beta1
Research Papers
Differential effects on mood of 12-15 (SMR) and 15-18 (beta1) Hz neurofeedback
The common assumption in EEG-neurofeedback is one of functional specificity of the trained spectral bands, though it has been posited that only a nonspecific generalised learning process may be engaged. Earlier we reported differential effects on attention in healthy participants measured with continuous performance tests and the P300, following training of the sensory-motor rhythm band (SMR, 12-15 Hz) compared with the adjacent beta1 (15-18 hz) band. Here previously unreported results are presented with phenomenological data from an activation checklist in support of the putative calming effect of SMR neurofeedback. While within sessions both protocols induced tiredness, this was paralleled by an increase in calmness only following SMR training. The differential effect on mood was theoretically consistent and extends evidence of cognitive functional specificity with neurofeedback to affective processes.
View Full Paper →Symbol Digit and the Quantitative EEG
The coordination of allocation resource model of brain functioning examines the relations between quantitative EEG (QEEG) variables and cognitive performance on specific tasks. The Digit Symbol (DS) subtest of the Wechsler Adult Intelligence Scales has proven to be a sensitive measure in a variety of clinical conditions. A conceptually and empirically similar task (Symbol Digit [SD]) was employed to examine the QEEG correlates of successful functioning. A sample of 119 participants engaged in a modified SD test for 200 seconds while QEEG data were obtained. The participant verbally provided the matching number to the examiner to avoid any motor component of the task. There were negative relations between performance and magnitudes across almost all locations and across a wide bandwidth (0-64 Hz). Negative relations to SD performance were also observed for increased relative power of beta1, whereas positive relations were found for absolute values of coherences of alpha, beta1 (13-32 Hz), and beta2 (32-64 Hz). The results showed the importance of spectral correlation coefficients (SCC) in cognitive functioning, in particular the SCC values within the frontal region and in the 13-64 frequency range.
View Full Paper →EEG biofeedback of low beta band components: frequency-specific effects on variables of attention and event-related brain potentials
OBJECTIVE: To test a common assumption underlying the clinical use of electroencephalographic (EEG) biofeedback training (neurofeedback), that the modulation of discreet frequency bands is associated with frequency-specific effects. Specifically, the proposal was assessed that enhancement of the low beta components sensorimotor rhythm (SMR: 12-15 Hz) and beta1 (15-18 Hz) affect different aspects of attentional processing. METHODS: Subjects (n=25) were randomly allocated to training with either an SMR or beta1 protocol, or to a non-neurofeedback control group. Subjects were assessed prior and subsequent to the training process on two tests of sustained attention. The neurofeedback participants were also assessed on target P300 event-related potential (ERP) amplitudes in a traditional auditory oddball paradigm. RESULTS: Protocol-specific effects were obtained in that SMR training was associated with increased perceptual sensitivity 'd prime' (d'), and reduced omission errors and reaction time variability. Beta1 training was associated with faster reaction times and increased target P300 amplitudes, whereas no changes were evident in the control group. CONCLUSIONS: Neurofeedback training of SMR and beta1 band components led to significant and protocol-specific effects in healthy subjects. The data can be interpreted as indicating a general attention-enhancing effect of SMR training, and an arousal-enhancing effect of beta1 training.
View Full Paper →The effects of neurofeedback training on the spectral topography of the electroencephalogram
Objective: To investigate the impact of EEG frequency band biofeedback (neurofeedback) training on spectral EEG topography, which is presumed to mediate cognitive-behavioural training effects. In order to assess the effect of commonly applied neurofeedback protocols on spectral EEG composition, two studies involving healthy participants were carried out. Methods: In Experiment 1, subjects were trained on low beta (12–15 Hz), beta1 (15–18 Hz), and alpha/theta (8–11 Hz/5–8 Hz) protocols, with spectral resting EEG assessed before and after training. The specific associations between learning indices of each individual training protocol and changes in absolute and relative spectral EEG topography was assessed by means of partial correlation analyses. Results of Experiment 1 served to generate hypotheses for Experiment 2, where subjects were randomly allocated to independent groups of low beta, beta1, and alpha/theta training. Spectral resting EEG measures were contrasted prior and subsequent to training within each group. Results: Only few associations between particular protocols and spectral EEG changes were found to be consistent across the two studies, and these did not correspond to expectations based on the operant contingencies trained. Low-beta training was found to be somewhat associated with reduced post-training low-beta activity, while more reliably, alpha/theta training was associated with reduced relative frontal beta band activity. Conclusions: The results document that neurofeedback training of frequency components does affect spectral EEG topography in healthy subjects, but that these effects do not necessarily correspond to either the frequencies or the scalp locations addressed by the training contingencies. The association between alpha/theta training and replicable reductions in frontal beta activity constitutes novel empirical neurophysiological evidence supporting inter alia the training's purported role in reducing agitation and anxiety. Significance: These results underline the complexity of the neural dynamics involved EEG self-regulation and emphasize the need for empirical validation of predictable neurophysiological outcomes of training EEG biofeedback protocols.
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