Biology subjects

Winawer, J.

Publications and source records attributed to Winawer, J..

9 recordsLinked to original sources

bioRxiv2018

Modeling visual performance differences with polar angle: A computational observer approach

Visual performance depends on polar angle, even when eccentricity is held constant; on many psychophysical tasks observers perform best when stimuli are presented on the horizontal meridian, worst on the upper vertical, and intermediate on the lower vertical meridian. This variation in performance around the visual field can be as pronounced as that of doubling the stimulus eccentricity. The causes of these asymmetries in performance are largely unknown. Some factors in the eye, e.g. cone density, are positively correlated with the reported variations in visual performance with polar angle. However, the question remains whether such correlations can quantitatively explain the perceptual differences observed around the visual field. To investigate the extent to which the earliest stages of vision -optical quality and cone density- contribute to performance differences with polar angle, we created a computational observer model. The model uses the open-source software package ISETBIO to simulate an orientation discrimination task for which visual performance differs with polar angle. The model starts from the photons emitted by a display, which pass through simulated human optics with fixational eye movements, followed by cone isomerizations in the retina. Finally, we classify stimulus orientation using a support vector machine to learn a linear classifier on the photon absorptions. To account for the 30% increase in contrast thresholds for upper vertical compared to horizontal meridian, as observed psychophysically on the same task, our computational observer model would require either an increase of ~7 diopters of defocus or a reduction of 500% in cone density. These values far exceed the actual variations as a function of polar angle observed in human eyes. Therefore, we conclude that these factors in the eye only account for a small fraction of differences in visual performance with polar angle. Substantial additional asymmetries must arise in later retinal and/or cortical processing.\n\nAuthor SummaryA fundamental goal in computational neuroscience is to link known facts from biology with behavior. Here, we considered visual behavior, specifically the fact that people are better at visual tasks performed to the left or right of the center of gaze, compared to above or below at the same distance from gaze. We sought to understand what aspects of biology govern this fundamental pattern in visual behavior. To do so, we implemented a computational observer model that incorporates known facts about the front end of the human visual system, including optics, eye movements, and the photoreceptor array in the retina. We found that even though some of these properties are correlated with performance, they fall far short of quantitatively explaining it. We conclude that later stages of processing in the nervous system greatly amplify small differences in the way the eye samples the visual world, resulting in strikingly different performance around the visual field.

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bioRxiv2018

Human posterior parietal cortex responds to visual stimuli as early as peristriate occipital cortex

Much of what is known about the timing of visual processing in the brain is inferred from intracranial studies in monkeys, with human data limited to mainly non-invasive methods with lower spatial resolution. Here, we estimated visual onset latencies from electrocorticographic (ECoG) recordings in a patient who was implanted with 112 sub-dural electrodes, distributed across the posterior cortex of the right hemisphere, for pre-surgical evaluation of intractable epilepsy. Functional MRI prior to surgery was used to determine boundaries of visual areas. The patient was presented with images of objects from several categories. Event Related Potentials (ERPs) were calculated across all categories excluding targets, and statistically reliable onset latencies were determined using a bootstrapping procedure over the single trial baseline activity in individual electrodes. The distribution of onset latencies broadly reflected the known hierarchy of visual areas, with the earliest cortical responses in primary visual cortex, and higher areas showing later responses. A clear exception to this pattern was robust, statistically reliable and spatially localized, very early responses on the bank of the posterior intra-parietal sulcus (IPS). The response in the IPS started nearly simultaneously with responses detected in peristriate visual areas, around 60 milliseconds post-stimulus onset. Our results support the notion of early visual processing in the posterior parietal lobe, not respecting traditional hierarchies, and give direct evidence for the upper limit of onset times of visual responses across the human cortex.

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bioRxiv2018

Individual differences in human retinotopic maps revealed by Bayesian analysis of retinotopic organization

Human visual cortex is organized into multiple retinotopic maps. Characterizing the arrangement of these maps on the cortical surface is essential to many visual neuroscience studies. Typically, maps are obtained by voxel-wise analysis of fMRI data. This method, while useful, maps only a portion of the visual field and is limited by measurement noise and subjective assessment of boundaries. We developed a novel Bayesian mapping approach which combines observation-a subjects retinotopic measurements from small amounts of fMRI time-with a prior-a learned retinotopic atlas. This process automatically draws areal boundaries, corrects discontinuities in the measured maps, and predicts validation data more accurately than an atlas alone or independent datasets alone. This new method can be used to improve the accuracy of retinotopic mapping, to analyze large fMRI datasets automatically, and to quantify differences in map properties as a function of health, development and natural variation between individuals.

