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Clinical Neuroscience and Computational Anatomy unit
The long-term goal of this unit is to understand psychiatric disorders, with an eye toward identifying means for correcting those disorders or minimizing their consequences. Furthermore, work carried out in this unit will promote development of computational and mathematical tools for handling neuroimaging data analyses which, in turn, will contribute to integrative evaluation of functional, structural and biochemical aspects of the brain, both disordered and healthy. This unit, led by Jun Soo Kwon, consists of two subunits. The ‘Clinical Neuroscience’ subunit, comprising Jun Soo Kwon and Sohee
Park, will focus on studies of the pathophysiology of mental/brain disorders, including schizophrenia, depression, bipolar disorder and obsessive-compulsive disorder, they will deploy an integrative set of neurometric (large-scale brain imaging techniques on human brains) and psychometric (various forms of high cognitive tasks) measurement tools. The ‘Computational Anatomy’ subunit, led by the collaboration between Jae Sung Lee and Moo K. Chung, will integrate neurometric data obtained from functional (fMRI, PET) and structural (DTI, MRI) images - major large-scale neurometric data from humans in modern cognitive neuroscience - into a single, coherent processing and analysis framework. The successful development of such tools will substantially help the other units to advance understanding of cortical and subcortical circuitries crucial for the target cognitive functions.
Jun Soo Kwon, MD, PhD, Dept. of Psychiatry, SNU Homepage
Jun Soo Kwon
- An expert in pathophysiology in the neuropsychiatric disorders such as schizophrenia and obsessive-compulsive disorder.
- Extensive publications in journals such as Arch Gen Psychiatry and Brain etc. marking over 80 score of the total impact factor during the last three years.
- Elected to be councilor in Collegium Internationale Neuro-Psychopharmacologicum (CINP) first in Korea
- Unit leader.
Jae Sung Lee, PhD, Dept. of Nuclear Med. and Biomedical Sci., SNU CV
Jae Sung Lee
- Research aim is to develop innovative tools to analyze biomedical image data.
- Developed novel gamma-ray detectors which allow PET images with very high resolution and sensitivity (IEEE TNS, 2008).
- Developing an experimental system for truly simultaneous PET/MR imaging.
- Recipients of Young Investigator's Award, Korean Society of Medical and Biological Eng./Nucl. Med./ Human Brain Mapp. (2004).
Moo K. Chung, PhD, Dept. of Biostatistics & Medical Informatics, U of Wisconsin-Madison Homepage
Moo K. Chung
- The algorithm and code presented in his 2005 NeuroImage paper is the most widely used cortical data smoothing technique at this moment
- Chung's cortical surface data filtering technique has been the standard to be compared and to be validated against in the field
- His 2001 NeuroImage paper on tensor-based morphometry was the first paper that shows the Jacobian determinant is the only meaningful metric in structural imaging
