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From Riding a Bike to Neurofeedback: Why Learning Needs Feedback

Henrik Röhr · 2026

Everything we have ever learned, we learned through feedback — information we received from our body and our environment as a result of our own actions. The first time we rode a bike, we scraped our knee, and the pain was "negative" feedback. After a few attempts, it finally worked, and the thrill of riding was "positive" feedback. Through a great deal of trial and error, our nervous system learned to control a whole range of muscles precisely enough to keep our balance and ride straight. When we learned to speak, we had to learn to control a huge number of small muscles in our tongue, lips, lungs, and vocal cords so they would produce sounds other people could understand. Here too, we received feedback — from the people around us. When we were understood — for example, by getting what we wanted — we received positive feedback. Our nervous system learned: "more of that."

The biological process underlying this kind of learning is called neuroplasticity. The neurons that make up our nervous system are "plastic" — meaning they are malleable and change over time. Seen this way, learning means that our nervous system is constantly making small adjustments, which is how we work out, for example, the exact combination of muscle tension needed to ride a bike. But this process only works under one important condition: our nervous system needs feedback to know what kind of adjustments are required. Without that feedback, learning is not possible. A tragic example of this is severely neglected children who experience almost no linguistic contact in their first years of life: even though their speech apparatus and hearing are often perfectly intact, without the constant linguistic feedback of their environment they never learn to speak properly.

This situation — receiving no feedback and therefore being unable to learn — isn't limited to neglected children. For example, most people don't consciously perceive the echo of sounds in their environment. As a result, they're unable to learn echolocation the way bats do. There are exceptions, though: some blind people are able to produce clicking sounds that let them perceive their surroundings through echolocation. As soon as we receive feedback, we can learn to make use of it.

This insight is the basis of biofeedback. The idea is this: if we can perceive a process happening in our body, we can, in many cases, learn to regulate it. For instance, very few people can voluntarily influence their heart rate variability or skin conductance, simply because the brain normally has no conscious "readout" of these physiological states. But if you give people a feedback signal — for example via a monitor or a tone — they often learn quickly to control these processes.

Neurofeedback is a special type of biofeedback, where the feedback relates specifically to processes in the brain. While we normally don't perceive our brainwaves directly, feedback can teach us to regulate them. One well-known application is attention disorders like ADHD, where neurofeedback is used as a treatment. Difficulty concentrating is often associated with particular patterns of brainwave activity. Neurofeedback training aims to change these patterns and thereby support attention regulation.

At Neurotropy, we use this principle to improve one of our most important abilities: learning. Brain research has identified a range of brain patterns associated with improved learning ability. Studies and meta-analyses building on this have shown that these brain patterns can be regulated through neurofeedback training, improving both working and episodic memory*. With Neurotropy, we want to bring these findings out of the lab and into everyday life: a comfortable EEG headband measures brain activity, and the aspects of that activity relevant to learning are converted into a feedback signal. This feedback allows users to guide their brain into a state in which learning works especially well and information is retained better.

References

Enriquez-Geppert, S., Smit, D., Eschmann, K. C. J., Marcos-Martínez, D., Sanchez, R. H., Hsieh, S., Dehais, F., & Huster, R. J. (2026). A mega-analysis of EEG-based frontal-midline theta neurofeedback reveals learning dynamics, individual variability, and response profiles. NeuroImage, 329, 121820. https://doi.org/10.1016/j.neuroimage.2026.121820

Eschmann, K. C. J., Bader, R., & Mecklinger, A. (2020). Improving episodic memory: Frontal-midline theta neurofeedback training increases source memory performance. NeuroImage, 222, 117219. https://doi.org/10.1016/j.neuroimage.2020.117219

Hsueh, J.-J., Chen, T.-S., Chen, J.-J., & Shaw, F.-Z. (2016). Neurofeedback training of EEG alpha rhythm enhances episodic and working memory. Human Brain Mapping, 37(7), 2662–2675. https://doi.org/10.1002/hbm.23201

Tseng, Y.-H., Tamura, K., & Okamoto, T. (2021). Neurofeedback training improves episodic and semantic long-term memory performance. Scientific Reports, 11(1), 17274. https://doi.org/10.1038/s41598-021-96726-5

Yeh, W.-H., Hsueh, J.-J., & Shaw, F.-Z. (2020). Neurofeedback of Alpha Activity on Memory in Healthy Participants: A Systematic Review and Meta-Analysis. Frontiers in Human Neuroscience, 14, 562360. https://doi.org/10.3389/fnhum.2020.562360

Yeh, W.-H., Ju, Y.-J., Liu, Y.-T., & Wang, T.-Y. (2022). Systematic Review and Meta-Analysis on the Effects of Neurofeedback Training of Theta Activity on Working Memory and Episodic Memory in Healthy Population. International Journal of Environmental Research and Public Health, 19(17), 11037. https://doi.org/10.3390/ijerph191711037