Sharpening Working Memory With Real-Time Electrophysiological Brain Signals: Which Neurofeedback Paradigms Work?

Yang Jiang, William Jessee, Stevie Hoyng, Soheil Borhani, Ziming Liu, Xiaopeng Zhao, Lacey K. Price, Walter High, Jeremiah Suhl, Sylvia Cerel-Suhl

Research output: Contribution to journalReview articlepeer-review

7 Scopus citations


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 of 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 psychological factors e.g., placebo effects and so-called “BCI illiteracy” (Brain Computer Interface illiteracy). We recommend the use of Neural modulation sensitivity or BCI insensitivity in the neurofeedback literature. Future directions include much needed research in mild cognitive impairment, in non-Alzheimer’s dementia populations, and neurofeedback using EEG features during resting and sleep for memory enhancement and as sensitive outcome measures.

Original languageEnglish
Article number780817
JournalFrontiers in Aging Neuroscience
StatePublished - Mar 28 2022

Bibliographical note

Publisher Copyright:
Copyright © 2022 Jiang, Jessee, Hoyng, Borhani, Liu, Zhao, Price, High, Suhl and Cerel-Suhl.


  • BCI illiteracy
  • EEG-ERPs
  • biofeedback
  • brain computer interface (BCI)
  • closed-loop feedback
  • working memory

ASJC Scopus subject areas

  • Aging
  • Cognitive Neuroscience


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