Pre-saccadic Neural Enhancements in Marmoset Area MT.

Each time we make an eye movement, attention moves before the eyes, resulting in a perceptual enhancement at the target. Recent psychophysical studies suggest that this pre-saccadic attention enhances the visual features at the saccade target, whereas covert attention causes only spatially selective enhancements. While previous nonhuman primate studies have found that pre-saccadic attention does enhance neural responses spatially, no studies have tested whether changes in neural tuning reflect an automatic feature enhancement. Here we examined pre-saccadic attention using a saccade foraging task developed for marmoset monkeys (one male and one female). We recorded from neurons in the middle temporal area with peripheral receptive fields that contained a motion stimulus, which would either be the target of a saccade or a distracter as a saccade was made to another location. We established that marmosets, like macaques, show enhanced pre-saccadic neural responses for saccades toward the receptive field, including increases in firing rate and motion information. We then examined if the specific changes in neural tuning might support feature enhancements for the target. Neurons exhibited diverse changes in tuning but predominantly showed additive and multiplicative increases that were uniformly applied across motion directions. These findings confirm that marmoset monkeys, like macaques, exhibit pre-saccadic neural enhancements during saccade foraging tasks with minimal training requirements. However, at the level of individual neurons, the lack of feature-tuned enhancements is similar to neural effects reported during covert spatial attention.

The Role of the Lateral Intraparietal Area in (the Study of) Decision Making.

Over the past two decades, neurophysiological responses in the lateral intraparietal area (LIP) have received extensive study for insight into decision making. In a parallel manner, inferred cognitive processes have enriched interpretations of LIP activity. Because of this bidirectional interplay between physiology and cognition, LIP has served as fertile ground for developing quantitative models that link neural activity with decision making. These models stand as some of the most important frameworks for linking brain and mind, and they are now mature enough to be evaluated in finer detail and integrated with other lines of investigation of LIP function. Here, we focus on the relationship between LIP responses and known sensory and motor events in perceptual decision-making tasks, as assessed by correlative and causal methods. The resulting sensorimotor-focused approach offers an account of LIP activity as a multiplexed amalgam of sensory, cognitive, and motor-related activity, with a complex and often indirect relationship to decision processes. Our data-driven focus on multiplexing (and de-multiplexing) of various response components can complement decision-focused models and provides more detailed insight into how neural signals might relate to cognitive processes such as decision making.

AAV-vectored expression of monospecific or bispecific monoclonal antibodies protects mice from lethal Pseudomonas aeruginosa pneumonia.

Pseudomonas aeruginosa poses a significant threat to immunocompromised individuals and those with cystic fibrosis. Treatment relies on antibiotics, but persistent infections occur due to intrinsic and acquired resistance of P. aeruginosa towards multiple classes of antibiotics. To date, there are no licensed vaccines for this pathogen, prompting the urgent need for novel treatment approaches to combat P. aeruginosa infection and persistence. Here we validated AAV vectored immunoprophylaxis as a strategy to generate long-term plasma and mucosal expression of highly protective monoclonal antibodies (mAbs) targeting the exopolysaccharide Psl (Cam-003) and the PcrV (V2L2MD) component of the type-III secretion system injectosome either as single mAbs or together as a bispecific mAb (MEDI3902) in a mouse model. When administered intramuscularly, AAV-αPcrV, AAV-αPsl, and AAV-MEDI3902 significantly protected mice challenged intranasally with a lethal dose of P. aeruginosa strains PAO1 and PA14 and reduced bacterial burden and dissemination to other organs. While all AAV-mAbs provided protection, AAV-αPcrV and AAV-MEDI3902 provided 100% and 87.5% protection from a lethal challenge with 4.47 × 107 CFU PAO1 and 87.5% and 75% protection from a lethal challenge with 3 × 107 CFU PA14, respectively. Serum concentrations of MEDI3902 were ~10× lower than that of αPcrV, but mice treated with this vector showed a greater reduction in bacterial dissemination to the liver, lung, spleen, and blood compared to other AAV-mAbs. These results support further investigation into the use of AAV vectored immunoprophylaxis to prevent and treat P. aeruginosa infections and other bacterial pathogens of public health concern for which current treatment strategies are limited.

Efficient Decoding of Large-Scale Neural Population Responses With Gaussian-Process Multiclass Regression.

