Biology subjects

Yates, J. L.

Publications and source records attributed to Yates, J. L..

13 recordsLinked to original sources

bioRxiv2026

Active sensing explains cortical variability and improves visual information

Active vision is often considered at the scale of saccades, with each fixation treated as a static visual sample. Yet the eyes continue to move during fixation, continually transforming the retinal input. Here we measured these movements at high precision while recording neuronal populations in the foveal primary visual cortex of awake marmosets viewing repeated flashed natural images. Fixational eye movements accounted for most conditional firing-rate variability and nearly all shared variability not explained by the trial-averaged response. An image-computable model captured this modulation largely from gaze-dependent retinal input; explicit eye-position and eye-velocity signals added little predictive power. Under natural viewing, retinal motion redistributed image power across temporal frequencies, and motion effects grew when this power engaged spatiotemporal tuning. In model-derived populations, fixational motion increased the spatial information carried per spike relative to stabilized input, with sharpening growing across successive nonlinear stages. Thus, activity commonly assigned to cortical noise is not just structured visual reafference generated by the movement of the observer, but is beneficial signal which sharpens spatial representations.

neuroscience↗

bioRxiv2024

Activity in the peripheral representation within primate V1 is substantially modulated during running

We recently investigated whether activity in primary visual cortex of a primate (Callithrix jacchus) is modulated during running, and found that the effects were small (and suppressive), a notable difference from the large and positive modulations observed in mice. In that first report, we noted that the majority of our data were collected from the retinotopic representation of the fovea, and surmised that running modulations might be different in the peripheral representation. Here, we report that running-correlated modulations of the peripheral representation in marmoset V1 are positive and substantial-- on order of 30%. In light of both the small and negative modulations observed in foveal V1, and the large and positive modulations seen in mouse V1, these results suggest that the foveal representation in primates may be unique. In this domain, non-foveal V1 in primates appears more similar to that of rodents.

neuroscience↗

bioRxiv2024

A refined human linear B cell epitope map of Outer surface protein C (OspC) from the Lyme disease spirochete, Borreliella burgdorferi

A detailed understanding of the human antibody response to Outer surface protein C (OspC) of Borrelellia burgdorferi has important implications for Lyme disease diagnostics and vaccines. In this report, a total of 13 peptides encompassing eight reported OspC linear B cell epitopes from OspC types A, B and K, including the conserved C-terminus (residues 193-210: peptide C10), were evaluated by multiplex immunoassay (MIA) for IgG reactivity with [~]700 human serum samples confirmed positive in a two-tiered Lyme disease diagnostic assay and [~]160 post-treatment Lyme disease (PTLD) serum samples. The VlsE C6-17 peptide was included as a positive control. Diagnostic serum IgG reacted with 11 of the 13 OspC-derived peptides, significantly more than controls, with the C10 peptide being the most reactive. In the PTLD serum samples, two OspC peptides including C10 were significantly more reactive than controls. Spearmans rank correlation matrices and hierarchical clustering indicated a strong correlation between C10 and VlsE C6-17 peptide reactivity but little demonstrable association between C10 and the other OspC peptides or recombinant OspC. OspC peptide reactivities (excluding C10) were strongly correlated with each other and were disproportionately influenced by a subset of pan-reactive samples. In the PTLD cohort, C10 clustered with the other OspC-derived peptides and was distinct from OspC and VlsE C6-17. The asynchronous serologic response to OspC, C10, and the OspC-derived peptides reveals the complexity of B cell responses to B. burgdorferi and confounds simple interpretation of antibody profiles associated with Lyme disease. IMPORTANCELyme disease is an emerging tick-borne infection caused by the spirochete, Borreliella burgdorferi. In humans, antibodies against spirochetal outer surface lipoproteins are proposed to play a role in disease resolution and in protection against reinfection. Some of those same antibodies also serve as diagnostic indicators of an active or history of Lyme disease. In this study, we sought to validate reported antibody binding sites on Outer surface protein C (OspC), a known target of both protective and diagnostic antibodies.

immunology↗

bioRxiv2023

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 brains understanding of the world, and hierarchical VAEs can effectively model this understanding.

neuroscience↗

bioRxiv2022

Pre-saccadic neural enhancements in marmoset area MT mimic covert attention

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 non-human primate studies have found that pre-saccadic attention does enhance neural responses spatially, no studies have tested if changes in neural tuning reflects an automatic feature enhancement. Here we examined pre-saccadic attention using a saccade foraging task developed for marmoset monkeys. We recorded from neurons in the middle temporal (MT) 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 towards 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. Significance StatementAttention leads eye movements producing perceptual enhancements at saccade targets. Recent psychophysical studies indicate that increases in pre-saccadic sensitivity are concentrated around features of the target. We tested at the neural level how pre-saccadic attention modulates the tuning curves of visual neurons in area MT of marmoset monkeys. While neurons exhibited clear pre-saccadic enhancements that were consistent with previous studies in macaques, the changes in tuning were uniform across tuning. These results show pre-saccadic enhancements are a general feature of visual processing, shared by New World monkeys, but at the level of individual neurons enhancements are uniform across features much like what has been reported previously for covert attention.

