[행사/세미나] CNIR 세미나 개최 안내
뇌과학이미징연구단에서 아래와 같이 세미나를 진행합니다.
오프라인으로 진행되는 세미나이며, 참석하시는 분께는 점심식사를 제공해드리오니 학생분들의 많은 참석 부탁드립니다.
- 아 래 -
Date: 12pm, Friday, Nov 18th
Title: Neuroimaging and Informatics in Alzheimer's disease Research
The complexity of neurodegenerative and psychiatric diseases often requires the collection of numerous data types from multiple modalities. These can be genetic, imaging, clinical and biosample data. In combination, they can provide biomarkers critical to chart the progression of the disease and to measure the efficacy of therapeutic intervention.
Mapping the human brain, and the brains of other species, has long been hampered by the fact that there is substantial variance in both the structure and function of this organ among individuals within a species. There are numerous probabilistic atlases that describe specific subpopulations, measure their variability and characterize the structural differences between them. Utilizing data from structural, functional, diffusion MRI, along with gwas studies and clinical measures we have built atlases with defined coordinate systems creating a framework for mapping and relating diverse data across studies.
A specific and important example of mapping multimodal data is the study of Alzheimer’s. The dynamic changes that occur in brain structure and function throughout life make the study of degenerative disorders of the aged difficult. The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a large national consortia established to collect, longitudinally, distributed and well described cohorts of age matched normals, mci's and Alzheimer’s patients. The consequences of this disease can be seen using a variety of imaging (including structural, diffusion and amyloid) and other data analyzed from the ADNI database.
Essential elements in performing this type of population based research are the informatics infrastructure to assemble, describe, disseminate and mine data collections along with computational resources necessary for large scale processing of big data such as whole genome sequence data and imaging data. This talk also describes the methods we have employed to address these challenges.