Development of radial frequency pattern perception in macaque monkeys.

Infant primates see poorly, and most perceptual functions mature steadily beyond early infancy. Behavioral studies on human and macaque infants show that global form perception, as measured by the ability to integrate contour information into a coherent percept, improves dramatically throughout the first several years after birth. However, it is unknown when sensitivity to curvature and shape emerges in early life or how it develops. We studied the development of shape sensitivity in 18 macaques, aged 2 months to 10 years. Using radial frequency stimuli, circular targets whose radii are modulated sinusoidally, we tested monkeys' ability to radial frequency stimuli from circles as a function of the depth and frequency of sinusoidal modulation. We implemented a new four-choice oddity task and compared the resulting data with that from a traditional two-alternative forced choice task. We found that radial frequency pattern perception was measurable at the youngest age tested (2 months). Behavioral performance at all radial frequencies improved with age. Performance was better for higher radial frequencies, suggesting the developing visual system prioritizes processing of fine visual details that are ecologically relevant. By using two complementary methods, we were able to capture a comprehensive developmental trajectory for shape perception.

Sensitivity to naturalistic texture relies primarily on high spatial frequencies.

Natural images contain information at multiple spatial scales. Though we understand how early visual mechanisms split multiscale images into distinct spatial frequency channels, we do not know how the outputs of these channels are processed further by mid-level visual mechanisms. We have recently developed a texture discrimination task that uses synthetic, multi-scale, "naturalistic" textures to isolate these mid-level mechanisms. Here, we use three experimental manipulations (image blur, image rescaling, and eccentric viewing) to show that perceptual sensitivity to naturalistic structure is strongly dependent on features at high object spatial frequencies (measured in cycles/image). As a result, sensitivity depends on a texture acuity limit, a property of the visual system that sets the highest retinal spatial frequency (measured in cycles/degree) at which observers can detect naturalistic features. Analysis of the texture images using a model observer analysis shows that naturalistic image features at high object spatial frequencies carry more task-relevant information than those at low object spatial frequencies. That is, the dependence of sensitivity on high object spatial frequencies is a property of the texture images, rather than a property of the visual system. Accordingly, we find human observers' ability to extract naturalistic information (their efficiency) is similar for all object spatial frequencies. We conclude that the mid-level mechanisms that underlie perceptual sensitivity effectively extract information from all image features below the texture acuity limit, regardless of their retinal and object spatial frequency.

The Bouma law accounts for crowding in 50 observers.

Crowding is the failure to recognize an object due to surrounding clutter. Our visual crowding survey measured 13 crowding distances (or "critical spacings") twice in each of 50 observers. The survey includes three eccentricities (0, 5, and 10 deg), four cardinal meridians, two orientations (radial and tangential), and two fonts (Sloan and Pelli). The survey also tested foveal acuity, twice. Remarkably, fitting a two-parameter model-the well-known Bouma law, where crowding distance grows linearly with eccentricity-explains 82% of the variance for all 13 × 50 measured log crowding distances, cross-validated. An enhanced Bouma law, with factors for meridian, crowding orientation, target kind, and observer, explains 94% of the variance, again cross-validated. These additional factors reveal several asymmetries, consistent with previous reports, which can be expressed as crowding-distance ratios: 0.62 horizontal:vertical, 0.79 lower:upper, 0.78 right:left, 0.55 tangential:radial, and 0.78 Sloan-font:Pelli-font. Across our observers, peripheral crowding is independent of foveal crowding and acuity. Evaluation of the Bouma factor, b (the slope of the Bouma law), as a biomarker of visual health would be easier if there were a way to compare results across crowding studies that use different methods. We define a standardized Bouma factor b' that corrects for differences from Bouma's 25 choice alternatives, 75% threshold criterion, and linearly symmetric flanker placement. For radial crowding on the right meridian, the standardized Bouma factor b' is 0.24 for this study, 0.35 for Bouma (1970), and 0.30 for the geometric mean across five representative modern studies, including this one, showing good agreement across labs, including Bouma's. Simulations, confirmed by data, show that peeking can skew estimates of crowding (e.g., greatly decreasing the mean or doubling the SD of log b). Using gaze tracking to prevent peeking, individual differences are robust, as evidenced by the much larger 0.08 SD of log b across observers than the mere 0.03 test-retest SD of log b measured in half an hour. The ease of measurement of crowding enhances its promise as a biomarker for dyslexia and visual health.

