Richard M Leahy

Director, Signal and Image Processing Institute

Professor of Electrical Engineering, Biomedical Engineering, and Radiology

Research Topics

  • Morphometric brain image analysis
  • MR-based modeling of structural and functional brain connectivity
  • Modeling brain activity and networks using EEG/MEG
  • Integration and analysis of multimodal brain data
  • Inverse problems with applications in biomedical image formation and analysis

Research Overview

My research is focused on exploring and developing new methods for the formation and analysis of brain images. The current focus in my lab is on problems related to mapping large-scale brain connectivity using electrophysiological measures (EEG, MEG and invasive recordings) as well as with diffusion and functional MRI. We collaborate with researchers in the clinical and cognitive neuroscience with the goal of developing and applying new computational approaches to exploring the human brain. Jointly with our long-term collaborators, we develop and distribute the BrainSuite software for analysis of MR images and the BrainStorm software for analysis of eletrophysiological recordings (MEG/EEG/ECoG/LFP).

Contact Information

Mailing Address Signal and Image Processing Institute
Department of Electrical Engineering
University of Southern California
3740 McClintock Ave, EEB400, MC 2564
Los Angeles, CA90089
Office Location EEB400
Office Phone (213) 740-4659
Lab Location RTH317
Lab Phone
Fax (213) 740-4651
Office Location EEB400



  • 1985 Ph.D. Electronic Engineering. University of Newcastle upon Tyne, England.
  • 1981 Electrical and Electronic Engineering, First Class Honors, University of Newcastle upon Tyne, Newcastle upon Tyne, England

Selected Publications

View a complete PubMed searchView a complete Google Scholar search
  • S Asharafulla, JP Haldar, AA Joshi, RM Leahy (2013) Canonical Granger Causality between Regions of Interest, Neuroimage, 83, 189–199.
  • S Aydore, D. Pantazis, RM Leahy (2013) A Note on the Phase Locking Value and its Properties, Neuroimage, 74:231-244.
  • JP  Haldar and RM Leahy, (2013) New linear transforms for data on a Fourier 2-sphere with applications to diffusion MRI, Neuroimage 71:233–247.
  • YT Chang, RM Leahy, D Pantazis (2012) Modularity-based graph partitioning using conditional expected models, Phys Rev E, 85(1): 016109. 
  • F Tadel, S Baillet, JC Mosher, D Pantazis, RM Leahy (2011) Brainstorm: A user-friendly application for MEG/EEG analysis, Computational Intelligence and Neuroscience, Vol. 2011, Article ID 879716.
  • D. Pantazis, A Joshi, J Jintao, DW  Shattuck, L. Bernstein, H Damasio, RM Leahy (2010) Comparison of landmark-based and automatic methods for the registration of the cortical surface, Neuroimage, 49(3):2479-2493.
  • A. Joshi, D.W. Shattuck, P.M. Thompson, R.M. Leahy (2007) Simultaneous Surface and Volumetric Brain Registration Using Harmonic Mappings, IEEE Trans. Med. Imag 26 (12): 1657-1669 
  • TE Nichols, J. Qi, E. Asma, RM Leahy (2002) Spatiotemporal Reconstruction of List Mode PET Data, IEEE Trans Med Imag., 21 (4): 396-404
  • S. Baillet, JC Mosher, RM Leahy (2001) Electromagnetic Brain Mapping, IEEE Signal Processing Magazine 18 (6): 14-30.
  • Z. Wu and R. Leahy (1993) An Optimal Graph Theoretic Approach To Data Clustering: Theory And Its Application To Image Segmentation, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 15(11): 1101-1113.