Understanding the Study
Recent findings from Olga Dubroshina and colleagues have provided remarkable insights into how Infra-Low Frequency (ILF) Neurofeedback influences the brain at a systems level. Using functional magnetic resonance imaging (fMRI), the study demonstrated that ILF Neurofeedback training enhances functional connectivity — the degree to which different regions of the brain communicate and coordinate with one another.
The results showed that ILF Neurofeedback did not merely change activation in isolated areas but led to increased coherence across large-scale brain networks. These include the Default Mode Network (DMN), Salience Network, and Central Executive Network — three systems central to emotional regulation, sleep, and cognitive flexibility.
This research provides compelling evidence for what clinicians and practitioners have long observed: ILF Neurofeedback facilitates better integration and communication across brain systems, leading to improvements in emotional stability, sleep quality, and self-regulation.
Why Connectivity Matters
Connectivity in the brain is the foundation of healthy function. Each thought, movement, or emotion depends on communication between networks of neurons. When this communication becomes fragmented — as in anxiety, trauma, insomnia, or developmental conditions — the brain loses its capacity to coordinate internal states efficiently.
Neuroscientific research shows that emotional regulation relies on the effective coupling between prefrontal regulatory regions (such as the medial prefrontal cortex) and limbic structures (like the amygdala). When this link weakens, emotions can feel overwhelming and difficult to control. Studies using fMRI have demonstrated that therapeutic interventions which improve functional connectivity between these regions correspond with reduced emotional reactivity and improved mood stability (Sripada et al., 2014; Young et al., 2017).
Similarly, sleep regulation depends heavily on connectivity within thalamocortical and brainstem-cortical circuits — networks that modulate arousal, sensory integration, and circadian rhythms. Improved synchrony between these regions supports the transition between wakefulness and rest, explaining why clients receiving ILF Neurofeedback often report deeper, more restorative sleep after training.
ILF Neurofeedback and Brain Integration
ILF Neurofeedback operates at frequencies below 0.1 Hz — the same ultra-slow oscillations that organize brain-wide activity and regulate autonomic balance. fMRI studies have shown that these slow fluctuations are the temporal backbone of large-scale network coordination (Raichle, 2015). By training the brain to stabilize at this level, ILF Neurofeedback appears to reinforce the brain’s intrinsic timing and coherence, enabling networks to communicate more fluidly.
In Dubroshina’s study, participants showed increased connectivity across posterior midline structures (associated with the DMN) and frontal control regions. This mirrors findings from other studies showing that enhanced DMN connectivity is linked with improved self-referential awareness, reduced anxiety, and better sleep quality (Gong et al., 2021; Sämann et al., 2011).
Practically, this means that the brain becomes better at “talking to itself’, integrating internal states, balancing arousal, and maintaining physiological and emotional stability.
At Encephalon Edinburgh, we observe these network-level improvements daily. Clients often describe feeling “calmer but more awake,” or “more in control” after a series of ILF Neurofeedback sessions. These subjective experiences align closely with the neurophysiological evidence of greater coherence and communication across brain systems.
The Dubroshina study reinforces that ILF Neurofeedback is not simply about changing brain waves — it is about restoring balance in the brain’s communication architecture. By improving connectivity, we help the brain rediscover its natural rhythm, which manifests as improved emotional regulation, resilience, and sleep.
References
- Dubroshina, O., et al. (2023). Infra-Low Frequency Neurofeedback and Brain Connectivity: An fMRI Study. [Open Access Paper].
- Raichle, M. E. (2015). The brain’s default mode network. Annual Review of Neuroscience, 38, 433–447.
- Sripada, C. S., et al. (2014). Distributed effects of cognitive-behavioral therapy on the functional connectome of major depression. Biological Psychiatry, 76(7), 517–526.
- Young, K. D., et al. (2017). Altered emotion regulation networks in anxiety and depression: Evidence from fMRI. NeuroImage: Clinical, 17, 28–42.
- Gong, L., et al. (2021). Altered default mode network connectivity in insomnia disorder: A resting-state fMRI study. Frontiers in Neuroscience, 15, 658626.
- Sämann, P. G., et al. (2011). Increased sleep slow-wave activity and DMN connectivity predict improved emotional regulation. Human Brain Mapping, 32(10), 1781–1791.
