Director, Mary and Mark Stevens Neuroimaging and Informatics Institute
Director, Laboratory of Neuro Imaging
Provost Professor of Ophthalmology, Neurology, Psychiatry and the Behavioral Sciences, Radiology, and Engineering
Ghada Irani Chair in Neuroscience
Dr. Toga’s research focuses on neuroimaging, informatics, mapping brain structure and function, and brain atlasing. He has developed multimodal imaging and data aggregation strategies and applied them in a variety of neurological diseases and psychiatric disorders, including neurodegenerative diseases, neurovascular diseases, and ocular diseases. His work in informatics includes the development and implementation of some of the largest and most widely used databases and data mining tools linking disparate data from genetics, imaging, clinical, and behavioral studies, and supporting global efforts in Alzheimer’s disease, Huntington’s Disease, and Parkinson’s Disease. His work also involves measurement of the dynamic brain during development and aging, and as a result of insult.
Learn more about Dr. Toga’s research.
Ph.D. in Neuroscience, St. Louis University
M.S. in Neuroscience, St. Louis University
B.S. in Psychology, University of Massachusetts
2016 - present: Ghada Irani Chair in Neuroscience
2013 - present: Provost Professor, Departments of Ophthalmology, Neurology, Psychiatry, and the Behavioral Sciences, Radiology and Engineering at the Keck School of Medicine of USC
2013 - present: Director, USC Mark and Mary Stevens Neuroimaging and Informatics Institute
2013 - present: Director, USC Laboratory of Neuro Imaging
2010 - 2012: Associate Vice Provost of Informatics, University of California, Los Angeles
2010 - 2013: Associate Dean, David Geffen School of Medicine, University of California, Los Angeles
1993 - 2010: Professor, Department of Neurology, University of California, Los Angeles
1993 - 2013: Associate Director, Division of Brain Mapping, Neuropsychiatric Institute, University of California, Los Angeles
1987 - 2013: Director, Laboratory of Neuro Imaging, Department of Neurology, University of California, Los Angeles
Dr. Ard aims to improve scientists’ understanding of neuroscientific data through novel visualizations, enabling human insight into highly complex datasets. Before joining LONI, he worked with USC’s Institute for Creative Technologies (ICT), where he mastered Virtual Reality techniques which he now applies to neuroimaging data.
2013 – Ph.D. in Neuroscience, Brown University
2006 – B.A. in Psychology, University of Colorado Boulder
Dr. Bienkowski’s research focuses on the relationship between anatomy, genetics, and function within brain regions involved in memory and emotion. His scientific goals are to identify the structural organization of neural networks, then dissect the functional role of specific network circuits to understand how the circuits cooperate to produce animal behavior.
2012 – Ph.D. in Neuroscience, University of Pittsburgh
2007 – B.S. in Neuroscience, University of Pittsburgh
Dr. Braskie’s research evaluates how genetic and environmental risk factors for Alzheimer’s Disease (AD) relate to brain structure, function, and connectivity throughout adulthood, with an emphasis on metabolic risk. She primarily studies cognitively intact adults and those with early mild cognitive impairment, studying how AD risk-related biological mechanisms and signaling pathways are associated with brain changes, using relevant blood and cerebrospinal fluid measures, as well as multimodal imaging (structural and functional MRI, diffusion tensor imaging, and PET).
2006 – Ph.D. in Neuroscience, UCLA
1994 – B.A. in Business Administration and Accounting, College of William and Mary
2013- present: Assistant Professor of Research USC
2011 -2013: Assistant Researcher UCLA
2009 - 2011: Post doctoral fellow UCLA
2006 -2009: Post doctoral fellow UC Berkeley
2002-2006: Graduate student researcher UCLA
2003-Teaching assistant to Dr. Arnold Scheibel UCLA
Dr. Dong’s primary focus is the Mouse Connectome Project (MCP), which seeks to reconstruct a 3D computer graphic mouse brain atlas and neuroinformatics-based database. He also uses a multimodal approach to distinguish and classify various neuronal cell types in the mammalian brain. A separate focus involves the understanding of neural circuits and molecular mechanisms that regulate the neuroendocrine responses underlying psychological stress.
