Neurofeedback facilitation of implicit motor learning

Ros, Tomas; Munneke, M.A.M.; Parkinson, L; Gruzelier, John

doi:10.1016/j.biopsycho.2013.04.013

Cited by 54 publications

(57 citation statements)

References 20 publications

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“…Increased performance was found when rTMS was applied ipsilaterally to the items to be retained, suggesting that enhanced alpha oscillations effectively suppressed irrelevant information. In this line, some NF studies have reported higher cognitive performance in healthy users after regulating the alpha oscillations, specifically measured in WM (Escolano et al, 2011; Nan et al, 2012), visuospatial rotation (Hanslmayr et al, 2005; Zoefel et al, 2011), and procedural learning (Ros et al, 2014). The reader is directed to Gruzelier (2013) for a review on NF studies on cognitive enhancement.…”

Section: Introductionmentioning

confidence: 98%

A controlled study on the cognitive effect of alpha neurofeedback training in patients with major depressive disorder

Escolano

Navarro-Gil²,

Campayo

et al. 2014

Front. Behav. Neurosci.

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Cognitive deficits are core symptoms of depression. This study aims to investigate whether neurofeedback (NF) training can improve working memory (WM) performance in patients with major depressive disorder (MDD). The NF group (n = 40) underwent eight NF sessions and was compared to a non-interventional control group (n = 20). The NF protocol aimed to increase the individual upper alpha power in the parieto-occipital area of the scalp. Main cognitive variable was WM, which was measured pre- and post- training along with other variables such as attention and executive functions. EEG was recorded in both eyes closed resting state and eyes open task-related activity, pre- and post- NF training, and pre- and post- the NF trials within each session. A power EEG analysis and an alpha asymmetry analysis were conducted at the sensor level. Frequency domain standardized low resolution tomography (sLORETA) was used to assess the effect at brain source level. Correlation analysis between the clinical/cognitive and EEG measurements was conducted at both the sensor and brain source level. The NF group showed increased performance as well as improved processing speed in a WM test after the training. The NF group showed pre-post enhancement in the upper alpha power after the training, better visible in task-related activity as compared to resting state. A current density increase appeared in the alpha band (8–12 Hz) for the NF group, localized in the subgenual anterior cingulate cortex (sgACC, BA 25). A positive correlation was found for the NF group between the improvement in processing speed and the increase of beta power at both the sensor and brain source level. These results show the effectiveness of this NF protocol in improving WM performance in patients with MDD.

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Section: Introductionmentioning

confidence: 98%

A controlled study on the cognitive effect of alpha neurofeedback training in patients with major depressive disorder

Escolano

Navarro-Gil²,

Campayo

et al. 2014

Front. Behav. Neurosci.

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“…Although some studies reported that alpha amplitude was smaller in one 30-min session when compared with resting baseline (Ros et al, 2013) or it reduced across two 15-min NF sessions (Wan et al, 2016), the within-session learning that describes alpha dynamic change within sessions is not clear yet. Moreover, previous work mainly reported the alpha learning at the group level whereas the inter-individual difference in alpha learning was little known (Ros et al, 2010, 2013, 2014b, 2016; Wan et al, 2016). …”

Section: Introductionmentioning

confidence: 99%

Eyes-Closed Resting EEG Predicts the Learning of Alpha Down-Regulation in Neurofeedback Training

et al. 2018

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Neurofeedback training, which enables the trainee to learn self-control of the EEG activity of interest based on online feedback, has demonstrated benefits on cognitive and behavioral performance. Nevertheless, as a core mechanism of neurofeedback, learning of EEG regulation (i.e., EEG learning) has not been well understood. Moreover, a substantial number of non-learners who fail to achieve successful EEG learning have often been reported. This study investigated the EEG learning in alpha down-regulation neurofeedback, aiming to better understand the alpha learning and to early predict learner/non-learner. Twenty-nine participants received neurofeedback training to down-regulate alpha in two days, while eight of them were identified as non-learners who failed to reduce their alpha within sessions. Through a stepwise linear discriminant analysis, a prediction model was built based on participant’s eyes-closed resting EEG activities in broad frequency bands including lower alpha, theta, sigma and beta 1 measured before training, which was validated in predicting learners/non-learners. The findings would assist in the early identification of the individuals who would not likely reduce their alpha during neurofeedback.

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“…Such EEG-based neurofeedback training has been used clinically, in order for example to suppress epileptic activity [20], or to treat symptoms of attention deficit hyperactivity disorder (ADHD) [21][22][23]. It has also been used to optimize performance in healthy volunteers, for example improving vision [24], memory [25][26][27], motor learning [28], musical performance [29], and cognitive processing speed [30] (see [31,32 ] for an overview). The main advantages of EEG as a tool for neurofeedback are that it is portable, relatively inexpensive, and that it has a very high temporal resolution.…”

Section: Neurofeedbackmentioning

confidence: 99%