scholarly journals Noninvasive Deep Brain Stimulation via Temporally Interfering Electric Fields

Cell ◽  
2017 ◽  
Vol 169 (6) ◽  
pp. 1029-1041.e16 ◽  
Author(s):  
Nir Grossman ◽  
David Bono ◽  
Nina Dedic ◽  
Suhasa B. Kodandaramaiah ◽  
Andrii Rudenko ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Electric Fields ◽  
Brain Stimulation ◽  
Deep Brain

scholarly journals Delivery of low intensity/low frequency electric fields via clinical Deep Brain Stimulation electrodes has anti-proliferative effects on Glioblastoma multiforme cell lines

2018 ◽  
Vol 20 (suppl_1) ◽  
pp. i11-i11
Author(s):  
Joshua Branter ◽  
Maria de los Angeles Estevez-Cebrero ◽  
Richard Grundy ◽  
Surajit Basu ◽  
Stuart Smith
Keyword(s):  
Deep Brain Stimulation ◽  
Glioblastoma Multiforme ◽  
Cell Lines ◽  
Electric Fields ◽  
Brain Stimulation ◽  
Low Frequency ◽  
Low Intensity ◽  
Deep Brain

scholarly journals FastField: An Open-Source Toolbox for Efficient Approximation of Deep Brain Stimulation Electric Fields

2020 ◽  
Author(s):  
Mehri Baniasadi ◽  
Daniele Proverbio ◽  
Jorge Gonçalves ◽  
Frank Hertel ◽  
Andreas Husch
Keyword(s):  
Deep Brain Stimulation ◽  
Open Source ◽  
Electric Fields ◽  
Brain Stimulation ◽  
Computational Models ◽  
Parameter Tuning ◽  
Principle Of Superposition ◽  
Limited Applicability ◽  
Efficient Approximation ◽  
Deep Brain

AbstractDeep brain stimulation (DBS) is a surgical therapy to alleviate symptoms of certain brain disorders by electrically modulating neural tissues. Computational models predicting electric fields and volumes of tissue activated are key for efficient parameter tuning and network analysis. Currently, we lack efficient and flexible software implementations supporting complex electrode geometries and stimulation settings. Available tools are either too slow (e.g. finite element method–FEM), or too simple, with limited applicability to basic use-cases. This paper introduces FastField, an efficient open-source toolbox for DBS electric field and VTA approximations. It computes scalable e-field approximations based on the principle of superposition, and VTA activation models from pulse width and axon diameter. In benchmarks and case studies, FastField is solved in about 0.2s, ~ 1000 times faster than using FEM. Moreover, it is almost as accurate as using FEM: average Dice overlap of 92%, which is around typical noise levels found in clinical data. Hence, FastField has the potential to foster efficient optimization studies and to support clinical applications.

scholarly journals Numerical Study on Electrode Design for Rodent Deep Brain Stimulation With Implantations Cranial to Targeted Nuclei

2021 ◽  
Vol 15 ◽  
Author(s):  
Konstantin Butenko ◽  
Rüdiger Köhling ◽  
Ursula van Rienen
Keyword(s):  
Deep Brain Stimulation ◽  
Electric Fields ◽  
Brain Stimulation ◽  
Numerical Study ◽  
Brain Regions ◽  
Electrode Design ◽  
Rodent Models ◽  
Neurological Damage ◽  
Direct Targeting ◽  
Deep Brain

The globus pallidus internus and the subthalamic nucleus are common targets for deep brain stimulation to alleviate symptoms of Parkinson's disease and dystonia. In the rodent models, however, their direct targeting is hindered by the relatively large dimensions of applied electrodes. To reduce the neurological damage, the electrodes are usually implanted cranial to the nuclei, thus exposing the non-targeted brain regions to large electric fields and, in turn, possible undesired stimulation effects. In this numerical study, we analyze the spread of the fields for the conventional electrodes and several modifications. As a result, we present a relatively simple electrode design that allows an efficient focalization of the stimulating field in the inferiorly located nuclei.

Computational analysis of non-invasive deep brain stimulation based on interfering electric fields

2019 ◽  
Vol 64 (23) ◽  
pp. 235010 ◽  
Author(s):  
Fariba Karimi ◽  
Ahmadreza Attarpour ◽  
Rassoul Amirfattahi ◽  
Abolghasem Zeidaabadi Nezhad
Keyword(s):  
Deep Brain Stimulation ◽  
Electric Fields ◽  
Brain Stimulation ◽  
Computational Analysis ◽  
Non Invasive ◽  
Deep Brain
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