Effects of Olfactory Learning Context Reactivation During Sleep on Training Success in a Double‐Blind Randomized Controlled Sensorimotor Rhythm Neurofeedback Protocol: A Pilot Study

Neurofeedback training (NFT) is used to modulate brain activity for therapeutic purposes in different patient populations. However, tested training protocols vary in several aspects, and the results of therapeutic benefit have been heterogeneous. The aim of the current study was to compare a SMR against a random frequency protocol and potentially strengthen NFT effects via olfactory context reactivation during sleep in a compact training protocol. 49 participants (mean age: 24.7 years; 29 women) without any neurological or psychiatric disorder were randomly (double-blind) assigned to three groups: sensorimotor rhythm (SMR) with or without context reactivation, or random frequencies with reactivation during sleep. Within 2 weeks, participants underwent eight training sessions (12 × 2 min training intervals) and slept three nights in the sleep lab. NFT sessions were scheduled every day or every other day for practical reasons. Nights two and three were used for reactivation. SMR training success was assessed at baseline, post treatment, and follow-up after 10 months. Neurofeedback was provided as pixelated video, which became clearer with better training performance. Although SMR amplitude did not significantly increase, NFT training seemed to have an effect on alpha amplitude over the course of training (p = 0.08), and both SMR groups showed by tendency improved objective sleep (e.g., higher sleep efficiency in night 2 vs. baseline night, p<sub>corr</sub> = 0.07). Reactivation did not immediately affect performance or EEG response. However, during the follow-up session, NFT performance was highest in the SMR + reactivation condition (SMR + R > SMR-R, p<sub>corr</sub> = 0.02), which could indicate a stabilizing effect of reactivation during sleep. Our data again suggest that (SMR) NFT could foster general relaxation and sleep. Concerning context reactivation, we did, however, only find limited evidence for a potential benefit. Future studies could add more reactivation nights or potentially utilize other forms of context reactivation.

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Journal
Psychophysiology
Published
2025-10-01
DOI
https://doi.org/10.1111/psyp.70154
Primary Topic
Sleep and Wakefulness Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Effects of Olfactory Learning Context Reactivation During Sleep on Training Success in a Double‐Blind Randomized Controlled Sensorimotor Rhythm Neurofeedback Protocol: A Pilot Study

Hong‐Viet V. Ngo, Julia Lechinger, Michael Schubert, Alexander Prehn‐Kristensen et al.
Psychophysiology
Sleep and Wakefulness Research
article

Effects of Olfactory Learning Context Reactivation During Sleep on Training Success in a Double‐Blind Randomized Controlled Sensorimotor Rhythm Neurofeedback Protocol: A Pilot Study

Hong‐Viet V. Ngo, Julia Lechinger, Michael Schubert, Alexander Prehn‐Kristensen, Catarina Newe, Robert Göder, Scott F. Nadler
article en

Abstract

Neurofeedback training (NFT) is used to modulate brain activity for therapeutic purposes in different patient populations. However, tested training protocols vary in several aspects, and the results of therapeutic benefit have been heterogeneous. The aim of the current study was to compare a SMR against a random frequency protocol and potentially strengthen NFT effects via olfactory context reactivation during sleep in a compact training protocol. 49 participants (mean age: 24.7 years; 29 women) without any neurological or psychiatric disorder were randomly (double-blind) assigned to three groups: sensorimotor rhythm (SMR) with or without context reactivation, or random frequencies with reactivation during sleep. Within 2 weeks, participants underwent eight training sessions (12 × 2 min training intervals) and slept three nights in the sleep lab. NFT sessions were scheduled every day or every other day for practical reasons. Nights two and three were used for reactivation. SMR training success was assessed at baseline, post treatment, and follow-up after 10 months. Neurofeedback was provided as pixelated video, which became clearer with better training performance. Although SMR amplitude did not significantly increase, NFT training seemed to have an effect on alpha amplitude over the course of training (p = 0.08), and both SMR groups showed by tendency improved objective sleep (e.g., higher sleep efficiency in night 2 vs. baseline night, p<sub>corr</sub> = 0.07). Reactivation did not immediately affect performance or EEG response. However, during the follow-up session, NFT performance was highest in the SMR + reactivation condition (SMR + R > SMR-R, p<sub>corr</sub> = 0.02), which could indicate a stabilizing effect of reactivation during sleep. Our data again suggest that (SMR) NFT could foster general relaxation and sleep. Concerning context reactivation, we did, however, only find limited evidence for a potential benefit. Future studies could add more reactivation nights or potentially utilize other forms of context reactivation.

PsychophysiologyVol. 62(10)
University of Essex (GB), Christian-Albrechts-Universität zu Kiel (DE), MSH Medical School Hamburg – University of Applied Sciences and Medical University (DE), University Hospital Schleswig-Holstein (DE), University of Lübeck (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 72%
Sleep and Wakefulness Research
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