Neurofeedback Can Protect and Enhance the Aging Brain
- John Davis
- 3 days ago
- 7 min read
What Is the Science of Training the Aging Brain?
Over the past 10 years, researchers have gradually changed how they think about protecting and enhancing cognitive health in older adults.
Instead of relying entirely on traditional behavioral exercises, scientists are increasingly exploring methods that target brain activity directly. Neurofeedback has become one of the most exciting developments in this area.
The basic concept is straightforward: the brain generates rhythmic electrical patterns that reflect how well a person is paying attention, remembering information, and preparing for mental tasks. These rhythms can change when people receive moment-to-moment information about what their brains are doing.
The two papers reviewed here approach this idea from different directions.
Jiang and colleagues offer a comprehensive theoretical overview of how electrophysiological feedback might sharpen working memory. At the same time, Wiłkość-Dębczyńska and her research team investigated a structured neurofeedback program in older adults with varying levels of cognitive functioning.
When read together, these works reveal a field evolving toward more precise and practical approaches to supporting cognition as people age.
What Did They Study?
Jiang and colleagues (2022) surveyed the broad landscape of neurofeedback for memory improvement, pulling together findings from dozens of studies to understand which approaches work, which ones fall short, and why some people benefit more than others. Their review covers healthy younger participants, healthy older adults, and individuals diagnosed with mild cognitive impairment.
The study by Wiłkość-Dębczyńska and colleagues (2024) took a different approach, focusing on a single training protocol delivered via a commercial system called NeuroPlay. Their participants included healthy older adults, people with mild cognitive impairment, and individuals with mild dementia.
The research team wanted to determine whether a 4-week training program could improve specific cognitive performance domains and whether certain groups of participants responded better than others.
How Did They Do It?
The review by Jiang and colleagues brings together neurofeedback studies that use electroencephalography, with special attention to frequency-based training approaches such as alpha, theta, beta, and sensorimotor rhythm protocols, along with the growing interest in event-related potentials. Across the studies they examined, training typically involved repeated sessions where participants tried to change particular brainwave patterns while receiving visual or auditory feedback about their success.
The authors point out several challenges that complicate this research, including placebo effects, the difficulty of creating double-blind study designs, and a phenomenon called brain-computer interface insensitivity, which refers to the fact that many participants cannot learn to produce the targeted brainwave changes, no matter how hard they try.
Wiłkość-Dębczyńska and colleagues used a carefully structured protocol in their study. Participants wore a 10-sensor EEG headband that connected to computer-based cognitive games, which responded to their brainwave activity in real time.
The system was designed to encourage increases in theta and alpha activity in the occipital regions at the back of the head, using fast Fourier transform algorithms to update the feedback in real time.
The program ran for 4 weeks, with two 45-minute sessions per week. An active control group completed traditional paper-and-pencil cognitive training exercises instead of neurofeedback. Before and after training, all participants completed a thorough neuropsychological test battery that measured attention, memory, language abilities, processing speed, and executive functioning.
What Did They Find?
Across the studies reviewed by Jiang and colleagues, neurofeedback consistently produced modest improvements in working memory and attention in both younger and older adults.
Not every training approach succeeded, and the size of the improvements varied considerably across studies. Even so, most studies reported positive effects on cognition, including studies with older adults who had mild cognitive impairment.
The review also highlighted that people differ dramatically in how well they respond to neurofeedback, with factors such as motivation, mood, expectations of success, and underlying differences in brain function all playing a role. The authors made an important observation that training focused on a single brainwave frequency may be too narrow an approach, and that the interaction between different rhythms, such as the coupling between theta and gamma waves, may hold greater promise for improving memory.
The findings from Wiłkość-Dębczyńska and colleagues were more focused and specific. Neurofeedback training improved scores on the ACE-III cognitive screening test in both the mild cognitive impairment and mild dementia groups, suggesting gains in attention, memory, and language.
For people with mild cognitive impairment, performance on the forward digit span task improved meaningfully only among those who received neurofeedback, not among those who received control training. Errors on the Continuous Performance Task also decreased in this group, suggesting sharper sustained attention.
Interestingly, healthy participants did not show broad cognitive gains from the training, and their simple reaction time actually slowed slightly. This pattern suggests that neurofeedback may be most helpful when cognitive systems are already struggling. Across all groups, some abilities did not improve at all, including verbal learning, executive functioning, and processing speed. This tells us that neurofeedback does not boost all cognitive processes equally.
What Were the Strengths and Limitations?
The review by Jiang and colleagues stands out for its breadth. It systematically identifies the wide variety of neurofeedback approaches that have been tried, the complexity of different EEG markers, and the methodological problems that make it hard to draw firm conclusions. By including both successful and unsuccessful studies, the authors provide a clearer picture of what factors seem to matter most for good outcomes. At the same time, the review inherits the field's weaknesses: long-term follow-up data are scarce, many studies lack rigorous control conditions, and most training protocols target only a narrow aspect of brain function.
