Motor imagery-based neurofeedback in older adults: neural signatures and feasibility in a randomized controlled trial targeting age-related cognitive decline

Abstract

Background Neurofeedback (NF) is a non-invasive endogenous stimulation technique that enables individuals to voluntarily modulate brain activity, which has shown potential to induce neuroplasticity. Among its promising applications is cognitive enhancement in healthy older adults to prevent age-related cognitive decline. However, its efficacy remains controversial due to methodological limitations and a high proportion of individuals unable to achieve effective self-regulation, known as non-responders. This study aimed (1) to evaluate the feasibility of motor imagery (MI)-based NF training in older adults and characterize associated brain activity patterns; and (2) to assess its potential cognitive benefits through a randomized, double-blind, controlled design.

Methods Ninety-two healthy participants aged 65–75 were randomly assigned to a training (TG), placebo (PG), or control group (CG). TG and PG completed ten electroencephalography (EEG)-based NF sessions over ten weeks, while CG engaged in ten classical cognitive stimulation sessions. All participants completed a comprehensive neuropsychological evaluation prior to and following the intervention. EEG data from the NF training sessions were analyzed using spectral and network metrics to characterize modulations in local activity and large-scale functional network patterns induced by the intervention.

Results Although a substantial proportion of TG participants achieved high MI accuracy values, statistical analyses revealed no cognitive improvements specific to TG, suggesting limited efficacy of the MI-based protocol compared to classical cognitive stimulation. Spectral and network analyses identified distinct modulation patterns during MI in responders, absent in non-responders. Moreover, specific resting-state features—namely increased (13–20 Hz) band relative power and reduced (8–13 Hz) band node strength—were associated with better self-regulation performance.

Conclusions The present study did not provide conclusive evidence supporting the effectiveness of MI-based NF training for cognitive enhancement in older adults. Nonetheless, the results offer valuable insights that may inform the refinement of future NF-based cognitive training protocols. Moreover, our findings suggest that baseline functional network organization may play a key role in determining the capacity for successful self-regulation. Identifying additional neurophysiological biomarkers will be essential to advance our understanding of the non-responsiveness phenomenon and to enable the development of more personalized NF interventions.