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Updated: Oct 7, 2025

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

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Published on: May 8, 2021

Physiologically informed neuromodulation.

Karen Wendt¹, Timothy Denison¹, Gaynor Foster²

¹Department of Engineering Science and MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.

Journal of the Neurological Sciences

|January 8, 2022

Summary

This summary is machine-generated.

Physiologically informed neuromodulation, using brain rhythms and electroencephalography (EEG), personalizes psychiatric treatments. This approach enhances neuroplasticity and may improve efficacy for various neurological and psychiatric conditions.

Keywords:

Biomarkers in psychiatry Brain-state dependent stimulation Deep brain stimulation Electroencephalography Neuromodulation Transcranial magnetic stimulation

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Published on: May 3, 2024

Area of Science:

Neuroscience
Psychiatry
Biomedical Engineering

Background:

Neuromodulation techniques are rapidly evolving, with a growing focus on personalized stimulation guided by patient neurophysiology.
Personalized treatment and target engagement have proven effective in conditions like Parkinson's disease.
Closed-loop paradigms are successfully used in cardiac defibrillators, with promising applications in psychiatry.

Purpose of the Study:

To explore the potential of physiologically informed neuromodulation in psychiatry.
To investigate how matching stimulation parameters to individual brain rhythms can enhance treatment efficacy.
To assess the utility of neurophysiological tools for diagnosing and managing psychiatric disorders.

Main Methods:

Utilizing transcranial magnetic stimulation (TMS) frequency matched to individual brain rhythms.
Combining TMS with electroencephalographic (EEG) recordings to match stimulation phase with brain rhythms.
Employing resting-state EEG and event-related potentials to assess brain connectivity.

Main Results:

Matching stimulation frequency to brain rhythms shows promise in TMS applications.
Phase-matching stimulation with brain rhythms may further enhance neuroplasticity.
EEG techniques can help diagnose underlying conditions like sleep disorders, epilepsy, or lesions contributing to depression.

Conclusions:

Neurophysiological tools, including EEG, can aid in diagnosing psychiatric conditions and assessing brain network status.
Future research using invasive recordings may identify mood biomarkers and network structures.
Safe implementation of closed-loop neuromodulation requires careful consideration of system operation and physiological dynamics.