A Protocol For Uncovering Neural Mechanisms Of Neurotherapeutic Effects On Electroencephalography Using The Human...

Area of Science:

• Computational Neuroscience
• Neuroscience
• Biophysics

Background:

• Electrophysiological methods like electroencephalography (EEG) offer millisecond-resolution biomarkers for central nervous system (CNS) disorders.
• Understanding the neural mechanisms generating these EEG biomarkers is crucial for developing effective diagnostics and therapeutics.
• Current limitations in mechanistic understanding hinder the full potential of EEG in clinical applications.

Purpose of the Study:

• To present a hypothesis-driven workflow using the Human Neocortical Neurosolver (HNN) software.
• To demonstrate how to link localized EEG biomarkers to their multiscale neural generators.
• To enable testing of neural mechanisms underlying EEG biomarkers and neurotherapeutic effects.

Main Methods:

• Utilized the open-source biophysical modeling software, Human Neocortical Neurosolver (HNN).
• Employed a hypothesis-driven workflow to optimize model parameters for fitting simulated and empirical current source waveforms.
• Visualized and quantified multiscale cell- and circuit-level activity to validate model predictions.

Main Results:

• Successfully demonstrated a workflow for testing neural mechanisms of neurotherapeutic-induced EEG biomarkers.
• Provided an example of examining neural mechanisms of early auditory evoked response components (P1, N1, P2).
• Showcased the assessment of changes in neural circuit activity following neurotherapeutic interventions.

Conclusions:

• The HNN protocol facilitates the design of simulation experiments to generate testable predictions.
• This approach links EEG biomarkers to underlying neural circuit mechanisms.
• The workflow is applicable to studying disease mechanisms and other therapeutic interventions in CNS disorders.