[Pain and opioid dependency as multilevel network phenomenon : Theoretical and metatheoretical aspects]. / Schmerz und Opioidabhängigkeit als Mehr-Ebenen-Netzwerk-Phänomen : Theoretische und metatheoretische Aspekte.

Methodological reflections on pain research and pain therapy focussing on addiction risks are addressed in this article. Starting from the incompleteness of objectification of the purely subjectively fully understandable phenomena of pain and addiction, the relevance of a comprehensive general psychology is underlined. It is shown that that reduction of pain and addiction to a mainly focally arguing neurobiology is only possible if both disciplines have a systemic concept of pain and addiction. With this aim, parallelized conceptual network models are presented.

The neurochemical mobile with non-linear interaction matrix: an exploratory computational model.

Several years ago, the "neurochemical mobile" was introduced as a visual tool for explaining the different balances between neurotransmitters in the brain and their role in mental disorders. Here we complement this concept with a non-linear computational systems model representing the direct and indirect interactions between neurotransmitters, as they have been described in the "neurochemical interaction matrix." The model is constructed within the framework of biochemical systems theory, which facilitates the mapping of numerically ill-characterized systems into a mathematical and computational construct that permits a variety of analyses. Simulations show how short- and long-term perturbations in any of the neurotransmitters migrate through the entire system, thereby affecting the balances within the mobile. In cases of short-term alterations, transients are of particular interest, whereas long-term changes shed light on persistently altered, allostatic states, which in mental diseases and sleep disorders could be due to a combination of unfavorable factors, resulting from a specific genetic predisposition, epigenetic effects, disease, or the repeated use of drugs, such as opioids and amphetamines.

Computational modelling of schizophrenic symptoms: basic issues.

Emerging "(computational) systems medicine" challenges neuropsychiatry regarding the development of heuristic computational brain models which help to explore symptoms and syndromes of mental disorders. This methodology of exploratory modelling of mental functions and processes and of their pathology requires a clear and operational definition of the target variable (explanandum). In the case of schizophrenia, a complex and heterogeneous disorder, single psychopathological key symptoms such as working memory deficiency, hallucination or delusion need to be defined first. Thereafter, measures of brain structures can be used in a multilevel view as biological correlates of these symptoms. Then, in order to formally "explain" the symptoms, a qualitative model can be constructed. In another step, numerical values have to be integrated into the model and exploratory computer simulations can be performed. Normal and pathological functioning is to be tested in computer experiments allowing the formulation of new hypotheses and questions for empirical research. However, the crucial challenge is to point out the appropriate degree of complexity (or simplicity) of these models, which is required in order to achieve an epistemic value that might lead to new hypothetical explanatory models and could stimulate new empirical and theoretical research. Some outlines of these methodological issues are discussed here, regarding the fact that measurements alone are not sufficient to build models.

Affective disorders as complex dynamic diseases--a perspective from systems biology.

Understanding mental disorders and their neurobiological basis encompasses the conceptual management of "complexity" and "dynamics". For example, affective disorders exhibit several fluctuating state variables on psychological and biological levels and data collected of these systems levels suggest quasi-chaotic periodicity leading to use concepts and tools of the mathematics of nonlinear dynamic systems. Regarding this, we demonstrate that the concept of "Dynamic Diseases" could be a fruitful way for theory and empirical research in neuropsychiatry. In a first step, as an example, we focus on the analysis of dynamic cortisol regulation that is important for understanding depressive disorders. In this case, our message is that extremely complex phenomena of a disease may be explained as resulting from perplexingly simple nonlinear interactions of a very small number of variables. Additionally, we propose that and how widely used complex circuit diagrams representing the macroanatomic structures and connectivities of the brain involved in major depression or other mental disorders may be "animated" by quantification, even by using expert-based estimations (dummy variables). This method of modeling allows to develop exploratory computer-based numerical models that encompass the option to explore the system by computer simulations (in-silico experiments). Also inter- and intracellular molecular networks involved in affective disorders could be modeled by this procedure. We want to stimulate future research in this theoretical context.

Effects of dopamine and glutamate on synaptic plasticity: a computational modeling approach for drug abuse as comorbidity in mood disorders.