Altered Balance of Receptive Field Excitation and Suppression in Visual Cortex of Amblyopic Macaque Monkeys.

In amblyopia, a visual disorder caused by abnormal visual experience during development, the amblyopic eye (AE) loses visual sensitivity whereas the fellow eye (FE) is largely unaffected. Binocular vision in amblyopes is often disrupted by interocular suppression. We used 96-electrode arrays to record neurons and neuronal groups in areas V1 and V2 of six female macaque monkeys (Macaca nemestrina) made amblyopic by artificial strabismus or anisometropia in early life, as well as two visually normal female controls. To measure suppressive binocular interactions directly, we recorded neuronal responses to dichoptic stimulation. We stimulated both eyes simultaneously with large sinusoidal gratings, controlling their contrast independently with raised-cosine modulators of different orientations and spatial frequencies. We modeled each eye's receptive field at each cortical site using a difference of Gaussian envelopes and derived estimates of the strength of central excitation and surround suppression. We used these estimates to calculate ocular dominance separately for excitation and suppression. Excitatory drive from the FE dominated amblyopic visual cortex, especially in more severe amblyopes, but suppression from both the FE and AEs was prevalent in all animals. This imbalance created strong interocular suppression in deep amblyopes: increasing contrast in the AE decreased responses at binocular cortical sites. These response patterns reveal mechanisms that likely contribute to the interocular suppression that disrupts vision in amblyopes.SIGNIFICANCE STATEMENT Amblyopia is a developmental visual disorder that alters both monocular vision and binocular interaction. Using microelectrode arrays, we examined binocular interaction in primary visual cortex and V2 of six amblyopic macaque monkeys (Macaca nemestrina) and two visually normal controls. By stimulating the eyes dichoptically, we showed that, in amblyopic cortex, the binocular combination of signals is altered. The excitatory influence of the two eyes is imbalanced to a degree that can be predicted from the severity of amblyopia, whereas suppression from both eyes is prevalent in all animals. This altered balance of excitation and suppression reflects mechanisms that may contribute to the interocular perceptual suppression that disrupts vision in amblyopes.

Asymmetric Dichoptic Masking in Visual Cortex of Amblyopic Macaque Monkeys.

In amblyopia, abnormal visual experience leads to an extreme form of eye dominance, in which vision through the nondominant eye is degraded. A key aspect of this disorder is perceptual suppression: the image seen by the stronger eye often dominates during binocular viewing, blocking the image of the weaker eye from reaching awareness. Interocular suppression is the focus of ongoing work aimed at understanding and treating amblyopia, yet its physiological basis remains unknown. We measured binocular interactions in visual cortex of anesthetized amblyopic monkeys (female Macaca nemestrina), using 96-channel "Utah" arrays to record from populations of neurons in V1 and V2. In an experiment reported recently (Hallum et al., 2017), we found that reduced excitatory input from the amblyopic eye (AE) revealed a form of balanced binocular suppression that is unaltered in amblyopia. Here, we report on the modulation of the gain of excitatory signals from the AE by signals from its dominant fellow eye (FE). Using a dichoptic masking technique, we found that AE responses to grating stimuli were attenuated by the presentation of a noise mask to the FE, as in a normal control animal. Responses to FE stimuli, by contrast, could not be masked from the AE. We conclude that a weakened ability of the amblyopic eye to modulate cortical response gain creates an imbalance of suppression that favors the dominant eye.SIGNIFICANCE STATEMENT In amblyopia, vision in one eye is impaired as a result of abnormal early visual experience. Behavioral observations in humans with amblyopia suggest that much of their visual loss is due to active suppression of their amblyopic eye. Here we describe experiments in which we studied binocular interactions in macaques with experimentally induced amblyopia. In normal monkeys, the gain of neuronal response to stimulation of one eye is modulated by contrast in the other eye, but in monkeys with amblyopia the balance of gain modulation is altered so that the weaker, amblyopic eye has little effect while the stronger fellow eye has a strong effect. This asymmetric suppression may be a key component of the perceptual losses in amblyopia.

