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Updated: Jul 10, 2025

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A Protocol for the Administration of Real-Time fMRI Neurofeedback Training
Published on: August 24, 2017
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Unconscious Manipulation of Conceptual Representations with Decoded Neurofeedback Impacts Search Behavior
Pedro Margolles1,2, Patxi Elosegi3,2, Ning Mei3
1Basque Center on Cognition, Brain and Language (BCBL), Donostia - San Sebastián, Gipuzkoa 20009, Spain pedromargolles@gmail.com d.soto@bcbl.eu.
Summary
Conscious awareness may be essential for complex human learning. Unconscious training using decoded neurofeedback (DecNef) altered neural patterns but impaired behavioral search, suggesting conscious awareness supports higher-order associations.
Area of Science:
- Neuroscience
- Cognitive Psychology
- Learning Science
Background:
- Conscious awareness's role in human learning is debated.
- Previous non-conscious associative learning studies faced replication issues and low signal-to-noise ratios.
Purpose of the Study:
- To investigate if associative learning can occur unconsciously using decoded neurofeedback (DecNef).
- To explore the behavioral consequences of unconscious associative learning on neural representations.
Main Methods:
- Functional magnetic resonance imaging (fMRI) decoded neurofeedback (DecNef) was used to train participants.
- Participants learned to generate specific neural patterns without conscious awareness of the associated content.
- Associative DecNef imbued neutral Japanese hiragana characters with perceptual meaning (e.g., dogs).
Main Results:
- Participants successfully learned to activate target perceptual representations unconsciously.
- The DecNef training did not prime visual search for the associated target.
- Participants were impaired in searching for the targeted perceptual category, indicating an unexpected behavioral consequence.
Conclusions:
- Conscious awareness may be crucial for higher-order associative learning.
- Lower-level neural plasticity and learning can occur unconsciously, impacting behavior outside the training context.
- DecNef effects can be explained by neural representational drift.

