Biology subjects

Wandell, B.

Publications and source records attributed to Wandell, B..

7 recordsLinked to original sources

bioRxiv2025

An image-computable, spatio-chromatic RF model of the midget RGC mosaic across the retina

Accurate image-computable models of retinal ganglion cell (RGC) mosaics across the retina do not currently exist. Here, we deploy a novel computational frame-work which synthesizes mosaics of linear spatio-chromatic receptive fields (RFs) of ON midget RGCs (mRGCs) by integrating published anatomical, physiological, and optical quality measurements. We use the synthesized mRGC mosaics to simulate both in vivo and in vitro physiological experiments and demonstrate the models consistency with published data. The model enables computation of how visual performance is shaped by the representation of visual information provided by the linear spatiochromatic processing stage of midget RGCs. The developed computational framework carefully accounts for the effect of physiological optics on mRGC responses, enables comparison of in vivo and in vitro data, and allows exploration of how different assumptions about RF organization, such as selectivity for the type of cones pooled by the RF center mechanism, affect physiological responses and psychophysical performance. The open-source and freely available implementation provides a platform for understanding how the linear spatiochromatic receptive field representation of the mRGCs shapes visual performance, as well as a foundation for future work that incorporates response nonlinearities, temporal filtering, and extends to additional RGC mosaics.

neuroscience↗

bioRxiv2022

Reproducible Tract Profiles (RTP2): from diffusion MRI acquisition to clinical practice and research

Diffusion MRI is a complex technique, where new discoveries and implementations occur at a fast pace. The expertise needed for data analyses and accurate and reproducible results is increasingly demanding and requires multidisciplinary collaborations. In the present work we introduce Reproducible Tract Profiles (RTP2): a set of flexible and automated methods to analyze anatomical MRI and diffusion weighted imaging (DWI) data for reproducible tractography. The tools read structural MRI data and process them through a succession of serialized containerized analyses. We describe the DWI algorithms used to identify white-matter tracts and their summary metrics, the flexible architecture of the platform, and the tools to programmatically access and control the computations. The combination of these three components provides an easy-to-use automatized tool developed and tested over 20 years, to obtain usable and reliable state-of-the-art diffusion metrics at the individual and group levels for basic research and clinical practice. HighlightsO_LIAutomated, flexible and reproducible protocol for white-matter tractography and tractometry. C_LIO_LIHigh computational (same data, different computations) and test-retest reproducibility (data from different sessions, different computations). C_LIO_LIOpen-source code and publicly available containers. C_LI

neuroscience↗

bioRxiv2022

Measuring brain beats: cardiac-aligned fast fMRI signals

Blood and cerebrospinal fluid (CSF) pulse and flow throughout the brain, driven by the cardiac cycle. These fluid dynamics, which are essential to healthy brain function, are characterized by several noninvasive magnetic resonance imaging (MRI) methods. Recent developments in fast MRI, specifically simultaneous multislice (SMS) acquisition methods, provide a new opportunity to rapidly and broadly assess cardiac-driven flow, including CSF spaces, surface vessels and parenchymal vessels. We use these techniques to assess blood and CSF flow dynamics in brief (3.5 minute) scans on a conventional 3T MRI scanner. Cardiac pulses are measured with a photoplethysmograph (PPG) on the index finger, along with fMRI signals in the brain. We retrospectively analyze the fMRI signals gated to the heart beat. Highly reliable cardiac-gated fMRI temporal signals are observed in CSF and blood on the timescale of one heartbeat (test-retest reliability within subjects R2>0.50). Cardiac pulsations with a local minimum following systole are observed in blood vessels, with earlier extrema in the carotid and basilar arteries and in branches of the anterior, posterior and middle cerebral arteries and extrema [~]200 ms later in the superior sagittal, transverse and straight sinuses. CSF spaces in the ventricles and subarachnoid space showed cardiac pulsations with a local maximum following systole instead. Similar responses are observed, with less temporal detail, in slower resting state scans with slice timing retrospectively aligned to the cardiac pulse in the same manner. The SMS measurements rapidly, noninvasively and reliably sample brain-wide fMRI signal pulsations aligned to the heartbeat. The measurements estimate the amplitude and phase of cardiac driven fMRI pulsations in the CSF relative to those in the arteries, which is thought to be an estimate of the local intracranial impedance. Cardiac aligned fMRI signals can provide new insights about fluid dynamics or diagnostics for diseases where these dynamics are important.

