Cortical layering disrupts multi-electrode current steering.

Objective.Blindness affects approximately 40 million people worldwide and has inspired the development of cortical visual prostheses for restoring sight. Cortical visual prostheses electrically stimulate neurons of the visual cortex to artificially evoke visual percepts. Of the 6 layers of the visual cortex, layer 4 contains neurons that are likely to evoke a visual percept. Intracortical prostheses therefore aim to target layer 4; however, this can be difficult due to cortical curvature, inter-subject cortical variability, blindness-induced anatomical changes in cortex, and electrode placement variations. We investigated the feasibility of using current steering to stimulate specific cortical layers between electrodes in the laminar column.Approach.We explored whether the multiunit neural activity peak can be manipulated between two simultaneously stimulating electrodes in different layers of the cortical column. A 64-channel, 4-shank electrode array was implanted into the visual cortex of Sprague-Dawley rats (n= 7) orthogonal to the cortical surface. A remote return electrode was positioned over the frontal cortex in the same hemisphere. Charge was supplied to two stimulating electrodes along a single shank. Differing ratios of charge (100:0, 75:25, 50:50) and separation distances (300-500µm) were tested.Results.Current steering across the cortical layers did not result in a consistent shift of the neural activity peak. Both single-electrode and dual-electrode stimulation induced activity throughout the cortical column. This contrasts observations that current steering evoked a controllable peak of neural activity between electrodes implanted at similar cortical depths. However, dual-electrode stimulation across the layers did reduce the stimulation threshold at each site compared to single-electrode stimulation.Significance.Multi-electrode stimulation is not suitable for targeted activation of layers using current steering. However, it can be used to reduce activation thresholds at adjacent electrodes within a given cortical layer. This may be applied to reduce the stimulation side effects of neural prostheses, such as seizures.

Intracortical current steering shifts the location of evoked neural activity.

Objective.Intracortical visual prostheses are being developed to restore sight in people who are blind. The resolution of artificial vision is dictated by the location, proximity and number of electrodes implanted in the brain. However, increasing electrode count and proximity is traded off against tissue damage. Hence, new stimulation methods are needed that can improve the resolution of artificial vision without increasing the number of electrodes. We investigated whether a technique known as current steering can improve the resolution of artificial vision provided by intracortical prostheses without increasing the number of physical electrodes in the brain.Approach.We explored how the locus of neuronal activation could be steered when low amplitude microstimulation was applied simultaneously to two intracortical electrodes. A 64-channel, four-shank electrode array was implanted into the visual cortex of rats (n= 7). The distribution of charge ranged from single-electrode stimulation (100%:0%) to an equal distribution between the two electrodes (50%:50%), thereby steering the current between the physical electrodes. The stimulating electrode separation varied between 300 and 500µm. The peak of the evoked activity was defined as the 'virtual electrode' location.Main results.Current steering systematically shifted the virtual electrode on average between the stimulating electrodes as the distribution of charge was moved from one stimulating electrode to another. This effect was unclear in single trials due to the limited sampling of neurons. A model that scales the cortical response to each physical electrode when stimulated in isolation predicts the evoked virtual electrode response. Virtual electrodes were found to elicit a neural response as effectively and predictably as physical electrodes within cortical tissue on average.Significance.Current steering could be used to increase the resolution of intracortical electrode arrays without altering the number of physical electrodes which will reduce neural tissue damage, power consumption and potential heat dispersion issues.

Marmosets: a promising model for probing the neural mechanisms underlying complex visual networks such as the frontal-parietal network.

The technology, methodology and models used by visual neuroscientists have provided great insights into the structure and function of individual brain areas. However, complex cognitive functions arise in the brain due to networks comprising multiple interacting cortical areas that are wired together with precise anatomical connections. A prime example of this phenomenon is the frontal-parietal network and two key regions within it: the frontal eye fields (FEF) and lateral intraparietal area (area LIP). Activity in these cortical areas has independently been tied to oculomotor control, motor preparation, visual attention and decision-making. Strong, bidirectional anatomical connections have also been traced between FEF and area LIP, suggesting that the aforementioned visual functions depend on these inter-area interactions. However, advancements in our knowledge about the interactions between area LIP and FEF are limited with the main animal model, the rhesus macaque, because these key regions are buried in the sulci of the brain. In this review, we propose that the common marmoset is the ideal model for investigating how anatomical connections give rise to functionally-complex cognitive visual behaviours, such as those modulated by the frontal-parietal network, because of the homology of their cortical networks with humans and macaques, amenability to transgenic technology, and rich behavioural repertoire. Furthermore, the lissencephalic structure of the marmoset brain enables application of powerful techniques, such as array-based electrophysiology and optogenetics, which are critical to bridge the gaps in our knowledge about structure and function in the brain.

