Individuals with autism spectrum disorder have altered visual encoding capacity.

Perceptual anomalies in individuals with autism spectrum disorder (ASD) have been attributed to an imbalance in weighting incoming sensory evidence with prior knowledge when interpreting sensory information. Here, we show that sensory encoding and how it adapts to changing stimulus statistics during feedback also characteristically differs between neurotypical and ASD groups. In a visual orientation estimation task, we extracted the accuracy of sensory encoding from psychophysical data by using an information theoretic measure. Initially, sensory representations in both groups reflected the statistics of visual orientations in natural scenes, but encoding capacity was overall lower in the ASD group. Exposure to an artificial (i.e., uniform) distribution of visual orientations coupled with performance feedback altered the sensory representations of the neurotypical group toward the novel experimental statistics, while also increasing their total encoding capacity. In contrast, neither total encoding capacity nor its allocation significantly changed in the ASD group. Across both groups, the degree of adaptation was correlated with participants' initial encoding capacity. These findings highlight substantial deficits in sensory encoding-independent from and potentially in addition to deficits in decoding-in individuals with ASD.

Sensory Evidence Accumulation Using Optic Flow in a Naturalistic Navigation Task.

Sensory evidence accumulation is considered a hallmark of decision-making in noisy environments. Integration of sensory inputs has been traditionally studied using passive stimuli, segregating perception from action. Lessons learned from this approach, however, may not generalize to ethological behaviors like navigation, where there is an active interplay between perception and action. We designed a sensory-based sequential decision task in virtual reality in which humans and monkeys navigated to a memorized location by integrating optic flow generated by their own joystick movements. A major challenge in such closed-loop tasks is that subjects' actions will determine future sensory input, causing ambiguity about whether they rely on sensory input rather than expectations based solely on a learned model of the dynamics. To test whether subjects integrated optic flow over time, we used three independent experimental manipulations, unpredictable optic flow perturbations, which pushed subjects off their trajectory; gain manipulation of the joystick controller, which changed the consequences of actions; and manipulation of the optic flow density, which changed the information borne by sensory evidence. Our results suggest that both macaques (male) and humans (female/male) relied heavily on optic flow, thereby demonstrating a critical role for sensory evidence accumulation during naturalistic action-perception closed-loop tasks.SIGNIFICANCE STATEMENT The temporal integration of evidence is a fundamental component of mammalian intelligence. Yet, it has traditionally been studied using experimental paradigms that fail to capture the closed-loop interaction between actions and sensations inherent in real-world continuous behaviors. These conventional paradigms use binary decision tasks and passive stimuli with statistics that remain stationary over time. Instead, we developed a naturalistic visuomotor visual navigation paradigm that mimics the causal structure of real-world sensorimotor interactions and probed the extent to which participants integrate sensory evidence by adding task manipulations that reveal complementary aspects of the computation.

Computational cross-species views of the hippocampal formation.

The discovery of place cells and head direction cells in the hippocampal formation of freely foraging rodents has led to an emphasis of its role in encoding allocentric spatial relationships. In contrast, studies in head-fixed primates have additionally found representations of spatial views. We review recent experiments in freely moving monkeys that expand upon these findings and show that postural variables such as eye/head movements strongly influence neural activity in the hippocampal formation, suggesting that the function of the hippocampus depends on where the animal looks. We interpret these results in the light of recent studies in humans performing challenging navigation tasks which suggest that depending on the context, eye/head movements serve one of two roles-gathering information about the structure of the environment (active sensing) or externalizing the contents of internal beliefs/deliberation (embodied cognition). These findings prompt future experimental investigations into the information carried by signals flowing between the hippocampal formation and the brain regions controlling postural variables, and constitute a basis for updating computational theories of the hippocampal system to accommodate the influence of eye/head movements.

Cognitive, Systems, and Computational Neurosciences of the Self in Motion.

Navigating by path integration requires continuously estimating one's self-motion. This estimate may be derived from visual velocity and/or vestibular acceleration signals. Importantly, these senses in isolation are ill-equipped to provide accurate estimates, and thus visuo-vestibular integration is an imperative. After a summary of the visual and vestibular pathways involved, the crux of this review focuses on the human and theoretical approaches that have outlined a normative account of cue combination in behavior and neurons, as well as on the systems neuroscience efforts that are searching for its neural implementation. We then highlight a contemporary frontier in our state of knowledge: understanding how velocity cues with time-varying reliabilities are integrated into an evolving position estimate over prolonged time periods. Further, we discuss how the brain builds internal models inferring when cues ought to be integrated versus segregated-a process of causal inference. Lastly, we suggest that the study of spatial navigation has not yet addressed its initial condition: self-location.

