Showing papers by "Brian A. Wandell published in 2013"

Compressive spatial summation in human visual cortex

Abstract: Neurons within a small (a few cubic millimeters) region of visual cortex respond to stimuli within a restricted region of the visual field. Previous studies have characterized the population response of such neurons using a model that sums contrast linearly across the visual field. In this study, we tested linear spatial summation of population responses using blood oxygenation level-dependent (BOLD) functional MRI. We measured BOLD responses to a systematic set of contrast patterns and discovered systematic deviation from linearity: the data are more accurately explained by a model in which a compressive static nonlinearity is applied after linear spatial summation. We found that the nonlinearity is present in early visual areas (e.g., V1, V2) and grows more pronounced in relatively anterior extrastriate areas (e.g., LO-2, VO-2). We then analyzed the effect of compressive spatial summation in terms of changes in the position and size of a viewed object. Compressive spatial summation is consistent with tolerance to changes in position and size, an important characteristic of object representation.

Quantifying the local tissue volume and composition in individual brains with magnetic resonance imaging.

Abstract: Here, we describe a quantitative neuroimaging method to estimate the macromolecular tissue volume (MTV), a fundamental measure of brain anatomy. By making measurements over a range of field strengths and scan parameters, we tested the key assumptions and the robustness of the method. The measurements confirm that a consistent quantitative estimate of MTV can be obtained across a range of scanners. MTV estimates are sufficiently precise to enable a comparison between data obtained from an individual subject with control population data. We describe two applications. First, we show that MTV estimates can be combined with T1 and diffusion measurements to augment our understanding of the tissue properties. Second, we show that MTV provides a sensitive measure of disease status in individual patients with multiple sclerosis. The MTV maps are obtained using short clinically appropriate scans that can reveal how tissue changes influence behavior and cognition.

GLMdenoise: a fast, automated technique for denoising task-based fMRI data.

Abstract: In task-based functional magnetic resonance imaging (fMRI), researchers seek to measure fMRI signals related to a given task or condition. In many circumstances, measuring this signal of interest is limited by noise. In this study, we present GLMdenoise, a technique that improves signal-to-noise ratio (SNR) by entering noise regressors into a general linear model (GLM) analysis of fMRI data. The noise regressors are derived by conducting an initial model fit to determine voxels unrelated to the experimental paradigm, performing principal components analysis (PCA) on the time-series of these voxels, and using cross-validation to select the optimal number of principal components to use as noise regressors. Due to the use of data resampling, GLMdenoise requires and is best suited for datasets involving multiple runs (where conditions repeat across runs). We show that GLMdenoise consistently improves cross-validation accuracy of GLM estimates on a variety of event-related experimental datasets and is accompanied by substantial gains in SNR. To promote practical application of methods, we provide MATLAB code implementing GLMdenoise. Furthermore, to help compare GLMdenoise to other denoising methods, we present the Denoise Benchmark (DNB), a public database and architecture for evaluating denoising methods. The DNB consists of the datasets described in this paper, a code framework that enables automatic evaluation of a denoising method, and implementations of several denoising methods, including GLMdenoise, the use of motion parameters as noise regressors, ICA-based denoising, and RETROICOR/RVHRCOR. Using the DNB, we find that GLMdenoise performs best out of all of the denoising methods we tested.

A two-stage cascade model of BOLD responses in human visual cortex.

Abstract: Visual neuroscientists have discovered fundamental properties of neural representation through careful analysis of responses to controlled stimuli. Typically, different properties are studied and modeled separately. To integrate our knowledge, it is necessary to build general models that begin with an input image and predict responses to a wide range of stimuli. In this study, we develop a model that accepts an arbitrary band-pass grayscale image as input and predicts blood oxygenation level dependent (BOLD) responses in early visual cortex as output. The model has a cascade architecture, consisting of two stages of linear and nonlinear operations. The first stage involves well-established computations—local oriented filters and divisive normalization—whereas the second stage involves novel computations—compressive spatial summation (a form of normalization) and a variance-like nonlinearity that generates selectivity for second-order contrast. The parameters of the model, which are estimated from BOLD data, vary systematically across visual field maps: compared to primary visual cortex, extrastriate maps generally have larger receptive field size, stronger levels of normalization, and increased selectivity for second-order contrast. Our results provide insight into how stimuli are encoded and transformed in successive stages of visual processing.

Human trichromacy revisited

Abstract: The presence of a photopigment (melanopsin) within certain retinal ganglion cells was a surprising and significant discovery. This pigment is routinely described as “nonvisual” to highlight its signaling role in pupil dilation and circadian rhythms. Here we asked whether light absorbed by melanopsin can be seen by healthy human subjects. To answer this requires delivering intense (above rod saturation), well-controlled lights using four independent primaries. We collected detection thresholds to many four-primary stimuli. Threshold measurements in the fovea are explained by trichromatic theory, with no need to invoke a fourth photopigment. In the periphery, where melanopsin is present, threshold measurements deviate from trichromatic theory; at high photopic levels, sensitivity is explained by absorptions in four, not three, photopigment classes. We consider a series of hypotheses to explain the tetrasensitivity at high photopic levels in the human peripheral field. The most likely hypothesis is that in healthy human subjects melanopsin absorptions influence visibility.

Diffusion-tensor properties along major white-matter fiber tracts in typically developing children between 2 and 5 years old.

Abstract: White-matter bundles consist of thousands of axons entering and exiting at various points to reach specific targets. Using a single diffusion parameter for the entirety of a tract may obscure potentially informative information. We quantified diffusion parameters along the length of the tract and describe localized tract differences, comparing properties between hemispheres and gender, as well as analyzing the influence of age.