Anand A. Joshi

sEEG-Suite provides a semi-automated pipeline for sEEG contact localization and anatomical labeling within Brainstorm, improving accuracy and efficiency in epileptic network mapping.

This paper introduces tools to optimize electrode placement and maximize information capacity for local field potentials in the cortex using subject-specific modeling.

This study uses MRI-based features and machine learning to predict post-traumatic epilepsy, achieving 0.78 AUC accuracy with a kernel support vector machine.

The paper introduces BrainSuite BIDS App, a containerized workflow for MRI analysis that supports structural, diffusion, and functional data processing using standardized BIDS formats.

BundleCleaner denoises and subsamples diffusion MRI tractography data, improving alignment with atlas bundles and enabling efficient tractometry analysis in Alzheimer's disease studies.

The paper presents a high-resolution MRI atlas with two parcellation schemes, using structural and functional data to improve cortical sub-parcellation.