The study by Wiłkość-Dębczyńska and colleagues has several notable strengths, including a reasonably large sample size, clear comparisons between groups, and an active control condition rather than simply comparing neurofeedback to no treatment. Their training protocol is practical and relatively brief, and it uses technology that could realistically be adopted in clinical practices and community settings.
However, some limitations should be noted.
Several cognitive measures showed no change, suggesting that the improvements may be specific to certain domains rather than reflecting a general boost in brain function.
The study did not include long-term follow-up assessments, so we do not know whether the benefits lasted after training ended. The control groups for participants with mild cognitive impairment and mild dementia were also quite small, which limits how confidently we can interpret the comparisons.
What Was the Impact?
Together, these two papers move the field toward a more sophisticated understanding of what neurofeedback can and cannot do for aging adults.
Jiang and collaborators map out the theoretical and methodological terrain that researchers need to navigate if neurofeedback is going to advance as a scientific field, calling for more advanced biomarkers, better reward strategies during training, and improved study designs that can address placebo effects.
Wiłkość-Dębczyńska and colleagues show that a streamlined, practical neurofeedback program can produce real and measurable improvements in attention and memory for people at risk of cognitive decline.
Their results support the idea that neurofeedback could become a useful addition to traditional cognitive training approaches, particularly for individuals with mild cognitive impairment.
These contributions strengthen the growing evidence that EEG-guided brain training may offer meaningful cognitive benefits during aging, while also making clear that the technology works differently for different people and affects some cognitive abilities more than others.
Key Takeaways
Neurofeedback provides real-time information about brain activity to help shape attention and memory processes, offering a biologically grounded approach to cognitive training that differs from traditional behavioral exercises.
Research across many studies shows that older adults, including those with mild cognitive impairment, can benefit from neurofeedback training, though the benefits are not uniform across individuals or cognitive abilities.
A four-week training protocol targeting theta and alpha rhythms can improve specific cognitive domains, particularly attention and short-term memory, in individuals with pre-existing cognitive vulnerabilities.
How well someone responds to neurofeedback varies considerably from person to person, influenced by neural factors, motivation levels, expectations about whether the training will work, and how well the person was functioning cognitively before training began.
The field is evolving toward more sophisticated training approaches that incorporate multiple frequency bands, examine how different brain rhythms interact, and use improved study designs to ensure that outcomes are lasting and clinically meaningful for the people who need them most.
Glossary
ACE-III cognitive screening test: a standardized clinical assessment evaluating attention, memory, fluency, language, and visuospatial abilities, commonly used to detect cognitive impairment.
alpha waves: a rhythmic pattern of brain activity associated with relaxed wakefulness and linked to memory and attentional processes.
beta waves: a pattern of brain activity reflecting active thinking, concentration, and motor planning.
brain–computer interface (BCI) insensitivity: a condition in which an individual is unable to learn or reliably perform the neural modulations required for successful neurofeedback performance.
Continuous Performance Task (CPT): a computerized test of sustained attention and response inhibition in which individuals must respond to target stimuli while withholding responses to non-targets.
electroencephalography (EEG): a method of measuring electrical activity generated by the brain through sensors placed on the scalp.
event-related potentials: electrical brain responses that occur following specific sensory or cognitive events.
forward digit span task: a short-term memory test requiring participants to repeat increasingly long sequences of digits in the same order presented, indexing attention and immediate verbal memory.
gamma rhythms: high-frequency brain oscillations associated with sensory integration and working memory.
placebo effects: psychological or physiological changes that occur because an individual expects a treatment to help, rather than because of the treatment’s active components.
sensorimotor rhythm: a mid-frequency brainwave pattern associated with movement inhibition and attentional readiness.
theta waves: a lower-frequency brain rhythm involved in working memory, learning, and encoding of new information.
theta–gamma coupling: an interaction between slow and fast brain rhythms believed to support working memory and information binding.
References
Jiang, Y., Jessee, W., Hoyng, S., Borhani, S., Liu, Z., Zhao, X., Price, L. K., High, W., Suhl, J., & Cerel-Suhl, S. (2022). Sharpening working memory with real-time electrophysiological brain signals: Which neurofeedback paradigms work? Frontiers in Aging Neuroscience, 14, 780817. https://doi.org/10.3389/fnagi.2022.780817
Wiłkość-Dębczyńska, M., Zając-Lamparska, L., Liberacka-Dwojak, M., Kukuła, D., & Werońska, A. (2024). Effectiveness of neurofeedback-based cognitive training in older adults. Human Technology, 20(2), 384–398. https://doi.org/10.14254/1795-6889.2024.20-2.7
About the Author
Dr. John Raymond Davis is an adjunct lecturer in the Department of Psychiatry and Behavioural Neurosciences at McMaster University's Faculty of Health Sciences. His scholarly contributions include research on EEG changes in major depression and case studies on neurological conditions. ​
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