Sharpening Working Memory With Real-Time Electrophysiological Brain Signals: Which Neurofeedback Paradigms Work? - Jiang, Yang; Jessee, William; Hoyng, Stevie; Borhani, Soheil; Liu, Ziming; Zhao, Xiaopeng; Price, Lacey K.; High, Walter; Suhl, Jeremiah; Cerel-Suhl, Sylvia (Frontiers in Aging Neuroscience, 2022)
Growing evidence supports the idea that the ultimate biofeedback is to reward sensory pleasure (e.g. enhanced visual clarity) in real-time to neural circuits that are associated with a desired performance, such as excellent memory retrieval. Neurofeedback is biofeedback that uses real-time sensory reward to brain activity associated with a certain performance (e.g. accurate and fast recall). Working memory is a key component of human intelligence. The challenges are in our current limited understanding in neurocognitive dysfunctions as well as in technical difficulties for closed-loop feedback in true real-time. Here we review recent advancements of real time neurofeedback to improve memory training in healthy young and older adults. With new advancements in neuromarkers of specific neurophysiological functions, neurofeedback training should be better targeted beyond a single frequency approach to include frequency interactions and event-related potentials. Our review confirms the positive trend that neurofeedback training mostly works to improve memory and cognition to some extent in most studies. Yet, the training typically takes multiple weeks with 2-3 sessions per week. We review various neurofeedback reward strategies and outcome measures. A well-known issue in such training is that some people simply do not respond to neurofeedback. Thus, we also review the literature of individual differences in placebo effects and so-called “BCI illiteracy” (Brain Computer Interface). We recommend the use of Neural modulation sensitivity instead of “BCI illiteracy” in the neurofeedback literature. Future directions can include much needed research in mild cognitive impairment, in non-Alzheimer’s dementia, and in the use of sleeping EEG components as sensitive outcome measures.