Protocol for quantitative characterization of human retinotopic maps using quasiconformal mapping

Area of Science:

• Neuroimaging
• Computational Neuroscience
• Geometric Analysis

Background:

• High-field functional MRI (fMRI) enables in vivo retinotopic mapping of the human visual cortex.
• Quantifying these retinotopic maps accurately remains a significant challenge in neuroscience.

Purpose of the Study:

• To present a novel computational pipeline for the quantitative characterization of human retinotopic maps.
• To enable precise analysis and reconstruction of visual field representations in the brain.

Main Methods:

• Cortical surface parameterization and surface-spline-based smoothing.
• Beltrami coefficient-based mapping derived from conformal geometry and Teichmüller theory.
• Application to retinotopic maps from the Human Connectome Project (HCP) V1 data.

Main Results:

• Successfully generated a quantitative and reconstructible description of retinotopic maps.
• Demonstrated the framework's utility in analyzing complex fMRI data from the HCP.
• Provided a robust method for characterizing visual cortex organization.

Conclusions:

• The proposed pipeline offers a powerful tool for quantitative analysis of human retinotopic maps.
• Conformal geometry and Teichmüller theory provide a robust mathematical framework for neuroimaging data.
• This method advances our ability to study visual system organization and function.