Modern society invests large amounts of resources, time, and knowledge into the development of optimal solutions for public healthcare. Nevertheless, it seems that various systemic dysfunctions, especially in the domain of mental health, are increasing every year. In the treatment of the most common mental disorders, such as depression and anxiety, we have not yet encompassed all aspects of holistic care, which would require a deeper and more comprehensive insight into the dynamics of mental processes. Rigid definitions that strictly separate one disorder from another should be reinterpreted or, in some instances, even abandoned. It is becoming increasingly clear that, within these arbitrary boundaries, behavioural and neurobiological characteristics of mental states are often intertwining or overlapping and can be best understood through the lens of dimensionality (Clark et al., 2017). In addition to the blurred boundaries between related disorders and the diversity of their symptom manifestations, this would also imply recognizing indicators of illness in individuals who do not meet the criteria for a clinical diagnosis but nonetheless suffer from a reduced quality of everyday life. The severity of symptoms of mental disorders is thought to be largely influenced by the frontoparietal cognitive control network, which, through its connections with other brain regions, regulates the symptoms of mental illness (Schultz et al., 2018). Due to its protective nature, it has also been referred to as the “immune system of the mind”, consisting of flexible hubs that direct the functioning of brain connections in accordance with the organism’s current goals (Cole et al., 2014). In this thesis, I have therefore tested the hypotheses about correlations between the severity of symptoms of depression and anxiety, and the degree of connectivity of the frontoparietal cognitive control network. I used data from the publicly available database of the Max Planck Institute in Germany, which includes, among other things, a large number of electroencephalographic (EEG) recordings and behavioural questionnaires. Some statistical correlations between them support the first and second hypotheses, which predicted that the expression of depressive and/or anxious symptomatology would be negatively correlated with measures of the frontoparietal cognitive control system, while behavioural measures of cognitive control would show positive correlation. If further research confirms or builds upon these findings, the proneness to depressive-anxious states could potentially be predicted from the results of certain psychometric instruments or even individual EEG measurements. This would encourage the general population to adopt preventive measures to ensure better mental health outcomes in the future or to seek medical advice in a timely manner.
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