Individual alpha neurofeedback training effect on short term memory
Highlights
► The individual alpha amplitude could be increased during neurofeedback training. ► Short term memory assessed by digit span was improved by neurofeedback training. ► Short term memory increase was correlated with individual upper alpha increase. ► The successful mental strategies varied among individuals. ► The most successful strategy type was related to positive thinking.
Introduction
The relation between memory performance and electroencephalogram (EEG) alpha activity has been reported by several studies in the last two decades (Klimesch, 1996, Klimesch, 1999, Klimesch et al., 2006). It has been observed that memory performance is positively related to resting power in the alpha band (Klimesch, 1999). One interesting question from the association between memory and alpha is, whether short term memory performance can be improved through the enhancement of alpha power by means of neurofeedback training (NFT).
NFT is an operant conditioning procedure in which individuals learn to self-regulate their brain activity. During NFT, the EEG is recorded from one or more electrodes placed on the scalp and the relevant components are extracted and fed back using an online feedback loop in the form of audio, visual or combined audio-visual information (Vernon, 2005). A number of studies have demonstrated the positive effects of NFT on treatment of psychological disorders such as attention deficit hyperactivity disorder (Friel, 2007, Heinrich et al., 2007), substance use disorder (Sokhadze et al., 2008), epilepsy (Sterman and Egner, 2006, Egner and Sterman, 2006) and autistic spectrum disorder (Coben et al., 2010). Besides clinical applications, the benefits of NFT have also been reported in enhancement of cognitive and artistic performance in healthy individuals (Egner and Gruzelier, 2003, Gruzelier et al., 2006, Gruzelier, 2009). For instance, semantic working memory can be enhanced by sensorimotor rhythm (SMR) NFT (Vernon et al., 2003) or by individual upper alpha NFT (Escolano et al., 2011). For mental rotation ability, it can be improved by NFT using SMR (Doppelmayr and Weber, 2011) or using individual upper alpha (Hanslmayr et al., 2005, Zoefel et al., 2011). In addition, increasing peak alpha frequency (PAF) by NFT can improve the cognitive processing speed and executive function in the elderly individuals (Angelakis et al., 2007).
Even though an increasing amount of studies reported positive effects of NFT in some fields, there is still a lack of successful NFT for the improvement in short term memory which refers to the temporary storage of information without the attention component of working memory (Conway et al., 2002, Stipacek et al., 2003). The early work by Bauer (1976) investigated the effect of fixed alpha frequency band (8.5–12.5 Hz) NFT on short term memory in young adults. The participants were asked to produce alpha as long as possible during the training. Short term memory performance was assessed by a verbal free recall task and a digit span task. Although a significant increase in the percentage alpha was achieved by the end of the four sessions, neither digit span task nor verbal free recall task showed improvement. Vernon (2005) stated that this failure could be explained by the use of a fixed frequency band instead of individual alpha frequency range as proposed by Klimesch (1999). Due to the large inter-individual differences in alpha frequency band, the personalization of alpha band is the only way to observe and interpret any findings that involve alpha frequency band (Klimesch, 1999, Klimesch et al., 2003). Another possible reason for the failure in Bauer (1976) is that the feedback parameter was the percentage alpha in terms of time instead of the alpha power that is related to memory performance (Klimesch, 1999).
Moreover, the mental strategies used during the NFT have not been provided with sufficient details in the literature. Angelakis et al. (2007) only described two subjects' self-report during alpha amplitude NFT. Suggestions on mental strategies to be used during NFT shall contribute greatly to increase the rate of successful NFT learning.
Considering the relation between memory performance and alpha power as well as the importance of personalization of alpha band (Klimesch, 1999), this study aimed to improve short term memory performance by individual alpha NFT. More specifically, we attempted to answer three questions, namely, (a) whether NFT can increase the relative amplitude in individual alpha band, (b) whether this increase in individual alpha band is correlated with short term memory improvement, and (c) which mental strategies are more effective for the training.
Section snippets
Participants
A total of 32 students (22 males and 10 females, aged 20–29 years: mean = 23.28, SD = 3.11) took part in the experiment. Informed written consent was obtained from all participants after the experimental nature and procedure were interpreted to them. The protocol was approved by the Research Ethics Committee (University of Macau).
EEG recordings
During the experiment, the participants sat in a quiet room. The EEG signal was recorded from Cz channel (according to the international 10–20 system) with a sampling
EEG results
The average of the relative amplitude in individual alpha band of all subjects showed increase over sessions. Further Pearson correlation test indicated that it had significant positive correlation with session number, indicating that the subjects could learn to increase their alpha activity by NFT (successful neurofeedback learning). This was a positive answer to Question (a) in the Introduction section. Besides individual alpha band, alpha, sigma, individual lower alpha and individual upper
Discussion
As expected, the participants in the NFT group can learn to increase the relative amplitude in individual alpha band during training sessions. Several key features in this training protocol were responsible for the successful neurofeedback learning. Firstly, the participants were familiar with the training display through the first two user control sessions, and they could try any strategies they like to observe the training effect. After this, they can gain some experience on how to
Acknowledgments
This work is supported in part by FCT SFRH/BSAB/1101/2010 and PEst-OE/EEI/LA0009/2011 grants and the Macau Science and Technology Development Fund under grant FDCT 036/2009/A and the University of Macau Research Committee under grants MYRG139(Y1-L2)-FST11-WF and MYRG079(Y1-L2)-FST12-VMI.
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