Multi-Subject Fmri Data Alignment
0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Multi-Subject Fmri Data Alignment
ABIDE
Latest papers with no code
Identification of Novel Diagnostic Neuroimaging Biomarkers for Autism Spectrum Disorder Through Convolutional Neural Network-Based Analysis of Functional, Structural, and Diffusion Tensor Imaging Data Towards Enhanced Autism Diagnosis
Autism spectrum disorder is one of the leading neurodevelopmental disorders in our world, present in over 1% of the population and rapidly increasing in prevalence, yet the condition lacks a robust, objective, and efficient diagnostic.
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.
Gradient Hyperalignment for multi-subject fMRI data alignment
Multi-subject fMRI data analysis is an interesting and challenging problem in human brain decoding studies.
Local Discriminant Hyperalignment for multi-subject fMRI data alignment
Multivariate Pattern (MVP) classification can map different cognitive states to the brain tasks.
