## 4 Common/Unifying Theoretical-Conceptual Framework
### qEEG Phenotype, Personality Traits, and Norm-Pathology Continuum
An important consideration regarding dimensionality is that (a) the relationship between increasing disruptions in functional mechanisms reflected in the characteristics of qEEG phenotypes and the severity of symptoms may be _non-linear_, with set-points that mark a transition to more severe pathology [515], and (b) a particular characteristic of the qEEG phenotype may have a different meaning and reflect a different underlying pathogenetic process as a function of the overall _context_ within which it emerges ('contextual functionality') [715]. Since there is abundant scientific evidence (see above) that normative qEEG values are the result of brain electrical rhythm autoregulation by a complex homeostatic system [248; 449] that displays a characteristic metastability around certain homeostatic levels, then deviations in characteristics of qEEG phenotypes may reflect a departure from homeostatic regulation that is a new stable state of altered brain activity [716] and can be a pathological _'set point'_ if this deviation is chronic and outside the normal range. This adaptation is referred to as _'allostasis'_ and is defined as _'homeostasis through change'_[716; 717], where normal mechanisms for homeostatic regulation have spun out of the physiological range, which can lead to a chronic condition of heightened vulnerability to pathology. The _price_ the brain pays to adapt to adverse psychosocial or physical situations (environments), which is related to how inefficient the response is and how many challenges the brain experiences for a sustained period of time, is defined as the _allostatic load_[718; 719]. Allostatic load is mediated by factors such as genes and early development, as well as learned behaviors, reflecting lifestyle choices of diet, exercise, drug use, and so on [716], all of which are reflected in the qEEG phenotype (see above), which is a long lasting 'brain signature'. Considering (a) the dimensional approach to neuropsychopathology (see above), (b) the functional continuum of normality-pathology (see above), and (c) the fact that the same symptoms (though with different expressions) are present in the majority of psychiatric disorders [720] due to the transdiagnostic nature of primary domains of functioning (traits) and their associated qEEG phenotypes' characteristics (see above), _neuropsychopathology_ can be conceptualized as the _degree of deviations_ across every domain (assessed by qEEG phenotypes' characteristics) and their _disposition_ (stabilized relative to each other's positions on the normality-pathology continuum), where the domain with the largest deviation (or combination of several deviant domains) may represent the leading pathogenic marker or risk factor that manifests as either in the permanent mental constitution or a heightened vulnerability to mental disorder. This is in line with animal models of neuropsychiatric disorders, where domain interplay was demonstrated [721]. In this context, developing a new diagnostic model should involve building a brain-based conceptualization of psychiatric illnesses [722], where _neuropsychopathology_ is quantified through qEEG phenotypes that are defined by the _degree of deviation_ from the normative (age- and sex-matched) data and the _disposition_ of qEEG characteristics and the associated transdiagnostic primary domains of functioning (traits) that are placed in the _functional continuum_ of normality-pathology. Here, the deviation from the normative values provides a probabilistic measure of the likelihood that the individual's electrical activity reflects abnormal brain functioning. Thus, concepts of _'normal'_ or _'abnormal'_ can be redefined based on the probability of qEEG characteristics associated with transdiagnostic primary domains of functioning relative to normative data, where _'abnormality'_ is defined statistically as improbable values exceeding those expected randomly [153]. It is assumed that the more statistically unusual the observation, the more likely it is that the underlying brain system is clinically abnormal.