Combining functional and anatomical connectivity reveals brain networks for auditory language comprehension

Area of Science:

• Neuroimaging
• Cognitive Neuroscience
• Network Science

Background:

• Cognitive functions rely on complex, interconnected brain networks.
• Understanding large-scale brain network topology is crucial in neuroimaging.
• Existing methods have limitations in precisely mapping functional interactions.

Purpose of the Study:

• To introduce a novel combined functional and anatomical connectivity approach.
• To investigate the network topology underlying auditory comprehension (phonological and semantic processing).
• To identify specific brain regions and white matter tracts involved in language processing.

Main Methods:

• Utilized directed partial correlation (dPC) on functional MRI data to identify direct functional interactions between brain regions.
• Employed probabilistic fiber tracking on diffusion tensor imaging data to map anatomical white matter tracts connecting functionally interacting regions.
• Applied the combined approach to analyze the network topology of speech perception and recognition.

Main Results:

• Directed partial correlation identified the functional network topology and central nodes for both phonological and semantic processing.
• Tractography revealed that functional interactions are mediated by distinct ventral and dorsal white matter pathways.
• Demonstrated segregation of lower-level and higher-level auditory comprehension processes within large-scale brain networks.

Conclusions:

• The combination of dPC and tractography offers a powerful method for studying brain network organization.
• This approach effectively maps how cognitive functions emerge from interactions between anatomically connected brain regions.
• Findings highlight the distinct large-scale network segregation underlying different levels of auditory language processing.