Deep learning-Using machine learning to study biological vision.

Many vision science studies employ machine learning, especially the version called "deep learning." Neuroscientists use machine learning to decode neural responses. Perception scientists try to understand how living organisms recognize objects. To them, deep neural networks offer benchmark accuracies for recognition of learned stimuli. Originally machine learning was inspired by the brain. Today, machine learning is used as a statistical tool to decode brain activity. Tomorrow, deep neural networks might become our best model of brain function. This brief overview of the use of machine learning in biological vision touches on its strengths, weaknesses, milestones, controversies, and current directions. Here, we hope to help vision scientists assess what role machine learning should play in their research.

Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.

To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT ("face patches") did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. Significance statement: We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior.

Deep neural networks rival the representation of primate IT cortex for core visual object recognition.

The primate visual system achieves remarkable visual object recognition performance even in brief presentations, and under changes to object exemplar, geometric transformations, and background variation (a.k.a. core visual object recognition). This remarkable performance is mediated by the representation formed in inferior temporal (IT) cortex. In parallel, recent advances in machine learning have led to ever higher performing models of object recognition using artificial deep neural networks (DNNs). It remains unclear, however, whether the representational performance of DNNs rivals that of the brain. To accurately produce such a comparison, a major difficulty has been a unifying metric that accounts for experimental limitations, such as the amount of noise, the number of neural recording sites, and the number of trials, and computational limitations, such as the complexity of the decoding classifier and the number of classifier training examples. In this work, we perform a direct comparison that corrects for these experimental limitations and computational considerations. As part of our methodology, we propose an extension of "kernel analysis" that measures the generalization accuracy as a function of representational complexity. Our evaluations show that, unlike previous bio-inspired models, the latest DNNs rival the representational performance of IT cortex on this visual object recognition task. Furthermore, we show that models that perform well on measures of representational performance also perform well on measures of representational similarity to IT, and on measures of predicting individual IT multi-unit responses. Whether these DNNs rely on computational mechanisms similar to the primate visual system is yet to be determined, but, unlike all previous bio-inspired models, that possibility cannot be ruled out merely on representational performance grounds.

First report on the Moroccan registry of primary immunodeficiencies: 15 years of experience (1998-2012).

PURPOSE: Primary immunodeficiencies (PIDs) are a large group of diseases characterized by susceptibility to infections. We provide the first comprehensive report on PIDs in Morocco, the epidemiological, clinical, etiological and outcome features which have never before been described. METHODS: A national registry was established in 2008, grouping together data for PID patients diagnosed since 1998. RESULTS: In total, 421 patients were diagnosed between 1998 and 2012. Parental consanguinity was common (recorded for 43.2 % of patients) and the median time to diagnosis was 2.0 years. Overall, 27.4 % of patients were considered to have well defined syndromes with immunodeficiency (48 cases of hyper-IgE syndrome and 40 of ataxia-telangiectasia); 22.7 % had predominantly antibody deficiencies (29 cases of agammaglobulinemia and 24 of CVID); 20.6 % had combined immunodeficiencies (37 cases of SCID and 26 of MHC II deficiencies) and 17.5 % had phagocyte disorders (14 cases of SCN and 10 of CGD). The principal clinical signs were lower respiratory tract infections (60.8 %), skin infections (33.5 %) and candidiasis (26.1 %). Mortality reached 28.8 %, and only ten patients underwent bone marrow transplantation. We analyzed the impact on mortality of residence, family history, parental consanguinity, date of diagnosis and time to diagnosis, but only date of diagnosis had a significant effect. CONCLUSIONS: The observed prevalence of PID was 0.81/100,000 inhabitants, suggesting considerable underdiagnosis and a need to increase awareness of these conditions in Morocco. The distribution of PIDs was different from that reported in Western countries, with a particularly high proportion of SCID, MHC II deficiencies, hyper-IgE syndrome and autosomal recessive agammaglobulinemia. However, we have now organized a national network, which should improve diagnosis rates in remote regions.