Neural decoding methods provide a powerful tool for quantifying the information content of neural population codes and the limits imposed by correlations in neural activity. However, standard decoding methods are prone to overfitting and scale poorly to high-dimensional settings. Here, we introduce a novel decoding method to overcome these limitations. Our approach, the gaussian process multiclass decoder (GPMD), is well suited to decoding a continuous low-dimensional variable from high-dimensional population activity and provides a platform for assessing the importance of correlations in neural population codes. The GPMD is a multinomial logistic regression model with a gaussian process prior over the decoding weights. The prior includes hyperparameters that govern the smoothness of each neuron's decoding weights, allowing automatic pruning of uninformative neurons during inference. We provide a variational inference method for fitting the GPMD to data, which scales to hundreds or thousands of neurons and performs well even in data sets with more neurons than trials. We apply the GPMD to recordings from primary visual cortex in three species: monkey, ferret, and mouse. Our decoder achieves state-of-the-art accuracy on all three data sets and substantially outperforms independent Bayesian decoding, showing that knowledge of the correlation structure is essential for optimal decoding in all three species.

A promoterless AAV6.2FF-based lung gene editing platform for the correction of surfactant protein B deficiency.

Surfactant protein B (SP-B) deficiency is a rare genetic disease that causes fatal respiratory failure within the first year of life. Currently, the only corrective treatment is lung transplantation. Here, we co-transduced the murine lung with adeno-associated virus 6.2FF (AAV6.2FF) vectors encoding a SaCas9-guide RNA nuclease or donor template to mediate insertion of promoterless reporter genes or the (murine) Sftpb gene in frame with the endogenous surfactant protein C (SP-C) gene, without disrupting SP-C expression. Intranasal administration of 3 × 1011 vg donor template and 1 × 1011 vg nuclease consistently edited approximately 6% of lung epithelial cells. Frequency of gene insertion increased in a dose-dependent manner, reaching 20%-25% editing efficiency with the highest donor template and nuclease doses tested. We next evaluated whether this promoterless gene editing platform could extend survival in the conditional SP-B knockout mouse model. Administration of 1 × 1012 vg SP-B-donor template and 5 × 1011 vg nuclease significantly extended median survival (p = 0.0034) from 5 days in the untreated off doxycycline group to 16 days in the donor AAV and nuclease group, with one gene-edited mouse living 243 days off doxycycline. This AAV6.2FF-based gene editing platform has the potential to correct SP-B deficiency, as well as other disorders of alveolar type II cells.

Antibody-based protection against respiratory syncytial virus in mice and their offspring through vectored immunoprophylaxis.

Respiratory syncytial virus (RSV) causes acute lower respiratory tract infections, with potential lower respiratory tract infections, which can be particularly problematic in infants and the elderly. There are no approved vaccines for RSV. The current standard of care for high-risk individuals is monthly administration of palivizumab, a humanized murine monoclonal antibody (mAb) targeting the RSV fusion protein. Adeno-associated virus (AAV)-mediated expression of mAbs has previously led to sustained expression of therapeutic concentrations of mAbs in several animal models, representing an alternative to repetitive passive administration. Intramuscular (IM) administration of AAV6.2FF expressing RSV antibodies, palivizumab or hRSV90, resulted in high concentrations of human (h)IgG1 mAbs in the serum and at various mucosal surfaces, while intranasal administration limited hIgG expression to the respiratory tract. IM administration of AAV6.2FF-hRSV90 or AAV6.2FF-palivizumab in a murine model provided sterilizing immunity against challenge with RSV A2. Evidence of maternal passive transfer of vectorized hRSV90 was detected in both murine and ovine models, with circulating mAbs providing sterilizing immunity in mouse progeny. Finally, addition of a "kill switch" comprised of LoxP sites flanking the mAb genes resulted in diminished serum hIgG after AAV-DJ-mediated delivery of Cre recombinase to the same muscle group that was originally transduced with the AAV-mAb vector. The ability of this AAV-mAb system to mediate robust, sustained mAb expression for maternal transfer to progeny in murine and ovine models emphasizes the potential of this platform for use as an alternative prophylactic vaccine for protection against neonatal infections, particularly in high-risk infants.

A confirmation bias in perceptual decision-making due to hierarchical approximate inference.