Demographic, Surgical, and Radiographic Risk Factors for Symptomatic Adjacent Segment Disease After Lumbar Fusion: A Systematic Review and Meta-Analysis.

BACKGROUND: Although multiple studies have investigated risk factors for symptomatic adjacent segment disease (ASD) after lumbar fusion, their findings were diverse and inconsistent. This review aimed to summarize risk factors for ASD in order to guide the management of ASD and future research. METHODS: Six electronic databases were systematically searched from inception to December 2019. Two reviewers independently screened titles, abstracts, and full-text articles to identify studies investigating risk factors for ASD after lumbar fusion in humans. The methodological quality of the included studies and the strength of evidence regarding risk factors were evaluated. RESULTS: Sixteen studies involving 3,553 patients were included. Meta-analyses revealed that high body mass index, facet joint violation, anterior shift of the preoperative and postoperative lumbosacral sagittal plumb line, decreased preoperative and postoperative lumbar lordosis, preoperative adjacent disc degeneration, decreased preoperative adjacent disc height, increased postoperative lumbopelvic mismatch, postoperative pelvic incidence, and postoperative pelvic tilt were significantly related to ASD. CONCLUSIONS: This meta-analysis addressed the limitations of prior reviews and summarized evidence with regard to risk factors for ASD following lumbar fusion. Future prospective studies should investigate whether modification of these risk factors can reduce the ASD development. LEVEL OF EVIDENCE: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Microstimulation-evoked neural responses in visual cortex are depth dependent.

BACKGROUND: Cortical visual prostheses often use penetrating electrode arrays to deliver microstimulation to the visual cortex. To optimize electrode placement within the cortex, the neural responses to microstimulation at different cortical depths must first be understood. OBJECTIVE: We investigated how the neural responses evoked by microstimulation in cortex varied with cortical depth, of both stimulation and response. METHODS: A 32-channel single shank electrode array was inserted into the primary visual cortex of anaesthetized rats, such that it spanned all cortical layers. Microstimulation with currents up to 14 µA (single biphasic pulse, 200 µs per phase) was applied at depths spanning 1600 µm, while simultaneously recording neural activity on all channels within a response window 2.25-11 ms. RESULTS: Stimulation elicited elevated neuronal firing rates at all depths of cortex. Compared to deep sites, superficial stimulation sites responded with higher firing rates at a given current and had lower thresholds. The laminar spread of evoked activity across cortical depth depended on stimulation depth, in line with anatomical models. CONCLUSION: Stimulation in the superficial layers of visual cortex evokes local neural activity with the lowest thresholds, and stimulation in the deep layers evoked the most activity across the cortical column. In conjunction with perceptual reports, these data suggest that the optimal electrode placement for cortical microstimulation prostheses has electrodes positioned in layers 2/3, and at the top of layer 5.

Visual responses in the dorsolateral frontal cortex of marmoset monkeys.

The marmoset monkey (Callithrix jacchus) has gained attention in neurophysiology research as a new primate model for visual processing and behavior. In particular, marmosets have a lissencephalic cortex, making multielectrode, optogenetic, and calcium-imaging techniques more accessible than other primate models. However, the degree of homology of brain circuits for visual behavior with those identified in macaques and humans is still being ascertained. For example, whereas the location of the frontal eye fields (FEF) within the dorsolateral frontal cortex has been proposed, it remains unclear whether neurons in the corresponding areas show visual responses-an important characteristic of FEF neurons in other species. Here, we provide the first description of receptive field properties and neural response latencies in the marmoset dorsolateral frontal cortex, based on recordings using Utah arrays in anesthetized animals. We find brisk visual responses in specific regions of the dorsolateral prefrontal cortex, particularly in areas 8aV, 8C, and 6DR. As in macaque FEF, the receptive fields were typically large (10°-30° in diameter) and the median responses latency was brisk (60 ms). These results constrain the possible interpretations about the location of the marmoset FEF and suggest that the marmoset model's significant advantages for the use of physiological techniques may be leveraged in the study of visuomotor cognition.NEW & NOTEWORTHY Behavior and cognition in humans and other primates rely on networks of brain areas guided by the frontal cortex. The marmoset offers exciting new opportunities to study links between brain physiology and behavior, but the functions of frontal cortex areas are still being identified in this species. Here, we provide the first evidence of visual receptive fields in the marmoset dorsolateral frontal cortex, an important step toward future studies of visual cognitive behavior.

