Biology subjects

Wandell, B. A.

Publications and source records attributed to Wandell, B. A..

10 recordsLinked to original sources

bioRxiv2025

Modeling Spectroradiometric Measurements of Oral Mucosal Autofluorescence

This study explores the potential of quantitative autofluorescence imaging (AFI) as an objective tool for monitoring the health of oral mucosal tissue. Our approach involves acquiring spectroradiometric measurements of tissue fluorescence and utilizing a model to understand the fluorophores influencing these measurements, including the impact of blood attenuation. We acquired fluorescence measurements from the dorsal tongue and inner lip of healthy human volunteers, subsequently fitting the model to these data to estimate individual fluorophore contributions and the optical density of the blood. Our dataset and model, which are freely shared in an open repository, aim to advance the development of quantitative, non-invasive diagnostic imaging systems for monitoring oral health, ultimately facilitating the detection and characterization of oral mucosal tissue abnormalities.

bioengineering↗

bioRxiv2024

Deriving the cone fundamentals: a subspace intersection method

Two ideas, proposed by Thomas Young and James Clerk Maxwell, form the foundations of color science: (1) Three types of retinal receptors encode light under daytime conditions, and (2) color matching experiments establish the critical spectral properties of this encoding. Experimental quantification of these ideas are used in international color standards. But, for many years the field did not reach consensus on the spectral properties of the biological substrate of color matching: the sensitivity of the in situ cones (cone fundamentals). By combining auxiliary data (thresholds, inert pigment analyses), complex calculations, and color matching from genetically analyzed dichromats, the human cone fundamentals have now been standardized. Here we describe a new computational method to estimate the cone fundamentals using only color matching from dichromatic observers. We show that it is not necessary to include data from trichromatic observers in the analysis or to know the primary lights used in the matching experiments. Remarkably, it is even possible to estimate the fundamentals by combining data from experiments using different, unknown primaries. We then suggest how the new method may be applied to color management in modern image systems.

neuroscience↗

bioRxiv2023

Limitations of line-scan MRI for directly measuring neural activity

Several groups have reported using 2D line-scan MRI sequences in humans and mice to directly measure neural responses to stimuli (the "DIANA response"). Other groups have been unable to replicate the DIANA response, even with higher field strength and more repetitions. Part of this discrepancy is likely due to a limited understanding of the noise profile of the line-scan MRI sequence: specifically, the consequences of deviations from the assumption of stationarity between each line acquisition. Here, we collected data using an MRI line-scan method while human subjects viewed a blank screen with the purpose of studying noise unique to the acquisition sequence. We found temporal fluctuations in the reconstructed time series from localized groups of voxels that could easily be confused with neural responses to stimuli. These fluctuations were present both in the head and in the surrounding empty volume along the span of the phase-encoding direction from the head. The timing of these fluctuations varied systematically and smoothly along the phase-encoding direction. These features can be explained by a model that accounts for the acquisition sequence and incorporates time-varying contrast fluctuations in the imaging substrate. Using the model, we quantify the amount of cortical- and scan-averaging one might need to reliably distinguish a DIANA response from noise.

neuroscience↗

bioRxiv2020

Population receptive field shapes in early visual cortex are nearly circular

The visual field region where a stimulus evokes a neural response is called the receptive field (RF). Analytical tools combined with functional MRI can estimate the receptive field of the population of neurons within a voxel. Circular population RF (pRF) methods accurately specify the central position of the pRF and provide some information about the spatial extent (diameter) of the receptive field. A number of investigators developed methods to further estimate the shape of the pRF, for example whether the shape is more circular or elliptical. There is a report that there are many pRFs with highly elliptical pRFs in early visual cortex (V1-V3; Silson et al., 2018). Large aspect ratios (>2) are difficult to reconcile with the spatial scale of orientation columns or visual field map properties in early visual cortex. We started to replicate the experiments and found that the software used in the publication does not accurately estimate RF shape: it produces elliptical fits to circular ground-truth data. We analyzed an independent data set with a different software package that was validated over a specific range of measurement conditions, to show that in early visual cortex the aspect ratios are less than 2. Furthermore, current empirical and theoretical methods do not have enough precision to discriminate ellipses with aspect ratios of 1.5 from circles. Through simulation we identify methods for improving sensitivity that may estimate ellipses with smaller aspect ratios. The results we present are quantitatively consistent with prior assessments using other methodologies. Significance StatementWe evaluated whether the shape of many population receptive fields in early visual cortex is elliptical and differs substantially from circular. We evaluated two tools for estimating elliptical models of the pRF; one tool was valid over the measured compliance range. Using the validated tool, we found no evidence that confidently rejects circular fits to the pRF in visual field maps V1, V2 and V3. The new measurements and analyses are consistent with prior theoretical and experimental assessments in the literature.

