Vince D. Calhoun, Ph.D.
Director, Image Analysis and MR Research,
The MIND Institute
Associate Professor, Dept. of Electrical and Computer Engineering, University of New Mexico
Associate Professor, Adjunct, Dept. of Psychiatry, Yale University
The MIND Institute
1101 Yale Boulevard
Albuquerque, NM 87131
Tel: (505) 272-1817, Fax: (505) 272-8002
Dr. Vince D. Calhoun, Ph.D. (vcalhoun@unm.edu) , Director of Image Analysis of MR Research, at The MIND Institute develops techniques for making sense of complex brain imaging data. Because each imaging modality has limitations, the integration of these data is needed to understand the healthy and especially the disordered human brain. Dr. Calhoun has created algorithms which map dynamic networks of brain function, structure, and genetics and how these are impacted while being stimulated by various tasks or in individuals with mental illness such as schizophrenia.
COURSES:
Analysis Methods
in Functional Magnetic Resonance Imaging
(Spring 2007)
Medical Imaging (Fall 2007)
Probabilistic
Methods in Engineering (Spring 2008)
LAB MEMBERS:
Postdoctoral Fellows:
- Jingyu (Jean) Liu (jliu@themindinstitute.org)
- Oguz Demirci (odemirci@themindinstitute.org)
- Madiha Jafri (mjafri@harthosp.org)
Research Assistants:
- Dae il Kim (seoulbrother@gmail.com)
- Diana Krenz (dkrenz@unm.edu)
Software Engineers:
- Srinivas Rachakonda (srachakonda@themindinstitute.org)
- Jill Fries (jfries@themindinstitute.org)
- Martin Jordan (mjordan@themindinstitute.org)
Students:
- Lai Xu (laixu@unm.edu)
- Lei Wu (wulei@ece.unm.edu)
Visiting Scholar:
- Quihua Lin (qhlin@dlut.edu.cn)
Outside Collaborators:
- Tulay Adali, Ph.D. (http://www.csee.umbc.edu/~adali/) (http://mlsp.umbc.edu/)
- Li (Leo) Yiou, PhD. Student
- Nicole Correa, PhD. Student
- Jim Pekar
- Godfrey Pearlson
- Michael Stevens
- Tom Eichele
- Matthias Moosman
- Pat Barta
AVAILABLE SOFTWARE:
Group ICA of fMRI Toolbox (GIFT) and Fusion ICA Toolbox (FIT)
GIFT is a Matlab toolbox which implements multiple algorithms for independent component analysis and blind source separation of group
(and single subject) functional magnetic resonance imaging data. FIT is a Matlab toolbox which implements data fusion approach using independent component analysis. It is used to examine the shared information between the features (SPM contrast image, EEG data).