A twisted visual field map in the primate dorsomedial cortex predicted by topographic continuity.

Adjacent neurons in visual cortex have overlapping receptive fields within and across area boundaries, an arrangement theorized to minimize wiring cost. This constraint is traditionally thought to create retinotopic maps of opposing field signs (mirror and nonmirror visual field representations) in adjacent areas, a concept that has become central in current attempts to subdivide the extrastriate cortex. We simulated the formation of retinotopic maps using a model that balances constraints imposed by smoothness in the representation within an area and by congruence between areas. As in the primate cortex, this model usually leads to alternating mirror and nonmirror maps. However, we found that it can also produce a more complex type of map, consisting of sectors with opposing field sign within a single area. Using fully quantitative electrode array recordings, we then demonstrate that this type of inhomogeneous map exists in the controversial dorsomedial region of the primate extrastriate cortex.

Differences in perceptual masking between humans and rats.

INTRODUCTION: The perception of a target stimulus can be impaired by a subsequent mask stimulus, even if they do not overlap temporally or spatially. This "backward masking" is commonly used to modulate a subject's awareness of a target and to characterize the temporal dynamics of vision. Masking is most apparent with brief, low-contrast targets, making detection difficult even in the absence of a mask. Although necessary to investigate the underlying neural mechanisms, evaluating masking phenomena in animal models is particularly challenging, as the task structure and critical stimulus features to be attended must be learned incrementally through rewards and feedback. Despite the increasing popularity of rodents in vision research, it is unclear if they are susceptible to masking illusions. METHODS: We characterized how spatially surrounding masks affected the detection of sine-wave grating targets. RESULTS: In humans (n = 5) and rats (n = 7), target detection improved with contrast and was reduced by the presence of a mask. After controlling for biases to respond induced by the presence of the mask, a clear reduction in detectability was caused by masks. This reduction was evident when data were averaged across all animals, but was only individually significant in three animals. CONCLUSIONS: While perceptual masking occurs in rats, it may be difficult to observe consistently in individual animals because the complexity of the requisite task pushes the limits of their behavioral capabilities. We suggest methods to ensure that masking, and similarly subtle effects, can be reliably characterized in future experiments.

Weighting neurons by selectivity produces near-optimal population codes.

Perception is produced by "reading out" the representation of a sensory stimulus contained in the activity of a population of neurons. To examine experimentally how populations code information, a common approach is to decode a linearly weighted sum of the neurons' spike counts. This approach is popular because of the biological plausibility of weighted, nonlinear integration. For neurons recorded in vivo, weights are highly variable when derived through optimization methods, but it is unclear how the variability affects decoding performance in practice. To address this, we recorded from neurons in the middle temporal area (MT) of anesthetized marmosets (Callithrix jacchus) viewing stimuli comprising a sheet of dots that moved coherently in 1 of 12 different directions. We found that high peak response and direction selectivity both predicted that a neuron would be weighted more highly in an optimized decoding model. Although learned weights differed markedly from weights chosen according to a priori rules based on a neuron's tuning profile, decoding performance was only marginally better for the learned weights. In the models with a priori rules, selectivity is the best predictor of weighting, and defining weights according to a neuron's preferred direction and selectivity improves decoding performance to very near the maximum level possible, as defined by the learned weights. NEW & NOTEWORTHY We examined which aspects of a neuron's tuning account for its contribution to sensory coding. Strongly direction-selective neurons are weighted most highly by optimal decoders trained to discriminate motion direction. Models with predefined decoding weights demonstrate that this weighting scheme causally improved direction representation by a neuronal population. Optimizing decoders (using a generalized linear model or Fisher's linear discriminant) led to only marginally better performance than decoders based purely on a neuron's preferred direction and selectivity.

Contrast and luminance adaptation alter neuronal coding and perception of stimulus orientation.

