2009 NIPS NeurIPS 2009

fMRI-Based Inter-Subject Cortical Alignment Using Functional Connectivity

Abstract

The inter-subject alignment of functional MRI (fMRI) data is important for improving the statistical power of fMRI group analyses. In contrast to existing anatomically-based methods, we propose a novel multi-subject algorithm that derives a functional correspondence by aligning spatial patterns of functional connectivity across a set of subjects. We test our method on fMRI data collected during a movie viewing experiment. By cross-validating the results of our algorithm, we show that the correspondence successfully generalizes to a secondary movie dataset not used to derive the alignment.

🌉 Interdisciplinary Bridge — Computer Vision and Healthcare & Medicine and Machine Learning
📈 Trend Setter — Domain Adaptation
🧭 Keyword Pioneer — cortical alignment
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization