Enhancing Attention in Older Adults: Lessons from fMRI Neurofeedback

As we age, our ability to focus on relevant information while ignoring distractions—known as selective attention—tends to decline. This cognitive shift is linked to changes in brain regions responsible for executive functions, particularly the dorsal anterior cingulate cortex (dACC). The dACC plays a crucial role in inhibitory control, which directly influences selective attention, helping us prioritize important information amidst distractions. Age-related declines in dACC function can lead to slower reaction times and reduced accuracy in tasks requiring sustained focus.

A recent study explored whether neurofeedback training could counteract these age-related declines. Using real-time fMRI neurofeedback, researchers trained older adults to regulate their dACC activity while performing a selective attention task. Over multiple training sessions, participants learned to increase dACC activation, leading to improved focus and faster reaction times. The study found not only increased dACC activity but also significant behavioral improvements in task accuracy and speed. These findings suggest that neurofeedback may be a promising tool for strengthening cognitive function in aging populations.

By investigating specific neurofeedback protocols, this research paves the way for potential applications in both fMRI and EEG neurofeedback, making these interventions more accessible for improving attention in older adults.

Methods

The study investigated how real-time fMRI neurofeedback could help older adults enhance selective attention. A total of 46 participants, including both younger and older adults, were divided into different training groups. The primary group—older adults in the up-regulation condition—received neurofeedback to increase dACC activity, as this brain region is essential for attention and cognitive control, particularly in tasks requiring distraction management.

Training Protocol:

Participants performed the Multi-Source Interference Task (MSIT) while receiving real-time feedback on their dACC activity. The MSIT required them to identify unique numbers within a sequence while ignoring distracting emotional expressions or faces.

During neurofeedback training, older adults aimed to earn “reward points” by increasing dACC activation, with a performance-based bonus of up to $100. The study also included:

• A control group of older adults trained to reduce dACC activity.

• A group of younger adults trained to increase dACC activity.

This design allowed researchers to assess age-related differences in neurofeedback training success.

Real-Time fMRI Feedback:

The neurofeedback system measured BOLD (Blood Oxygen Level Dependent) signals in the dACC, adjusting feedback based on individual baseline scans. Over seven training sessions, participants received continuous real-time feedback, enabling them to gradually learn how to control their dACC activity.

By comparing the effects of up-regulation vs. down-regulation of dACC activity, researchers assessed how neurofeedback training impacted attention performance in aging individuals.

Results

Key Findings:

• Older adults trained to increase dACC activity successfully enhanced their selective attention.

  • This group showed higher dACC activation and earned more reward points across training sessions, indicating they were effectively learning to regulate their brain activity.

• Improved attention performance was observed, with faster reaction times and greater accuracy on the MSIT task over time.

• Control groups (younger adults and older adults trained to reduce dACC activity) did not show similar benefits.

The Brain-Behavior Link:

A direct correlation emerged between increased dACC activity and improved behavioral performance. Older adults in the up-regulation group consistently outperformed those in the down-regulation condition, suggesting that boosting dACC activation plays a crucial role in maintaining attentional control in aging.

Interestingly, younger adults did not show significant benefits from the training, possibly due to differences in cognitive needs or motivation. Conversely, older adults who reduced dACC activity experienced a decline in task performance, reinforcing the importance of dACC activation for selective attention in aging populations.

Discussion

Enhancing Cognitive Aging Through Neurofeedback

This study demonstrates that real-time fMRI neurofeedback can effectively improve selective attention in older adults by targeting the dACC. By focusing on distraction management, researchers trained participants to actively regulate a brain region crucial for sustained attention. These findings highlight neurofeedback’s potential to support cognitive aging by promoting neuroplasticity—the brain’s ability to adapt and reorganize itself through training.

Implications for Neurofeedback Practitioners

The results underscore the value of individualized neurofeedback protocols in clinical settings. By targeting specific brain regions or neural networks, practitioners can tailor training to clients experiencing age-related cognitive decline. Compared to traditional cognitive interventions, neurofeedback provides a direct pathway to modulating brain activity, leading to more sustained behavioral improvements.

For healthcare professionals, this study supports the clinical relevance of neurofeedback over generalized cognitive training programs. By promoting selective neural activation, neurofeedback offers a targeted, evidence-based approach to enhancing cognitive resilience in aging.

Future Research and Considerations

One intriguing aspect of the study is the motivation factor—older adults remained more engaged over time, which may have contributed to their success. Future research should explore personalized neurofeedback protocols that adapt to individual motivation levels and cognitive needs. Additionally, investigating EEG-based adaptations could make neurofeedback more accessible and cost-effective for broader clinical applications.

Brendan’s Perspective

This study offers valuable insights for both fMRI-based and qEEG-based neurofeedback approaches.

Targeted Brain Training

By focusing on the dACC, the study illustrates the power of targeted neurofeedback training. In qEEG neurofeedback, while spatial precision is lower than in fMRI, training specific frequency bands—such as theta, alpha, and SMR—can enhance attention and cognitive control. The success of increasing dACC activity suggests that boosting theta or alpha frequencies in similar cortical regions could yield comparable attention benefits, making qEEG neurofeedback an accessible alternative for older adults.

qEEG Parallels and Protocol Optimization

The study’s up-regulation vs. down-regulation design highlights the importance of protocol specificity—a principle that translates well to EEG neurofeedback. Training theta in frontal regions or SMR in sensorimotor areas may similarly improve attentional control, offering a practical way to apply these findings outside of fMRI settings.

Accessibility and Real-World Application

qEEG neurofeedback presents a cost-effective and scalable solution compared to fMRI. By targeting neural markers of attention, qEEG-based training can replicate the benefits of dACC-focused neurofeedback in clinics and home settings, making cognitive enhancement more widely available for aging populations.

Conclusion

This study provides compelling evidence that real-time fMRI neurofeedback can improve selective attention in older adults by increasing dACC activity. The observed gains in attention and task performance underscore neurofeedback’s potential to support cognitive health in aging.

Crucially, these findings also suggest that qEEG-based adaptations could provide a more accessible alternative for enhancing attention in older adults. As neurofeedback continues to gain recognition as a powerful cognitive enhancement tool, this study reinforces the importance of protocol-specific approaches—demonstrating that targeting key brain regions or frequency bands can produce tangible cognitive benefits.

Reference

Lin, T., Rana, M., Liu, P., Polk, R., Heemskerk, A., Weisberg, S. M., Bowers, D., Sitaram, R., & Ebner, N. C. (2024). Real-Time fMRI Neurofeedback Training of Selective Attention in Older Adults. Brain Sciences, 14(931). https://doi.org/10.3390/brainsci14090931