might reflect a general mechanism for feature-mismatch illusions in visual perception.

Motion-onset visual evoked potentials predict performance during a global direction discrimination task

The relationship between cognitive processing stages and event-related potential components has been extensively researched for single components, but even the simplest task comprises multiple electrophysiological and cognitive components. Here we examined the relationship between behavioral measures and several visual evoked potentials (VEPs) related to global motion onset during a visual motion discrimination task. In addition to reaction time and accuracy, the EZ diffusion model was used to characterize elements of the decision process. Results showed that latencies, but not amplitudes, from three VEP components reliably predicted about 40% of the variance in reaction times for motion discrimination. These included the latency from stimulus motion onset to N2 onset, the latency from N2 onset to N2 peak, and the latency from the N2 peak to the peak of a late positive potential. These latencies were also able to predict the rate of information accumulation during the decision process and the duration of non-decision processes, but not the observer's threshold (boundary) for making a response. This pattern of results is consistent with an interpretation of these three latencies as reflecting a non-specific visual perceptual process, a motion-specific process, and a decision process, respectively. The relationship between the earliest interval and drift rate estimated with the EZ model also supports the notion that early perceptual processing might be a constituent part of the decision process itself.

Motion adaptation and the velocity coding of natural scenes

Estimating relative velocity in the natural environment is challenging because natural scenes vary greatly in contrast and spatial structure. Widely accepted correlation-based models for elementary motion detectors (EMDs) are sensitive to contrast and spatial structure and consequently generate ambiguous estimates of velocity. Identified neurons in the third optic lobe of the hoverfly can reliably encode the velocity of natural images largely independent of contrast, despite receiving inputs directly from arrays of such EMDs. This contrast invariance suggests an important role for additional neural processes in robust encoding of image motion. However, it remains unclear which neural processes are contributing to contrast invariance. By recording from horizontal system neurons in the hoverfly lobula, we show two activity-dependent adaptation mechanisms acting as near-ideal normalizers for images of different contrasts that would otherwise produce highly variable response magnitudes. Responses to images that are initially weak neural drivers are boosted over several hundred milliseconds. Responses to images that are initially strong neural drivers are reduced over longer time scales. These adaptation mechanisms appear to be matched to higher-order natural image statistics reconciling the neurons' accurate encoding of image velocity with the inherent ambiguity of correlation-based motion detectors.

Cognitive neural prosthetics

The cognitive neural prosthetic (CNP) is a very versatile method for assisting paralyzed patients and patients with amputations. The CNP records the cognitive state of the subject, rather than signals strictly related to motor execution or sensation. We review a number of high-level cortical signals and their application for CNPs, including intention, motor imagery, decision making, forward estimation, executive function, attention, learning, and multi-effector movement planning. CNPs are defined by the cognitive function they extract, not the cortical region from which the signals are recorded. However, some cortical areas may be better than others for particular applications. Signals can also be extracted in parallel from multiple cortical areas using multiple implants, which in many circumstances can increase the range of applications of CNPs. The CNP approach relies on scientific understanding of the neural processes involved in cognition, and many of the decoding algorithms it uses also have parallels to underlying neural circuit functions.

Adaptive integration in the visual cortex by depressing recurrent cortical circuits

Neurons in the visual cortex receive a large amount of input from recurrent connections, yet the functional role of these connections remains unclear. Here we explore networks with strong recurrence in a computational model and show that short-term depression of the synapses in the recurrent loops implements an adaptive filter. This allows the visual system to respond reliably to deteriorated stimuli yet quickly to high-quality stimuli. For low-contrast stimuli, the model predicts long response latencies, whereas latencies are short for high-contrast stimuli. This is consistent with physiological data showing that in higher visual areas, latencies can increase more than 100 ms at low contrast compared to high contrast. Moreover, when presented with briefly flashed stimuli, the model predicts stereotypical responses that outlast the stimulus, again consistent with physiological findings. The adaptive properties of the model suggest that the abundant recurrent connections found in visual cortex serve to adapt the network's time constant in accordance with the stimulus and normalizes neuronal signals such that processing is as fast as possible while maintaining reliability.

Temporal dynamics of 2D motion integration for ocular following in macaque monkeys

Several recent studies have shown that extracting pattern motion direction is a dynamical process where edge motion is first extracted and pattern-related information is encoded with a small time lag by MT neurons. A similar dynamics was found for human reflexive or voluntary tracking. Here, we bring an essential, but still missing, piece of information by documenting macaque ocular following responses to gratings, unikinetic plaids, and barber-poles. We found that ocular tracking was always initiated first in the grating motion direction with ultra-short latencies (approximately 55 ms). A second component was driven only 10-15 ms later, rotating tracking toward pattern motion direction. At the end the open-loop period, tracking direction was aligned with pattern motion direction (plaids) or the average of the line-ending motion directions (barber-poles). We characterized the dependency on contrast of each component. Both timing and direction of ocular following were quantitatively very consistent with the dynamics of neuronal responses reported by others. Overall, we found a remarkable consistency between neuronal dynamics and monkey behavior, advocating for a direct link between the neuronal solution of the aperture problem and primate perception and action.