Making good decisions requires updating beliefs according to new evidence. This is a dynamical process that is prone to biases: in some cases, beliefs become entrenched and resistant to new evidence (leading to primacy effects), while in other cases, beliefs fade over time and rely primarily on later evidence (leading to recency effects). How and why either type of bias dominates in a given context is an important open question. Here, we study this question in classic perceptual decision-making tasks, where, puzzlingly, previous empirical studies differ in the kinds of biases they observe, ranging from primacy to recency, despite seemingly equivalent tasks. We present a new model, based on hierarchical approximate inference and derived from normative principles, that not only explains both primacy and recency effects in existing studies, but also predicts how the type of bias should depend on the statistics of stimuli in a given task. We verify this prediction in a novel visual discrimination task with human observers, finding that each observer's temporal bias changed as the result of changing the key stimulus statistics identified by our model. The key dynamic that leads to a primacy bias in our model is an overweighting of new sensory information that agrees with the observer's existing belief-a type of 'confirmation bias'. By fitting an extended drift-diffusion model to our data we rule out an alternative explanation for primacy effects due to bounded integration. Taken together, our results resolve a major discrepancy among existing perceptual decision-making studies, and suggest that a key source of bias in human decision-making is approximate hierarchical inference.

Dissociated functional significance of decision-related activity in the primate dorsal stream.

During decision making, neurons in multiple brain regions exhibit responses that are correlated with decisions. However, it remains uncertain whether or not various forms of decision-related activity are causally related to decision making. Here we address this question by recording and reversibly inactivating the lateral intraparietal (LIP) and middle temporal (MT) areas of rhesus macaques performing a motion direction discrimination task. Neurons in area LIP exhibited firing rate patterns that directly resembled the evidence accumulation process posited to govern decision making, with strong correlations between their response fluctuations and the animal's choices. Neurons in area MT, in contrast, exhibited weak correlations between their response fluctuations and choices, and had firing rate patterns consistent with their sensory role in motion encoding. The behavioural impact of pharmacological inactivation of each area was inversely related to their degree of decision-related activity: while inactivation of neurons in MT profoundly impaired psychophysical performance, inactivation in LIP had no measurable impact on decision-making performance, despite having silenced the very clusters that exhibited strong decision-related activity. Although LIP inactivation did not impair psychophysical behaviour, it did influence spatial selection and oculomotor metrics in a free-choice control task. The absence of an effect on perceptual decision making was stable over trials and sessions and was robust to changes in stimulus type and task geometry, arguing against several forms of compensation. Thus, decision-related signals in LIP do not appear to be critical for computing perceptual decisions, and may instead reflect secondary processes. Our findings highlight a dissociation between decision correlation and causation, showing that strong neuron-decision correlations do not necessarily offer direct access to the neural computations underlying decisions.

Stimulus-choice (mis)alignment in primate area MT.

For stimuli near perceptual threshold, the trial-by-trial activity of single neurons in many sensory areas is correlated with the animal's perceptual report. This phenomenon has often been attributed to feedforward readout of the neural activity by the downstream decision-making circuits. The interpretation of choice-correlated activity is quite ambiguous, but its meaning can be better understood in the light of population-wide correlations among sensory neurons. Using a statistical nonlinear dimensionality reduction technique on single-trial ensemble recordings from the middle temporal (MT) area during perceptual-decision-making, we extracted low-dimensional latent factors that captured the population-wide fluctuations. We dissected the particular contributions of sensory-driven versus choice-correlated activity in the low-dimensional population code. We found that the latent factors strongly encoded the direction of the stimulus in single dimension with a temporal signature similar to that of single MT neurons. If the downstream circuit were optimally utilizing this information, choice-correlated signals should be aligned with this stimulus encoding dimension. Surprisingly, we found that a large component of the choice information resides in the subspace orthogonal to the stimulus representation inconsistent with the optimal readout view. This misaligned choice information allows the feedforward sensory information to coexist with the decision-making process. The time course of these signals suggest that this misaligned contribution likely is feedback from the downstream areas. We hypothesize that this non-corrupting choice-correlated feedback might be related to learning or reinforcing sensory-motor relations in the sensory population.

Motion Perception in the Common Marmoset.