neuroscience↗

bioRxiv2020

A validation framework for neuroimagingsoftware: the case of populationreceptive fields

Neuroimaging software methods are complex, making it a near certainty that some implementations will contain errors. Modern computational techniques (i.e., public code and data repositories, continuous integration, containerization) enable the reproducibility of the analyses and reduce coding errors, but they do not guarantee the scientific validity of the results. It is difficult, nay impossible, for researchers to check the accuracy of software by reading the source code; ground truth test datasets are needed. Computational reproducibility means providing software so that for the same input anyone obtains the same result, right or wrong. Computational validity means obtaining the right result for the ground-truth test data. We describe a framework for validating and sharing software implementations. We apply the framework to an application: population receptive field (pRF) methods for functional MRI data. The framework is composed of three main components implemented with containerization methods to guarantee computational reproducibility: (1) synthesis of fMRI time series from ground-truth pRF parameters, (2) implementation of four public pRF analysis tools and standardization of inputs and outputs, and (3) report creation to compare the results with the ground truth parameters. We identified realistic conditions that lead to imperfect parameter recovery in all four implementations, and we provide means to reduce this problem. The computational validity framework supports scientific rigor and creativity, as opposed to the oft-repeated suggestion that investigators rely upon a few agreed upon packages. The framework and methods can be extended to other critical neuroimaging algorithms. Having validation frameworks help (1) developers to build new software, (2) research scientists to verify the softwares accuracy, and (3) reviewers to evaluate the methods used in publications and grants. Author SummaryComputer science provides powerful tools and techniques for implementing and deploying software. These techniques support software collaboration, reduce coding errors and enable reproducibility of the analyses. A further question is whether the software estimates are correct (valid). We describe a framework for validating and sharing software implementations based on ground-truth testing. We applied the framework to four separate applications that implemented population receptive field (pRF) estimates for functional MRI data. We quantified the validity, and we also documented limitations with these applications. Finally, we provide ways to mitigate these limitations. Implementing a software validation framework along with sharing and reproducibility is an important step for the complex methods used in neuroscience. Validation will help developers to build new software, researchers verify that the results are valid, and reviewers to evaluate the precision of methods in publications and grants.

neuroscience↗

bioRxiv2019

A computational observer model of spatial contrast sensitivity: Effects of photocurrent encoding, fixational eye movements and inference engine

We have recently shown that using the information carried by the mosaic of cone excitations of a stationary retina, the relative spatial contrast sensitivity function (CSF) of a computational observer has the same shape as a typical human subject. Absolute human sensitivity, however, is lower than the computational observer by a factor of 5 to 10. Here we model how additional known features of early vision affect spatial contrast sensitivity: fixational eye movements and the conversion of cone photopigment excitations to cone photocurrent responses. For a computational observer that uses a linear classifier applied to the responses of a stimulus-matched linear filter, fixational eye movements substantially change the shape of the spatial CSF, primarily by reducing sensitivity at spatial frequencies above 10 c/deg. For a computational observer that uses a translation-invariant calculation, in which decisions are based on the squared response of a quadrature-pair of linear filters, the CSF shape is little changed by eye movements, but there is a two-fold reduction in sensitivity. The noise and response dynamics of conversion of cone excitations into photocurrent introduce an additional two-fold sensitivity decrease. Hence, the combined effects of fixational eye movements and phototransduction bring the absolute sensitivity of the translation-invariant computational observer CSF to within a factor of 1 to 2 of the human CSF. We note that the human CSF depends on processing of the initial representation by many thalamic and cortical neurons, which are individually quite noisy. Our computational modeling suggests that the net effect of this noise on contrast-detection performance, when considered at the neural population level and behavioral level, is quite small: the inference mechanisms that determine the CSF, presumably in cortex, make efficient use of the information available from the cone photocurrents of the fixating eye.