1999 - Ph.D., the Fourth Military Medical University (Xi’an, China) and University of Southern California, (Neuroscience)
1996 - M.S., the Fourth Military Medical University (Xi’an, China), (Neuroscience)
1993 - M.D., the Fourth Military Medical University (Xi’an, China), (Medicine)
2006 - Present Assistant Professor, Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine
2004 - 2006 Senior Analyst Neuroanatomy, Allen Institute for Brain Science (AIBS), Seattle
2002 - 2003 Research Assistant Professor, Neuroscience Program & Department of Biology, University of Southern California (USC)
1997 - 2002 Postdoctoral Fellow, Research Associate, Laboratory of L.W. Swanson, Neuroscience Program, University of Southern California
Small animal stereotaxic brain surgery
Neural tract tracing
Brain atlas development
Dr. Duncan’s expertise lies in the development of analytical tools to extract information from biomedical data. Both her Ph.D. and postdoctoral research used EEG data to isolate patterns indicating the onset of epileptic seizures. She has worked on developing algorithms, such as Unsupervised Diffusion Component Analysis, to identify early signs of Alzheimer's disease in patients using structural MRI data. Her recent projects include identifying biomarkers to predict epilepsy following a traumatic brain injury and using Virtual Reality to improve segmentation, a manual error-correction process required to analyze brain imaging data.
2013 - PhD in Electrical Engineering, Yale University
2007 - BS in Mathematics and Polish Literature, University of Chicago
Dr. Hintiryan has extensive experience examining the brain’s neural networks using classic and viral tract tracers. She uses large-scale connectomics data to investigate information processing within specific neural circuits. Her current research focus involves identifying aberrant connections in mouse models of neurological disorders such as Alzheimer’s Disease via the Mouse Connectome Project.
2009 – Ph.D. in Psychology and Behavioral Neuroscience, USC
2003 – M.A. in Psychology and Behavioral Neuroscience, USC
2000 – B.A. in Psychology and English, USC
Dr. Jahanshad is part of INI’s Imaging Genetics Center, where she researches genetic influences on brain structure using high-resolution structural and diffusion imaging. She also develops protocols for large-scale meta-analyses of brain structure and connectivity for the ENIGMA consortium. Her work with diffusion imaging involves monitoring the effects of infectious diseases, such as HIV, on the brain.
2012 – Ph.D. in Biomedical Engineering, UCLA
2006 – B.A. in Biomedical and Electrical Engineering
Dr. Jann develops analytical tools and clinical translations of functional MRI technology. He studies the relationship between functional connectivity, complexity and metabolism of brain networks. His multimodal approach involves a combination of fMRI, connectivity measures, cerebral blood flow, Transcranial Magnetic Stimulation (TMS) excitation and inhibition, and Magnetic Resonance Spectroscopy (MRS). He is also exploring the use of neuromodulation, such as TMS, in the treatment of various neuropsychiatric disorders.
2009 – Ph.D. in the Faculties of Medicine, Science and Veterinary Medicine, University of Bern (Switzerland)
2004 – Dipl. Sc. Nat. in Biology (Neuroscience focus), Swiss Federal Institute of Technology
2016, Assistant Project Scientist at the Laboratory of Functional MRI Technology, Ahmanson-Lovelace Brain Mapping Center, UCLA
2016, Postdoctoral researcher at the Laboratory of Functional MRI Technology, Ahmanson-Lovelace Brain Mapping Center, UCLA
2010 -2013, Postdoctoral researcher at the Department of Psychiatric Neurophysiology, University Hospital of Psychiatry, University of Bern, Switzerland
2009-2010, Research assistant at the Department of Psychiatric Neurophysiology, University Hospital of Psychiatry, University of Bern, Switzerland
Dr. Kim’s research spans an interdisciplinary cross-section of medical image processing, machine learning and neuroscience, covering both clinical neurology and neuropsychiatry. He studies multicontrast image registration and segmentation as well as surface modeling of both cortical and subcortical structures. One of his current projects involves the prediction of neurodevelopmental outcomes for preterm babies. He is also developing an online neuroimaging data quality control (image QC) system.
2016- Postdoctoral Fellowship in Imaging of Neurodevelopment, UC San Francisco
2012 -PhD in Biomedical Engineering (specialty: brain image analysis), McGill University / Montreal Neurological Institute experience neuroimaging, image processing, machine learning, clinical neuroimaging (preterm newborns, sleep disorders, epilepsy)
2011 – Ph.D. in Biomedical Engineering, Montreal Neurological Institute, McGill University
2003-M.S. in Biomedical Engineering, Hanyang University (Seoul, Korea)
2000-B.S. in Mechanical Engineering, Hanyang Unversity (Seoul, Korea)
Assistant Professor of Neurology
Assistant Professor of Biokinesiology and Physical Therapy,
USC Chan Division of Occupational Science and Occupational Therapy.
