Ramesh Sridharan

Learn More
We present an analysis framework for large studies of multimodal clinical quality brain image collections. Processing and analysis of such datasets is challenging due to low resolution, poor contrast, mis-aligned images, and restricted field of view. We adapt existing registration and segmentation methods and build a computational pipeline for spatial(More)
We develop a method for unsupervised analysis of functional brain images that learns group-level patterns of functional response. Our algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary activation variable. At the next level, we define a prior over(More)
Functional MRI studies have uncovered a number of brain areas that demonstrate highly specific functional patterns. In the case of visual object recognition, small, focal regions have been characterized with selectivity for visual categories such as human faces. In this paper, we develop an algorithm that automatically learns patterns of functional(More)
We propose and demonstrate an inference algorithm for the automatic segmentation of cerebrovascular pathologies in clinical MR images of the brain. Identifying and differentiating pathologies is important for understanding the underlying mechanisms and clinical outcomes of cerebral ischemia. Manual delineation of separate pathologies is infeasible in large(More)
We present a model that describes the structure in the responses of different brain areas to a set of stimuli in terms of stimulus categories (clusters of stimuli) and functional units (clusters of voxels). We assume that voxels within a unit respond similarly to all stimuli from the same category, and design a nonparametric hierarchical model to capture(More)
Pattern reversal visual evoked potentials were studied in 21 patients with spinocerebellar ataxias among whom 6 had Friedreich's ataxia, 10 had hereditary spastic ataxia and 5 had spinocerebellar degeneration with slow eye movements (olivopontocerebellar degeneration). The VEP abnormalities found in 4 cases of Friedreich's ataxia and one with(More)
We present a semi-parametric generative model for predicting anatomy of a patient in subsequent scans following a single baseline image. Such predictive modeling promises to facilitate novel analyses in both voxel-level studies and longitudinal biomarker evaluation. We capture anatomical change through a combination of population-wide regression and a(More)
Pattern reversal visual evoked potentials (VEPs) elicited in four patients with ataxia telangiectasia revealed normal results in two and absent responses in two. The pathogenesis of the VEP abnormalities is discussed. It is surmised that the VEP changes reflect progressive degeneration of the nerve fibres in the anterior visual pathway, as in Friedreich's(More)