According to the latest WHO data, 3 million people die each year worldwide as a result of harmful alcohol consumption. This corresponds to 5.3 % of all deaths (ABC). Supporting the patient's abstinence after a detoxification or rehabilitation seems like the biggest challenge of all in the fight against alcohol addiction. Current therapy options only seem to have limited success, particularly in terms of relapse rate (Bottlender and Soyka, 2005), so new therapy methods have been sought for decades. Despite intense scientific research and public health imperatives, addiction treatment outcomes have not improved significantly in more than 50 years.

One of the approaches that could give the patient control over their own health and abstinence is neurofeedback (NF). NF can non-invasively modulate human brain activity to treat mental illness. NF techniques are often based on either electroencephalography (EEG) or real-time functional magnetic resonance imaging (rtfMRI). With this therapeutic approach, patients are immediately shown information about changes in their neuronal activity (Zotev et al., 2014). In NF treatment, participants learn to regulate their own brain activity with direct feedback. The aim is for the patients to learn in this way how to change their own reactions in the brain. These changes are accompanied by modulations of experience and behaviour.

Through a systematic review of the scientific literature, Fovet et al. investigated the rationale and expected applications of real-time fMRI-NF in psychiatry (Fovet et al., 2015). It has been shown that in most psychiatric disorders (major depression, schizophrenia, personality disorders, addiction disorders) the patients can learn voluntary control of the neural activity of the target region(s) (Fovet et al., 2015).

NF could therefore be used as a therapeutic approach for managing alcohol addiction. This approach could primarily aim at influencing one of the most important symptoms in addiction disorders, the strong desire to consume a certain substance or to show a certain behaviour - craving. In particular, the strong association between craving and the likelihood of relapse underlines the importance of modulating craving in the therapeutic process (Karch et al., 2015). FMRI-based NF, especially as a non-invasive procedure, could therefore represent an additional and supportive option in the therapy of addiction disorders.

Li and al. (2013) have shown that the reduction of neuronal activity in addiction-associated brain areas can be accompanied by reduced craving (Li et al., 2013). It has been already shown that craving can be modulated in patients with alcohol dependence through NF with rtfMRI. The results showed a significant reduction in neuronal activity at the end of the training compared to the beginning of the treatment, especially in frontal and temporal regions (especially ACC, insula, gyrus temporalis inferior, gyrus frontalis medialis) (Karch et al., 2015). The fMRI findings confirm that regions related to reward and cognitive control are involved in addiction (Baler and Volkow, 2012).

Although there are studies that investigate the application of NF training to treat addiction, to date, most rtfMRI NF studies have focused on controlling activity in brain regions during a task state to demonstrate the effects of training.

Resting-state fMRI is increasingly being used to assess changes in functional brain connectivity after treatments. Resting-state fMRI is a relatively new modality that potentially overcomes several important limitations in task-stimulated fMRI studies. By comparing resting state data before and after NF training, the changed functional connectivity could be calculated, and the longer-term effect of NF training could be indicated. Therefore, resting state analysis could be a suitable method to gain insights into the neural mechanisms underlying NF training (Yeo et al., 2011).

Furthermore, resting state fMRI is important to study the pathophysiology of psychiatric disorders in general, as it enables the identification of spontaneous neuronal activities that coincide in time and form neural networks. Such networks seem to reflect all of the cognitive elements necessary for task processing. Compared to task-based fMRI methods, data acquisition is relatively fast and straightforward, which is a useful characteristic when assessing patient populations with variable attentional, executive, and motor control impairments (MT Sutherland et al., 2012).

Despite all the research progress as mentioned, in the current literature there are only a few studies that investigated resting state activity in patients with alcohol dependence who received NF training.

This study investigated whether those resting state activities in the regions that play a particularly important role in addiction disorders can be modulated by NF training in patients with alcohol dependence.