Major depressive disorder (MDD) affects about 16% of the general population and is a leading cause of death in the United States and around the world. Aggravating the situation is the fact that "drug use disorders" are highly comorbid in MDD patients, and VICE VERSA. Drug use and MDD share a common component, the dopamine system, which is critical in many motivation and reward processes, as well as in the regulation of stress responses in MDD. A potentiating mechanism in drug use disorders appears to be synaptic plasticity, which is regulated by dopamine transmission. In this article, we describe a computational model of the synaptic plasticity of GABAergic medium spiny neurons in the nucleus accumbens, which is critical in the reward system. The model accounts for effects of both dopamine and glutamate transmission. Model simulations show that GABAergic medium spiny neurons tend to respond to dopamine stimuli with synaptic potentiation and to glutamate signals with synaptic depression. Concurrent dopamine and glutamate signals cause various types of synaptic plasticity, depending on input scenarios. Interestingly, the model shows that a single 0.5 mg/kg dose of amphetamine can cause synaptic potentiation for over 2 h, a phenomenon that makes synaptic plasticity of medium spiny neurons behave quasi as a bistable system. The model also identifies mechanisms that could potentially be critical to correcting modifications of synaptic plasticity caused by drugs in MDD patients. An example is the feedback loop between protein kinase A, phosphodiesterase, and the second messenger cAMP in the postsynapse. Since reward mechanisms activated by psychostimulants could be crucial in establishing addiction comorbidity in patients with MDD, this model might become an aid for identifying and targeting specific modules within the reward system and lead to a better understanding and potential treatment of comorbid drug use disorders in MDD.

Mental illness, synapses and the brain--behavioral disorders by a system of molecules within a system of neurons?

The multi-level systems view conceiving the brain as a "network of networks of neurons" rises the question how it could be possible to understand this complex system with respect to mental functions and dysfunctions. One crucial issue is related to the analysis of the connectivity of these networks by the study of synapses. Also synapses are complex dynamical molecular systems that can only be understood by computer-based methodologies in order to analyze complex data sets and for modeling complex molecular networks. Many data are available but there is a lack models that capture the dynamic features of synapses that are involved in psychiatric disorders and psychopharmaceutical treatment. One strategy of research could be offered by Systems Biology. Here some challenges for modeling synapses in mental disorders are discussed.

Systems biology and addiction.

The onset of addiction is marked with drug induced positive experiences that keep being repeated. During that time, adaptation occurs and addiction is stabilized. Interruption of those processes induces polysymptomatic withdrawal syndromes. Abstinence is accompanied by risks of relapse. These features of addiction suggest adaptive brain dynamics with common pathways in complex neuronal networks. Addiction research has used animal models, where some of those phenomena could be reproduced, to find correlates of addictive behavior. The major thrust of those approaches has been on the involvement of genes and proteins. Recently, an enormous amount of data has been obtained by high throughput technologies in these fields. Therefore, (Computational) "Systems Biology" had to be implemented as a new approach in molecular biology and biochemistry. Conceptually, Systems Biology can be understood as a field of theoretical biology that tries to identify patterns in complex data sets and that reconstructs the cell and cellular networks as complex dynamic, self-organizing systems. This approach is embedded in systems science as an interdisciplinary effort to understand complex dynamical systems and belongs to the field of theoretical neuroscience (Computational Neuroscience). Systems biology, in a similar way as computational neuroscience is based on applied mathematics, computer-based computation and experimental simulation. In terms of addiction research, building up "computational molecular systems biology of the (addicted) neuron" could provide a better molecular biological understanding of addiction on the cellular and network level. Some key issues are addressed in this article.

Philosophy of neuroscience and options of systems science.

Molecular biology as a research approach in psychiatry has gathered a huge amount of data that can hardly be used for explanation of mental disorders by cellular dysfunctions. In a philosophical sense "explanation" means the application of general laws on specific cases. This is more than description. Most findings of molecular biology only help to describe these processes more in detail. On contrary, systems biology aims to create a computer-based model of the cell. For this project mathematics plays a crucial role. In that respect systems biology also provides tools for data analysis.