neuroscience↗

bioRxiv2019

Reproducible Tract Profiles (RTP): from diffusion MRI acquisition to publication

Reproducible Tract Profiles (RTP) comprises a set of methods to manage and analyze diffusion weighted imaging (DWI) data for reproducible tractography. The tools take MRI data from the scanner and process them through a series of analysis implemented as Docker containers that are integrated into a modern neuroinformatics platform (Flywheel). The platform guarantees that the entire pipeline can be re-executed, using the same data and computational parameters. In this paper, we describe (1) a cloud based neuroinformatics platform, (2) a tool to programmatically access and control the platform from a client, and (3) the DWI analysis tools that are used to identify the positions of 22 tracts and their diffusion profiles. The combination of these three components defines a system that transforms raw data into reproducible tract profiles for publication.\n\nGraphical abstractReproducible Tract Profiles (RTP) comprises a set of methods to manage and analyze diffusion weighted imaging (DWI) data for reproducible tractography. The RTP methods comprise two main parts. O_LIServer side software tools for storing data and metadata and managing containerized computations.\nC_LIO_LIClient side software tools that enable the researcher to read data and metadata and manage server-side computations.\nC_LI\n\nThe server-side computational tools are embedded in containers that are linked to a JSON file with a complete specification of the computational parameters. The data and computational infrastructure on the server is fully reproducible.

neuroscience↗

bioRxiv2019

Ray tracing 3D spectral scenes through human optics models

Scientists and engineers have created computations and made measurements that characterize the first steps of seeing. ISETBio software integrates such computations and data into an open-source software package. The initial ISETBio implementations modeled image formation (physiological optics) for planar or distant scenes. The ISET3d software described here extends that implementation, simulating image formation for three-dimensional scenes. The software system relies on a quantitative computer graphics program that ray traces the scene radiance through the physiological optics to the retinal irradiance. We describe and validate the implementation for several model eyes. Then, we use the software to quantify the impact of several physiological optics parameters on three-dimensional image formation. ISET3d is integrated with ISETBio, making it straightforward to convert the retinal irradiance into cone excitations. These methods help the user compute the predictions of optics models for a wide range of spatially-rich three-dimensional scenes. They can also be used to evaluate the impact of nearby visual occlusion, the information available to binocular vision, or the retinal images expected from near-field and augmented reality displays.

neuroscience↗

bioRxiv2018

Computational-Observer Analysis of Illumination Discrimination

The spectral properties of the ambient illumination provide useful information about time of day and weather. We study the perceptual representation of illumination by analyzing measurements of how well people discriminate between illuminations across scene configurations. More specifically, we compare human performance to a computational-observer analysis that evaluates the information available in the isomerizations of the cones in a model human photoreceptor mosaic. Some patterns of human performance are predicted by the computational observer, other aspects are not. The analysis clarifies which aspects of performance require additional explanation in terms of the action of visual mechanisms beyond the isomerization of light by the cones.

neuroscience↗

bioRxiv2017

Simulation of visual perception and learning with a retinal prosthesis

The nature of artificial vision with a retinal prosthesis, and the degree to which the brain can adapt to the unnatural input from such a device, are poorly understood. Therefore, the development of current and future devices may be aided by theory and simulations that help to infer and understand what prosthesis patients see. A biologically-informed, extensible computational framework is presented here to predict visual perception and the potential effect of learning with a subretinal prosthesis. The framework relies on optimal linear reconstruction of the stimulus from retinal responses to infer the visual information available to the patient. A simulation of the physiological optics of the eye and light responses of the major retinal neurons was used to calculate the optimal linear transformation for reconstructing natural images from retinal activity. The result was then used to reconstruct the visual stimulus during the artificial activation expected from a subretinal prosthesis in a degenerated retina, as a proxy for inferred visual perception. Several simple observations reveal the potential utility of such a simulation framework. The inferred perception obtained with prosthesis activation was substantially degraded compared to the inferred perception obtained with normal retinal responses, as expected given the limited resolution and lack of cell type specificity of the prosthesis. Consistent with clinical findings and the importance of cell type specificity, reconstruction using only ON cells, and not OFF cells, was substantially more accurate. Finally, when reconstruction was re-optimized for prosthesis stimulation, simulating the greatest potential for learning by the patient, the accuracy of inferred perception was much closer to that of healthy vision. The reconstruction approach thus provides a more complete method for exploring the potential for treating blindness with retinal prostheses than has been available previously. It may also be useful for interpreting patient data in clinical trials, and for improving prosthesis design.

neuroscience↗