Dr. Liew runs the Neural Plasticity and Neurorehabilitation Lab (NPNL) in the USC Chan Division of Occupational Science and Occupational Therapy. Her team aims to enhance neural plasticity in a wide population of individuals, especially those who have suffered severe strokes, exploring the applications of noninvasive brain stimulation, brain computer interfaces, neuroimaging, virtual reality, and behavioral techniques.
2012 – Ph.D. in Cognitive Neuroscience, USC
2008 – M.A. in Occupational Therapy, USC
2006 – B.A. in Kinesiology and English, Rice University
Dr. Neu’s research involves the management and visualization of neuroinformatics data. He develops numerical methods for image classification and feature extraction. At LONI, he is a key contributor to the Alzheimer’s Disease Neuroimaging Initiative (ADNI), the Global Alzheimer’s Association Interactive Network (GAAIN), the Parkinson’s Progression Markers Initiative (PPMI), and other projects.
1999 – M.S. in Computer Science, UCLA
1997 – Ph.D. in Physics, UCLA
1993 – M.S. in Physics, UCLA
1991 – B.S. in Physics and Mathematics, University of Wisconsin
UCLA Laboratory of Neuro-Imaging, 2002-2013
UCLA Department of Radiological Sciences, 1998-2002
Dr. Pa researches early brain dysfunction in older adults and individuals at risk for Alzheimer’s Disease with the goal of identifying biomarkers and designing effective interventions to slow or halt the onset of the disease. For example, she is working on several pilot projects combining physical and cognitive interventions in novel ways. She also analyzes neural alterations in brain function and network connectivity in individuals with mild cognitive impairment.
2007 - PhD in Psychology (specialty: Cognitive Neuroscience), UC Irvine
2002 – B.A. in Psychology, UC Irvine
Doctor of Medicine from University of California, Los Angeles
Ph.D. in Biomedical Engineering from University of California, Los Angeles
B.S. in Biomedical Engineering, Brown University
2018-2019: Fellowship, Neuroradiology, University of Southern California
2014-2018: Residency, Diagnostic Radiology, University of California, Los Angeles
2013-2014: Internship, Transitional Year, University of Hawaii
Interests involve mapping brain tissue macro and micro-structure using MRI, with the specific aim of obtaining micro-level neuroanatomical biomarkers. Also interested in studying microstructural alteration of brain tissue during development and aging.
Dr. Sepehrband uses MRI to map brain tissue macro- and micro-structure, with the specific aim of obtaining micro-level neuroanatomical biomarkers. He also studies the microstructural alteration of brain tissue during development and aging. Sepehrband also has extensive experience working with diffusion MRI and digital signal processing.
2015 – Ph.D. in Biotechnology and Neuroscience, University of Queensland (Australia)
2010 – M.S. in Digital Electronics, Sharif University of Technology (Iran)
Diffusion Magnetic Resonance Imaging
Brain tissue macro- and micro-structure mapping
Digital signal processing
My research focuses on the development of cutting-edge image analysis algorithms and their application in studying human brain structure and function.
Dr. Shi develops cutting-edge image analysis algorithms, which he applies to the study of human brain structure and function. He seeks to more accurately model the brain’s fibers in diffusion imaging using Fiber Orientation Distribution (FOD) reconstruction. He also studies anatomical shape modeling using the Laplace-Beltrami system, in order to create better brain mapping algorithms for use in researching Alzheimer’s Disease, retinopathies, and other disorders.
2005 – Ph.D. in Electrical Engineering, Boston University
1999 – M.S. in Electrical Engineering, Southeast University (Nanjing, China)
1996 – B.S. in Electrical Engineering, Southeast University (Nanjing, China)
Assistant Professor, Department of Neurology, UCLA School of Medicine, 2009-2013
PostDoctoral Fellow, Department of Neurology, UCLA School of Medicine, 2005-2009
Level set algorithms, inverse problems and regularization, statistical signal processing.
Associate Director, Mary and Mark Stevens Neuroimaging and Informatics Institute
Director, Imaging Genetics Center
Professor of Ophthalmology, Neurology, Psychiatry and the Behavioral Sciences, Radiology, Pediatrics and Engineering
Dr. Thompson’s primary focus is imaging genetics, the study of how individual genetic differences lead to differences in brain wiring, structure, and intellectual function. He co-founded a worldwide imaging genetics consortium, ENIGMA, which studies 22 brain diseases in 37 countries, and has published the largest-ever neuroimaging studies of schizophrenia, major depression, bipolar disorder, and obsessive-compulsive disorder. Other research pursuits include developing new computational algorithms for neuroimaging, dynamic (4D) brain mapping, creation of a probabilistic atlas of the human brain and cortex, and creation of population-based atlases for Alzheimer’s Disease, Schizophrenia, and other disorders. Learn more about Dr. Thompson’s research.