Simple spike dynamics of Purkinje cells in the macaque vestibulo-cerebellum during passive whole-body self-motion.

Theories of cerebellar functions posit that the cerebellum implements internal models for online correction of motor actions and sensory estimation. As an example of such computations, an internal model resolves a sensory ambiguity where the peripheral otolith organs in the inner ear sense both head tilts and translations. Here we exploit the response dynamics of two functionally coupled Purkinje cell types in the vestibular part of the caudal vermis (lobules IX and X) to understand their role in this computation. We find that one population encodes tilt velocity, whereas the other, translation-selective, population encodes linear acceleration. We predict that an intermediate neuronal type should temporally integrate the output of tilt-selective cells into a tilt position signal.

Increased variability but intact integration during visual navigation in Autism Spectrum Disorder.

Autism Spectrum Disorder (ASD) is a common neurodevelopmental disturbance afflicting a variety of functions. The recent computational focus suggesting aberrant Bayesian inference in ASD has yielded promising but conflicting results in attempting to explain a wide variety of phenotypes by canonical computations. Here, we used a naturalistic visual path integration task that combines continuous action with active sensing and allows tracking of subjects' dynamic belief states. Both groups showed a previously documented bias pattern by overshooting the radial distance and angular eccentricity of targets. For both control and ASD groups, these errors were driven by misestimated velocity signals due to a nonuniform speed prior rather than imperfect integration. We tracked participants' beliefs and found no difference in the speed prior, but there was heightened variability in the ASD group. Both end point variance and trajectory irregularities correlated with ASD symptom severity. With feedback, variance was reduced, and ASD performance approached that of controls. These findings highlight the need for both more naturalistic tasks and a broader computational perspective to understand the ASD phenotype and pathology.

Supervised Multisensory Calibration Signals Are Evident in VIP But Not MSTd.

Multisensory plasticity enables our senses to dynamically adapt to each other and the external environment, a fundamental operation that our brain performs continuously. We searched for neural correlates of adult multisensory plasticity in the dorsal medial superior temporal area (MSTd) and the ventral intraparietal area (VIP) in 2 male rhesus macaques using a paradigm of supervised calibration. We report little plasticity in neural responses in the relatively low-level multisensory cortical area MSTd. In contrast, neural correlates of plasticity are found in higher-level multisensory VIP, an area with strong decision-related activity. Accordingly, we observed systematic shifts of VIP tuning curves, which were reflected in the choice-related component of the population response. This is the first demonstration of neuronal calibration, together with behavioral calibration, in single sessions. These results lay the foundation for understanding multisensory neural plasticity, applicable broadly to maintaining accuracy for sensorimotor tasks.SIGNIFICANCE STATEMENT Multisensory plasticity is a fundamental and continual function of the brain that enables our senses to adapt dynamically to each other and to the external environment. Yet, very little is known about the neuronal mechanisms of multisensory plasticity. In this study, we searched for neural correlates of adult multisensory plasticity in the dorsal medial superior temporal area (MSTd) and the ventral intraparietal area (VIP) using a paradigm of supervised calibration. We found little plasticity in neural responses in the relatively low-level multisensory cortical area MSTd. By contrast, neural correlates of plasticity were found in VIP, a higher-level multisensory area with strong decision-related activity. This is the first demonstration of neuronal calibration, together with behavioral calibration, in single sessions.

Dynamics of Heading and Choice-Related Signals in the Parieto-Insular Vestibular Cortex of Macaque Monkeys.

