Biology subjects

Victor, J. D.

Publications and source records attributed to Victor, J. D..

11 recordsLinked to original sources

bioRxiv2026

Eye movements enhance stereoscopic 3D vision

In moving organisms, sensory systems must recover spatial properties of the world from signals continually altered by their own movements. These self-generated temporal signals carry useful spatial information across various sensory modalities, but it remains unclear whether they also contribute to fine visual computations traditionally thought to rely on the spatial structure of the retinal images. In humans, stereopsis estimates depth from differences between the images in the two eyes with extraordinary precision. Yet fixational eye movements continually alter these differences, causing binocular disparity to fluctuate over time. Here we show that stereopsis critically depends on these oculomotor-induced input changes. Using high-resolution binocular eye tracking and gaze-contingent display control, we selectively manipulated the retinal consequences of the differential (vergence) and common (version) components of binocular eye movements. Suppressing eye-movement-induced disparity modulations severely impairs stereopsis, even when retinal image motion in each eye is preserved. Across viewing conditions, the strength of disparity modulations closely predicts performance, regardless of whether they are generated by vergence or version. These findings establish stereopsis as a spatiotemporal process and reveal disparity dynamics induced by eye movements as a critical resource for fine depth perception.

neuroscience↗

bioRxiv2025

What one sees depends on how far the eye has moved

Humans explore visual scenes through frequent, rapid gaze shifts known as saccades. These movements redirect the high-acuity region of the retina toward objects of interest, thus selecting information based on location. Here, we show that saccade amplitude provides a separate and complementary form of selection, effectively filtering visual information by spatial frequency rather than location. Specifically, a reduction in saccade amplitude attenuates post-saccadic visual sensitivity in an amplitude-dependent range of low spatial frequencies. This effect is highly robust, so that even minute changes in saccade size considerably affect visibility. We show that this phenomenon arises from the way the magnitude-dependent kinematic characteristics of saccades transform the visual world into a spatiotemporal flow: post-saccadic visibility closely follows theoretical predictions based on the spatial information that saccade transients convey within the temporal bandwidth of retinal sensitivity. Thus, saccades not only guide selection based on location, but also filter visual information based on content, actively shaping perception.

neuroscience↗

bioRxiv2025

Residual Foveal Motion Facilitates Processing of Visually Tracked Objects

Humans and other species visually track moving objects via pursuit eye movements. These movements fail to stabilize the stimulus on the retina, an effect often attributed to errors in oculomotor control. However, it remains unclear whether the resulting residual retinal motion serves visual functions. Using high-resolution eye tracking, we reconstructed foveal motion during discrimination of both stationary and moving stimuli. We show that the retinal motion elicited by pursuit is heavily constrained and strikingly mirrors the motion present during normal active fixation. We then show that this motion performs an important information-compression computational function by equalizing luminance modulations in a low-spatial-frequency range during tracking of natural stimuli. Finally, we show that the resulting visual signals during tracking contribute to perceptual judgments, shifting spatial sensitivity toward lower frequencies relative to fixation. These results suggest that retinal motion during pursuit constitutes an active strategy for encoding space in the joint space-time domain.

neuroscience↗

bioRxiv2024

Electrophysiological responses to appetitive and consummatory behavior in the rostral nucleus tractus solitarius in awake, unrestrained rats

As the intermediate nucleus in the brainstem receiving information from the tongue and transmitting information upstream, the rostral portion of the nucleus tractus solitarius (rNTS) is most often described as a "taste relay". Although recent evidence implicates the NTS in a broad neural circuit involved in regulating ingestion, there is little information about how cells in this structure respond when an animal is eating solid food. Here, single cells in the rNTS were recorded in awake, unrestrained rats as they explored and ate solid foods (Eating paradigm) chosen to correspond to the basic taste qualities: milk chocolate for sweet, salted peanuts for salty, Granny Smith apples for sour and broccoli for bitter. A subset of cells was also recorded as the animal licked exemplars of the five basic taste qualities: sucrose, NaCl, citric acid, quinine and MSG (Lick paradigm). Results showed that most cells were excited by exploration of a food-filled well, sometimes responding prior to contact with the food. In contrast, cells that were excited by food well exploration became significantly less active while the animal was eating the food. Most cells were broadly tuned across foods, and those cells that were recorded in both the Lick and Eating paradigms showed little correspondence in their tuning across paradigms. The preponderance of robust responses to the appetitive versus the consummatory phase of ingestion suggests that multimodal convergence onto cells in the rNTS may be used in decision making about ingestion. Significance StatementThe rostral part of the NTS has traditionally, but perhaps narrowly, been thought of as a "taste relay". While it is true that this structure receives and transmits information about tastants in the mouth to higher order structures in the central gustatory pathway, data presented here show that its function is more diverse. Specifically, in addition to the responses to liquid tastants in the mouth, its responses to approach and exploration of solid food define a significant role for the rNTS in the appetitive phase of eating. Moreover, responses to food consumption, albeit weaker than those during appetitive behavior, buttress the idea that the rNTS is part of the larger hindbrain circuit guiding energy regulation.