1998 – Ph.D. in Neuroscience, UCLA
1993 – M.A. in Mathematics and Philosophy, Oxford University
1991 – B.A. in Greek and Latin Languages, Oxford University
2010 – 2013: Professor of Neurology, Step 6; Professor of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, UCLA
2007 – 2013: Professor of Neurology, Step 2, David Geffen School of Medicine, UCLA
2003 – 2007: Associate Professor of Neurology, David Geffen School of Medicine, UCLA
1998 – 2003: Assistant Professor of Neurology, David Geffen School of Medicine, UCLA
1993 – 1998: Fellow, Howard Hughes Medical Institute
1993 – 1998: Research Grantee, United States Information Agency, Washington, DC
1993 – 1998: Fulbright Scholar, U.S.-U.K. Fulbright Commission, London, England
Associate Professor of Clinical Neurology
Director of Education, USC Mary and Mark Stevens Neuroimaging and Informatics Institute.
Dr. Van Horn directs the educational efforts of the institute, including the Neuro Imaging and Informatics (NIIN) master’s program and the Training Coordinating Center (TCC), sponsored by the NIH Big Data to Knowledge initiative. He also studies Traumatic Brain Injury, Autism Spectrum Disorder, and the anatomy and connectivity of the human claustrum. He has expertise with in vivo imaging techniques such as fMRI and diffusion tensor imaging (DTI), mathematical and engineering solutions for neuroimaging, and neuroinformatics, including neuroimaging databases and data mining.
2000 – M.S. in Engineering (Electrical and Computer), University of Maryland
1989-1992: Doctor of Philosophy, Experimental Psychology, Department of Psychology, University College London, University of London, Gower Street, London, WC1E 6BT England
1992 – Ph.D. in Experimental Psychology, University of London
1992-1997: IRTA Postdoctoral Research Fellow, Unit on Integrative Neuroimaging, National Institute of Mental Health, Building 10-4C108, 9000 Rockville Pike, Bethesda, MD 20892, and Clinical Brain Disorders Branch, NIMH, Neurosciences Center at
at St. Elizabeth's Hospital, 2700 Martin Luther King Jr. Avenue SE, Washington, D.C. 20032
1985-1989: Bachelor of Arts in Psychology, (67 Credit Major), Department of Psychology, Eastern Washington University, Cheney, WA 99004
2013-Present: Associate Professor of Neurology, Keck School of Medicine of USC, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, 2025 Zonal Avenue, SHN, Los Angeles, CA 90033; Courtesy appointments in the USC Neuroscience Graduate Program
(NGP) and in the Viterbi School of Engineering
2006-2013: Assistant Professor of Neurology, Department of Neurology, Laboratory of Neuro Imaging, University of California Los Angeles, David Geffen School of Medicine, 635 Charles Young Drive South, Suite 225, Los Angeles, California 90095-7334
2002-2006: Research Associate Professor, Psychology and Brain Science/Center for Cognitive Neuroscience, Dartmouth College, 6162 Moore Hall, Hanover, New Hampshire 03755
2002-2006: Assistant Director, Dartmouth Brain Imaging Center, Dartmouth College, 6162 Moore Hall, Hanover, New Hampshire 03755
2001-2006: Operations Director, The fMRI Data Center, 6162 Moore Hall, Hanover, New Hampshire 03755
2000-2002: Research Assistant Professor, Psychology and Brain Science/Center for Cognitive Neuroscience, Dartmouth College, 6162 Moore Hall, Hanover, New Hampshire 03755
1997-Present: Honorary Research Fellow, Department of Psychology, University College London, University of London, Gower Street, London, WC1E 6BT England
1997-2000: NIH Staff Fellow, Laboratory of Brain and Cognition, National Institute of Mental Health, 10 Center Drive 4C-104, Bethesda, MD 20892
1997-2000: Guest Researcher, Brain Imaging Center, National Institute of Drug Abuse, Johns Hopkins Bayview Campus, Baltimore, MD
Linux/UNIX (e.g. Sun OS/Solaris); ANSI-C; HTML/PHP; Matlab; MS Visual Studio.
Dr. Wang runs the Laboratory of Functional MRI Technology (LOFT), where he develops techniques and clinical translations of arterial spin labeling (ASL) and performs cross-scale and modality complexity analysis of resting state fMRI and electrophysiology data. He also researches electric current mapping of transcranial direct current stimulation (tCDS). Another current project involves the development of low-dose CT perfusion technology, which may help significantly reduce radiation exposure without compromising image quality.