Human V4 size predicts crowding distance.

Visual recognition is limited by both object size (acuity) and spacing. The spacing limit, called "crowding", is the failure to recognize an object in the presence of other objects. Here, we take advantage of individual differences in crowding behavior to investigate its biological basis. Crowding distance, the minimum object spacing needed for recognition, varies 2-fold among healthy adults. We test the conjecture that this variation in psychophysical crowding distance is due to variation in cortical map size. To test this, we made paired measurements of brain and behavior in 50 observers. We used psychophysics to measure crowding distance and calculate λ, the number of letters that fit into each observer's visual field without crowding. In the same observers, we used fMRI to measure the surface area A (mm^2) of retinotopic maps V1, V2, V3, and V4. Across observers, λ is proportional to the surface area of V4 but is uncorrelated with the surface area of V1 to V3. The proportional relationship of λ to area of V4 indicates conservation of cortical crowding distance across individuals: letters can be recognized if they are spaced by at least 1.4 mm on the V4 map, irrespective of map size and psychophysical crowding distance. We conclude that the size of V4 predicts the spacing limit of visual perception.

Developmentally stable representations of naturalistic image structure in macaque visual cortex.

We studied visual development in macaque monkeys using texture stimuli, matched in local spectral content but varying in "naturalistic" structure. In adult monkeys, naturalistic textures preferentially drive neurons in areas V2 and V4, but not V1. We paired behavioral measurements of naturalness sensitivity with separately-obtained neuronal population recordings from neurons in areas V1, V2, V4, and inferotemporal cortex (IT). We made behavioral measurements from 16 weeks of age and physiological measurements as early as 20 weeks, and continued through 56 weeks. Behavioral sensitivity reached half of maximum at roughly 25 weeks of age. Neural sensitivities remained stable from the earliest ages tested. As in adults, neural sensitivity to naturalistic structure increased from V1 to V2 to V4. While sensitivities in V2 and IT were similar, the dimensionality of the IT representation was more similar to V4's than to V2's.

Developmentally stable representations of naturalistic image structure in macaque visual cortex.

To determine whether post-natal improvements in form vision result from changes in mid-level visual cortex, we studied neuronal and behavioral responses to texture stimuli that were matched in local spectral content but varied in "naturalistic" structure. We made longitudinal measurements of visual behavior from 16 to 95 weeks of age, and of neural responses from 20 to 56 weeks. We also measured behavioral and neural responses in near-adult animals more than 3 years old. Behavioral sensitivity reached half-maximum around 25 weeks of age, but neural sensitivities remained stable through all ages tested. Neural sensitivity to naturalistic structure was highest in V4, lower in V2 and inferotemporal cortex (IT), and barely discernible in V1. Our results show a dissociation between stable neural performance and improving behavioral performance, which may reflect improved processing capacity in circuits downstream of visual cortex.

EasyEyes - A new method for accurate fixation in online vision testing.

Online methods allow testing of larger, more diverse populations, with much less effort than in-lab testing. However, many psychophysical measurements, including visual crowding, require accurate eye fixation, which is classically achieved by testing only experienced observers who have learned to fixate reliably, or by using a gaze tracker to restrict testing to moments when fixation is accurate. Alas, both approaches are impractical online as online observers tend to be inexperienced, and online gaze tracking, using the built-in webcam, has a low precision (±4 deg). EasyEyes open-source software reliably measures peripheral thresholds online with accurate fixation achieved in a novel way, without gaze tracking. It tells observers to use the cursor to track a moving crosshair. At a random time during successful tracking, a brief target is presented in the periphery. The observer responds by identifying the target. To evaluate EasyEyes fixation accuracy and thresholds, we tested 12 naive observers in three ways in a counterbalanced order: first, in the laboratory, using gaze-contingent stimulus presentation; second, in the laboratory, using EasyEyes while independently monitoring gaze using EyeLink 1000; third, online at home, using EasyEyes. We find that crowding thresholds are consistent and individual differences are conserved. The small root mean square (RMS) fixation error (0.6 deg) during target presentation eliminates the need for gaze tracking. Thus, this method enables fixation-dependent measurements online, for easy testing of larger and more diverse populations.