Sensory systems face a barrage of stimulation that continually changes along multiple dimensions. These simultaneous changes create a formidable problem for the nervous system, as neurons must dynamically encode each stimulus dimension, despite changes in other dimensions. Here, we measured how neurons in visual cortex encode orientation following changes in luminance and contrast, which are critical for visual processing, but nuisance variables in the context of orientation coding. Using information theoretic analysis and population decoding approaches, we find that orientation discriminability is luminance and contrast dependent, changing over time due to firing rate adaptation. We also show that orientation discrimination in human observers changes during adaptation, in a manner consistent with the neuronal data. Our results suggest that adaptation does not maintain information rates per se, but instead acts to keep sensory systems operating within the limited dynamic range afforded by spiking activity, despite a wide range of possible inputs.

Correlated Variability in the Neurons With the Strongest Tuning Improves Direction Coding.

Sensory perception depends on neuronal populations creating an accurate representation of the external world. The amount of information that a population can represent depends on the tuning of individual neurons and the trial-by-trial variability shared among neurons. Although on average, pairwise spike-count correlations between neurons are positive, the distribution is wide, and the relationship between correlations and encoding is not straightforward. Here, we examine how single-neuron and population-level factors impact the efficacy of the neural code. We recorded responses to moving visual stimuli from motion-sensitive neurons in the middle temporal area of anesthetized marmosets (Callithrix jacchus) and trained decoders to assess how correlated and uncorrelated populations encoded stimulus motion direction. We found that the most responsive, direction-selective, and least variable neurons are the most relied-upon neurons in an uncorrelated population. In correlated populations, the same neurons do the most to shape the shared variability across the population in a way that facilitates decoding, and decoding is improved by the presence of temporally stable correlations. This suggests that the least variable neurons with the strongest stimulus representations enhance the population code by providing a strong signal and shaping correlations in variability orthogonally to the locus defined by the mean response.

Understanding Sensory Information Processing Through Simultaneous Multi-area Population Recordings.

The goal of sensory neuroscience is to understand how the brain creates its myriad of representations of the world, and uses these representations to produce perception and behavior. Circuits of neurons in spatially segregated regions of brain tissue have distinct functional specializations, and these regions are connected to form a functional processing hierarchy. Advances in technology for recording neuronal activity from multiple sites in multiple cortical areas mean that we are now able to collect data that reflects how information is transformed within and between connected members of this hierarchy. This advance is an important step in understanding the brain because, after the sensory organs have transduced a physical signal, every processing stage takes the activity of other neurons as its input, not measurements of the physical world. However, as we explore the potential of studying how populations of neurons in multiple areas respond in concert, we must also expand both the analytical tools that we use to make sense of these data and the scope of the theories that we attempt to define. In this article, we present an overview of some of the most promising analytical approaches for making inferences from population recordings in multiple brain areas, such as dimensionality reduction and measuring changes in correlated variability, and examine how they may be used to address longstanding questions in sensory neuroscience.

Long-term sensorimotor adaptation in the ocular following system of primates.

The sudden movement of a wide-field image leads to a reflexive eye tracking response referred to as short-latency ocular following. If the image motion occurs soon after a saccade the initial speed of the ocular following is enhanced, a phenomenon known as post-saccadic enhancement. We show in macaque monkeys that repeated exposure to the same stimulus regime over a period of months leads to progressive increases in the initial speeds of ocular following. The improvement in tracking speed occurs for ocular following with and without a prior saccade. As a result of the improvement in ocular following speeds, the influence of post-saccadic enhancement wanes with increasing levels of training. The improvement in ocular following speed following repeated exposure to the same oculomotor task represents a novel form of sensori-motor learning in the context of a reflexive movement.

Sensitivity of neurons in the middle temporal area of marmoset monkeys to random dot motion.

Neurons in the middle temporal area (MT) of the primate cerebral cortex respond to moving visual stimuli. The sensitivity of MT neurons to motion signals can be characterized by using random-dot stimuli, in which the strength of the motion signal is manipulated by adding different levels of noise (elements that move in random directions). In macaques, this has allowed the calculation of "neurometric" thresholds. We characterized the responses of MT neurons in sufentanil/nitrous oxide-anesthetized marmoset monkeys, a species that has attracted considerable recent interest as an animal model for vision research. We found that MT neurons show a wide range of neurometric thresholds and that the responses of the most sensitive neurons could account for the behavioral performance of macaques and humans. We also investigated factors that contributed to the wide range of observed thresholds. The difference in firing rate between responses to motion in the preferred and null directions was the most effective predictor of neurometric threshold, whereas the direction tuning bandwidth had no correlation with the threshold. We also showed that it is possible to obtain reliable estimates of neurometric thresholds using stimuli that were not highly optimized for each neuron, as is often necessary when recording from large populations of neurons with different receptive field concurrently, as was the case in this study. These results demonstrate that marmoset MT shows an essential physiological similarity to macaque MT and suggest that its neurons are capable of representing motion signals that allow for comparable motion-in-noise judgments.NEW & NOTEWORTHY We report the activity of neurons in marmoset MT in response to random-dot motion stimuli of varying coherence. The information carried by individual MT neurons was comparable to that of the macaque, and the maximum firing rates were a strong predictor of sensitivity. Our study provides key information regarding the neural basis of motion perception in the marmoset, a small primate species that is becoming increasingly popular as an experimental model.