neuroscience↗

bioRxiv2021

Interpreting sensory and cognitive signals in the cortical reading network

Voxels in the visual cortex contain neurons that are responsive to small regions of the visual field; these regions can be quantified using population receptive field (pRF) analysis. We measured pRFs using several types of patterns: words, visually matched false-fonts, and visually dissimilar checker patterns. In visual field maps pRF estimates using words and false-fonts are similar, but pRF estimates using checkers differ substantially. The pattern of results in the contiguous ventral occipito-temporal reading circuitry is different: word pRF estimates differ from false-fonts and checkers. These findings were replicated at two research sites. We explain these results with a qualitative model, where the response differences in the visual field maps arise from sensory signals, and the differences in the reading circuitry arise from the integration of sensory and cognitive signals.

neuroscience↗

bioRxiv2021

Simulations of fluorescence imaging in the oral cavity

We describe an end-to-end image systems simulation that models a device capable of measuring fluorescence in the oral cavity. Our software includes a 3D model of the oral cavity and excitation-emission matrices of endogenous fluorophores that predict the spectral radiance of oral mucosal tissue. The predicted radiance is transformed by a model of the optics and image sensor to generate expected sensor image values. We compare simulated and real camera data from tongues in healthy individuals and show that the camera sensor chromaticity values can be used to quantify the fluorescence from porphyrins relative to the bulk fluorescence from multiple fluorophores (elastin, NADH, FAD, and collagen). Validation of the simulations supports the use of soft-prototyping in guiding system design for fluorescence imaging. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

bioengineering↗

bioRxiv2018

A computational observer model of spatial contrast sensitivity: Effects of wavefront-based optics, cone mosaic structure, and inference engine

We present a computational observer model of the human spatial contrast sensitivity (CSF) function based on the Image Systems EngineeringTools for Biology (ISETBio) simulation framework. We demonstrate that ISETBio-derived CSFs agree well with CSFs derived using traditional ideal observer approaches, when the mosaic, optics, and inference engine are matched. Further simulations extend earlier work by considering more realistic cone mosaics, more recent measurements of human physiological optics, and the effect of varying the inference engine used to link visual representations to psy-chohysical performance. Relative to earlier calculations, our simulations show that the spatial structure of realistic cone mosaics reduces upper bounds on performance at low spatial frequencies, whereas realistic optics derived from modern wavefront measurements lead to increased upper bounds high spatial frequencies. Finally, we demonstrate that the type of inference engine used has a substantial effect on the absolute level of predicted performance. Indeed, the performance gap between an ideal observer with exact knowledge of the relevant signals and human observers is greatly reduced when the inference engine has to learn aspects of the visual task. ISETBio-derived estimates of stimulus representations at different stages along the visual pathway provide a powerful tool for computing the limits of human performance.

neuroscience↗

bioRxiv2017

Simulating retinal encoding: factors influencing Vernier acuity

Humans resolve the spatial alignment between two visual stimuli at a resolution that is substantially finer than the spacing between the foveal cones. In this paper, we analyze the factors that limit the information at the cone photoreceptors that is available to make these acuity judgments (Vernier acuity). We use open-source software, ISETBIO1 to quantify the stimulus and encoding stages in the front-end of the human visual system, starting with a description of the stimulus spectral radiance and a computational model that includes the physiological optics, inert ocular pigments, eye movements, photoreceptor sampling and absorptions. The simulations suggest that the visual system extracts the information available within the spatiotemporal pattern of photoreceptor absorptions within a small spatial (0.12 deg) and temporal (200 ms) regime. At typical display luminance levels, the variance arising from the Poisson absorptions and small eye movements (tremors and microsaccades) both appear to be critical limiting factors for Vernier acuity.

neuroscience↗