Perceptual decision-making is increasingly being understood to involve an interaction between bottom-up sensory-driven signals and top-down choice-driven signals, but how these signals interact to mediate perception is not well understood. The parieto-insular vestibular cortex (PIVC) is an area with prominent vestibular responsiveness, and previous work has shown that inactivating PIVC impairs vestibular heading judgments. To investigate the nature of PIVC's contribution to heading perception, we recorded extracellularly from PIVC neurons in two male rhesus macaques during a heading discrimination task, and compared findings with data from previous studies of dorsal medial superior temporal (MSTd) and ventral intraparietal (VIP) areas using identical stimuli. By computing partial correlations between neural responses, heading, and choice, we find that PIVC activity reflects a dynamically changing combination of sensory and choice signals. In addition, the sensory and choice signals are more balanced in PIVC, in contrast to the sensory dominance in MSTd and choice dominance in VIP. Interestingly, heading and choice signals in PIVC are negatively correlated during the middle portion of the stimulus epoch, reflecting a mismatch in the polarity of heading and choice signals. We anticipate that these results will help unravel the mechanisms of interaction between bottom-up sensory signals and top-down choice signals in perceptual decision-making, leading to more comprehensive models of self-motion perception.SIGNIFICANCE STATEMENT Vestibular information is important for our perception of self-motion, and various cortical regions in primates show vestibular heading selectivity. Inactivation of the macaque vestibular cortex substantially impairs the precision of vestibular heading discrimination, more so than inactivation of other multisensory areas. Here, we record for the first time from the vestibular cortex while monkeys perform a forced-choice heading discrimination task, and we compare results with data collected previously from other multisensory cortical areas. We find that vestibular cortex activity reflects a dynamically changing combination of sensory and choice signals, with both similarities and notable differences with other multisensory areas.

Causal inference accounts for heading perception in the presence of object motion.

The brain infers our spatial orientation and properties of the world from ambiguous and noisy sensory cues. Judging self-motion (heading) in the presence of independently moving objects poses a challenging inference problem because the image motion of an object could be attributed to movement of the object, self-motion, or some combination of the two. We test whether perception of heading and object motion follows predictions of a normative causal inference framework. In a dual-report task, subjects indicated whether an object appeared stationary or moving in the virtual world, while simultaneously judging their heading. Consistent with causal inference predictions, the proportion of object stationarity reports, as well as the accuracy and precision of heading judgments, depended on the speed of object motion. Critically, biases in perceived heading declined when the object was perceived to be moving in the world. Our findings suggest that the brain interprets object motion and self-motion using a causal inference framework.

Genetically eliminating Purkinje neuron GABAergic neurotransmission increases their response gain to vestibular motion.

Purkinje neurons in the caudal cerebellar vermis combine semicircular canal and otolith signals to segregate linear and gravitational acceleration, evidence for how the cerebellum creates internal models of body motion. However, it is not known which cerebellar circuit connections are necessary to perform this computation. We first showed that this computation is evolutionarily conserved and represented across multiple lobules of the rodent vermis. Then we tested whether Purkinje neuron GABAergic output is required for accurately differentiating linear and gravitational movements through a conditional genetic silencing approach. By using extracellular recordings from lobules VI through X in awake mice, we show that silencing Purkinje neuron output significantly alters their baseline simple spike variability. Moreover, the cerebellum of genetically manipulated mice continues to distinguish linear from gravitational acceleration, suggesting that the underlying computations remain intact. However, response gain is significantly increased in the mutant mice over littermate controls. Altogether, these data argue that Purkinje neuron feedback regulates gain control within the cerebellar circuit.

Flexible egocentric and allocentric representations of heading signals in parietal cortex.

By systematically manipulating head position relative to the body and eye position relative to the head, previous studies have shown that vestibular tuning curves of neurons in the ventral intraparietal (VIP) area remain invariant when expressed in body-/world-centered coordinates. However, body orientation relative to the world was not manipulated; thus, an egocentric, body-centered representation could not be distinguished from an allocentric, world-centered reference frame. We manipulated the orientation of the body relative to the world such that we could distinguish whether vestibular heading signals in VIP are organized in body- or world-centered reference frames. We found a hybrid representation, depending on gaze direction. When gaze remained fixed relative to the body, the vestibular heading tuning of VIP neurons shifted systematically with body orientation, indicating an egocentric, body-centered reference frame. In contrast, when gaze remained fixed relative to the world, this representation changed to be intermediate between body- and world-centered. We conclude that the neural representation of heading in posterior parietal cortex is flexible, depending on gaze and possibly attentional demands.

Visual and Vestibular Selectivity for Self-Motion in Macaque Posterior Parietal Area 7a.