Orientation selectivity in rat primary visual cortex emerges earlier with low-contrast and high-luminance stimuli.

In natural vision, rapid and sustained variations in luminance and contrast change the reliability of information available about a visual scene, and markedly affect both neuronal and behavioural responses. The hallmark property of neurons in primary visual cortex (V1), orientation selectivity, is unaffected by changes in stimulus contrast, but it remains unclear how sustained differences in mean luminance and contrast affect the time-course of orientation selectivity, and the amount of information that neurons carry about orientation. We used reverse correlation with characterize the temporal dynamics of orientation selectivity in rat V1 neurons under four luminance-contrast conditions. We show that orientation selectivity and mutual information between neuronal responses and stimulus orientation are invariant to contrast or mean luminance. Critically, the time-course of the emergence of orientation selectivity was affected by both factors; response latencies were longer for low- than high-luminance gratings, and surprisingly, response latencies were also longer for high- than low-contrast gratings. Modelling suggests that luminance-modulated changes in feedforward gain, in combination with hyperpolarization caused by high contrasts can account for our physiological data. The hyperpolarization at high contrasts may increase signal-to-noise ratios, whereas a more depolarized membrane may lead to greater sensitivity to weak stimuli.

Masking reduces orientation selectivity in rat visual cortex.

In visual masking the perception of a target stimulus is impaired by a preceding (forward) or succeeding (backward) mask stimulus. The illusion is of interest because it allows uncoupling of the physical stimulus, its neuronal representation, and its perception. To understand the neuronal correlates of masking, we examined how masks affected the neuronal responses to oriented target stimuli in the primary visual cortex (V1) of anesthetized rats (n = 37). Target stimuli were circular gratings with 12 orientations; mask stimuli were plaids created as a binarized sum of all possible target orientations. Spatially, masks were presented either overlapping or surrounding the target. Temporally, targets and masks were presented for 33 ms, but the stimulus onset asynchrony (SOA) of their relative appearance was varied. For the first time, we examine how spatially overlapping and center-surround masking affect orientation discriminability (rather than visibility) in V1. Regardless of the spatial or temporal arrangement of stimuli, the greatest reductions in firing rate and orientation selectivity occurred for the shortest SOAs. Interestingly, analyses conducted separately for transient and sustained target response components showed that changes in orientation selectivity do not always coincide with changes in firing rate. Given the near-instantaneous reductions observed in orientation selectivity even when target and mask do not spatially overlap, we suggest that monotonic visual masking is explained by a combination of neural integration and lateral inhibition.

Rapid Adaptation Induces Persistent Biases in Population Codes for Visual Motion.

Each visual experience changes the neural response to subsequent stimuli. If the brain is unable to incorporate these encoding changes, the decoding, or perception, of subsequent stimuli is biased. Although the phenomenon of adaptation pervades the nervous system, its effects have been studied mainly in isolation, based on neuronal encoding changes induced by an isolated, prolonged stimulus. To understand how adaptation-induced biases arise and persist under continuous, naturalistic stimulation, we simultaneously recorded the responses of up to 61 neurons in the marmoset (Callithrix jacchus) middle temporal area to a sequence of directions that changed every 500 ms. We found that direction-specific adaptation following only 0.5 s of stimulation strongly affected encoding for up to 2 s by reducing both the gain and the spike count correlations between pairs of neurons with preferred directions close to the adapting direction. In addition, smaller changes in bandwidth and preferred direction were observed in some animals. Decoding individual trials of adaptation-affected activity in simultaneously recorded neurons predicted repulsive biases that are consistent with the direction aftereffect. Surprisingly, removing spike count correlations by trial shuffling did not impact decoding performance or bias. When adaptation had the largest effect on encoding, the decoder made the most errors. This suggests that neural and perceptual repulsion is not a mechanism to enhance perceptual performance but is instead a necessary consequence of optimizing neural encoding for the identification of a wide range of stimulus properties in diverse temporal contexts. SIGNIFICANCE STATEMENT: Although perception depends upon decoding the pattern of activity across a neuronal population, the encoding properties of individual neurons are unreliable: a single neuron's response to repetitions of the same stimulus is variable, and depends on both its spatial and temporal context. In this manuscript, we describe the complete cascade of adaptation-induced effects in sensory encoding and show how they predict population decoding errors consistent with perceptual biases. We measure the time course of adaptation-induced changes to the response properties of neurons in isolation, and to the correlation structure across pairs of simultaneously recorded neurons. These results provide novel insight into how and for how long adaptation affects the neural code, particularly during continuous, naturalistic vision.

