Human memory retention and recall processes:A review of EEG and fMRI studies

Human memory is an important concept in cognitive psychology and neuroscience. Our brain is actively engaged in functions of learning and memorization. Generally, human memory has been classified into 2 groups: short-term/working memory, and longterm memory. Using different memory paradigms and brain mapping techniques, psychologists and neuroscientists have identified 3 memory processes: encoding, retention, and recall. These processes have been studied using EEG and functional MRI (fMRI) in cognitive and neuroscience research. This study reviews previous research reported for human memory processes, particularly brain behavior in memory retention and recall processes with the use of EEG and fMRI. We discuss issues and challenges related to memory research with EEG and fMRI techniques.</p

Detrended fluctuation analysis for major depressive disorder

Clinical utility of Electroencephalography (EEG) based diagnostic studies is less clear for major depressive disorder (MDD). In this paper, a novel machine learning (ML) scheme was presented to discriminate the MDD patients and healthy controls. The proposed method inherently involved feature extraction, selection, classification and validation. The EEG data acquisition involved eyes closed (EC) and eyes open (EO) conditions. At feature extraction stage, the de-trended fluctuation analysis (DFA) was performed, based on the EEG data, to achieve scaling exponents. The DFA was performed to analyzes the presence or absence of long-range temporal correlations (LRTC) in the recorded EEG data. The scaling exponents were used as input features to our proposed system. At feature selection stage, 3 different techniques were used for comparison purposes. Logistic regression (LR) classifier was employed. The method was validated by a 10-fold cross-validation. As results, we have observed that the effect of 3 different reference montages on the computed features. The proposed method employed 3 different types of feature selection techniques for comparison purposes as well. The results show that the DFA analysis performed better in LE data compared with the IR and AR data. In addition, during Wilcoxon ranking, the AR performed better than LE and IR. Based on the results, it was concluded that the DFA provided useful information to discriminate the MDD patients and with further validation can be employed in clinics for diagnosis of MDD.</p

Development of Enhanced Stimulus Content to Improve the Treatment Efficacy of EEG–Based Frontal Alpha Asymmetry Neurofeedback for Stress Mitigation

The neurofeedback stimulus content has direct implications for the efficacy of the psychophysiological applications for neurofeedback modality. In particular, enhancements of neurofeedback stimulus content can facilitate improvements in the efficacy of neurofeedback applications in clinical practice. To further elaborate on this aspect, this study introduced systematic enhancements in neurofeedback stimulus content by developing enhanced neurofeedback stimulus content for stress mitigation. The enhancements included the automatic selection of colour of neurofeedback stimulus content environment and instruction messages, as well as, the adaptive selection of threshold of quantitative electroencephalogram (QEEG) features, such as frontal alpha power and frontal alpha asymmetry. The enhancements were based on the outcomes from previous research on the selection of neurofeedback stimulus content for stress mitigation. The improvement in the efficacy of neurofeedback stimulus content was measured statistically by comparing the QEEG and topographic maps. In this study, electroencephalogram data from 20 participants were acquired during multiple sessions of neurofeedback. Analysis of variance and a post hoc test were used to verify the improvement on the efficacy of the neurofeedback application for stress mitigation after the enhancements of the neurofeedback stimulus content; a t-test was used to verify the statistical significance of the stress mitigation by the neurofeedback. The results indicate that the enhancement of the developed neurofeedback stimulus content facilitated stress mitigation during the early sessions of neurofeedback. In conclusion, the efficacy of neurofeedback can be improved using the developed stimulus content with enhancements.</p