Neurofeedback for alcohol addiction: Changes in resting state network activity✰.

Alcohol dependence continues to be a major global burden despite significant research progress and treatment development. The aim of this study was to investigate whether neurofeedback training can alter resting state fMRI activity in brain regions that play a crucial role in addiction disorders in patients with alcohol dependence. For this purpose, a total of 52 patients were recruited for the present study, randomized, and divided into an active and a sham group. Patients in the active group received three sessions of neurofeedback training. We compared the resting state data in the active group as part of the NF training on six measurement days. When comparing the results of the active group from neurofeedback day 3 with baseline 1, a significant reduction in activated voxels in the ventral attention network area was seen. This suggests that reduced activity over the course of therapy in subjects may lead to greater independence from external stimuli. Overall, a global decrease in activated voxels within all three analysed networks compared to baseline was observed in the study. The use of resting-state data as potential biomarkers, as activity changes within these networks, may be to help restore cognitive processes and alcohol abuse-related craving and emotions.

EEG-neurofeedback training and quality of life of institutionalized elderly women (a pilot study).

This pilot study attempted to study the applicability of neurofeedback for elderly persons living in nursing homes. We hypothesized an improve of cognitive functioning and the independence in daily life (IDL) of elderly people by using low beta (12-15HZ) EEG neurofeedback training (E-NFT). The participants (active E-NFT group, n=10; control group, n=6) were community living elderly women without dementia. Neurofeedback training was adjusted ten times within 9 weeks, with a training duration of 21 minutes by use of a single electrode, which was centrally placed on the skull surface. Executive functioning (measured with the Rey and fluency tasks), memory capacity (measured with the 15 words test), and IDL (measured with the Groningen Activity Restriction Scale) were measured before and after ten E-NFT sessions in nine weeks. No effects were found for IDL nor executive functioning. Interestingly, performance on the memory test improved in the experimental group, indicating a possible positive effect of E-NFT on memory in elderly women. This study demonstrates that E-NFT is applicable to older institutionalized women. The outcome of this pilot-study justifies the investigation of possible memory effects in future studies.

Short and long-term effects of sham-controlled prefrontal EEG-neurofeedback training in healthy subjects.

OBJECTIVE: In this study we evaluated long-term effects of frontal beta EEG-neurofeedback training (E-NFT) on healthy subjects. We hypothesized that E-NFT can change frontal beta activity in the long-term and that changes in frontal beta EEG activity are accompanied by altered cognitive performance. METHODS: 25 healthy subjects were included and randomly assigned to active or sham E-NFT. On average the subjects underwent 15 E-NFT training sessions with a training duration of 45 min. Resting-state EEG was recorded prior to E-NFT training (t1) and in a 3-year follow-up (t3). RESULTS: Compared to sham E-NFT, which was used for the control group, real E-NFT increased beta activity in a predictable way. This increase was maintained over a period of three years post training. However, E-NFT did not result in significantly improved cognitive performance. CONCLUSION: Based on our results, we conclude that EEG-NFT can selectively modify EEG beta activity both in short and long-term. SIGNIFICANCE: This is a sham controlled EEG neurofeedback study demonstrating long-term effects in resting state EEG.