Visual motion processing is a well-established model system for studying neural population codes in primates. The common marmoset, a small new world primate, offers unparalleled opportunities to probe these population codes in key motion processing areas, such as cortical areas MT and MST, because these areas are accessible for imaging and recording at the cortical surface. However, little is currently known about the perceptual abilities of the marmoset. Here, we introduce a paradigm for studying motion perception in the marmoset and compare their psychophysical performance with human observers. We trained two marmosets to perform a motion estimation task in which they provided an analog report of their perceived direction of motion with an eye movement to a ring that surrounded the motion stimulus. Marmosets and humans exhibited similar trade-offs in speed versus accuracy: errors were larger and reaction times were longer as the strength of the motion signal was reduced. Reverse correlation on the temporal fluctuations in motion direction revealed that both species exhibited short integration windows; however, marmosets had substantially less nondecision time than humans. Our results provide the first quantification of motion perception in the marmoset and demonstrate several advantages to using analog estimation tasks.

A simple linear readout of MT supports motion direction-discrimination performance.

Motion discrimination is a well-established model system for investigating how sensory signals are used to form perceptual decisions. Classic studies relating single-neuron activity in the middle temporal area (MT) to perceptual decisions have suggested that a simple linear readout could underlie motion discrimination behavior. A theoretically optimal readout, in contrast, would take into account the correlations between neurons and the sensitivity of individual neurons at each time point. However, it remains unknown how sophisticated the readout needs to be to support actual motion-discrimination behavior or to approach optimal performance. In this study, we evaluated the performance of various neurally plausible decoders, trained to discriminate motion direction from small ensembles of simultaneously recorded MT neurons. We found that decoding the stimulus without knowledge of the interneuronal correlations was sufficient to match an optimal (correlation aware) decoder. Additionally, a decoder could match the psychophysical performance of the animals with flat integration of up to half the stimulus and inherited temporal dynamics from the time-varying MT responses. These results demonstrate that simple, linear decoders operating on small ensembles of neurons can match both psychophysical performance and optimal sensitivity without taking correlations into account and that such simple read-out mechanisms can exhibit complex temporal properties inherited from the sensory dynamics themselves.NEW & NOTEWORTHY Motion perception depends on the ability to decode the activity of neurons in the middle temporal area. Theoretically optimal decoding requires knowledge of the sensitivity of neurons and interneuronal correlations. We report that a simple correlation-blind decoder performs as well as the optimal decoder for coarse motion discrimination. Additionally, the decoder could match the psychophysical performance with moderate temporal integration and dynamics inherited from sensory responses.

Continuous psychophysics: Target-tracking to measure visual sensitivity.

We introduce a novel framework for estimating visual sensitivity using a continuous target-tracking task in concert with a dynamic internal model of human visual performance. Observers used a mouse cursor to track the center of a two-dimensional Gaussian luminance blob as it moved in a random walk in a field of dynamic additive Gaussian luminance noise. To estimate visual sensitivity, we fit a Kalman filter model to the human tracking data under the assumption that humans behave as Bayesian ideal observers. Such observers optimally combine prior information with noisy observations to produce an estimate of target position at each time step. We found that estimates of human sensory noise obtained from the Kalman filter fit were highly correlated with traditional psychophysical measures of human sensitivity (R2 > 97%). Because each frame of the tracking task is effectively a "minitrial," this technique reduces the amount of time required to assess sensitivity compared with traditional psychophysics. Furthermore, because the task is fast, easy, and fun, it could be used to assess children, certain clinical patients, and other populations that may get impatient with traditional psychophysics. Importantly, the modeling framework provides estimates of decision variable variance that are directly comparable with those obtained from traditional psychophysics. Further, we show that easily computed summary statistics of the tracking data can also accurately predict relative sensitivity (i.e., traditional sensitivity to within a scale factor).

Open Iris - An Open Source Framework for Video-Based Eye-Tracking Research and Development.

Eye-tracking is an essential tool in many fields, yet existing solutions are often limited for customized applications due to cost or lack of flexibility. We present OpenIris, an adaptable and user-friendly open-source framework for video-based eye-tracking. OpenIris is developed in C# with modular design that allows further extension and customization through plugins for different hardware systems, tracking, and calibration pipelines. It can be remotely controlled via a network interface from other devices or programs. Eye movements can be recorded online from camera stream or offline post-processing recorded videos. Example plugins have been developed to track eye motion in 3-D, including torsion. Currently implemented binocular pupil tracking pipelines can achieve frame rates of more than 500Hz. With the OpenIris framework, we aim to fill a gap in the research tools available for high-precision and high-speed eye-tracking, especially in environments that require custom solutions that are not currently well-served by commercial eye-trackers.

Recombinant Newcastle disease viruses expressing immunological checkpoint inhibitors induce a pro-inflammatory state and enhance tumor-specific immune responses in two murine models of cancer.

