Showing papers by "Brian A. Wandell published in 2012"

Tract Profiles of White Matter Properties: Automating Fiber-Tract Quantification

Abstract: Tractography based on diffusion weighted imaging (DWI) data is a method for identifying the major white matter fascicles (tracts) in the living human brain. The health of these tracts is an important factor underlying many cognitive and neurological disorders. In vivo, tissue properties may vary systematically along each tract for several reasons: different populations of axons enter and exit the tract, and disease can strike at local positions within the tract. Hence quantifying and understanding diffusion measures along each fiber tract (Tract Profile) may reveal new insights into white matter development, function, and disease that are not obvious from mean measures of that tract. We demonstrate several novel findings related to Tract Profiles in the brains of typically developing children and children at risk for white matter injury secondary to preterm birth. First, fractional anisotropy (FA) values vary substantially within a tract but the Tract FA Profile is consistent across subjects. Thus, Tract Profiles contain far more information than mean diffusion measures. Second, developmental changes in FA occur at specific positions within the Tract Profile, rather than along the entire tract. Third, Tract Profiles can be used to compare white matter properties of individual patients to standardized Tract Profiles of a healthy population to elucidate unique features of that patient's clinical condition. Fourth, Tract Profiles can be used to evaluate the association between white matter properties and behavioral outcomes. Specifically, in the preterm group reading ability is positively correlated with FA measured at specific locations on the left arcuate and left superior longitudinal fasciculus and the magnitude of the correlation varies significantly along the Tract Profiles. We introduce open source software for automated fiber-tract quantification (AFQ) that measures Tract Profiles of MRI parameters for 18 white matter tracts. With further validation, AFQ Tract Profiles have potential for informing clinical management and decision-making.

Development of white matter and reading skills

Abstract: White matter tissue properties are highly correlated with reading proficiency; we would like to have a model that relates the dynamics of an individual’s white matter development to their acquisition of skilled reading. The development of cerebral white matter involves multiple biological processes, and the balance between these processes differs between individuals. Cross-sectional measures of white matter mask the interplay between these processes and their connection to an individual’s cognitive development. Hence, we performed a longitudinal study to measure white-matter development (diffusion-weighted imaging) and reading development (behavioral testing) in individual children (age 7–15 y). The pattern of white-matter development differed significantly among children. In the left arcuate and left inferior longitudinal fasciculus, children with above-average reading skills initially had low fractional anisotropy (FA) that increased over the 3-y period, whereas children with below-average reading skills had higher initial FA that declined over time. We describe a dual-process model of white matter development comprising biological processes with opposing effects on FA, such as axonal myelination and pruning, to explain the pattern of results.

Learning to see words.

Abstract: Skilled reading requires recognizing written words rapidly; functional neuroimaging research has clarified how the written word initiates a series of responses in visual cortex. These responses are communicated to circuits in ventral occipitotemporal (VOT) cortex that learn to identify words rapidly. Structural neuroimaging has further clarified aspects of the white matter pathways that communicate reading signals between VOT and language systems. We review this circuitry, its development, and its deficiencies in poor readers. This review emphasizes data that measure the cortical responses and white matter pathways in individual subjects rather than group differences. Such methods have the potential to clarify why a child has difficulty learning to read and to offer guidance about the interventions that may be useful for that child.

Digital camera simulation.

Abstract: We describe a simulation of the complete image processing pipeline of a digital camera, beginning with a radiometric description of the scene captured by the camera and ending with a radiometric description of the image rendered on a display. We show that there is a good correspondence between measured and simulated sensor performance. Through the use of simulation, we can quantify the effects of individual digital camera components on system performance and image quality. This computational approach can be helpful for both camera design and image quality assessment.

Position sensitivity in the visual word form area

Abstract: Seeing words involves the activity of neural circuitry within a small region in human ventral temporal cortex known as the visual word form area (VWFA). It is widely asserted that VWFA responses, which are essential for skilled reading, do not depend on the visual field position of the writing (position invariant). Such position invariance supports the hypothesis that the VWFA analyzes word forms at an abstract level, far removed from specific stimulus features. Using functional MRI pattern-classification techniques, we show that position information is encoded in the spatial pattern of VWFA responses. A right-hemisphere homolog (rVWFA) shows similarly position-sensitive responses. Furthermore, electrophysiological recordings in the human brain show position-sensitive VWFA response latencies. These findings show that position-sensitive information is present in the neural circuitry that conveys visual word form information to language areas. The presence of position sensitivity in the VWFA has implications for how word forms might be learned and stored within the reading circuitry.

Learning of image processing pipeline for digital imaging devices

Abstract: A learning technique is provided that learns how to process images by exploiting the spatial and spectral correlations inherent in image data to process and enhance images. Using a training set of input and desired output images, regression coefficients are learned that are optimal for a predefined estimation function that estimates the values at a pixel of the desired output image using a collection of similarly located pixels in the input image. Application of the learned regression coefficients is fast, robust to noise, adapts to the particulars of a dataset, and generalizes to a large variety of applications. The invention enables the use of image sensors with novel color filter array designs that offer expanded capabilities beyond existing sensors and take advantage of typical high pixel counts.

Methods for detecting abnormalities and degenerative processes in soft tissue using magnetic resonance imaging (MRI)

Abstract: The present invention provides methods to detect degenerative processes and abnormalities in soft tissues at high spatial resolution, high signal-to-noise ratio and short scanning times, based on quantitative tissue properties. These methods might provide a useful tool to detect and assess abnormalities in soft tissues and to monitor disease progression.

Squaring cortex with color

Abstract: A long-standing puzzle has been the seeming inconsistency between neuronal responses in primary visual cortex to colored stimuli and the elementary perceptual attributes of color vision. Nonlinear analysis resolves this paradox.