We examined the responses of neurons in posterior parietal area 7a to passive rotational and translational self-motion stimuli, while systematically varying the speed of visually simulated (optic flow cues) or actual (vestibular cues) self-motion. Contrary to a general belief that responses in area 7a are predominantly visual, we found evidence for a vestibular dominance in self-motion processing. Only a small fraction of neurons showed multisensory convergence of visual/vestibular and linear/angular self-motion cues. These findings suggest possibly independent neuronal population codes for visual versus vestibular and linear versus angular self-motion. Neural responses scaled with self-motion magnitude (i.e., speed) but temporal dynamics were diverse across the population. Analyses of laminar recordings showed a strong distance-dependent decrease for correlations in stimulus-induced (signal correlation) and stimulus-independent (noise correlation) components of spike-count variability, supporting the notion that neurons are spatially clustered with respect to their sensory representation of motion. Single-unit and multiunit response patterns were also correlated, but no other systematic dependencies on cortical layers or columns were observed. These findings describe a likely independent multimodal neural code for linear and angular self-motion in a posterior parietal area of the macaque brain that is connected to the hippocampal formation.

Optic flow parsing in the macaque monkey.

During self-motion, an independently moving object generates retinal motion that is the vector sum of its world-relative motion and the optic flow caused by the observer's self-motion. A hypothesized mechanism for the computation of an object's world-relative motion is flow parsing, in which the optic flow field due to self-motion is globally subtracted from the retinal flow field. This subtraction generates a bias in perceived object direction (in retinal coordinates) away from the optic flow vector at the object's location. Despite psychophysical evidence for flow parsing in humans, the neural mechanisms underlying the process are unknown. To build the framework for investigation of the neural basis of flow parsing, we trained macaque monkeys to discriminate the direction of a moving object in the presence of optic flow simulating self-motion. Like humans, monkeys showed biases in object direction perception consistent with subtraction of background optic flow attributable to self-motion. The size of perceptual biases generally depended on the magnitude of the expected optic flow vector at the location of the object, which was contingent on object position and self-motion velocity. There was a modest effect of an object's depth on flow-parsing biases, which reached significance in only one of two subjects. Adding vestibular self-motion signals to optic flow facilitated flow parsing, increasing biases in direction perception. Our findings indicate that monkeys exhibit perceptual hallmarks of flow parsing, setting the stage for the examination of the neural mechanisms underlying this phenomenon.

A model-based reassessment of the three-dimensional tuning of head direction cells in rats.

In a recent study, Shinder and Taube (Shinder ME, Taube JS. J Neurophysiol 121: 4-37, 2019) concluded that head direction cells in the anterior thalamus of rats are tuned to one-dimensional (1D, yaw-only) motion, in contrast to recent findings in bats, mice, and rats. Here we reinterpret the author's experimental results using model comparison and demonstrate that, contrary to their conclusions, experimental data actually supports the dual-axis rule (lson JJ, Jeffery KJ. JNeurophysiol 119: 192-208, 2018) and tilted azimuth model (Laurens J, Angelaki DE. Neuron 97: 275-289, 2018), where head direction cells use gravity to integrate 3D rotation signals about all cardinal axes of the head. We further show that the Shinder and Taube study is inconclusive regarding the presence of vertical orientation tuning; i.e., whether head direction cells encode 3D orientation in the horizontal and vertical planes conjunctively. Using model simulations, we demonstrate that, even if 3D tuning existed, the experimental protocol and data analyses used by Shinder and Taube would not have revealed it. We conclude that the actual experimental data of Shinder and Taube are compatible with the 3D properties of head direction cells discovered by other groups, yet incorrect conclusions were reached because of incomplete and qualitative analyses.NEW & NOTEWORTHY We conducted a model-based analysis previously published data where rat head direction cells were recorded during three-dimensional motion (Shinder ME, Taube JS. J Neurophysiol 121: 4-37, 2019). We found that these data corroborate previous models ("dual-axis rule," Page HJI, Wilson JJ, Jeffery KJ. J Neurophysiol 119: 192-208, 2018; and "tilted azimuth model," Laurens J, Angelaki DE. Neuron 97: 275-289, 2018) where head direction cells integrate rotations along all three head axes to encode head orientation in a gravity-anchored reference frame.

Processing of object motion and self-motion in the lateral subdivision of the medial superior temporal area in macaques.

