BEST Toolbox: Brain Electrophysiological recording & STimulation Toolbox

Presented During:

Poster No:


Submission Type:

Abstract Submission 


Umair Hassan1, Steven Pillen1, Christoph Zrenner2, Til Ole Bergmann1


1Deutsches Resilienz Zentrum (DRZ), Mainz, Germany, 2Department of Neurology & Stroke, & Hertie Institute for Clinical Brain Research, Tübingen, Germany

First Author:

Umair Hassan  
Deutsches Resilienz Zentrum (DRZ)
Mainz, Germany


Steven Pillen  
Deutsches Resilienz Zentrum (DRZ)
Mainz, Germany
Christoph Zrenner  
Department of Neurology & Stroke, & Hertie Institute for Clinical Brain Research, Tübingen
Til Ole Bergmann  
Deutsches Resilienz Zentrum (DRZ)
Mainz, Germany


Non-invasive brain stimulation (NIBS) experiments involve many standard procedures that are nonetheless not sufficiently standardized in the community. Transcranial magnetic stimulation (TMS) protocols usually require motor hotspot search, motor threshold hunting, motor evoked potential (MEP) and TMS-evoked EEG potential (TEP) measurements, estimation of stimulus-response curves, paired-pulse TMS, rTMS intervention protocols, etc., and since recently also real-time EEG-triggered stimulation. Given the diversity in application and experience of the experimenter, standardized, automated, and yet flexible, data collection and analysis tools are needed. Here, we introduce the Brain Electrophysiological recording and STimulation (BEST) Toolbox, a MATLAB based open source software that interfaces with a wide variety of EEG, EMG, and TMS devices, and allows to run flexibly configured but fully automated closed-loop protocols. The BEST toolbox provides a software framework for brain stimulation studies, including real-time closed-loop applications. It is powered by state-of-the-art signal processing algorithms, combined with an easy to use graphical user interface (GUI) in order to facilitate data collection, live and interactive data analyses and visualization, data sharing, study comparison and replication, student training, and open science.


The BEST toolbox is designed to work with any stimulation device that can be triggered by TTL pulses, and it can set stimulation parameters for TMS devices via the MAGIC toolbox [1]. Regarding the input hardware, the BEST toolbox is currently optimized for the BOSS Box (BlindSight, DE), a data processing and control system implemented as Simulink© Real-Time model on a high performance computer system (Figure 1), receiving a digital real-time data stream from an EEG system such as "NeurOne TESLA" (Bittium, FL) or "actiCHamp Plus" (BrainProducts, DE). Additionally, the FieldTrip real-time buffer [2] has been integrated to the BEST Toolbox to provide a system-independent input interface, establishing compatibility with any EEG/EMG hardware solution capable of writing to a MATLAB buffer. The BEST toolbox is written in MATLAB in an object-oriented software architecture and has been tested with MATLAB versions 2017b and higher.
Supporting Image: Fig1_submitted_ohbm.jpg


The BEST toolbox comprises a constantly growing number of functions (currently motor hotspot search, closed-loop motor threshold hunting, MEP input-output curves, MEP measurements, TEP measurements, repetitive TMS (rTMS) protocols, resting-state EEG analysis, generic event-related EEG potentials, and real-time EEG-triggered TMS), which can be executed in any sequence and number of repetitions required by the experimental design. The BEST toolbox empowers students and basic users as well as clinicians to use complex multimodal methods such as EEG-triggered TMS [3,4] to test their hypotheses in a plug-and-play manner. The GUI of the BEST toolbox (Figure 2) allows to design, save, load, and run experiments with multiple sessions, as well as to pause and resume experiments, and analyze, visualize, and store data online. The integrated storage of experimental parameters and data ensures full transparency and reproducibility, while the full automation of procedures (such as threshold hunting) increases objectivity and reliability of data collection and parameter estimation.
Supporting Image: Fig2_final_ohbm_submitted.jpg


The BEST toolbox facilitates and standardizes brain stimulation experiments, including motor cortical excitability measures, rTMS interventions, and closed-loop stimulation experiments. Code is publicly available via GitHub:

Brain Stimulation:

Non-invasive Magnetic/TMS
Non-Invasive Stimulation Methods Other 2

Modeling and Analysis Methods:

Methods Development


Data analysis
Data Organization
Electroencephaolography (EEG)
Experimental Design
Transcranial Magnetic Stimulation (TMS)
Other - Non-Invasive Brain Stimulation (NIBS)

1|2Indicates the priority used for review

My abstract is being submitted as a Software Demonstration.


Please indicate below if your study was a "resting state" or "task-activation” study.


Healthy subjects only or patients (note that patient studies may also involve healthy subjects):

Healthy subjects

Was any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.


Was any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.

Not applicable

Please indicate which methods were used in your research:

Other, Please specify  -   real-time EEG triggered TMS

Provide references using author date format

[1] Saatlou, F.H. (2018), MAGIC: An open-source MATLAB toolbox for external control of transcranial magnetic stimulation devices. Brain Stimulation: Basic, Translational, and Clinical Research in Neuromodulation, 11(5), 1189-1191.
[2] Oostenveld, R. (2011), FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Computational intelligence and neuroscience, 2011, 1.
[3] Zrenner, C. (2018), Real-time EEG-defined excitability states determine the efficacy of TMS-induced plasticity in human motor cortex. Brain stimulation , 11 (2), 374-389.
[4] Bergmann TO., (2019), Pulsed Facilitation of Corticospinal Excitability by the Sensorimotor mu-Alpha Rhythm. J Neurosci 39:10034-10043.