Brain Exercising Games With Consumer-Grade Single-Channel Electroencephalogram Neurofeedback: Pre-Post Intervention Study.

Background: The aging population is one of the major challenges affecting societies worldwide. As the proportion of older people grows dramatically, so does the number of age-related illnesses such as dementia-related illnesses. Preventive care should be emphasized as an effective tool to combat and manage this situation.

A game-based neurofeedback training system to enhance cognitive performance in healthy elderly subjects and in patients with amnestic mild cognitive impairment.

Introduction: This study examines the clinical efficacy of a game-based neurofeedback training (NFT) system to enhance cognitive performance in patients with amnestic mild cognitive impairment (aMCI) and healthy elderly subjects. The NFT system includes five games designed to improve attention span and cognitive performance. The system estimates attention levels by investigating the power spectrum of Beta and Alpha bands.

Effectiveness of neurofeedback versus medication for attention-deficit/hyperactivity disorder.

Background: Neurofeedback (NF) is an operant conditioning procedure that trains participants to self-regulate brain activity. NF is a promising treatment for attention-deficit/hyperactivity disorder (ADHD), but there have been only a few randomized controlled trials comparing the effectiveness of NF with medication with various NF protocols. The aim of this study was therefore to evaluate the effectiveness of unipolar electrode NF using theta/beta protocol compared with methylphenidate (MPH) for ADHD.

EEG-based emotion recognition using deep learning network with principal component based covariate shift adaptation.

Automatic emotion recognition is one of the most challenging tasks. To detect emotion from nonstationary EEG signals, a sophisticated learning algorithm that can represent high-level abstraction is required. This study proposes the utilization of a deep learning network (DLN) to discover unknown feature correlation between input signals that is crucial for the learning task.