A Searchlight Factor Model Approach for Locating Shared Information in Multi-Subject fMRI Analysis
This work addresses the problem of anatomical and functional variability in fMRI analysis for neuroscientists, offering an incremental improvement in spatial localization.
The paper tackles the challenge of locating shared information in multi-subject fMRI analysis by proposing a searchlight-based shared response model, which identifies informative local regions with validation showing improved spatial resolution in classification tasks.
There is a growing interest in joint multi-subject fMRI analysis. The challenge of such analysis comes from inherent anatomical and functional variability across subjects. One approach to resolving this is a shared response factor model. This assumes a shared and time synchronized stimulus across subjects. Such a model can often identify shared information, but it may not be able to pinpoint with high resolution the spatial location of this information. In this work, we examine a searchlight based shared response model to identify shared information in small contiguous regions (searchlights) across the whole brain. Validation using classification tasks demonstrates that we can pinpoint informative local regions.