Modelling transcranial ultrasound neuromodulation: an energy-based multiscale framework

Area of Science:

• Biophysics
• Neuroscience
• Computational Modeling

Background:

• Low-intensity transcranial ultrasound (TUS) shows potential for non-invasive neuromodulation.
• The precise mechanisms of TUS neuromodulation and optimal parameters remain unclear.
• A hypothesis suggests TUS alters nerve activity via mechanical energy and entropy conversions.

Purpose of the Study:

• To propose and validate a multiscale modeling framework for examining neuromodulation energy states under TUS.
• To investigate the relationship between TUS parameters and energy dynamics at the cellular level.
• To provide a scalable framework for in silico predictions for personalized TUS treatments.

Main Methods:

• Macroscopic acoustic simulations of TUS on a monkey brain model.
• Microscopic finite element modeling of a neuronal axon under simulated TUS mechanical loading.
• Computation and mapping of energy densities (stored and dissipated) against TUS parameters.

Main Results:

• The multiscale framework successfully analyzed axonal vibrational patterns and energy states.
• Computed energy dynamics correlated with TUS parameters and aligned with existing neuromodulation data.
• The model demonstrated potential for identifying optimized acoustic parameters for TUS.

Conclusions:

• The proposed multiscale energetic approach offers a scalable framework for in silico TUS predictions.
• This method can aid in understanding cellular-level TUS mechanisms and optimizing treatment parameters.
• The framework supports the development of personalized TUS therapies for neurological disorders.