About

Brian A. Wandell is the Isaac and Madeline Stein Family Professor and a member of the Stanford Psychology faculty, with courtesy appointments in Electrical Engineering, Ophthalmology, and the Graduate School of Education. His research centers on vision science, encompassing topics such as visual disorders, reading development in children, and digital imaging devices and algorithms for magnetic resonance imaging and digital imaging. Wandell's work in visual neuroscience employs functional, structural, and quantitative MRI, along with behavior testing and modeling, to understand the organization and functioning of the visual portions of the brain. His lab has contributed to identifying and understanding the organization of visual field maps in the human brain, color and motion processing within these maps, the potential for reorganization following injury, and the development of cortical circuitry for reading. Additionally, Wandell develops software tools for digital imaging applications, including methods for analyzing MRI data and designing cameras for various applications such as consumer photography, medical imaging, and artificial intelligence in automotive contexts. His work has led to commercial ventures, including co-founding companies like Imageval, LLC, and Flywheel.io, LLC. Wandell founded and directed Stanford's Center for Cognitive and Neurobiological Imaging from 2008 to 2023 and served as deputy director of the Wu Tsai Neurosciences Institute from 2013 to 2021.

Research topics

• Artificial Intelligence
• Data Mining
• Computer Science
• Psychology
• Neuroscience
• Programming language
• Psychiatry
• Software engineering
• Clinical psychology
• Cognitive psychology
• Theoretical computer science

Selected publications

• The Brain Imaging Data Structure (BIDS) Specification

  Zenodo (CERN European Organization for Nuclear Research) · 2026-02-10

  otherOpen access

  The Brain Imaging Data Structure (BIDS) is a simple and intuitive way to organize and describe data.

  PublisherDOI

• An image-computable spatio-chromatic receptive field model of the midget retinal ganglion cell mosaic across the retina

  Journal of Computational Neuroscience · 2026-04-01

  articleOpen access

  Image-computable models of primate retinal ganglion cell (RGC) mosaics that are synthesized and constrained jointly by optical, anatomical and physiological properties, and which operate on images defined by their spatial-spectral radiance, do not currently exist. Here, we deploy a novel computational framework which synthesizes mosaics of linear spatio-chromatic receptive fields (RFs) of ON midget RGCs (mRGCs) by integrating published anatomical, physiological, and optical quality measurements, all varying with eccentricity. We use the synthesized mRGC mosaics to simulate both in vivo and in vitro physiological experiments and demonstrate the model’s 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.

  PublisherDOI

• ISETHDR: A Physics-Based Synthetic Radiance Dataset for High Dynamic Range Driving Scenes

  IEEE Sensors Journal · 2025-03-17

  articleSenior author

  This article presents a physics-based simulation that models the complete imaging pipeline from scene radiance to the final rendered image. We use this simulation to evaluate sensor designs optimized for high dynamic range (HDR) environments, such as driving through daytime tunnels or in nighttime conditions. The work makes three main contributions: 1) a synthetic, labeled dataset of HDR driving scenes with instance segmentation and depth information; 2) open-source simulation software with validated performance; and 3) a comparative analysis of two single-shot sensor designs optimized for HDR imaging. Both the dataset [(ISETHDR)] and simulation software (ISETHDRSensor) are made publicly available and can be used to evaluate sensor designs for HDR environments, such as nighttime driving scenes.

  PublisherDOI

• Modeling Spectroradiometric Measurements of Oral Mucosal Autofluorescence

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-06-25

  preprintOpen accessSenior author

  Abstract 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.

  PublisherOA PDFDOI

• Invited Session I: Focusing on the Human Fovea: Plasticity and stability in human foveal pathways

  Journal of Vision · 2025-04-01

  reviewOpen access

  The fovea is highly specialised in the human retina both structurally and functionally. Although it occupies a small fraction of the retina, a great deal of neural territory is devoted to processing its outputs downstream. What happens to these pathways when the fovea is compromised, and individuals rely more on peripheral vision? Examining structure and function in several different special populations, we will describe how human foveal pathways respond to changes in input both early and later in development.

  PublisherDOI

• An image-computable spatio-chromatic receptive field model of the midget retinal ganglion mosaic across the retina

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-10-20

  preprint

  Abstract 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 model’s 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.

  PublisherDOI

• Modeling spectroradiometric measurements of oral mucosal tissue autofluorescence

  Biomedical Optics Express · 2025-12-04

  articleOpen accessSenior author

  Spectroradiometric fluorescence measurements were collected from the dorsal tongue and inner lip of healthy volunteers. These sites were chosen to represent the distinct spectral features that differentiate keratinized from non-keratinized oral tissues, as documented in previous studies. A computational model was then applied to estimate the relative contributions of key fluorophores and to quantify the influence of blood absorption on the observed fluorescence spectra. The resulting dataset and model, both freely available, serve as reference standards for healthy oral tissue and support the development of quantitative, non-invasive imaging systems for consistent and reproducible assessment of oral mucosal health.

