MagCPP: A C++ toolbox for Combining Neurofeedback with Magstim transcranial magnetic stimulators

Abstract

Transcranial magnetic stimulation (TMS) is an established method to treat various neurological diseases, such as depression, Alzheimer’s disease, and tinnitus. New applications for TMS are closed loop neurofeedback (NF) scenarios, which require software control of the TMS system, instead of the currently used manual control. Hence, the MagCPP (https://github.com/MagCPP) toolbox was developed and is described in this work. The toolbox enables the external control of Magstim TMS devices via a C++ interface. Comparing MagCPP to two other toolboxes in a TMS application scenario with 40% power, we found that MagCPP works faster and has lower variability in repeated runs (MagCPP, Python, MATLAB [mean±std in seconds]: 1.19±0.00, 1.59±0.01, 1.44±0.02). An integration of MagCPP in a real-time data processing platform MNE-CPP with an optional GUI demonstrates its ability as part of a closed-loop NF-scenario. With its performing advantages over other toolboxes, MagCPP is a first step towards a complete closed loop NF scenario and offers possibilities for novel study designs.

Keywords

• tms
• eeg
• closed loop
• bci
• data acquisition
• data processing
• medical software