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.

Self-care and improving one’s well-being has been growing rapidly in recent years for manifold reasons (e.g. higher workload, corona pandemic). Consumer-grade noninvasive stimulation devices are therefore on the rise to counteract the occurrence of mood disorders and burn-out symptoms. Here, we aim at investigating the impact of dynamically varying auditory-visual stimulation patterns on neural entrainment patterns and resonance phenomena. Twenty-two healthy volunteers (11 female, 25.4±5.1 years, one dropout, seven in control group) participated in the study. EEG data (64 channel; equidistant layout) were acquired preand during stimulation for each volunteer. Visual and auditory stimuli were presented via a headset (ATUM, Neuro- Bright; https://www.neurobright.co.uk/). Presentation patterns (frequency, intensity, spatial distribution) varied within a presentation session but were kept constant across all volunteers. Stimulus intensity was adjusted to individual comfort levels. Individual alpha peak frequencies (iAPF) were calculated via the power spectral density with 50% overlapping 10s epochs from pre-stimulation segments. For both, the study and the control group, a time-frequency representation was calculated for the pre- and during-stimulation segments. From this, power values were determined for different frequency-bands (iAPF, stimulation frequencies and second harmonics of the latter). Statistical analyses focused on contrasting the power values between pre- and during stimulation. Mean iAPF values were 10.25±0.99Hz for the study and 10.63±1.21Hz for the control group respectively. Both, power values at the stimulation frequencies and their second harmonics differed significantly between pre- and during stimulation (pstim=0.001; pharm=0.001) in the study group. No such difference was found for the control group (pstim=0.352; pharm=0.237). Further, neither the study nor the control group showed significant iAPF power differences (pstudy=0.035; pcontrol=0.352; alpha*=0.008). Our results suggest that lightweight, portable auditory-visual presentation devices represent an effective tool for generating entrainment and resonance effects at home. Further analyses will focus on the investigation of individual differences driving such modulatory effects.

Photic driving in the human visual cortex evoked by intermittent photic stimulation is usually characterized in averaged data by an ongoing oscillation showing frequency entrainment and resonance phenomena during the course of stimulation. We challenge this view of an ongoing oscillation by analyzing unaveraged data. 64-channel EEGs were recorded during visual stimulation with light flashes at eight stimulation frequencies for fourteen healthy volunteers. Time-frequency analyses were performed in averaged and unaveraged data. While we find ongoing oscillations in the averaged data during intermittent photic stimulation, we find transient events (bursts) of activity in the unaveraged data. Both resonance and entrainment occur for the ongoing oscillations in the averaged data and the bursts in the unaveraged data. We argue that the continuous oscillations in the averaged signal may be composed of brief, transient bursts in single trials. Our results can also explain previously observed amplitude fluctuations in averaged photic driving data. Single trail analyses might consequently improve our understanding of resonance and entrainment phenomena in the brain.