neuroscience↗

bioRxiv2022

A dynamic sequence of visual processing initiated by gaze shifts

Animals move their head and eyes as they explore and sample the visual scene. Previous studies have demonstrated neural correlates of head and eye movements in rodent primary visual cortex (V1), but the sources and computational roles of these signals are unclear. We addressed this by combining measurement of head and eye movements with high density neural recordings in freely moving mice. V1 neurons responded primarily to gaze shifts, where head movements are accompanied by saccadic eye movements, but not to head movements where compensatory eye movements stabilize gaze. A variety of activity patterns immediately followed gaze shifts, including units with positive, biphasic, or negative responses, and together these responses formed a temporal sequence following the gaze shift. These responses were greatly diminished in the dark for the vast majority of units, replaced by a uniform suppression of activity, and were similar to those evoked by sequentially flashed stimuli in head-fixed conditions, suggesting that gaze shift transients represent the temporal response to the rapid onset of new visual input. Notably, neurons responded in a sequence that matches their spatial frequency preference, from low to high spatial frequency tuning, consistent with coarse-to-fine processing of the visual scene following each gaze shift. Recordings in foveal V1 of freely gazing head-fixed marmosets revealed a similar sequence of temporal response following a saccade, as well as the progression of spatial frequency tuning. Together, our results demonstrate that active vision in both mice and marmosets consists of a dynamic temporal sequence of neural activity associated with visual sampling. HighlightsO_LIDuring free movement, neurons in mouse V1 respond to head movements that are accompanied by a gaze-shifting saccadic eye movement, but not a compensatory eye movement. C_LIO_LINeurons respond to gaze shifts with diverse temporal dynamics that form a sequence across the population, from early positive responses to biphasic and negative responses. C_LIO_LIIn darkness, most neurons show a uniform suppression following a gaze shift. C_LIO_LITemporal dynamics of responses correspond to a neurons temporal and spatial frequency preferences, consistent with a coarse-to-fine processing sequence. C_LIO_LIA similar temporal sequence following saccades is observed in foveal V1 of freely gazing head-fixed marmosets, demonstrating shared aspects of active visual processing across species. C_LI

neuroscience↗

bioRxiv2022

Running modulates primate and rodent visual cortex via common mechanism but quantitatively distinct implementation

When mice run, activity in their primary visual cortex (V1) is strongly modulated. This observation has altered conceptions of a brain region assumed to be a passive image processor. Extensive work has followed to dissect the circuits and functions of running-correlated modulation. However, it remains unclear whether visual processing in primates might similarly change during locomotion. We therefore measured V1 activity in marmosets while they viewed stimuli on a treadmill. In contrast to mouse, running-correlated modulations of marmoset V1 were small, and tended to be slightly suppressive. Population-level analyses revealed trial- to-trial fluctuations of shared gain across V1 in both species, but while strongly correlated with running in mice, gain modulations were smaller and more often negatively correlated with running in marmosets. Thus, population-wide fluctuations of V1 may reflect a common feature of mammalian visual cortical function, but important quantitative differences point to distinct consequences for the relation between vision and action in primates versus rodents.

neuroscience↗

bioRxiv2022

The Flexible Linker of Decorin Binding Protein A from Borrelia burgdorferi is a Target of Antibodies in Lyme disease

Decorin binding protein A (DbpA) is a surface adhesin expressed by Borrelia burgdorferi, the causative agent of Lyme disease. While DbpA is one of the most immunogenic B. burgdorferi antigens in Lyme disease patients, the B cell epitopes recognized over the course of infection have not been defined. In this report we profiled [~]300 human serum samples from early, mid, and late-stage Lyme disease for IgM and IgG reactivity with DbpA and a tiled DbpA 18-mer peptide array derived from B.b. strains B31 and 297. Using ELISA and multiplex immunoassays (MIA), we identified 12 DbpA-derived peptides whose reactivity was elevated in Lyme disease patients as compared to healthy controls. The most reactive peptide ("A7") corresponds to the flexible loop between DbpAB31 -helix 1 and -helix 2, implicated in influencing DbpA binding to heparin and dermatan sulfate. An A7-like peptide is also reportedly a target of antibodies in Lyme neuroborreliosis patients. The remaining peptides, while highly reactive in serum samples across disease stages, likely represent non-native epitopes, as antibody reactivity to a subset of peptides in competition assays was unaffected by the addition of soluble DbpA. Moreover, peptide reactivity of any given patient sample rarely correlated with overall DbpA antibody levels, suggesting the antibodies were raised against DbpA degradation products. Insights into B cell epitopes on DbpA elicited during Lyme disease have important implications for understanding how B.burgdorferi persists in the face of an overwhelming antibody response. IMPORTANCEThe bacterium, Borrelia burgdorferi, is the causative agent of Lyme disease, the most reported tick-borne illness in the United States. In humans, clinical manifestations of Lyme disease are complex and can persist for months, even in the face of a robust antibody response directed against numerous B. burgdorferi surface proteins, including decorin binding protein A (DbpA), which is involved in early stages of infection. In this study we employed [~]300 serum samples from Lyme disease patients to better understand antibody reactivity with specific regions ("epitopes") of DbpA. We identified one epitope on DbpA recognized by antibodies from almost half of the serum samples tested and that, theoretically, should block DbpAs ability to function in promoting B. burgdorferi colonization of human hosts.

