Neha Reddy

This study maps whole-brain motor activity during shoulder abduction tasks using fMRI, showing subject-specific activation patterns and consistent amplitude across regions.

This study compares ME-ICA denoising approaches in motor-task fMRI, finding that a conservative method better preserves task-related signal while reducing noise in high-motion scenarios.

This study evaluates statistical methods for analyzing whole-brain task-based fMRI data, finding that a whole-brain voxel-level approach with FDR correction offers highest sensitivity and consistency.

The paper shows that task instructions modulate stretch-evoked motor responses in the human brainstem, as evidenced by changes in reticulospinal activation during fMRI.

This paper applies multi-echo fMRI and precision mapping to identify auditory activation patterns at both group and individual levels.

This study examines the BOLD response in ipsilateral primary somatosensory cortex to tactile stimuli, finding biphasic responses in BA1 and BA3b with the secondary phase being more sensitive to stimulus force.

This paper develops methods to estimate cerebrovascular reactivity (CVR) amplitude and delay in breath-hold fMRI when PETCO2 data quality is low, using rescaled RVT and deep learning-predicted PETCO2.

This study maps sensory activation across the cortex, subcortex, and brainstem using whole-brain fMRI, showing distinct responses to hand and foot stimulation and differentiating small brainstem nuclei.

This study evaluates ME-ICA's effectiveness in reducing task-correlated head motion artifacts in motor-task fMRI data, showing improved signal clarity and stability in both subject and group analyses.