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Found 4 papers, 0 papers with code
Shared Space Transfer Learning for analyzing multi-site fMRI data
The optimization procedure extracts the common features for each site by using a single-iteration algorithm and maps these site-specific common features to the site-independent shared space.
Deep Representational Similarity Learning for analyzing neural signatures in task-based fMRI dataset
This paper develops Deep Representational Similarity Learning (DRSL), a deep extension of RSA that is appropriate for analyzing similarities between various cognitive tasks in fMRI datasets with a large number of subjects, and high-dimensionality -- such as whole-brain images.
Supervised Hyperalignment for multi-subject fMRI data alignment
This paper proposes a Supervised Hyperalignment (SHA) method to ensure better functional alignment for MVP analysis, where the proposed method provides a supervised shared space that can maximize the correlation among the stimuli belonging to the same category and minimize the correlation between distinct categories of stimuli.
Statistical Inference, Learning and Models in Big Data
The need for new methods to deal with big data is a common theme in most scientific fields, although its definition tends to vary with the context.