immunology↗

bioRxiv2021

Beyond Fixation: detailed characterization of neural selectivity in free-viewing primates

Virtually all vision studies use a fixation point to stabilize gaze, rendering stimuli on video screens fixed to retinal coordinates. This approach 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 show this approach recovers receptive fields and tuning properties of visual neurons from multiple cortical areas of marmoset monkeys. Combined with high-precision eye-tracking, it achieves sufficient resolution to recover the receptive fields of foveal V1 neurons. These findings demonstrate the power of free viewing to characterize neural response while simultaneously studying the dynamics of natural behavior. HighlightsO_LIWe introduce a free-viewing paradigm for studying neural mechanisms of visual processing during active vision C_LIO_LIReceptive fields (RFs) and neural selectivity in primary visual cortex (V1) and area MT can be extracted during free-viewing in minimally-trained subjects C_LIO_LINovel high-resolution eye tracking in this context supports detailed measurements of receptive fields in foveal V1 C_LI

neuroscience↗

bioRxiv2020

Cortical synaptic diversity naturally arises with heterogeneous neural populations

The synaptic inputs to single cortical neurons exhibit substantial diversity in their sensory-driven activity. What this diversity reflects is unclear, and appears counter-productive in generating selective somatic responses to specific stimuli. We propose that synaptic diversity arises because neurons decode information from upstream populations. Focusing on a single sensory variable, orientation, we construct a probabilistic decoder that estimates the stimulus orientation from the responses of a realistic, hypothetical input population of neurons. We provide a straightforward mapping from the decoder weights to real excitatory synapses, and find that optimal decoding requires diverse input weights. Analytically derived weights exhibit diversity whenever upstream input populations consist of noisy, correlated, and heterogeneous neurons, as is typically found in vivo. In fact, in silico weight diversity was necessary to accurately decode orientation and matched the functional heterogeneity of dendritic spines imaged in vivo. Our results indicate that synaptic diversity is a necessary component of information transmission and reframes studies of connectivity through the lens of probabilistic population codes. These results suggest that the mapping from synaptic inputs to somatic selectivity may not be directly interpretable without considering input covariance and highlights the importance of population codes in pursuit of the cortical connectome.

neuroscience↗

bioRxiv2019

Stimulus-choice (mis)alignment in primate MT cortex

For stimuli near perceptual threshold, the trial-by-trial activity of single neurons in many sensory areas is correlated with the animals 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 area during perceptual-decision-making, we extracted low-dimensional neural tra jectories 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 neural trajectories 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. Author summaryIn sensorimotor decision-making, internal representation of sensory stimuli is utilized for the generation of appropriate behavior for the context. Therefore, the correlation between variability in sensory neurons and perceptual decisions is sometimes explained by a causal, feedforward role of sensory noise in behavior. However, this correlation could also originate via feedback from decision-making mechanisms downstream of the sensory representation. This cannot be resolved by analyzing single unit responses, but requires a population level analysis. Area MT contains both sensory and choice information and is known to be the key sensory area for visual motion perception. Thus the decision-making process may be corrupting the sensory representation. However, we find that the sensory stimuli and choice variables are separate at the population level,contradicting the previous interpretations based on single unit recordings. This new insight postulates how neural systems can maintain a mixed representation while allows learning and adaptation.

neuroscience↗

bioRxiv2019

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 to 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 vs. 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 non-decision time than humans. Our results provide the first quantification of motion perception in the marmoset and demonstrate several advantages to using analog estimation tasks.

neuroscience↗

bioRxiv2018

Discrete stepping and nonlinear ramping dynamics underlie spiking responses of LIP neurons during decision-making

Neurons in macaque area LIP exhibit gradual ramping in their trial-averaged spike responses during sensory decision-making. However, recent work has sparked debate over whether single-trial LIP spike trains are better described by discrete \"stepping\" or continuous drift-diffusion (\"ramping\") dynamics. Here we address this controversy using powerful model-based analyses of LIP spike responses. We extended latent dynamical models of LIP spike trains to incorporate non-Poisson spiking, baseline firing rates, and various nonlinear relationships between the latent variable and firing rate. Moreover, we used advanced model-comparison methods, including cross-validation and a fully Bayesian information criterion, to evaluate and compare models. These analyses revealed that when non-Poisson spiking was incorporated into existing stepping and ramping models, a majority of neurons remained better described by stepping dynamics, even when conditioning on evidence level or choice. However, an extended ramping model with a non-zero baseline and a compressive output nonlinearity accounted for roughly as many neurons as the stepping model. The latent dynamics inferred under this model exhibited high diffusion variance for many neurons, making them qualitatively different than slowly-evolving continuous dynamics. These findings generalized to alternative tasks, suggesting that a robust fraction of LIP neurons are better described by each model class.

neuroscience↗