Synergistic entrainment: a multiscale neurodynamic framework for closed-loop cross-modal neuromodulation.

Area of Science:

• Neuroscience
• Cognitive Science
• Computational Neuroscience

Background:

• Higher cognitive functions depend on integrating multimodal information via neural oscillations.
• Current neuromodulation methods struggle with inter-individual variability and lack mechanistic understanding.
• Reliable control of brain dynamics is crucial for therapeutic interventions.

Purpose of the Study:

• To propose the Synergistic Entrainment Framework for understanding and controlling brain dynamics.
• To conceptualize the brain as a dynamical system where neural oscillations regulate information processing.
• To provide a theoretical and operational scaffold for state-dependent, closed-loop neuromodulation.

Main Methods:

• Conceptualizing the brain as a dynamical system.
• Modeling the interaction of rhythmic inputs across different physical modalities.
• Analyzing multiscale mechanisms: microscopic interference, mesoscopic phase resetting, and macroscopic synchronization.
• Linking stimulation timing with intrinsic brain dynamics.

Main Results:

• Rhythmic inputs can nonlinearly interact to amplify or stabilize neural responses when timed with cortical dynamics.
• The framework integrates microscopic, mesoscopic, and macroscopic scales of neural interaction.
• It offers a theoretical perspective for formulating testable hypotheses in neuromodulation.

Conclusions:

• The Synergistic Entrainment Framework provides a novel approach to neuromodulation.
• It emphasizes the importance of aligning stimulation timing with intrinsic brain dynamics.
• This framework can guide future research in closed-loop brain stimulation for cognitive enhancement and treatment.