Multiple areas of macaque cortex are involved in visual motion processing, but their relative functional roles remain unclear. The medial superior temporal (MST) area is typically divided into lateral (MSTl) and dorsal (MSTd) subdivisions that are thought to be involved in processing object motion and self-motion, respectively. Whereas MSTd has been studied extensively with regard to processing visual and nonvisual self-motion cues, little is known about self-motion signals in MSTl, especially nonvisual signals. Moreover, little is known about how self-motion and object motion signals interact in MSTl and how this differs from interactions in MSTd. We compared the visual and vestibular heading tuning of neurons in MSTl and MSTd using identical stimuli. Our findings reveal that both visual and vestibular heading signals are weaker in MSTl than in MSTd, suggesting that MSTl is less well suited to participate in self-motion perception than MSTd. We also tested neurons in both areas with a variety of combinations of object motion and self-motion. Our findings reveal that vestibular signals improve the separability of coding of heading and object direction in both areas, albeit more strongly in MSTd due to the greater strength of vestibular signals. Based on a marginalization technique, population decoding reveals that heading and object direction can be more effectively dissociated from MSTd responses than MSTl responses. Our findings help to clarify the respective contributions that MSTl and MSTd make to processing of object motion and self-motion, although our conclusions may be somewhat specific to the multipart moving objects that we employed. NEW & NOTEWORTHY Retinal image motion reflects contributions from both the observer's self-motion and the movement of objects in the environment. The neural mechanisms by which the brain dissociates self-motion and object motion remain unclear. This study provides the first systematic examination of how the lateral subdivision of area MST (MSTl) contributes to dissociating object motion and self-motion. We also examine, for the first time, how MSTl neurons represent translational self-motion based on both vestibular and visual cues.

Bayesian comparison of explicit and implicit causal inference strategies in multisensory heading perception.

The precision of multisensory perception improves when cues arising from the same cause are integrated, such as visual and vestibular heading cues for an observer moving through a stationary environment. In order to determine how the cues should be processed, the brain must infer the causal relationship underlying the multisensory cues. In heading perception, however, it is unclear whether observers follow the Bayesian strategy, a simpler non-Bayesian heuristic, or even perform causal inference at all. We developed an efficient and robust computational framework to perform Bayesian model comparison of causal inference strategies, which incorporates a number of alternative assumptions about the observers. With this framework, we investigated whether human observers' performance in an explicit cause attribution and an implicit heading discrimination task can be modeled as a causal inference process. In the explicit causal inference task, all subjects accounted for cue disparity when reporting judgments of common cause, although not necessarily all in a Bayesian fashion. By contrast, but in agreement with previous findings, data from the heading discrimination task only could not rule out that several of the same observers were adopting a forced-fusion strategy, whereby cues are integrated regardless of disparity. Only when we combined evidence from both tasks we were able to rule out forced-fusion in the heading discrimination task. Crucially, findings were robust across a number of variants of models and analyses. Our results demonstrate that our proposed computational framework allows researchers to ask complex questions within a rigorous Bayesian framework that accounts for parameter and model uncertainty.

Inferring decoding strategies for multiple correlated neural populations.

Studies of neuron-behaviour correlation and causal manipulation have long been used separately to understand the neural basis of perception. Yet these approaches sometimes lead to drastically conflicting conclusions about the functional role of brain areas. Theories that focus only on choice-related neuronal activity cannot reconcile those findings without additional experiments involving large-scale recordings to measure interneuronal correlations. By expanding current theories of neural coding and incorporating results from inactivation experiments, we demonstrate here that it is possible to infer decoding weights of different brain areas at a coarse scale without precise knowledge of the correlation structure. We apply this technique to neural data collected from two different cortical areas in macaque monkeys trained to perform a heading discrimination task. We identify two opposing decoding schemes, each consistent with data depending on the nature of correlated noise. Our theory makes specific testable predictions to distinguish these scenarios experimentally without requiring measurement of the underlying noise correlations.

Joint representation of translational and rotational components of optic flow in parietal cortex.

