Neurofeedback (NF) is a tool that has proven helpful in the treatment of various disorders such as epilepsy or attention deficit disorder (ADHD). Depending on the respective application, a high number of training sessions might be necessary before participants can voluntarily modulate the electroencephalographic (EEG) rhythms as instructed. In addition, many individuals never learn to do so despite numerous training sessions. Thus, we are interested in determining whether or not performance during the early training sessions can be used to predict if a participant will learn to regulate the EEG rhythms. Here, we propose an easy to use, but accurate method for predicting the performance of individual participants. We used a sample set of sensorimotor rhythm (SMR 12-15 Hz) NF training sessions (experiment 1) to predict the performance of the participants of another study (experiment 2). We then used the data obtained in experiment 2 to predict the performance of participants in experiment 1. We correctly predicted the performance of 12 out of 13 participants in the first group and all 14 participants in the second group; however, we were not able to make these predictions before the end of the eleventh training session.

Neurofeedback training (NFT) has been demonstrated to be a useful, inexpensive, nonpharmacological tool in the treatment of attention deficit hyperactivity disorder and epilepsy in humans. Different neurofeedback training protocols have been associated with positive effects on performance in sports, creativity, memory, and simple reaction time tasks. During NFT, individuals receive visual or acoustic feedback of their brain oscillations, which are recorded by electroencephalogram (EEG). Through operant conditioning that employs this feedback, the individuals subsequently may be able to modulate the respective oscillations. The most widely used training protocols focus on either the enhancement of the sensorimotor rhythm (SMR; 12-15 Hz) or modulation of the theta/beta ratio (TBR; theta: 4.5-7.5 Hz, beta: 17-21 Hz). We investigated whether healthy individuals are able to learn, within 30 NFT sessions, how to modulate either the SMR (n ¼ 13) or the TBR (n ¼ 14), and whether such modulation can lead to an enhancement in different cognitive or creative tasks. A control group (n ¼ 14) that received NFT with daily changing frequency bands and instructions was included for comparison. Although neither the TBR group nor the control group was able to modulate the EEG in the trained frequency bands, the SMR group was successful in doing so. In addition, only the SMR group was able to attain significantly better results in simple and choice reaction time tasks and a spatial rotation task after training as compared to the two other groups. No effects of NFT were found for the other attention-related tasks or for creative tasks. A series of 30 SMR training sessions can increase the ability to increase SMR amplitudes and therefore may have a future application in settings where the cultivation of fast reactions and good visuospatial abilities are relevant (e.g., in sports).

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Background Cognitive deficits including impaired information processing speed as assessed by the Symbol Digit Modalities Test (SDMT) are common in multiple sclerosis (MS). Oscillatory markers of processing speed may be extracted from magnetoencephalographic (MEG) and electroencephalographic (EEG) resting-state recordings. In this context, an increased proportion of frontal slow-wave (theta, 4–8 Hz) to fast-wave (beta, 13–30 Hz) EEG activity was indicative of impaired SDMT performance. Such an increased theta/beta ratio may reflect oscillatory slowing associated with deficits in attention control. Therapeutic approaches that consider atypical oscillatory activity in MS remain sparse. Objectives In a cross-sectional design, we examined the relation between SDMT performance, the EEG theta/beta ratio and its components. We also explored longitudinally, whether EEG neurofeedback could be used to induce a putatively adaptive alteration in these EEG parameters, toward a pattern indicative of improved processing speed. Methods N = 58 MS patients (RRMS/SPMS/PPMS N: 18/35/3, 2 cases excluded) participated in a neuropsychological examination and a resting-state EEG recording. Subsequently, N = 10 patients received neurofeedback training for two weeks in a hospitalized setting. The purpose was to reduce the frontal theta/beta ratio through operant conditioning. Results In the cross-sectional examination, patients with slow SDMT speed displayed an increased theta/beta ratio, relative to those with normal speed. This involved increased frontal theta power, whereas beta power was equal across groups. The theta/beta ratio remained stable during neurofeedback across sessions of the two-week training period. In an exploratory secondary analysis, within sessions a reduction in the theta/beta ratio during active training blocks relative pre/post session resting-states was observed, driven by reduced theta power. Conclusions These findings provide support for utilizing frontal EEG theta activity as an inverse marker of processing speed in MS. Across sessions, there was no support for successful operant conditioning of the theta/beta ratio during the two-week training period. The observed state-specific shift within sessions, involving a transient reduction in theta activity, nevertheless may provide a rationale for a further investigation of neurofeedback as a treatment approach in MS.

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