Introduction: Tumor microenvironments are immunosuppressive due to progressive accumulation of mutations in cancer cells that can drive expression of a range of inhibitory ligands and cytokines, and recruitment of immunomodulatory cells, including myeloid-derived suppressor cells (MDSC), tumor-associated macrophages, and regulatory T cells (Tregs). Methods: To reverse this immunosuppression, we engineered mesogenic Newcastle disease virus (NDV) to express immunological checkpoint inhibitors anti-cytotoxic T lymphocyte antigen-4 and soluble programmed death protein-1. Results: Intratumoral administration of recombinant NDV (rNDV) to mice bearing intradermal B16-F10 melanomas or subcutaneous CT26LacZ colon carcinomas led to significant changes in the tumor-infiltrating lymphocyte profiles. Vectorizing immunological checkpoint inhibitors in NDV increased activation of intratumoral natural killer cells and cytotoxic T cells and decreased Tregs and MDSCs, suggesting induction of a pro-inflammatory state with greater infiltration of activated CD8+ T cells. These notable changes translated to higher ratios of activated effector/suppressor tumor-infiltrating lymphocytes in both cancer models, which is a promising prognostic marker. Whereas all rNDV-treated groups showed evidence of tumor regression and increased survival in the CT26LacZ and B16-F10, only treatment with NDV expressing immunological checkpoint blockades led to complete responses compared to tumors treated with NDV only. Discussion: These data demonstrated that NDV expressing immunological checkpoint inhibitors could reverse the immunosuppressive state of tumor microenvironments and enhance tumor-specific T cell responses.

Intranasal vaccination with an NDV-vectored SARS-CoV-2 vaccine protects against Delta and Omicron challenges.

The rapid development and deployment of vaccines following the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been estimated to have saved millions of lives. Despite their immense success, there remains a need for next-generation vaccination approaches for SARS-CoV-2 and future emerging coronaviruses and other respiratory viruses. Here we utilized a Newcastle Disease virus (NDV) vectored vaccine expressing the ancestral SARS-CoV-2 spike protein in a pre-fusion stabilized chimeric conformation (NDV-PFS). When delivered intranasally, NDV-PFS protected both Syrian hamsters and K18 mice against Delta and Omicron SARS-CoV-2 variants of concern. Additionally, intranasal vaccination induced robust, durable protection that was extended to 6 months post-vaccination. Overall, our data provide evidence that NDV-vectored vaccines represent a viable next-generation mucosal vaccination approach.

Mucosal Vaccination with a Newcastle Disease Virus-Vectored Vaccine Reduces Viral Loads in SARS-CoV-2-Infected Cynomolgus Macaques.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged following an outbreak of unexplained viral illness in China in late 2019. Since then, it has spread globally causing a pandemic that has resulted in millions of deaths and has had enormous economic and social consequences. The emergence of SARS-CoV-2 saw the rapid and widespread development of a number of vaccine candidates worldwide, and this never-before-seen pace of vaccine development led to several candidates progressing immediately through clinical trials. Many countries have now approved vaccines for emergency use, with large-scale vaccination programs ongoing. Despite these successes, there remains a need for ongoing pre-clinical and clinical development of vaccine candidates against SARS-CoV-2, as well as vaccines that can elicit strong mucosal immune responses. Here, we report on the efficacy of a Newcastle disease virus-vectored vaccine candidate expressing SARS-CoV-2 spike protein (NDV-FLS) administered to cynomolgus macaques. Macaques given two doses of the vaccine via respiratory immunization developed robust immune responses and had reduced viral RNA levels in nasal swabs and in the lower airway. Our data indicate that NDV-FLS administered mucosally provides significant protection against SARS-CoV-2 infection, resulting in reduced viral burden and disease manifestation, and should be considered as a viable candidate for clinical development.

On determining the intracranial sources of visual evoked potentials from scalp topography: a reply to Kelly et al. (this issue).

