공지사항
[2025] 제5회 SNUBIC Art Fair Series 워크샵
작성자
admbic
작성일
2025-09-10
조회
2
주최: 서울대학교 뇌영상센터(SNUBIC)
과제명: 인프라 고도화: 고경사 확산 자기공명 영상장치 도입을 통한 뇌 구조와 기능에 대한 난제 해결(RS-2024-00435727)
후원: 국가연구시설장비진흥센터(NFEC), 교육부
- 행사명 : SNUBIC ART FAIR SERIES #3
- 행사 일시 : 8/24(목) 11:00-12:00
- 행사 장소 : 서울대학교 28동 303호
- 연사: 최승홍 교수(서울대학교 의과대학 영상의학과)
- 발표 제목: Foundation Models for Neuroscience
- Abstract:This presentation explores "Large Brain Models," applying the paradigm of foundation models—characterized by scale and emergent abilities—to neuroscience. To overcome the scalability limitations of current neuroimaging research, we developed SwiFT, an end-to-end transformer model for spatiotemporal fMRI data.
Trained on a large-scale dataset, SwiFT significantly outperforms previous models on prediction tasks like age and sex, and demonstrates high adaptability through pre-training and fine-tuning. These findings suggest that Large Brain Models, coupled with high-performance computing, can become a transformative tool for accurately analyzing the brain's spatiotemporal representations and interpreting the non-verbal world, much like LLMs have for language.
- Abstract:This presentation explores "Large Brain Models," applying the paradigm of foundation models—characterized by scale and emergent abilities—to neuroscience. To overcome the scalability limitations of current neuroimaging research, we developed SwiFT, an end-to-end transformer model for spatiotemporal fMRI data.
Trained on a large-scale dataset, SwiFT significantly outperforms previous models on prediction tasks like age and sex, and demonstrates high adaptability through pre-training and fine-tuning. These findings suggest that Large Brain Models, coupled with high-performance computing, can become a transformative tool for accurately analyzing the brain's spatiotemporal representations and interpreting the non-verbal world, much like LLMs have for language.