neuroscience↗

bioRxiv2024

Inhibitory control of locomotor statistics in walking Drosophila

In order to forage for food, many animals regulate not only specific limb movements but the statistics of locomotor behavior over time, switching between long-range dispersal and localized search depending on resource availability. How pre-motor circuits regulate such locomotor statistics is not clear. Here we analyze and model locomotor statistics in walking Drosophila, and their modulation by attractive food odor. Odor evokes three motor regimes in flies: baseline walking, upwind running during odor, and search behavior following odor loss. During search behavior, we find that flies adopt higher angular velocities and slower ground speeds, and tend to turn for longer periods of time in one direction. We further find that flies spontaneously adopt periods of different mean ground speed, and that these changes in state influence the length of odor-evoked runs. We next developed a simple model of neural locomotor control that suggests that contralateral inhibition plays a key role in regulating the statistical features of locomotion. As the fly connectome predicts decussating inhibitory neurons in the lateral accessory lobe (LAL), a pre-motor structure, we gained genetic access to a subset of these neurons and tested their effects on behavior. We identified one population of neurons whose activation induces all three signature of search and that bi-directionally regulates angular velocity at odor offset. We identified a second group of neurons, including a single LAL neuron pair, that bi-directionally regulate ground speed. Together, our work develops a biologically plausible computational architecture that captures the statistical features of fly locomotion across behavioral states and identifies potential neural substrates of these computations.

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bioRxiv2023

The geometry of low- and high-level perceptual spaces

Low-level features are typically continuous (e.g., the gamut between two colors), but semantic information is often categorical (there is no corresponding gradient between dog and turtle) and hierarchical (animals live in land, water, or air). To determine the impact of these differences on cognitive representations, we characterized the geometry of perceptual spaces of five domains: a domain dominated by semantic information (animal names presented as words), a domain dominated by low-level features (colored textures), and three intermediate domains (animal images, lightly-texturized animal images that were easy to recognize, and heavily-texturized animal images that were difficult to recognize). Each domain had 37 stimuli derived from the same animal names. From 13 subjects (9F), we gathered similarity judgments in each domain via an efficient psychophysical ranking paradigm. We then built geometric models of each domain for each subject, in which distances between stimuli accounted for subjects similarity judgments and intrinsic uncertainty. Remarkably, the five domains had similar global properties: each required 5 to 7 dimensions, and a modest amount of spherical curvature provided the best fit. However, the arrangement of the stimuli within these embeddings depended on the level of semantic information: dendrograms derived from semantic domains (word, image, and lightly texturized images) were more tree-like than those from feature-dominated domains (heavily texturized images and textures). Thus, the perceptual spaces of domains along this feature-dominated to semantic-dominated gradient have a similar global geometry, but the points within the spaces shift to a tree-like organization when semantic information dominates. Significance StatementUnderstanding the nature of knowledge representation is a fundamental goal of systems neuroscience. Low-level visual features (e.g., color), form continuous domains, while semantic information is typically organized into categories and subcategories. Here, using a novel psychophysical paradigm and computational modeling strategy, we find that despite these major differences, the mental representations of these domains lie in spaces with similar overall geometry. However, within these spaces, semantic information is arranged in a more tree-like representation, and the transition to tree-like representations is relatively abrupt once semantic information becomes apparent. These findings provide insight into visual stream processing at an algorithmic level. Furthermore, they support the idea that processing along the ventral stream reflects commonalities of intrinsic cortical function.

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bioRxiv2022

Fine oculomotor knowledge enhances high-acuity vision

It has long been debated how humans resolve fine details and perceive a stable visual world despite the fixational motion of their eyes, the incessant ocular jitter that occurs in the intervals between voluntary gaze shifts. Current theories assume these processes to rely solely on the visual input to the retina, without contributions from motor and/or proprioceptive sources. Here we show that contrary to this widespread assumption, the visual system has access to high-resolution extra-retinal knowledge of fixational eye motion and uses it to deduce spatial relations. Building on recent advances in gaze-contingent display control, we created a spatial discrimination task in which the stimulus configuration was entirely determined by oculomotor activity. Our results show that humans correctly infer geometrical relations even when no spatial information is delivered to the retina and accurately combine high-resolution extraretinal monitoring of gaze displacement with retinal signals. These findings reveal a multimodal strategy for encoding spatial details, in which fine oculomotor knowledge is used to interpret the fixational input to the retina.

neuroscience↗

bioRxiv2022

Geometry of spiking activity in early visual cortex: a Topological Data Analytic approach

In the brain, spiking patterns live in a high-dimensional space of neurons and time. Thus, determining the intrinsic structure of this space presents a theoretical and experimental challenge. To address this challenge, we introduce a new framework for applying topological data analysis (TDA) to spike train data and use it to determine the geometry of spiking patterns in the visual cortex. Key to our approach is a parameterized family of distances based on the timing of spikes that quantifies the dissimilarity between neuronal responses. We applied TDA to visually driven single-unit and multiple single-unit spiking activity in macaque V1 and V2. TDA across timescales reveals a common geometry for spiking patterns in V1 and V2 which, among simple models, is most similar to that of a low-dimensional space endowed with Euclidean or hyperbolic geometry with modest curvature. Remarkably, the inferred geometry depends on timescale, and is clearest for the timescales that are important for encoding contrast, orientation, and spatial correlations.

