In a rapidly changing society, knowledge and education are key factors for indivdual well-being and social development. To create ideal learning environments and achieve both, it is important to know how our mind develops over the life span. This is also highly relevant for mental health and especially the prevention of psychological stress. On the other hand, the physiological stress reaction is considered to play a vital role in psychobiological development. There is a long tradition to model psychobiological development based on behavioral data (e.g. cognitive perfomance, IQ, personality factors, social skills) and biographical data (e.g. family history, educational status, traumatic life events, psychiatric symptoms). Recent technological innovations in the life sciences (gene sequencing methods, imaging techniques) made it possible to also assess molecular (genetic and epigenetic) and neural correlates of psychobiological development. This is most obvious for the example of stress and the question how we relate psychophysiological and molecular (hormonal, epigenetic and genetic) measures to the experienced psychological stress. Especially, epigenetic mechanisms seem to contribute significantly to developmental processes in general and to the development of the physiological stress reaction in particular. But concepts that integrate newly genetic, epigenetic, neural and neuro-cognitive findings in an overall theory of psychobiological development have yet to be developed. Gilbert Gottlieb's probabilistic epigenesis and his scheme of psychobiological development provide an ideal starting point for this effort. Based on a modified version of Gottlieb's scheme of psychobiological development, this study aims at integrating different levels of empirical data collection relevant for psychobiological development. Possibilities and challenges of the model are discussed using the physiological stress reaction and the psychological stress concept as an example. The goal is to provide detailed hypotheses of inter-level interactions which can be tested in future empirical studies. Accordingly, epigenetic mechanisms are modeled as molecular underpinnings mediating interactions between neural and genetic activity levels. Three different functional contexts of epigenetic mechanisms in neuronal cells are identified: genomic, developmental, and synaptic. Furthermore, the distinction between structural and functional data usually used to interpret the difference between neural data and neuro-cognitive data is questioned. As shown for the example of stress, the model overall provides a new framework to interpret molecular and neural data in relation to behavioral and biographical data usually used in clinical practice.


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