Computational Neuroscience of Drug Addiction by Vladimir L. Tsibulsky, Andrew B. Norman (auth.), Boris

By Vladimir L. Tsibulsky, Andrew B. Norman (auth.), Boris Gutkin, Serge H. Ahmed (eds.)

Drug habit is still the most vital public illnesses in western societies and is a emerging difficulty for constructing international locations. over the last three a long time, experimental learn at the neurobiology and psychology of drug dependancy has generated a torrent of intriguing info, from the molecular as much as the behavioral degrees. for that reason, a brand new and urgent problem for dependancy examine is to formulate a man-made theoretical framework that is going well past mere medical eclectism to deepen our figuring out of drug habit and to foster our potential to avoid and to therapy drug dependancy. Intrigued by way of the obvious irrational habit of drug addicts, researchers from quite a lot of clinical disciplines have formulated a plethora of theoretical schemes through the years to appreciate habit. even though, almost all these theories and types are qualitative in nature and are formulated utilizing phrases which are frequently ill-defined. consequently, the empirical validity of those types has been tricky to check conscientiously, which has served to generate extra controversy than readability. during this context, as in different medical fields, mathematical and computational modeling should still give a contribution to the improvement of extra testable and rigorous types of addiction.

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Extra info for Computational Neuroscience of Drug Addiction

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1987). After tolerance has been established, the slow adaptation is responsible for a shift in the output level to below normal in the interval between drug administrations. The magnitude of these negative reactions in the tolerant situation depends on the length of the interval. When a drug is taken infrequently, the organism is not much affected during the intervals; when the frequency of administration is high, the shift can become considerable. The fast regulator is a complex system and determines to a large extent how tolerance develops.

In this configuration, the adaptive regulator learns to change the transfer function of the sensor in a way that counteracts the effect of the drug on the sensor’s sensitivity to the messenger. 8 shows a model of a regulated process in which the information transfer is disturbed by a drug. The adaptive regulator gradually learns to suppress the effect of the drug on the sensor signal by changing the sensitivity of the sensor. The adaptive regulator bases its action on information it receives from the sensor, Ssens , and on information about the drug administration, Pd .

Pharmacol Rev 9:242–246 Sizemore GM, Martin TJ (2000) Toward a mathematical description of dose-effect functions for self-administered drugs in laboratory animal models. Neuropsychopharmacology 153:57–66 Tsibulsky VL, Norman AB (1999) Satiety threshold: A quantitative model of maintained cocaine self-administration. Brain Res 839:85–93 Tsibulsky VL, Norman AB (2005) Real time computation of in vivo drug levels during drug selfadministration experiments. Brain Res Brain Res Protoc 15:38–45 Weeks JR (1962) Experimental morphine addiction: Method for automatic intravenous injections in unrestrained rats.

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