TY - JOUR
T1 - Sharpening Working Memory With Real-Time Electrophysiological Brain Signals
T2 - Which Neurofeedback Paradigms Work?
AU - Jiang, Yang
AU - Jessee, William
AU - Hoyng, Stevie
AU - Borhani, Soheil
AU - Liu, Ziming
AU - Zhao, Xiaopeng
AU - Price, Lacey K.
AU - High, Walter
AU - Suhl, Jeremiah
AU - Cerel-Suhl, Sylvia
N1 - Publisher Copyright:
Copyright © 2022 Jiang, Jessee, Hoyng, Borhani, Liu, Zhao, Price, High, Suhl and Cerel-Suhl.
PY - 2022/3/28
Y1 - 2022/3/28
N2 - 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.
AB - 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.
KW - BCI illiteracy
KW - EEG-ERPs
KW - biofeedback
KW - brain computer interface (BCI)
KW - closed-loop feedback
KW - working memory
UR - http://www.scopus.com/inward/record.url?scp=85128368806&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85128368806&partnerID=8YFLogxK
U2 - 10.3389/fnagi.2022.780817
DO - 10.3389/fnagi.2022.780817
M3 - Review article
AN - SCOPUS:85128368806
SN - 1663-4365
VL - 14
JO - Frontiers in Aging Neuroscience
JF - Frontiers in Aging Neuroscience
M1 - 780817
ER -