Sheela Ramanna

The paper uses computational topology to analyze rs-fMRI data, identifying persistent BOLD signal structures called cortical lag threads and visualizing them as persistent barcodes.

The paper measures information entropy in fMRI data and finds higher entropy in associative brain regions compared to primary sensory areas, suggesting the brain operates in higher dimensions than the environment.

The paper introduces a novel fMRI analysis method, maximal nucleus clustering, to detect hidden temporal patterns of entropy in brain activity, suggesting evidence for a fourth spatial dimension in the brain.

This paper proposes a mathematical framework combining Borsuk's theory of shape and the Borsuk-Ulam theorem to model perception as a topological and ecological process.