Richard M. Leahy

This study demonstrates that directional microelectrode arrays improve seizure detection and spatial localization compared to traditional ring electrodes in a rat model.

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

Untamed improves cortical parcellation by combining tensor decomposition and graph node embedding, producing spatially coherent regions aligned with functional networks.

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 investigates how brain rhythms track speech fundamental frequency (F0) across different speech rates using magnetoencephalography, finding coupling in auditory and somatomotor regions.

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.

This study finds that the optimal regularization parameter for MEG connectivity estimation is smaller than that for source imaging and provides open-source code for analysis.

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

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

This study examines age-related changes in brain functional architecture using multi-scale fMRI analyses in younger and older adults, finding both global and network-specific dedifferentiation patterns.

This paper introduces a functional network atlas of the human brain using rs-fMRI data, identifying 23 networks that are spatially overlapped and temporally correlated, and shows their association with ADHD.

The paper introduces an open-source software suite for analyzing and managing invasive neurophysiology data, enhancing reproducibility and transparency in electrophysiology research.