**4. Discussion**

**Figure 1.** Pre-training (on the left) and post-training (on the right) EEG in the 43-year-old male subject. EEG recorded in the linked ear montage/reference during VCPT performance. Scale: 200uV/cm, speed–1.875 mm/s, time constant–10.0 s

**Figure 2.** EEG power spectra at Fz in the 43-year-old male subject before and after training**.** Pre-training–Lower curve,

post-training–Upper curve, X-axis–Frequency and Y-axis–Spectral power in logarithmic scale.

(0.016 Hz), low frequency filter–0.5 Hz.

82 Biofeedback

All participants had normal mental and physical development and had no history of any neurological abnormalities. However, most of them reported some form of self-perceived psychological and physiological issues such as fatigue, depressed mood, symptoms of inner tension, mood swings, headache, and sleep problems. These were accompanied by cognitive concerns such as diminished attention or poor working memory.

After 20 sessions of ILF training, the pattern of ILF activity at rest changed dramatically. The main difference was an increase in the amplitude of the ILF activity up to 0.3–1.0 mV in all recording sites.

These results indicate that ILF training modified the baseline brain state in each case. It is important to add here that the changes in brain dynamics were associated with improvement in subjective perception of stress, fatigue, mood disturbances, and sleep problems after completion of 20 sessions of ILF training. Decreases in inner tension and in stress reactivity were reported. The psychological evaluation also reflects positive changes, including improved stability of mood, better body and space awareness, increase in energy level, and improved concentration and cognitive performance (e.g., working memory).

Therefore, the positive effects of ILF feedback on the "renormalization of functional connectivity of resting-state networks" proposed by Othmer and colleagues can be linked with the normalization in the metabolic balance in the brain tissue as a specific effect of the ILF

Effect of Infra-Low Frequency Neurofeedback on Infra-Slow EEG Fluctuations

http://dx.doi.org/10.5772/intechopen.77154

85

The present research can be considered as the first step in uncovering the physiological basis of ILF training as the method that targets the balance within brain systems involved in metabolic regulation of brain and body. The role of ILF training on the DMN network regulation is a subject of future research, where the specific physiological effect of this practice in different

Our study has shown the changes in the amplitude distribution within the ILF spectral range in all participants that seems to be induced by the ILF training. In other words, the ILF training leads to the changes of the functional state of the brain. We suggest that the modification of the baseline ILF EEG pattern may reflect the normalization in the metabolic balance in the brain tissue and increasing efficiency of compensatory mechanisms in the stress regulation

The authors thank Susan Othmer, Clinical Director of the EEG Institute, Woodland Hills, California, for development of neurofeedback protocols used in this study, and Siegfried

The authors declare that the research was conducted in the absence of any commercial or

VAG-Y recruited subjects, participated in experimental design, data acquisition, interpretation, and drafting of the manuscript. VAP performed statistical analysis and interpreted the data. BW developed the ILF NF technology. OK was involved in drafting of the manuscript. MG analyzed data. VAI participated in interpretation of data. JDK supervised the study and was involved in study design, interpretation of data and critical review of the

Othmer, Chief Scientist of the EEG Institute for the critical review of the manuscript.

financial relationships that could be construed as a potential conflict of interest.

training [35].

**5. Conclusions**

**Acknowledgements**

**Conflict of interest**

**Author contributions**

manuscript.

systems.

brain diseases will be disclosed.

The effect of ILF training on the subjective perception of positive psychological changes was previously reported by a number of researchers and practitioners that utilize ILF training in their practice [35, 47]. Our analysis has both supported previous observations and established a link between the observed improvement in participants' condition with objective changes in physiological parameters that reflect the dynamics of the brain functional organization.

The previous studies have shown stability of the individual spectral characteristics of ILF brain potentials recorded both from scalp as well from intra-cortical and deep-brain electrodes [25, 26].

Consequently, the increase in the amplitude of the ILF activity found in the present study can be discussed in accordance with the mechanisms of the individual compensatory-adaptive brain-body regulation in response to stress factors [48]. In the present research, we assume that our participants had initial constraints in compensatory-adaptive brain reactions, which lead to the reduced brain tissue metabolic regulation followed by energy deficient state. The present study shows that ILF training outcomes are associated with an increase in amplitude of ILF. The increase in amplitude and regularity of ILF was previously described and discussed as a sign of improved tissue metabolic activity [48–50]. Therefore, the positive trend in ILF characteristics observed in our study may be linked to the increased compensatory mechanisms in the stress regulation systems.

It is important to mention that post-training enhancement of spectral power in the 0–0.5 Hz frequency band were the most prominent over the frontal-central and the posterior brain areas. The distribution of increased activity at infra low frequency is correlated with the principal hubs of the default mode network (DMN), located frontally and parietally on the midline. The DMN is by far the most dominant among our intrinsic connectivity networks (ICNs), typically accounting for more than 95% of the ambient activity of cortex. Among the ICNs, it bears the principal responsibility for the management of the tonic state of the brain. As such it can be thought of as setting the context for more specific functions such as cognitive and emotional control [51].

Previously published results discussed the possible involvement of ILF in the modulation of the internal organization of the DMN, which is associated with the brain homeostatic balance and is involved in the autonomic regulation [35, 36, 51]. These results support the hypothesis of the metabolic stress regulatory mechanisms [48] and raise the question on the role of DMN network in homeostatic balance and metabolic compensation in stress response.

At the same time, the disrupted connectivity within DMN was found in a number of diseases, especially related to faults in the stress-regulation system such as post-traumatic stress disorder [52], general anxiety disorder [53], major depressive disorder [54], and traumatic brain injuries [55].

Therefore, the positive effects of ILF feedback on the "renormalization of functional connectivity of resting-state networks" proposed by Othmer and colleagues can be linked with the normalization in the metabolic balance in the brain tissue as a specific effect of the ILF training [35].

The present research can be considered as the first step in uncovering the physiological basis of ILF training as the method that targets the balance within brain systems involved in metabolic regulation of brain and body. The role of ILF training on the DMN network regulation is a subject of future research, where the specific physiological effect of this practice in different brain diseases will be disclosed.
