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.
Cognitive aging has become a major social concern because life expectancy has increased (Baltes and Lindenberger, 1997). To preserve cognitive reserve in aging populations, research in cognitive training increased (Baltes et al., 1989), and researchers have developed tools favoring cognitive maintenance. It is known that there is a positive correlation between fluid intelligence and cognitive reserve, as well Additionally, neurofeedback has been used to neuromodulate psychiatric and neurological conditions such as epilepsy, anxiety, depression and addiction (Hardt and Kamiya, 1978; Sterman, 1996; Thompson and Thompson, 1998; Hammond, 2005), and most were treated using SMR training (see Monastra et al., 2005). as, executive function, mainly in working memory, attention and information processing (Craik and Bialystok, 2006). However, natural changes expected in cognitive aging also affect these capabilities; therefore, these changes can be a burden to a population that is still socially active. To counteract these changes, neurofeedback, a form of neuromodulation in which individuals have information about their neurological state and are able to self-regulate their brain activity through an operant conditioning paradigm, may be a technique to preserve cognitive reserve.
During neurofeedback training, an individual receives, through a computational interface, real-time visual and/or audio information about their brain wave activity as feedback after achieving a goal. Moreover, neurofeedback training works dynamically in the cortex, that is, it can induce the individual to increase the rhythm or amplitude of a specific frequency range in the cortex; likewise, it can inhibit the rhythm or amplitude of another frequency range, either in the same training protocol or during separate training when the parameter is electrical brain activity. Accordingly, the cognitive model of Lacroix (1986) provides a broader view of neurofeedback training; it suggests that brain modification occurs not only through operant conditioning feedback but also by the modification of the individual’s perception of his physiological state, thus promoting a cognitive integration of the conditioned behavior. Therefore, there are two processes involved with neurofeedback: one is unconscious by operant conditioning and the other is conscious cognitive self-perception.
One of the firsts protocol that evaluated the association between operant conditioning and brain activity was performed by Sterman et al. (1970), in which cats trained to increase activation at 12–15 Hz in the sensory motor area were shown to be resistant to hydrazine, a convulsive compound. Afterwards, they successfully tested this protocol in humans with seizure disorders to diminish seizures, this frequency band is known as sensorimotor rhythm (SMR).
Thereafter, Lubar and Lubar (1984) tested the same protocol to increase SMR in hyperkinetic children with ADHD and demonstrated that this protocol was able to reduce excessive motor movements and increase attention.
The circuitry of SMR is a thalami-cortical, bottom-up mechanism that reduces the interference of somatosensory information, as the motor activity can interfere in information processing that results in diminished cognitive performance (Kober et al., 2015). Therefore, this inhibition, driven by the increase in SMR, leads to a greater integration of information processing in the cortex, and the SMR neurofeedback training acts within the inhibitory mechanism of the thalamic circuitry (Egner and Gruzelier, 2004). Although, Kropotov (2009) proposed that SMR is part of the alpha rhythms, similar to mu activation as thalami-cortical desynchronization with eyes opened.
Additionally, neurofeedback has been used to neuromodulate psychiatric and neurological conditions such as epilepsy, anxiety, depression and addiction (Hardt and Kamiya, 1978; Sterman, 1996; Thompson and Thompson, 1998; Hammond, 2005), and most were treated using SMR training (see Monastra et al., 2005).
Studies of neurofeedback training in healthy, young populations have indicated that the standard SMR protocol might be an efficient method to increase semantic working memory, improve attention and perceptive ability; reduce reaction times and errors by commission (Vernon et al., 2003). On the other hand, studies on cognitive aging have highlighted the need for new instruments, technologies and tools that benefit the protection and preservation of brain activity, as its decline compromises quality of life and increases risk factors for dementia (Lustig et al., 2009). Therefore, the neurofeedback protocol presented in this article was designed to enhance cognitive performance in aging people.