[Acute alcohol intoxication in adolescents: preliminary results of a pilot project in Munich]. / Akute Alkoholvergiftung bei Jugendlichen: Erste Ergebnisse eines Münchener Pilotprojekts.

OBJECTIVE: To present preliminary results of a pilot project on the prevention of alcohol-associated problems in adolescents with acute alcohol intoxication. METHOD: Questionnaires were filled in by 110 of 128 adolescents (85.9% response rate) who had been admitted to a hospital in Munich, Germany, between December 2007 and July 2008, because of alcohol intoxication. Data were obtained on sociodemographic characteristics, alcohol intoxication and drinking patterns, and were analysed using descriptive methods. RESULTS: Half of these adolescents mainly suffered from moderate to severe degrees of alcohol intoxication. Drinking patterns leading to alcohol intoxication were characterized by relatively low drinking frequency interspersed by episodes of excessive alcohol intake (binge drinking). Thirteen (14.8%) of the adolescents reported previous hospital admissions for alcohol intoxication, nine (17.3%) did not know about the life-threatening danger of alcohol intoxication and twelve (22.2%) reported taking illegal drugs within the last 12 months. CONCLUSION: Adolescents who had been admitted to hospital because of alcohol intoxication had a drinking pattern which put them at a higher risk for alcohol intoxication and acute alcohol-related problems than adolescents in the general population. Re-admission to hospital within 12 months because of alcohol intoxication, revealing a lack of knowledge about the life-threatening danger of alcohol intoxications and of consuming illegal drugs, may indicate an increased risk for alcohol-related problems. This points to the need for preventive action in adolescents showing these indicators, a need that was met within this pilot project by brief intervention.

Systems biology and psychiatry - modeling molecular and cellular networks of mental disorders.

Biological psychiatry has more and more directed it's focus on the involvement of genes and molecules in mental health and disease. On these levels, new approaches in other medical fields are noticed that are collectively dubbed "Systems Biology". Conceptually, this new paradigm tries to view molecular interactions in cellular networks as dynamic, self-organizing events that eventually result in an ordered maintenance of the whole system. A great deal of applied mathematics is required in systems biology to set up and carry out computer modeling and simulation. In terms of psychiatric research, developing "systems biology of the neuron" could become a pivotal achievement for a better understanding of mental illness on the molecular level. A brief outline of imminent tasks and links between systems biology and biological psychiatry is presented.

[The brain-mind debate. Problems in the philosophy of science with regard to psychiatry]. / Gehirn-Geist-Debatte. Wissenschaftsphilosophische Probleme im Hinblick auf die Psychiatrie.

The present interdisciplinary brain-mind debate with regard to neurobiology shows deficits in the criticism of methods and in the precision of language and argumentation. Simplifying localisations of psychic functions, insufficient explanations and over-interpretations in the sense of physical determinism are the consequence. This can be demonstrated in deficits of neurobiological theories of volitional action. Therefore, the current concept of man is less perturbed than is proposed by neurobiologists. For psychiatry besides the neurobiological approach also a separate way of building models seems to be useful if present theoretical psychology and systems science would be regarded. In particular, the systems science of natural systems offers new opportunities to bridge gaps between disciplines involved in the brain-mind debate.

Towards systemic theories in biological psychiatry.

Although still rather controversial, empirical data on the neurobiology of schizophrenia have reached a degree of complexity that makes it hard to obtain a coherent picture of the malfunctions of the brain in schizophrenia. Theoretical neuropsychiatry should therefore use the tools of theoretical sciences like cybernetics, informatics, computational neuroscience or systems science. The methodology of systems science permits the modeling of complex dynamic nonlinear systems. Such procedures might help us to understand brain functions and the disorders and actions of psychiatric drugs better.

Schizophrenia, neurobiology and the methodology of systemic modeling.

Progress in the pharmacological treatment of schizophrenia is dependent on the extent of our understanding of the brain as the basis of this disease. Detailed examination of neurobiological data shows that only a systemic approach will integrate this wealth of information. For this reason, the steps involved in model building should be clarified, as further progress will necessitate closer cooperation between neuropsychiatrists, neurobiologists and systems scientists.