Cholinergic systems provide diffuse innervation to nearly every area of the brain, and drive or modulate a wide variety of behaviors. Nicotinic acetylcholine receptors (nAChRs) have been implicated in many diseases, such as epilepsy, addiction, schizophrenia, Parkinson's disease, vascular dementia, dementia with Lewy bodies, and Alzheimer's disease. In this application, we propose experiments that are interactively coupled to computer models of synaptic function. The computer models are intended to be generalized tools that enhance the experimentalist's insights into basic synaptic mechanisms, pharmacology, and disease. We are initiating this approach by focusing on cholinomimetic drugs at nicotinic synapses. Such drugs are now the only approved treatments for mild to moderate Alzheimer's disease (AD). The working hypothesis is that the cholinergic drugs have varied mechanistic effects at nicotinic cholinergic synapses, and by affecting nAChRs, these drugs also influence the release of other neurotransmitters.
Our aim i s to implement this approach with three levels of interactive modeling and experimentation. At each level we have used data from the literature to develop preliminary computer models. The models produce simulations that guide the design and interpretation of the experiments. At the first level of interaction between simulations and experimentation, we apply patch-clamp electrophysiology in tissue culture and slice to determine activation and desensitization parameters for the nAChRs. These basic data supplement those from the literature, enabling us to develop reliable models of nAChR kinetics that will be used throughout this research. At the second level of interaction, we use electrophysiology to examine the pharmacology of cholinomimetic drugs at nicotinic synapses. The experiments are guided and the interpretation assisted by a model of a CNS nicotinic synapse. At the third level, we use cyclic voltammetry in striatal brain slices to examine cholinergic/dopaminergic interactions guided by a model of interacting CNS synapses. The work proposed here will serve as the basis for future extensions to network interactions among neurotransmitter systems and future applications to other neurological diseases.
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