beta frequency
Research Papers
SMR Neurofeedback Training Facilitates Working Memory Performance in Healthy Older Adults: A Behavioral and EEG Study
Cognitive aging has become a major concern because life expectancy has increased and elderly populations are socially and economically active. Neurofeedback is a technique of neuromodulation through operant conditioning paradigm that uses a computer interface to provide real-time information about brain activity to increase individual self-perception and assist in modulation. The sensorimotor rhythm (SMR) training protocol is known to enhance attention and has been applied to improve cognitive performance, primarily for attention and memory gains. The aim of this study is to test if the SMR protocol can improve working memory performance in an aging population and consequently favor cognitive reserve. Seventeen older adults (12 females) took part in a randomized placebo-controlled study. They completed a visual working memory test, Delayed Matching to Sample Task (DMTS), before and after the SMR neurofeedback protocol in order to compare their visual working memory performance. Moreover, a 19-channels EEG was collected while they perform the DMTS pre- and post-training. The experimental group showed an improvement in their working memory performance after the training with similar activation power, mainly in theta and beta frequency band at frontal and alpha at temporal regions. The sham group showed some variations in the score of working memory after the training, but were not statistically significant and their power spectrum demonstrate enhancement in alpha and beta band frontal and temporal. The group that did not receive neurofeedback training did not show a change in their working memory performance, neither in their EEG spectrum. The results suggest that neurofeedback can benefit brain reserve in an aging population because individuals enhanced their working memory performance after training and have their EEG activation changed according to expected in working memory tasks.
View Full Paper →The Coordinated Allocation of Resource (CAR) Electrophysiological Patterns of Recalling Names of Faces in Children, Adolescents and Adults and the Central Processing Unit (CPU) of the Brain
The quantitative EEG (QEEG) has proven to be an important methodology in the understanding of brain functioning. The Coordinated Allocation of Resource (CAR) model maintains that cognitive effectiveness depends on the employment of a specific set of resources for specific cognitive tasks, which overlap in some situations. The model employs the flashlight metaphor in understanding the coherence and phase relations between locations. The metaphor asserts that each location can function as a flashlight that sends out a “beam” to the other locations within a frequency. The “beam” can involve all the other locations or be a mini-flashlight that involves only selected locations. The task of recalling names of faces was examined in the context of the CAR model. The developmental changes that occur during the encoding of names of faces include increases in diffusely located communication connections involving theta (4–8 Hz) and alpha (8–13 Hz), increases in the relative power values of the beta variables (13–64 Hz), peak frequency of beta1 (13–32 Hz) and alpha, decreases in communication patterns involving the beta2 (32–64 Hz) and delta (0–4 Hz) frequencies as well as decreasing values of variables involving the lower frequencies (delta, theta), relative power values of alpha and magnitudes of alpha, beta2 and peak amplitudes of beta2.The face-name task is both a verbal and visual task as the participant is hearing the name while he looks at the photograph. Variables that relate to success during the encoding task involve diffuse increases in flashlight activity from F7 and T3 across all frequencies to and between central locations. The QEEG variables that relate to immediate and delayed recall success involve flashlights from T3 across 4 frequencies, F7 involving 3 frequencies and the appearance of a heuristic “central processing unit” involving frontal (F3, Fz, F4), central (C3, Cz, C4) and posterior (P3, Pz, P4) locations.
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