New NeuroImage Study Provides a Mechanistic Foundation for ILF Neurofeedback
fMRI study shows stable brain network changes only for the full ILF protocol
Neurofeedback has been used in clinical practice for many years. At the same time, there is ongoing discussion about the neurophysiological mechanisms through which different neurofeedback approaches exert their effects. In the case of Infra-Low Frequency (ILF) neurofeedback in particular, imaging studies demonstrating objective changes in the brain beyond subjective reports have so far been limited.
A study published in December 2025 in the scientific journal NeuroImage addresses this gap. The aim of the work was not to evaluate the clinical efficacy of neurofeedback, but to investigate the neurophysiological effects of the signal components of an established ILF neurofeedback protocol from a mechanistic perspective.
ILF neurofeedback as a combined approach
ILF neurofeedback is not a single-signal method. It is based on the combination of multiple EEG timescales, including:
- classical EEG frequency band signals reflecting fast neural dynamics
- infra-low-frequency signals capturing very slow regulatory processes
This combination corresponds to the clinical ILF neurofeedback configuration as it is used in therapeutic practice.
To better understand the underlying mechanisms, the signal components combined in ILF neurofeedback were deliberately examined separately in the study and analyzed both individually and in combination. This separation served the mechanistic investigation of the established ILF approach.
Study design: mechanistic analysis of an established protocol
The study comprised three randomized, double-blind, sham-controlled crossover experiments with a total of 135 healthy participants. In each sub-study, participants completed a single 30-minute neurofeedback session, accompanied by functional MRI measurements before and after the session.
Three experimental conditions were examined:
- classical EEG frequency band signals alone
- infra-low-frequency signals alone
- the combination of frequency band and infra-low-frequency signals corresponding to the clinical ILF neurofeedback configuration
Resting-state fMRI data were analyzed using multivariate functional connectivity pattern analysis (fc-MVPA), an established method for assessing large-scale brain networks.
Central findings
The central finding of the study is clear. Robust and statistically reliable changes in functional brain connectivity were observed exclusively when frequency band and infra-low-frequency signals were applied in combination.
When the individual signal components were applied in isolation, no comparably stable effects were observed after statistical correction. The results therefore indicate that consistent neurophysiological changes emerge only from the combination of different EEG timescales.
Importantly, the study does not identify a novel combination. Rather, it demonstrates the neurophysiological relevance of the complete ILF neurofeedback protocol as it is used in clinical practice.
Relevance of the findings for ILF neurofeedback by BEE Medic
The results provide, for the first time, an imaging-based mechanistic foundation for the ILF neurofeedback approach that BEE Medic has exclusively developed and technically implemented in this consistent clinical configuration.
The study shows that the observed effects are not driven by individual EEG signals alone, but by the targeted coupling of fast and very slow neuronal dynamics as realized in ILF neurofeedback. In this way, an approach that has previously been shaped primarily by clinical experience is now based on a clear neurophysiological footing.
Study context
The study is designed as a neurophysiological basic research investigation. It does not make any statements about clinical efficacy, specific symptoms, or long-term effects. Its contribution lies in the objective, imaging-based analysis of the underlying mechanisms.
Conclusion
The fMRI study published in NeuroImage demonstrates that the complete ILF neurofeedback protocol, meaning the combination of classical EEG frequency band signals and infra-low-frequency signals, leads to stable and measurable changes in functional brain networks.
The study therefore provides, for the first time, an imaging-based mechanistic foundation for the ILF neurofeedback approach as it is used clinically and technically implemented by BEE Medic devices.