  PublisherDOI

• Population Receptive Field Modeling: Methods, Challenges, and Insights

  Journal of Vision · 2025-07-15

  articleOpen access

  Population receptive field (pRF) modeling is a quantitative technique for characterizing neural responses to visual stimuli. It is most commonly used to measure the spatial sensitivity (position and spatial extent in the visual field) of neural populations. Recent advances have significantly expanded its applications and accessibility: pRF solutions across many voxels can now used by deep neural networks to automate segmentation of visual areas; some pRF models are now used to estimate temporal or spatiotemporal tuning; and pRFs are used in clinical applications to track patient disease progression and monitor treatment. These developments make pRF modeling more powerful and accessible than ever before, but also highlight the need for collaborative efforts to establish standards and quality checks, and to share expertise. In this work, we introduce an open collaborative initiative concerning methods for pRF modeling. The goals of the initiative are to examine key aspects of pRF analysis, from data acquisition to model fitting, and suggest how methodological choices influence pRF estimates. We identify challenges to common implementation and interpretation and propose solutions based on collective experience. For non-pRF users, we aim to provide accessible explanations of the method, along with suggested guidelines and potential applications. For current pRF users, we discuss practical challenges that may arise during implementation and suggest strategies to address these issues. For method developers, we highlight areas that need improvement and propose possible directions for future research and validation of models. We will present our initiative's current progress, discuss our planned publication, and invite interested practitioners to collaborate with the group.

  PublisherDOI

• Midget retinal ganglion cell surrounds in macaque: cone-selective or not?

  Journal of Vision · 2024-09-15 · 3 citations

  articleOpen access

  Despite decades-long study of macaque midget retinal ganglion cells (mRGC), significant knowledge gaps exist regarding their receptive field (RF) properties. One example is the controversy regarding cone pooling in mRGC surrounds. Anatomy and in-vitro physiology, the latter in peripheral retina, indicate that L- and M-cones contribute non-selectively to mRGC RF surrounds, whereas in-vivo physiology in more central retina indicates that the RF surrounds are highly cone-type selective. To better understand the mRGCs, we developed a model of their linear spatiochromatic RFs. We model the cone inputs to the mRGCs based on anatomical and physiological data, taking into account the impact of physiological optics. Knowledge of these factors allows us to model the mRGC RFs across a large part of the visual field. We use the model to compute responses of synthetic mRGCs to cone-isolating grating and m-sequence stimuli, matched to those that have been employed by in-vivo physiological studies. Simulation enables us to compute the expected in-vivo responses for mRGCs with different surround L- to M-cone ratios. We perform the simulations over a range of eccentricities, taking into account the eccentricity dependence of the physiological optics, the cone fundamentals used to derive cone-isolating stimuli, and the mRGC RF structure. Our results reveal that near the fovea, where centers receive one or two cone inputs, physiological optics significantly enlarges the stimulus-referred RF center, thereby attenuating the antagonistic responses from surround-cones of the same type as the center cone. For this reason, the surround measured in vivo can appear heavily biased toward selective pooling of cones of the non-center cone type. In particular, this happens for models in which the simulated RF surrounds draw indiscriminately on L- and M-cones. This phenomenon, which we observed with both m-sequence and drifting grating simulations, provides a plausible explanation for the discrepancy in conclusions across studies.

  PublisherDOI

• Comparing pRF Mapping Estimates for Words and Checker Patterns

  Journal of Vision · 2024-09-15

  articleOpen access

  Functional MRI responses from voxels in the visual cortex are driven by stimuli within restricted regions of the visual field, their so-called population receptive fields (pRF). The central position and size of every voxel’s receptive field can be quantified using pRF mapping. In a previous report, we measured the pRF centers of individual voxels using words and contrast-reversing checker patterns shown within the stimulation area. The pRF centers measured with words differed from those measured with checkers. Voxels with a pRF center in the near periphery (5-10 degrees visual angle from the fixation) are more eccentric (1-3 degrees) when measured with checkers compared to words. To gain a deeper understanding of these effects, we acquired new datasets that differed significantly from the previous data. These variations included using different MRI scanners, fields of view, and acquisition sequences with either high-temporal or high-spatial resolution. Additionally, we adapted the used stimuli (such as variations in bar width and speed, flickering frequency) and participant populations, including individuals with both uncorrected and corrected visual acuity. Data were analyzed using a highly reproducible containerized public analysis platform (prfprepare and prfanalyze-vista). Results confirm the main effect in higher visual areas (hV4, VO1, IPS0-1). Further, initial measurements suggest specific stimulus manipulations (including defocus) impact the size of the change in eccentricity. Moreover, these manipulations may have different impacts on the eccentricity shift measured in different visual field maps. These findings offer a compelling starting point to further investigate stimuli induced pRF differences.

  PublisherDOI

Recent grants

• NIH Grant P41RR009784

  NIH · $5.4M · 2015

• The Human Visual Pathways and Skilled Reading

  NSF · $681k · 2012–2016

• NIH Grant R01EY003164

  NIH · $5.7M · 2013

• NIH Grant R01EY015000

  NIH · $4.9M · 2014

Frequent coauthors

• Joyce Farrell

  Stanford University

  55 shared

• Garikoitz Lerma‐Usabiaga

  Basque Center on Cognition, Brain and Language

  52 shared

• Robert F. Dougherty

  47 shared

• Jonathan Winawer

  New York University

  38 shared

• David H. Brainard

  University of Pennsylvania

  37 shared

• Serge O. Dumoulin

  Vrije Universiteit Amsterdam

  30 shared

• Michal Ben‐Shachar

  28 shared

• Jason D. Yeatman

  26 shared

Education

• PhD, Social Sciences

  University of California, Irvine

  1977

Awards & honors

• Proctor Medal, Association for Research in Vision and Ophtha…
• George Miller Prize, Cognitive Neuroscience Society (2016)
• Oberdorfer Award, ARVO (2012)
• Member, American Academy of Arts and Sciences (2011)
• Electronic Imaging Scientist of the Year, SPIE/IS&T (2007)