The cruciform model posits that if a Visual Evoked Potential component originates in cortical area V1, then stimuli placed in the upper versus lower visual field will generate responses with opposite polarity at the scalp. In our original paper (Ales et al., 2010b) we showed that the cruciform model provides an insufficient criterion for identifying V1 sources. This conclusion was reached on the basis of simulations that used realistic 3D models of early visual areas to simulate scalp topographies expected for stimuli of different sizes and shapes placed in different field locations. The simulations indicated that stimuli placed in the upper and lower visual field produce polarity inverting scalp topographies for activation of areas V2 and V3, but not for area V1. As a consequence of the non-uniqueness of the polarity inversion criterion, we suggested that past studies using the cruciform model had not adequately excluded contributions from sources outside V1. In their comment on our paper, Kelly et al. (this issue) raise several concerns with this suggestion. They claim that our initial results did not use the proper stimulus locations to constitute a valid test of the cruciform model. Kelly et al., also contend that the cortical source of the initial visually evoked component (C1) can be identified based on latency and polarity criteria derived from intracranial recordings in non-human primates. In our reply we show that simulations using the suggested critical stimulus locations are consistent with our original findings and thus do not change our conclusions regarding the use of the polarity inversion criterion. We further show that the anatomical assumptions underlying the putatively optimal locations are not consistent with available V1 anatomical data. We then address the non-human primate data, describing how differences in stimuli across studies and species confound an effective utilization of the non-human primate data for interpreting human evoked potential responses. We also show that, considered more broadly, the non-human primate literature shows that multiple visual areas onset simultaneously with V1. We suggest several directions for future research that will further clarify how to make the best use of scalp data for inferring cortical sources.

Hierarchical VAEs provide a normative account of motion processing in the primate brain.

The relationship between perception and inference, as postulated by Helmholtz in the 19th century, is paralleled in modern machine learning by generative models like Variational Autoencoders (VAEs) and their hierarchical variants. Here, we evaluate the role of hierarchical inference and its alignment with brain function in the domain of motion perception. We first introduce a novel synthetic data framework, Retinal Optic Flow Learning (ROFL), which enables control over motion statistics and their causes. We then present a new hierarchical VAE and test it against alternative models on two downstream tasks: (i) predicting ground truth causes of retinal optic flow (e.g., self-motion); and (ii) predicting the responses of neurons in the motion processing pathway of primates. We manipulate the model architectures (hierarchical versus non-hierarchical), loss functions, and the causal structure of the motion stimuli. We find that hierarchical latent structure in the model leads to several improvements. First, it improves the linear decodability of ground truth factors and does so in a sparse and disentangled manner. Second, our hierarchical VAE outperforms previous state-of-the-art models in predicting neuronal responses and exhibits sparse latent-to-neuron relationships. These results depend on the causal structure of the world, indicating that alignment between brains and artificial neural networks depends not only on architecture but also on matching ecologically relevant stimulus statistics. Taken together, our results suggest that hierarchical Bayesian inference underlines the brain's understanding of the world, and hierarchical VAEs can effectively model this understanding.

Activity in primate visual cortex is minimally driven by spontaneous movements.

Organisms process sensory information in the context of their own moving bodies, an idea referred to as embodiment. This idea is important for developmental neuroscience, robotics and systems neuroscience. The mechanisms supporting embodiment are unknown, but a manifestation could be the observation in mice of brain-wide neuromodulation, including in the primary visual cortex, driven by task-irrelevant spontaneous body movements. We tested this hypothesis in macaque monkeys (Macaca mulatta), a primate model for human vision, by simultaneously recording visual cortex activity and facial and body movements. We also sought a direct comparison using an analogous approach to those used in mouse studies. Here we found that activity in the primate visual cortex (V1, V2 and V3/V3A) was associated with the animals' own movements, but this modulation was largely explained by the impact of the movements on the retinal image, that is, by changes in visual input. These results indicate that visual cortex in primates is minimally driven by spontaneous movements and may reflect species-specific sensorimotor strategies.

Detailed characterization of neural selectivity in free viewing primates.

Fixation constraints in visual tasks are ubiquitous in visual and cognitive neuroscience. Despite its widespread use, fixation requires trained subjects, is limited by the accuracy of fixational eye movements, and ignores the role of eye movements in shaping visual input. To overcome these limitations, we developed a suite of hardware and software tools to study vision during natural behavior in untrained subjects. We measured visual receptive fields and tuning properties from multiple cortical areas of marmoset monkeys who freely viewed full-field noise stimuli. The resulting receptive fields and tuning curves from primary visual cortex (V1) and area MT match reported selectivity from the literature which was measured using conventional approaches. We then combined free viewing with high-resolution eye tracking to make the first detailed 2D spatiotemporal measurements of foveal receptive fields in V1. These findings demonstrate the power of free viewing to characterize neural responses in untrained animals while simultaneously studying the dynamics of natural behavior.