2010 – M.S.C.E. (Master of Science in Clinical Epidemiology), University of Pennsylvania School of Medicine
1998 -Ph.D. University of Science and Technology of China, Beijing, China (Biophysics)
1993- B.S. Fu Dan University, Shanghai, China (Biophysics)
2012-present Executive Director, UCLA-Beijing Joint Center for Advanced Brain Imaging.
2015-2016 Professor-in-Residence (secondary), Department of Radiology, UCLA David Geffen School of Medicine.
2015-2016 Professor-in-Residence, Department of Neurology, UCLA David Geffen School of Medicine.
2011-2015 :Associate Professor-in-Residence (secondary), Department of Radiology, UCLA David Geffen School of Medicine.
2010-2015: Associate Professor-in-Residence, Department of Neurology, UCLA David Geffen School of Medicine.
2011-2013: Adjunct Associate Professor, Department of Radiology, University of Pennsylvania School of Medicine.
2006-2010 :Research Assistant Professor, Department of Neurology, University of Pennsylvania School of Medicine.
2003-2010 : Research Assistant Professor, Department of Radiology, University of Pennsylvania School of Medicine.
Dr. Yan’s work involves functional MRI data acquisition and post processing, as well as MRI sequence development, including novel arterial spin labeling (ASL) technical development and non-contrast 4D dynamic Magnetic Resonance Angiography. One of her primary research projects is the assessment of intracranial vascular compliance (VC) using ASL MRI techniques, and the study of how intracranial VC changes in the aging brain.
2010 – Ph.D. in Biophysics, Institute of Biophysics, Chinese Academy of Sciences
2005 – B.S. in Biomedical Engineering, Huazhong University of Science and Technology
2013-2016:Assistant Researcher, Department of Neurology, UCLA
2010-2013:Postdoctoral Scholar, Department of Neurology, UCLA
I'm interested in web development, big data, and system design.
B.S. in Computer Science, Kansai University Department of Computer Science, Osaka, Japan, 1997 - 2002
International Exchange Program, University of Hawaii at Manoa, Honolulu, Hawaii 2000 - 2001
2013 - Present, Programmer Analyst, Institute for Neuroimaging and Informatics, Keck School of Medicine of USC
2006 - 2013, Programmer Analyst, Laboratory of Neuro Imaging, UCLA David Geffen School of Medicine
2003 - 2006, System Engineer, Future Spirits Co., Ltd., Japan
2002-2003, IT Engineer, IBM Japan
Dr. Cabeen works on the development and evaluation of computational tools for modeling, visualizing, and analyzing neuroimaging datasets. His current research projects aim to improve our understanding of brain microstructure and connectivity using diffusion MR imaging. He is the creator and developer of the Quantitative Imaging Toolkit (QIT), a software platform for visualizing and analyzing neuroimaging datasets. Learn more at http://cabeen.io.
PhD in Computer Science from Brown University
MSc in Computer Science from Brown University
BSc in Engineering and Applied Science from the California Institute of Technology
Data analysis for neuroimaging, image processing, numerical optimization.
Study of changes in structural and functional connectivity of human brain due to visual impairment.
PhD., Nanyang Technological University, 2012
B.Eng in communication and information engineering and B. Sc in mathematics and applied mathematics, University of Electronic Science and Technology of China, 2007
Fast Heritability Estimation Method using Linear Mixed Model
Statistical Analysis of Brain Images
University of Southern California, PhD, Computational Biology and Bioinformatics, 2016 - present
Tsinghua University, BS, Mathematics, Probability and Statistics Track, 2012 - 2016
Research Assistant in Imaging Genetics Center, USC Stevens Neuroimaging and Informatics Institute
Research Assistant in Scientific Computing and Applied Statistics group, Department of Mathematical Sciences, Tsinghua University
Research Assistant in Brain Imaging lab, Department of Psychology, Tsinghua University
Computational neuroimaging analysis and the application to studies of neuroanatomy and brain connectivity networks and their relationship to development, aging and pathological conditions.
PhD, Signal Processing, Tampere University of Technology, Finland, 2010
MSc, Signal Processing and Communication, University of Edinburgh, UK, 2005
BSc, Electronics and Information Engineering, Harbin University of Science and Technology, China, 2004
Postdoctoral Research Fellow, Montreal Neurological Institute, McGill University, Canada, 2010-2015