A theoretical framework for investigating/improving neurofeedback success
-
1
Birkbeck College, Department of Psychological Sciences, United Kingdom
In a recent commentary, Thibault and Raz (2015) critically state that neurofeedback can only be acceptable as part of a clinical toolbox when three challenges are met: (1) similar therapeutic results as standard treatments, (2) outperform placebo controls, and (3) provide a clear mechanism underlying therapeutic benefits. They report that only one properly conducted study exists (on stroke), highlighting that after decades of work, neurofeedback studies still omit crucial (methodological and statistical) information or simply show benefits of medication over neurofeedback. Thus, the jury is still out whether to accept EEG neurofeedback.
In this talk, I will focus on a framework in which the mechanisms of successful neurofeedback can be understood (addressing point 3). In particular, the theory is described at the neuronal level and integrates work from single-cell recordings and system neuroscience and in doing so harnesses the knowledge from the two disciplines to address the neural mechanisms of successful neurofeedback. The theory is implemented as a computer simulation of alpha upregulation, but in principle any (arbitrary) frequency band at one or more electrode sites could be addressed. The system generates EEG time-series that are analysed in real-time to provide feedback. It is shown that the compuer simulation indeed learns to upregulate alpha, but that there are limits, such that beyond a certain level any further training would be fruitless. Critically, the framework includes the methodology used in the neurofeedback, making it possible to evaluate and optimise methodological practice. A mathematical abstraction of the implemented model explores the impact of threshold setting on the maximum amount of learning that can be achieved. In mathematical terms, neurofeedback can be conceptualised as a search process that uses importance sampling to estimate the posterior probability distribution over representational space, with each representation being associated with a probability distribution of values of the target EEG band. The findings show that successful neurofeedback requires (1) passive learning through rejection sampling, (2) placing the threshold such to minimise false alarms, and (3) knowledge of the target distribution of EEG values. In the absence of the latter, a simple adaptive threshold algorithm is explored to approximate the target distribution.
The framework allows (1) personalisation and monitoring of neurofeedback methodology to maximise the likelihood of success above and beyond placebo effect (to address TR's points 1 and 2), (2) incorporation of (dose-dependent) drug actions to explore drug-neurofeedback interactions, and (3) theoretical evaluation of existing or new protocols before embarking on costly clinical trials (to address TR's point 1).
Keywords:
computational modeling,
EEG,
Neurofeedback,
brain training,
BCI
Conference:
SAN2016 Meeting, Corfu, Greece, 6 Oct - 9 Oct, 2016.
Presentation Type:
Oral Presentation in SAN 2016 Conference
Topic:
Oral Presentations
Citation:
Davelaar
EJ
(2016). A theoretical framework for investigating/improving neurofeedback success.
Conference Abstract:
SAN2016 Meeting.
doi: 10.3389/conf.fnhum.2016.220.00024
Copyright:
The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers.
They are made available through the Frontiers publishing platform as a service to conference organizers and presenters.
The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated.
Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed.
For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions.
Received:
29 Jul 2016;
Published Online:
30 Jul 2016.
*
Correspondence:
Dr. Eddy J Davelaar, Birkbeck College, Department of Psychological Sciences, London, WC1E7HX, United Kingdom, frontierscognitivescience.sce@gmail.com