EasyEyes - Accurate fixation for online vision testing of crowding and beyond.

Online methods allow testing of larger, more diverse populations, with much less effort than in-lab testing. However, many psychophysical measurements, including visual crowding, require accurate eye fixation, which is classically achieved by testing only experienced observers who have learned to fixate reliably, or by using a gaze tracker to restrict testing to moments when fixation is accurate. Alas, both approaches are impractical online since online observers tend to be inexperienced, and online gaze tracking, using the built-in webcam, has a low precision (±4 deg, Papoutsaki et al., 2016). The EasyEyes open-source software reliably measures peripheral thresholds online with accurate fixation achieved in a novel way, without gaze tracking. EasyEyes tells observers to use the cursor to track a moving crosshair. At a random time during successful tracking, a brief target is presented in the periphery. The observer responds by identifying the target. To evaluate EasyEyes fixation accuracy and thresholds, we tested 12 naive observers in three ways in a counterbalanced order: first, in the lab, using gaze-contingent stimulus presentation (Kurzawski et al., 2023; Pelli et al., 2016); second, in the lab, using EasyEyes while independently monitoring gaze; third, online at home, using EasyEyes. We find that crowding thresholds are consistent (no significant differences in mean and variance of thresholds across ways) and individual differences are conserved. The small root mean square (RMS) fixation error (0.6 deg) during target presentation eliminates the need for gaze tracking. Thus, EasyEyes enables fixation-dependent measurements online, for easy testing of larger and more diverse populations.

Binocular integration of pattern motion signals by MT neurons and by human observers.

Analysis of the movement of a complex visual stimulus is expressed in the responses of pattern-direction-selective neurons in area MT, which depend in turn on directionally selective inputs from area V1. How do MT neurons integrate their inputs? Pattern selectivity in MT breaks down when the gratings comprising a moving plaid are presented to non-overlapping regions of the (monocular) receptive field. Here we ask an analogous question, is pattern selectivity maintained when the component gratings are presented dichoptically to binocular MT neurons? We recorded from single units in area MT, measuring responses to monocular gratings and plaids, and to dichoptic plaids in which the components are presented separately to each eye. Neurons that are pattern selective when tested monocularly lose this selectivity when stimulated with dichoptic plaids. When human observers view these same stimuli, dichoptic plaids induce binocular rivalry. Yet motion signals from each eye can be integrated despite rivalry, revealing a dissociation of form and motion perception. These results reveal the role of monocular mechanisms in the computation of pattern motion in single neurons, and demonstrate that the perception of motion is not fully represented by the responses of individual MT neurons.

Activation of the peroxisome proliferator-activated receptor gamma promotes the development of colon tumors in C57BL/6J-APCMin/+ mice.

The development of colorectal cancer, one of the most frequent cancers, is influenced by prostaglandins and fatty acids. Decreased prostaglandin production, seen in mice with mutations in the cyclooxygenase 2 gene or in animals and humans treated with cyclooxygenase inhibitors, prevents or attenuates colon cancer development. There is also a strong correlation between the intake of fatty acids from animal origin and colon cancer. Therefore, the peroxisome proliferator-activated receptor gamma (PPARgamma), a downstream transcriptional mediator for prostaglandins and fatty acids which is highly expressed in the colon may be involved in this process. Activation of PPARgamma by two different synthetic agonists increased the frequency and size of colon tumors in C57BL/6J-APCMin/+ mice, an animal model susceptible to intestinal neoplasia. Tumor frequency was only increased in the colon, and did not change in the small intestine, coinciding with the colon-restricted expression of PPARgamma. Treatment with PPARgamma agonists increased beta-catenin levels both in the colon of C57BL/61-APCMin/+ mice and in HT-29 colon carcinoma cells. Genetic abnormalities in the Wnt/wingless/APC pathway, which enhance the transcriptional activity of the beta-catenin-T-cell factor/lymphoid enhancer factor 1 transcription complex, often underly the development of colon tumors. Our data indicate that PPARgamma activation modifies the development of colon tumors in C57BL/61-APCMin/+ mice.