Noisy decision thresholds can account for suboptimal detection of low coherence motion.

Noise in sensory signals can vary over both space and time. Moving random dot stimuli are commonly used to quantify how the visual system accounts for spatial noise. In these stimuli, a fixed proportion of "signal" dots move in the same direction and the remaining "noise" dots are randomly replotted. The spatial coherence, or proportion of signal versus noise dots, is fixed across time; however, this means that little is known about how temporally-noisy signals are integrated. Here we use a stimulus with low temporal coherence; the signal direction is only presented on a fraction of frames. Human observers are able to reliably detect and discriminate the direction of a 200 ms motion pulse, even when just 25% of frames within the pulse move in the signal direction. Using psychophysical reverse-correlation analyses, we show that observers are strongly influenced by the number of near-target directions spread throughout the pulse, and that consecutive signal frames have only a small additional influence on perception. Finally, we develop a model inspired by the leaky integration of the responses of direction-selective neurons, which reliably represents motion direction, and which can account for observers' sub-optimal detection of motion pulses by incorporating a noisy decision threshold.

Reflexive tracking eye movements and motion perception: one or two neural populations?

Motion-sensitive neurons in the middle temporal (MT) and medial superior temporal (MST) areas perform the sensory analysis required for both motion perception and controlling smooth eye movements. The perceptual and oculomotor systems are characterized by high variability, even when responding to identical stimulus repetitions. If a single population of neurons performs the motion analysis driving perception and eye movements, errors in perception and action might show similar direction-dependent biases, or their variability might be correlated across trials. However, previous studies have produced conflicting reports of the presence of significant single-trial correlations between motion perception and the velocity of smooth pursuit, a volitional tracking eye movement. We studied ocular following, a reflexive tracking eye movement, simultaneously measuring eye movement direction and perceived direction of a moving random dot field. Oculomotor errors were largest for near-cardinal directions, providing the first evidence for cardinal repulsion in reflexive eye movements. Biases in perceptual and oculomotor errors were correlated across test directions, but not across single trials with the same direction. Based on the similar direction-dependent anisotropies in eye movements and perception, there is reason to believe that partially overlapping populations of sensory neurons underlie motion perception and oculomotor behaviors, with independent downstream sources of noise masking trial-by-trial correlations between perception and action.

Adaptation to speed in macaque middle temporal and medial superior temporal areas.

The response of a sensory neuron to an unchanging stimulus typically adapts, showing decreases in response gain that are accompanied by changes in the shape of tuning curves. It remains unclear whether these changes arise purely due to spike rate adaptation within single neurons or whether they are dependent on network interactions between neurons. Further, it is unclear how the timescales of neural and perceptual adaptation are related. To examine this issue, we compared speed tuning of middle temporal (MT) and medial superior temporal neurons in macaque visual cortex after adaptation to two different reference speeds. For 75% of speed-tuned units, adaptation caused significant changes in tuning that could be explained equally well as lateral shifts, vertical gain changes, or both. These tuning changes occurred rapidly, as both neuronal firing rate and Fano factor showed no evidence of changing beyond the first 500 ms after motion onset, and the magnitude of tuning curve changes showed no difference between trials with adaptation durations shorter or longer than 1 s. Importantly, the magnitude of tuning shifts was correlated with the transient-sustained index, which measures a well characterized form of rapid response adaptation in MT, and is likely associated with changes at the level of neuronal networks. Tuning curves changed in a manner that increased neuronal sensitivity around the adapting speed, consistent with improvements in human and macaque psychophysical performance that we observed over the first several hundred ms of adaptation.