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bioRxiv2020

Enhancing GABAergic Tone in the Rostral Nucleus of the Solitary Tract Reconfigures Sensorimotor Neural Activity

Recent work has shown that most cells in the rostral, gustatory portion of the nucleus tractus solitarius (rNTS) in awake, freely licking rats show lick-related firing. However, the relationship between taste-related and lick-related activity in rNTS remains unclear. Here, we tested if GABA-derived inhibitory activity regulates the balance of lick- and taste-driven neuronal activity. Combinatorial viral tools were used to restrict expression of ChR2-EYFP to GAD1+ GABAergic neurons. Viral infusions were bilateral in rNTS. 2-4wks later, an optical fiber attached to 8-16 drivable microwires was implanted into the rNTS. After recovery, water-deprived rats were presented with taste stimuli in an experimental chamber. Trials were 5 consecutive taste licks [NaCl, KCl, NH4Cl, sucrose, MSG/IMP, citric acid, quinine, or artificial saliva (AS)] separated by 5 AS licks on a VR5 schedule. Each taste lick triggered a 1s train of laser light (25Hz; 473nm; 8-10mW) in a random half of the trials. In all, 113 cells were recorded in the rNTS, 50 responded to one or more taste stimuli without GABA enhancement. Selective changes in response magnitude (spike count) within cells shifted across unit patterns but preserved inter-stimulus relationships. Cells where enhanced GABAergic tone increased lick coherence conveyed more information distinguishing basic taste qualities and different salts than other cells. In addition, GABA activation significantly amplified the amount of information that discriminated palatable vs. unpalatable tastants. By dynamically regulating lick coherence and remodeling the across-unit response patterns to taste, enhancing GABAergic tone in rNTS reconfigures the neural activity reflecting sensation and movement. Significance StatementThe rostral nucleus tractus solitarius (rNTS) is the first structure in the central gustatory pathway. Electrophysiological recordings from the rNTS in awake, freely-licking animals show that cells in this area have lick- as well as taste-related activity, but the relationship between these characteristics is not well understood. Here, we showed evidence that GABA activation can dynamically regulate both of these two properties in rNTS cells to enhance the information conveyed, especially about palatable vs. unpalatable tastants. These data provide insights into the role of inhibitory activity in the rNTS.

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bioRxiv2019

Sensitivity to grayscale textures is adapted to natural scene statistics

Previously, in [1], we showed that when sampling is limiting, the efficient coding principle leads to a "variance is salience" hypothesis, and that this hypothesis accounts for visual sensitivity to binary image statistics. Here, using extensive new psychophysical data and image analysis, we show that this hypothesis accounts for visual sensitivity to a large set of grayscale image statistics at a striking level of detail, and also identify the limits of the prediction. We define a 66-dimensional space of local grayscale light-intensity correlations, and measure the relevance of each direction to natural scenes. The "variance is salience" hypothesis predicts that two-point correlations are most salient, and predicts their relative salience. We tested these predictions in a texture-segregation task using un-natural, synthetic textures. As predicted, correlations beyond second order are not salient, and predicted thresholds for over 300 second-order correlations match psychophysical thresholds closely (median fractional error < 0.13).

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bioRxiv2018

Systematic differences between visually-relevant global and local image statistics of brain MRI and natural scenes

An important heuristic in developing image processing technologies is to mimic the computational strategies used by humans. Relevant to this, recent studies have shown that the human brains processing strategy is closely matched to the characteristics of natural scenes, both in terms of global and local image statistics. However, structural MRI images and natural scenes have fundamental differences: the former are two-dimensional sections through a volume, the latter are projections. MRI image formation is also radically different from natural image formation, involving acquisition in Fourier space, followed by several filtering and processing steps that all have the potential to alter image statistics. As a consequence, aspects of the human visual system that are finely-tuned to processing natural scenes may not be equally well-suited for MRI images, and identification of the differences between MRI images and natural scenes may lead to improved machine analysis of MRI.\n\nWith these considerations in mind, we analyzed spectra and local image statistics of MRI images in several databases including T1 and FLAIR sequence types and of simulated MRI images,[1]-[6] and compared this analysis to a parallel analysis of natural images[7] and visual sensitivity[7][8]. We found substantial differences between the statistical features of MRI images and natural images. Power spectra of MRI images had a steeper slope than that of natural images, indicating a lack of scale invariance. Independent of this, local image statistics of MRI and natural images differed: compared to natural images, MRI images had smaller variations in their local two-point statistics and larger variations in their local three-point statistics - to which the human visual system is relatively insensitive. Our findings were consistent across MRI databases and simulated MRI images, suggesting that they result from brain geometry at the scale of MRI resolution, rather than characteristics of specific imaging and reconstruction methods.

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