Grouping in object recognition: the role of a Gestalt law in letter identification.

The Gestalt psychologists reported a set of laws describing how vision groups elements to recognize objects. The Gestalt laws "prescribe for us what we are to recognize 'as one thing'" (Kohler, 1920). Were they right? Does object recognition involve grouping? Tests of the laws of grouping have been favourable, but mostly assessed only detection, not identification, of the compound object. The grouping of elements seen in the detection experiments with lattices and "snakes in the grass" is compelling, but falls far short of the vivid everyday experience of recognizing a familiar, meaningful, named thing, which mediates the ordinary identification of an object. Thus, after nearly a century, there is hardly any evidence that grouping plays a role in ordinary object recognition. To assess grouping in object recognition, we made letters out of grating patches and measured threshold contrast for identifying these letters in visual noise as a function of perturbation of grating orientation, phase, and offset. We define a new measure, "wiggle", to characterize the degree to which these various perturbations violate the Gestalt law of good continuation. We find that efficiency for letter identification is inversely proportional to wiggle and is wholly determined by wiggle, independent of how the wiggle was produced. Thus the effects of three different kinds of shape perturbation on letter identifiability are predicted by a single measure of goodness of continuation. This shows that letter identification obeys the Gestalt law of good continuation and may be the first confirmation of the original Gestalt claim that object recognition involves grouping.

Dynamics of motion signaling by neurons in macaque area MT.

Most neurons in macaque area MT are selective for the direction of stimulus motion. By comparing direction selectivity for gratings and plaids, we classified MT neurons as pattern direction selective (PDS) or component direction selective (CDS). We compared the time course of responses in CDS and PDS neurons in opiate-anesthetized macaques, using a rapid pseudorandom sequence of gratings and plaids that moved in different directions. On average, responses began 6 ms earlier in CDS neurons than in PDS neurons. More importantly, the pattern-selective responses of PDS neurons did not reach their fully selective state until 50-75 ms after the responses of CDS neurons had stabilized. The population motion response of MT is therefore initially dominated by component motion signals, and does not completely represent pattern motion until substantially later. The circuits that compute pattern motion take more time to finish their work than those signaling component motion.

Motion integration by neurons in macaque MT is local, not global.

Direction-selective neurons in primary visual cortex have small receptive fields that encode the motions of local features. These motions often differ from the motion of the object to which they belong and must therefore be integrated elsewhere. A candidate site for this integration is visual cortical area MT (V5), in which cells with large receptive fields compute the motion of patterns. Previous studies of motion integration in MT have used stimuli that fill the receptive field, and thus do not test whether motion information is really integrated across this whole area. For each MT neuron, we identified two regions ("patches") within the receptive field that were approximately equally effective in driving responses. We then measured responses to plaids whose component gratings overlapped within a patch, and compared them with responses to the same component gratings presented in separate patches. Cells that were selective for the direction of motion of the whole pattern when the gratings overlapped lost this selectivity when the gratings were separated and became selective instead for the direction of motion of the individual components. If MT cells simply pooled all of the inputs that endow them with a receptive field, they would encode all of the motions in the receptive field as belonging to a single object. Our results indicate instead that critical elements of the computations underlying pattern-direction selectivity in MT are done locally, on a scale smaller than the whole receptive field.

A new code for contrast in the primate visual pathway.

We characterize a hitherto undocumented type of neuron present in the regions bordering the principal layers of the macaque lateral geniculate nucleus. Neurons of this type were distinguished by a high and unusually regular maintained discharge that was suppressed by spatiotemporal modulation of luminance or chromaticity within the receptive field. The response to any effective stimulus was a reduction in discharge, reminiscent of the "suppressed-by-contrast" cells of the cat retina. To a counterphase-modulated grating, the response was a phase-insensitive suppression modulated at twice the stimulus frequency, implying a receptive field comprised of multiple mechanisms that generate rectifying responses. This distinctive nonlinearity makes the neurons well suited to computing a measure of contrast energy; such a signal might be important in regulating sensitivity early in visual cortex.