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bioRxiv2018

The HCP 7T Retinotopy Dataset

About a quarter of human cerebral cortex is dedicated mainly to visual processing. The large-scale organization of visual cortex can be measured with functional magnetic resonance imaging (fMRI) while subjects view spatially modulated visual stimuli, also known as retinotopic mapping. One of the datasets collected by the Human Connectome Project (HCP) involved ultra-high-field (7 Tesla) fMRI retinotopic mapping in 181 healthy young adults (1.6-mm resolution), yielding the largest freely available collection of retinotopy data. Here, we describe the experimental paradigm and the results of model-based analysis of the fMRI data. These results provide estimates of population receptive field position and size. Our analyses include both results from individual subjects as well as results obtained by averaging fMRI time-series across subjects at each cortical and subcortical location and then fitting models. Both the group-average and individual-subject results reveal robust signals across much of the brain, including occipital, temporal, parietal, and frontal cortex as well as subcortical areas. The group-average results agree well with previously published parcellations of visual areas. In addition, split-half analyses show strong within-subject reliability, further demonstrating the high quality of the data. We make publicly available the analysis results for individual subjects and the group average, as well as associated stimuli and analysis code. These resources provide an opportunity for studying fine-scale individual variability in cortical and subcortical organization and the properties of high-resolution fMRI. In addition, they provide a set of observations that can be compared with other HCP measures acquired in these same participants.

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bioRxiv2017

Compressive Temporal Summation in Human Visual Cortex

Combining sensory inputs over space and time is fundamental to vision. Population receptive field models have been successful in characterizing spatial encoding throughout the human visual pathways. A parallel question--how visual areas in the human brain process information distributed over time--has received less attention. One challenge is that the most widely used neuroimaging method--fMRI--has coarse temporal resolution compared to the time-scale of neural dynamics. Here, via carefully controlled temporally modulated stimuli, we show that information about temporal processing can be readily derived from fMRI signal amplitudes in male and female subjects. We find that all visual areas exhibit sub-additive summation, whereby responses to longer stimuli are less than the linear prediction from briefer stimuli. We also find fMRI evidence that the neural response to two stimuli is reduced for brief interstimulus intervals (indicating adaptation). These effects are more pronounced in visual areas anterior to V1-V3. Finally, we develop a general model that shows how these effects can be captured with two simple operations: temporal summation followed by a compressive nonlinearity. This model operates for arbitrary temporal stimulation patterns and provides a simple and interpretable set of computations that can be used to characterize neural response properties across the visual hierarchy. Importantly, compressive temporal summation directly parallels earlier findings of compressive spatial summation in visual cortex describing responses to stimuli distributed across space. This indicates that for space and time, cortex uses a similar processing strategy to achieve higher-level and increasingly invariant representations of the visual world.\n\nSignificance statementCombining sensory inputs over time is fundamental to seeing. Two important temporal phenomena are summation, the accumulation of sensory inputs over time, and adaptation, a response reduction for repeated or sustained stimuli. We investigated these phenomena in the human visual system using fMRI. We built predictive models that operate on arbitrary temporal patterns of stimulation using two simple computations: temporal summation followed by a compressive nonlinearity. Our new temporal compressive summation model captures (1) subadditive temporal summation, and (2) adaptation. We show that the model accounts for systematic differences in these phenomena across visual areas. Finally, we show that for space and time, the visual system uses a similar strategy to achieve increasingly invariant representations of the visual world.

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bioRxiv2017

Broadband spectral responses in visual cortex revealed by a new MEG denoising algorithm

Currently, non-invasive methods for studying the human brain do not reliably measure spike-rate-dependent signals, independent of other responses such as hemodynamic coupling (fMRI) and subthreshold neuronal synchrony (oscillations and event-related potentials). In contrast, invasive methods - animal microelectrode recordings and human electrocorticography (ECoG) - have recently measured broadband power elevation in field potentials (~50-200Hz) as a proxy for the locally averaged spike rates. Here, we sought to detect and quantify stimulus-related broadband responses using magnetoencephalography (MEG) in individual subjects. Because extracranial measurements like MEG have multiple global noise sources and a relatively low signal-to-noise ratio, we developed an automated denoising technique, adapted from (Kay et al., 2013), that helps reveal the broadband signal of interest. Subjects viewed 12-Hz contrast-reversing patterns in the left, right, or bilateral visual field. Sensor time series were separated into an evoked component (12-Hz amplitude) and a broadband component (60-150Hz, excluding stimulus harmonics). In all subjects, denoised broadband responses were reliably measured in sensors over occipital cortex. The spatial pattern of the broadband measure depended on the stimulus, with greater broadband power in sensors contralateral to the stimulus. Because we obtain reliable broadband estimates with relatively short experiments (~20 minutes), with a sufficient signal-to-noise-ratio to distinguish responses to different stimuli, we conclude that MEG broadband signals, denoised with our method, offer a practical, non-invasive means for characterizing spike-rate-dependent neural activity for a wide range of scientific questions about human brain function.\n\nSignificance StatementNeuronal activity causes perturbations in nearby electrical fields. These perturbations can be measured non-invasively in the living human brain using EEG and MEG. These techniques have emphasized two kinds of measurements: oscillations and event-related responses. A third type of signal, a stimulus-related increase in power spanning a wide range of frequencies ( broadband), is routinely measured in invasive recordings, but not with MEG and EEG. This broadband response is of great interest because unlike oscillations and event-related responses, it is correlated with neuronal spike rates. Here we report quantitative, spatially specific measurements of broadband fields in individual human subjects using MEG. These results demonstrate that a spike-rate-dependent measure of brain activity can be obtained non-invasively from the living human brain.

