Large-scale signal propagation modes in the human brain

Area of Science:

• Neuroscience
• Cognitive Science
• Systems Neuroscience

Background:

• Understanding brain temporal dynamics is crucial for cognition, but complexity and inconsistent methods hinder progress.
• A unified framework for brain-wide signal propagation modes is needed to capture spatiotemporal features.

Purpose of the Study:

• To identify a limited set of brain-wide signal propagation modes that capture diverse spatiotemporal features.
• To develop a coherent framework for understanding brain temporal dynamics and their relation to cognition.

Main Methods:

• Applied dynamic mode decomposition (DMD) to resting-state functional magnetic resonance imaging (fMRI) data.
• Identified five distinct propagation modes, termed dynamic modes (DMs), from brain-wide signal dynamics.

Main Results:

• Five DMs were identified, corresponding to key neural resource allocation dimensions like multisensory integration, salience network modulation, and interhemispheric coordination.
• The superposition of these DMs generates canonical spatiotemporal phenomena, including wave propagation and time-varying functional connectivity.
• Individual differences in brain temporal dynamics, modeled by DMs, correlate with cognitive abilities, show heritability, and are cross-task stable.

Conclusions:

• Dynamic modes (DMs) provide a parsimonious framework for modeling coherent brain dynamics.
• This system-level approach offers a scalable tool for studying cognition and individual differences in brain temporal dynamics.