Spatio-temporal correlation tensors reveal functional structure in human brain.

Area of Science:

• Neuroimaging
• Neuroscience
• Biophysics

Background:

• Resting-state functional MRI (fMRI) measures functional connectivity in cortical regions.
• Diffusion tensor imaging (DTI) characterizes structural connectivity of white matter tracts.
• Integrating fMRI and DTI for structure-function relations in neural networks is challenging due to signal origins and tissue specificity.

Purpose of the Study:

• To develop a method for directly integrating resting-state fMRI and DTI data.
• To characterize structure-function relations within distributed neural networks.
• To map the functional structure of neural networks and integrate structure-function relations in the human brain.

Main Methods:

• Demonstrated comparable MRI signal variations and power spectra between gray and white matter during rest.
• Observed persistent long-distance temporal correlations of fMRI signals within white matter structures.
• Derived a local spatio-temporal correlation tensor to capture directional resting-state correlation variations.

Main Results:

• MRI signal variations in white matter during rest convey information similar to gray matter.
• Low-frequency resting-state signals exhibit distinct anisotropy in neighboring intervoxel correlations.
• The derived tensor reveals distinct structures in both white and gray matter.

Conclusions:

• White matter MRI signal variations during rest contain functional information.
• A novel local spatio-temporal correlation tensor enables direct integration of structure-function relations.
• This technique has potential for mapping neural network functional structure in vivo.