Quick Question?

Quick Question?
Please let us know your name.
Please let us know your email address.
Please write a subject for your message.
Please let us know your message.
Invalid Input

The science behind GTEN 100 Neuromodulation

SymposiaOnDemand button

View EGI's GTEN Symposium presented at OHBM 2016.
See it now with EGI SYMPOSIA OnDemand

The technology behind GTEN 100 Brain Region 1Neuromodulation
EGI's study using GTEN 100 Research System and pulsed protocols showed long-term depression of motor cortex excitability, sustained over 90 minutes following current injection Luu et al. (2016). Slow-Frequency Pulsed Transcranial Electrical Stimulation for Modulation of Cortical Plasticity Based on Reciprocity Targeting with Precision Electrical Head Modeling. Front Hum Neurosci, 10, 377.

The GTEN 100 Neuromodulation technology uses the reciprocity principle, which allowed EGI to develop a superior method for selecting electrodes for current injection for a given target. Fernandez-Corazza, et al. (2016). Transcranial Electrical Neuromodulation Based on the Reciprocity Principle. Front Psychiatry, 7, 87.

High resolution head models
Realistic high resolution head models are critical for the most accurate neuromodulation planning algorithms. EGI uses Finite Difference Method (FDM) head models.

Epileptic Source Localization Comparing High-Resolution Individual Head Models Against Conformal Atlas and Standard Atlas Head Models with Dense Array EEG

ACNS MR PosterPoster presented at the American Clinical Neurophysiology Society 2017 Conference. Rasmussen, et al. from EGI, University of Oregon, and University of Washington.

View the poster.

Good conductivity estimates and good geometry descriptions in the head model improve the accuracy of source localization. Song, et al. (2013). Anatomically accurate head models and their derivatives for dense array EEG source localization. Funct Neurol Rehabil Ergon, 3(2-3), 275-293.

A dense array of electrodes with whole head coverage, including the neck and face regions, is critical for accurate source analysis. Song et al., (2015) EEG source localization: Sensor density and head surface coverage. J Neurosci Methods, 256, 9-21.

EGI head models and source estimation correctly identify a small known area of the motor cortex. Kuo, et al. (2014). Localizing movement-related primary sensorimotor cortices with multi-band EEG frequency changes and functional MRI. PloS one, 9(11), e112103.

Based on this research, we integrated dense array EEG and the best head models into our new GeoSource Research products to create what we believe to be the most accurate source estimation product available. We tested the ability of GeoSource source estimation to identify a small known area of the motor cortex, and were able to show localization to a known anatomical location, as well as comparable results to fMRI studies (Kuo et al., 2014).

Creating individual head modelsBrain Image 2
To create conformal or individual FDM head models, GeoSource electrical source imaging and GTEN 100 neuromodulation system use a step-by-step workflow that takes a fraction of the time typically required for this level of accuracy. Li, K., Papademetris, X., & Tucker, D. (2016). BrainK for Structural Imaging Processing: Creating Electrical Models of the Human Head. Computational Intelligence and Neuroscience, 2016, Article ID 1349851.


EGI’s work is covered by several patents and patents pending. Net Station 5.4, GeoSource 3, and GTEN 100 products are protected by one or more of the following issued US patents: 6,330,470, 6,594,521, and 9,326,699. GeoSource Research products are protected by one or more of the following US patents: 8,478,011.