Terrestrial navigation naturally involves translations within the horizontal plane and eye rotations about a vertical (yaw) axis to track and fixate targets of interest. Neurons in the macaque ventral intraparietal (VIP) area are known to represent heading (the direction of self-translation) from optic flow in a manner that is tolerant to rotational visual cues generated during pursuit eye movements. Previous studies have also reported that eye rotations modulate the response gain of heading tuning curves in VIP neurons. We tested the hypothesis that VIP neurons simultaneously represent both heading and horizontal (yaw) eye rotation velocity by measuring heading tuning curves for a range of rotational velocities of either real or simulated eye movements. Three findings support the hypothesis of a joint representation. First, we show that rotation velocity selectivity based on gain modulations of visual heading tuning is similar to that measured during pure rotations. Second, gain modulations of heading tuning are similar for self-generated eye rotations and visually simulated rotations, indicating that the representation of rotation velocity in VIP is multimodal, driven by both visual and extraretinal signals. Third, we show that roughly one-half of VIP neurons jointly represent heading and rotation velocity in a multiplicatively separable manner. These results provide the first evidence, to our knowledge, for a joint representation of translation direction and rotation velocity in parietal cortex and show that rotation velocity can be represented based on visual cues, even in the absence of efference copy signals.

Dissociation of Self-Motion and Object Motion by Linear Population Decoding That Approximates Marginalization.

We use visual image motion to judge the movement of objects, as well as our own movements through the environment. Generally, image motion components caused by object motion and self-motion are confounded in the retinal image. Thus, to estimate heading, the brain would ideally marginalize out the effects of object motion (or vice versa), but little is known about how this is accomplished neurally. Behavioral studies suggest that vestibular signals play a role in dissociating object motion and self-motion, and recent computational work suggests that a linear decoder can approximate marginalization by taking advantage of diverse multisensory representations. By measuring responses of MSTd neurons in two male rhesus monkeys and by applying a recently-developed method to approximate marginalization by linear population decoding, we tested the hypothesis that vestibular signals help to dissociate self-motion and object motion. We show that vestibular signals stabilize tuning for heading in neurons with congruent visual and vestibular heading preferences, whereas they stabilize tuning for object motion in neurons with discrepant preferences. Thus, vestibular signals enhance the separability of joint tuning for object motion and self-motion. We further show that a linear decoder, designed to approximate marginalization, allows the population to represent either self-motion or object motion with good accuracy. Decoder weights are broadly consistent with a readout strategy, suggested by recent computational work, in which responses are decoded according to the vestibular preferences of multisensory neurons. These results demonstrate, at both single neuron and population levels, that vestibular signals help to dissociate self-motion and object motion.SIGNIFICANCE STATEMENT The brain often needs to estimate one property of a changing environment while ignoring others. This can be difficult because multiple properties of the environment may be confounded in sensory signals. The brain can solve this problem by marginalizing over irrelevant properties to estimate the property-of-interest. We explore this problem in the context of self-motion and object motion, which are inherently confounded in the retinal image. We examine how diversity in a population of multisensory neurons may be exploited to decode self-motion and object motion from the population activity of neurons in macaque area MSTd.

Gain Modulation as a Mechanism for Coding Depth from Motion Parallax in Macaque Area MT.

Observer translation produces differential image motion between objects that are located at different distances from the observer's point of fixation [motion parallax (MP)]. However, MP can be ambiguous with respect to depth sign (near vs far), and this ambiguity can be resolved by combining retinal image motion with signals regarding eye movement relative to the scene. We have previously demonstrated that both extra-retinal and visual signals related to smooth eye movements can modulate the responses of neurons in area MT of macaque monkeys, and that these modulations generate neural selectivity for depth sign. However, the neural mechanisms that govern this selectivity have remained unclear. In this study, we analyze responses of MT neurons as a function of both retinal velocity and direction of eye movement, and we show that smooth eye movements modulate MT responses in a systematic, temporally precise, and directionally specific manner to generate depth-sign selectivity. We demonstrate that depth-sign selectivity is primarily generated by multiplicative modulations of the response gain of MT neurons. Through simulations, we further demonstrate that depth can be estimated reasonably well by a linear decoding of a population of MT neurons with response gains that depend on eye velocity. Together, our findings provide the first mechanistic description of how visual cortical neurons signal depth from MP.SIGNIFICANCE STATEMENT Motion parallax is a monocular cue to depth that commonly arises during observer translation. To compute from motion parallax whether an object appears nearer or farther than the point of fixation requires combining retinal image motion with signals related to eye rotation, but the neurobiological mechanisms have remained unclear. This study provides the first mechanistic account of how this interaction takes place in the responses of cortical neurons. Specifically, we show that smooth eye movements modulate the gain of responses of neurons in area MT in a directionally specific manner to generate selectivity for depth sign from motion parallax. We also show, through simulations, that depth could be estimated from a population of such gain-modulated neurons.