Contrast induced changes in response latency depend on stimulus specificity

Neurones in visual cortex show increasing response latency with decreasing stimulus contrast. Neurophysiological recordings from neurones in inferior temporal cortex (IT) and the superior temporal sulcus (STS), show that the increment in response latency with decreasing stimulus contrast is considerably greater in higher visual areas than that seen in primary visual cortex. This suggests that the majority of the latency change is not retinal or V1 in origin, instead each cortical processing area adds latency at low contrast. I show that, as in earlier visual areas, response latency is more strongly dependent on stimulus contrast than stimulus identity. There is large variation in the extent to which response latency increases with decreasing stimulus contrast. I show that this between cell variability is, at least in part, related to the stimulus specificity of the neurones: the increase in response latency as stimulus contrast decreases is greater for neurones that respond to few stimuli compared to neurones that respond to many stimuli.

Direction and contrast tuning of macaque MSTd neurons during saccades

Saccades are rapid eye movements that change the direction of gaze, although the full-field image motion associated with these movements is rarely perceived. The attenuation of visual perception during saccades is referred to as saccadic suppression. The mechanisms that produce saccadic suppression are not well understood. We recorded from neurons in the dorsal medial superior temporal area (MSTd) of alert macaque monkeys and compared the neural responses produced by the retinal slip associated with saccades (active motion) to responses evoked by identical motion presented during fixation (passive motion). We provide evidence for a neural correlate of saccadic suppression and expand on two contentious results from previous studies. First, we confirm the finding that some neurons in MSTd reverse their preferred direction during saccades. We quantify this effect by calculating changes in direction tuning index for a large cell population. Second, it has been noted that neural activity associated with saccades can arrive in the parietal cortex <or=30 ms earlier than activity produced by similar visual stimulation during fixation. This led to the question of whether the saccade-related responses were visual in origin or were motor signals arising from saccade-planning areas of the brain. By comparing the responses to saccades made over textured backgrounds of different contrasts, we provide strong evidence that saccade-related responses were visual in origin. Refinements of the possible models of saccadic suppression are discussed.

V1 response timing and surface filling-in

There is ample evidence from demonstrations such as color induction and stabilized images that information from surface boundaries plays a special role in determining the perception of surface interiors. Surface interiors appear to "fill-in." Psychophysical experiments also show that surface perception involves a slow scale-dependent process distinct from mechanisms involved in contour perception. The present experiments aimed to test the hypothesis that surface perception is associated with relatively slow scale-dependent neural filling-in. We found that responses in macaque primary visual cortex (V1) are slower to surface interiors than responses to optimal bar stimuli. Moreover, we found that the response to a surface interior is delayed relative to the response to the surface's border and the extent of the delay is proportional to the distance between a receptive field and the border. These findings are consistent with some forms of neural filling-in and suggest that V1 may provide the neural substrate for perceptual filling-in.

Forward estimation of movement state in posterior parietal cortex

During goal-directed movements, primates are able to rapidly and accurately control an online trajectory despite substantial delay times incurred in the sensorimotor control loop. To address the problem of large delays, it has been proposed that the brain uses an internal forward model of the arm to estimate current and upcoming states of a movement, which are more useful for rapid online control. To study online control mechanisms in the posterior parietal cortex (PPC), we recorded from single neurons while monkeys performed a joystick task. Neurons encoded the static target direction and the dynamic movement angle of the cursor. The dynamic encoding properties of many movement angle neurons reflected a forward estimate of the state of the cursor that is neither directly available from passive sensory feedback nor compatible with outgoing motor commands and is consistent with PPC serving as a forward model for online sensorimotor control. In addition, we found that the space-time tuning functions of these neurons were largely separable in the angle-time plane, suggesting that they mostly encode straight and approximately instantaneous trajectories.

The effect of middle temporal spike phase on sensory encoding and correlates with behavior during a motion-detection task

Previous studies have shown that sensory neurons that are the most informative of the stimulus tend to be the best correlated with the subject's perceptual decision. We wanted to know whether this relationship might also apply to short time segments of a neuron's response. We asked whether spikes that conveyed more information about a motion stimulus were also more tightly linked to the perceptual behavior. We examined single-neuron activity in middle temporal (MT) area while monkeys performed a motion-detection task. Because of a slow stimulus update (every 27 ms), activity in many MT neurons was entrained and phase-locked to the stimulus. These stimulus-entrained neuronal oscillations allowed us to separate spikes based on phase. We observed a large amount of variability in how spikes at different phases of the oscillation encoded the stimulus, as revealed by the spike-triggered average of the motion. Spikes during certain phases of the cycle were much more informative about the presence of coherent motion than others. Importantly, we found that the phases that were the most informative about the motion stimulus were also more correlated with the behavioral performance and reaction time of the animal. Our results suggest that the relationship between a neuron's spikes, the stimulus, and behavior can vary on a time scale of tens of milliseconds.