Human brain networks function in connectome-specific harmonic waves.

Area of Science:

• Neuroscience
• Complex Systems
• Computational Biology

Background:

• Human brain activity features coherent, spatially distributed oscillations forming behavior-dependent networks.
• The fundamental principles governing these brain networks remain largely unknown.

Purpose of the Study:

• To identify underlying principles of human brain network organization.
• To investigate the role of harmonic patterns and the human connectome in brain activity.

Main Methods:

• Introduction of a novel technique extending the Fourier basis to the human connectome, termed 'connectome harmonics'.
• Analysis of resting-state human brain oscillatory networks using this new representation.
• Development of a continuous neural field model simulating excitatory-inhibitory interactions on the connectome.

Main Results:

• Resting-state oscillatory brain networks align with specific harmonic wave patterns predicted by the connectome.
• Demonstration of a neural mechanism for the self-organization of these connectome harmonics.
• The model's findings correlate with neurophysiological changes during altered states of consciousness.

Conclusions:

• Harmonic patterns, steered by cortical anatomy, are a fundamental principle predicting human brain functional networks.
• Connectome harmonics offer a new framework for understanding brain organization and consciousness.
• The study links neural field dynamics and excitation-inhibition balance to consciousness.