Sub-Second Fluctuation between Top-Down and Bottom-Up Modes Distinguishes Diverse Human Brain States

Area of Science:

• Neuroscience
• Cognitive Science
• Computational Neuroscience

Background:

• Brain activity involves continuous information flow with dynamic patterns across consciousness states.
• Understanding real-time brain dynamics and directional information processing is crucial.

Purpose of the Study:

• Introduce Relative Phase Analysis (RPA) to reveal real-time brain dynamics.
• Investigate sub-second transitions between top-down and bottom-up processing modes.
• Explore the neural basis of these dynamics and their relation to consciousness and ADHD.

Main Methods:

• Developed and applied Relative Phase Analysis (RPA) using phase-lead/lag relationships.
• Utilized simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) recordings.
• Employed a coupled-oscillator model of the structural brain network.

Main Results:

• The brain switches between top-down (anterior-to-posterior) and bottom-up (posterior-to-anterior) modes on a sub-second timescale.
• These directional dynamics are strongest in full consciousness and diminish with reduced awareness.
• Top-down mode correlates with higher-order cognitive networks, bottom-up with sensory systems.
• Attention deficit hyperactivity disorder (ADHD) inattentive cohort shows distinct imbalances in transition dynamics.
• A computational model successfully recapitulates these emergent directional patterns.

Conclusions:

• RPA provides a framework for real-time whole-brain dynamics analysis.
• Sub-second fluctuations in directional processing modes are fundamental to human information processing.
• RPA shows potential as a diagnostic biomarker for neuropsychiatric conditions like ADHD.