TY - JOUR

T1 - Neurofeedback and neural self-regulation

T2 - A new perspective based on allostasis

AU - Mirifar, Arash

AU - Keil, Andreas

AU - Ehrlenspiel, Felix

N1 - Funding Information: Research funding: AM and FE received no financial support for the research, authorship, and/or publication of this article. AK was supported by grant R01MH112558, by the National Institute of Mental Health.

PY - 2022/8/26

Y1 - 2022/8/26

N2 - The field of neurofeedback training (NFT) has seen growing interest and an expansion of scope, resulting in a steadily increasing number of publications addressing different aspects of NFT. This development has been accompanied by a debate about the underlying mechanisms and expected outcomes. Recent developments in the understanding of psychophysiological regulation have cast doubt on the validity of control systems theory, the principal framework traditionally used to characterize NFT. The present article reviews the theoretical and empirical aspects of NFT and proposes a predictive framework based on the concept of allostasis. Specifically, we conceptualize NFT as an adaptation to changing contingencies. In an allostasis four-stage model, NFT involves (a) perceiving relations between demands and set-points, (b) learning to apply collected patterns (experience) to predict future output, (c) determining efficient set-points, and (d) adapting brain activity to the desired ("set") state. This model also identifies boundaries for what changes can be expected from a neurofeedback intervention and outlines a time frame for such changes to occur.

AB - The field of neurofeedback training (NFT) has seen growing interest and an expansion of scope, resulting in a steadily increasing number of publications addressing different aspects of NFT. This development has been accompanied by a debate about the underlying mechanisms and expected outcomes. Recent developments in the understanding of psychophysiological regulation have cast doubt on the validity of control systems theory, the principal framework traditionally used to characterize NFT. The present article reviews the theoretical and empirical aspects of NFT and proposes a predictive framework based on the concept of allostasis. Specifically, we conceptualize NFT as an adaptation to changing contingencies. In an allostasis four-stage model, NFT involves (a) perceiving relations between demands and set-points, (b) learning to apply collected patterns (experience) to predict future output, (c) determining efficient set-points, and (d) adapting brain activity to the desired ("set") state. This model also identifies boundaries for what changes can be expected from a neurofeedback intervention and outlines a time frame for such changes to occur.

KW - allostasis framework

KW - neurofeedback training

KW - psychophysiological regulation

KW - self-regulation

UR - http://www.scopus.com/inward/record.url?scp=85124630107&partnerID=8YFLogxK

U2 - 10.1515/revneuro-2021-0133

DO - 10.1515/revneuro-2021-0133

M3 - Review article

C2 - 35122709

AN - SCOPUS:85124630107

VL - 33

SP - 607

EP - 629

JO - Reviews in the neurosciences

JF - Reviews in the neurosciences

SN - 0334-1763

IS - 6

ER -