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bioRxiv2017

Systematic changes in temporal summation across human visual cortex

Neuronal responses in visual cortex show a diversity of complex temporal properties. These properties include sub-additive temporal summation, response reduction with repeated or sustained stimuli (adaptation), and slower dynamics at low stimulus contrast. Here, we hypothesize that these seemingly disparate effects can be explained by a single, shared computational mechanism. We propose a model consisting of a linear stage, followed by history-dependent gain control. The model accounts for these various temporal phenomena, tested against an unusually diverse set of measurements - intracranial electrodes in patients, fMRI, and macaque single unit spiking. The model further enables us to uncover a systematic and rich variety of temporal encoding strategies across visual cortex: First, temporal receptive field shape differs both across and within visual field maps. Second, later visual areas show more rapid and pronounced adaptation. Our study provides a new framework to understand the transformation between visual input and dynamical cortical responses.\n\nAuthor SummaryThe nervous system extracts meaning from the distribution of light over space and time. Spatial vision has been a highly successful research area, and the spatial receptive field has served as a fundamental and unifying concept that spans perception, computation, and physiology. While there has also been a large interest in temporal vision, the temporal domain has lagged the spatial domain in terms of quantitative models of how signals are transformed across the visual hierarchy. Here we present a model of temporal dynamics of neuronal responses in human cerebral cortex. We show that the model can accurately predict responses at the millisecond scale using intracortical electrodes in patient volunteers, and that the same model generalizes to multiple types of other measurements, including functional MRI and action potentials from monkey cortex. Further, we show that a single model can account for a variety of temporal phenomena, including short-term adaptation and slower dynamics at low stimulus contrast. By developing a computational model and showing that it successfully generalizes across measurement types, cortical areas, and stimuli, we provide new insights into how time-varying images are encoded and transformed into dynamic cortical responses.

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bioRxiv2016

Neuronal synchrony and the relation between the BOLD response and the local field potential.

The most widespread measures of human brain activity are the blood oxygen level dependent (BOLD) signal and surface field potential. Prior studies report a variety of relationships between these signals. To develop an understanding of how to interpret these signals and the relationship between them, we developed a model of (a) neuronal population responses, and (b) transformations from neuronal responses into the fMRI BOLD signal and electrocorticographic (ECoG) field potential. Rather than seeking a transformation between the two measures directly, this approach interprets each measure with respect to the underlying neuronal population responses. This model accounts for the relationship between BOLD and ECoG data from human visual cortex in V1-V3, with the model predictions and data matching in three ways: Across stimuli, the BOLD amplitude and ECoG broadband power were positively correlated, the BOLD amplitude and alpha power (8-13 Hz) were negatively correlated, and the BOLD amplitude and narrowband gamma power (30-80 Hz) were uncorrelated. The two measures provide complementary information about human brain activity and we infer that features of the field potential that are uncorrelated with BOLD arise largely from changes in synchrony, rather than level, of neuronal activity.

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bioRxiv2016

Visual field map clusters in human frontoparietal cortex

The visual neurosciences have made enormous progress in recent decades, in part because of the ability to drive visual areas by their sensory inputs, allowing researchers to reliably define visual areas across individuals and across species. Similar strategies for parceling higher-order cortex have proven elusive. Here, using a novel experimental task and nonlinear population receptive field modeling we map and characterize the topographic organization of several regions in human frontoparietal cortex. We discover maps of both polar angle and eccentricity that are organized into clusters, similar to visual cortex, where multiple maps of polar angle of the contralateral visual field share a confluent fovea. This is striking because neural activity in frontoparietal cortex is believed to reflect higher-order cognitive functions rather than external sensory processing. Perhaps the spatial topography in frontoparietal cortex parallels the retinotopic organization of sensory cortex to enable an efficient interface between perception and higher-order cognitive processes. Critically, these visual maps constitute well-defined anatomical units that future study of frontoparietal cortex can reliably target.

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