A Cortical Folding Pattern-Guided Model of Intrinsic Functional Brain Networks in Emotion Processing

Area of Science:

• Neuroscience
• Cognitive Science
• Computational Biology

Background:

• Emotion processing involves complex interactions within large-scale intrinsic functional brain networks.
• Understanding these neural networks is crucial for deciphering the brain's emotional mechanisms.

Purpose of the Study:

• To propose and test a novel cortical folding pattern-guided model of intrinsic brain networks in emotion processing.
• To elucidate the functional mechanisms of interregional neural communication within these networks.

Main Methods:

• Utilized task-based functional magnetic resonance imaging (fMRI) data from the Human Connectome Project (68 subjects).
• Employed a computational framework involving dictionary learning and sparse representation.
• Developed a model where cortical gyri function as global connection centers and sulci as local functional units.

Main Results:

• The proposed model differentiates the roles of gyri and sulci in neural communication during emotion processing.
• Gyri facilitate long-distance interregional communication, while sulci manage local and indirect communication.
• The model offers a new perspective on the functional organization of intrinsic brain networks.

Conclusions:

• The cortical folding pattern-guided model provides novel insights into the functional mechanisms of emotion processing.
• This framework advances our understanding of how the brain processes emotions through intrinsic network interactions.