| Paper: | RS-1A.3 |
| Session: | Late Breaking Research 1A |
| Location: | Late-Breaking Research Area |
| Session Time: | Thursday, September 6, 16:30 - 18:30 |
| Presentation Time: | Thursday, September 6, 16:30 - 18:30 |
| Presentation: |
Poster
|
| Publication: |
2018 Conference on Cognitive Computational Neuroscience, 5-8 September 2018, Philadelphia, Pennsylvania |
| Paper Title: |
A massive benchmark high-field fMRI dataset of responses to natural scenes |
| Authors: |
Kendrick Kay, University of Minnesota, United States; Thomas Naselaris, Medical University of South Carolina, United States |
| Abstract: |
Machine learning (ML) techniques typically require far more data than is typically collected during conventional neuroscience experiments. The goal of this project is to drive the application of ML techniques to neuroscience research by generating a massive dataset of brain responses from the human visual system. Data will be collected using high-field (7 Tesla) fMRI and processed using modern pre-processing and denoising techniques. The resulting dataset will be freely available to scientists, educators, and students. We hope to foster open collaboration between neuroscientists and artificial intelligence researchers and a culture of sharing data, ideas, and progress. |
