This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Background Anesthetic agents modulate a number of voltage gated and ligand gated ion channels, but there does not seem to be specific channels that are the site of action for all anesthetics. Even when the site of action of a specific anesthetic is known, the process whereby anesthetic modulation of ion channels leads to the anesthetic state has yet to be established. The overall goal of this research is to use large scale computational models to elucidate the integrated systems level response of model neurons to anesthetics. The data generated from computing resources requested in this application will be used to support an application to NIH for additional resources to continue this work. To appreciate the importance of building a computational bridge between anesthetic action at the receptor level and the systems level, it is necessary to realize the fundamentally different responses to anesthetics in each domain. A single anesthetic can modulate the activity of one or more voltage gated and/or ligand gated ion channels. Typically, the concentration effect curves for a given channel are relatively shallow with midpoints occurring at anesthetic concentrations that are well above those used clinically. This graded modulation of ion channel behavior contrasts the abrupt changes that anesthetics induce at the systems level. For clinically useful anesthetic concentrations the brain is far from quiescent, as revealed by electroencephalographic and functional imaging studies. Over a population of subjects, the onset of the anesthetic state is relatively abrupt as anesthetic concentration is increased, and the concentration at which this occurs is considerably below the midpoint of the concentration effect curve for the putative ion channels. The systems level response to anesthetics is additionally complex because it encompasses a number of distinct features that emerge at distinct anesthetic concentrations. Minimally these include amnesia, loss of consciousness, blockade of painful stimuli, and immobility. Importantly, these effects can be produced by anesthetics that target entirely different sets of receptors. The qualitatively disparate behaviors described demonstrate the need for approaches linking anesthetic action at the receptor level with large scale systems level behavior. Although there is no specific network behavior that is definitively linked to general anesthesia, there is a growing appreciation that at least some aspects of general anesthesia are linked to the ability of the brain to generate coherent oscillations. These oscillations are thought to originate in the thalamic circuitry and the synchronization of these oscillations are dependent on the interaction established between the thalamus and the cortex. It is reasonable to hypothesize that these effects on the thalamus and cortex could be an important component of the anesthetic state since this region has already been shown to be closely associated with both sleep and consciousness. Furthermore, our preliminary results have demonstrated the ability of anesthetics to both synchronize and slow oscillations in a model of the thalamic relay and reticular nucleus neurons. The possible impact of these alterations on the rest of the thalamus and its interaction with the cortex are important considerations which have yet to be examined. To date, we have examined the effects of a variety of anesthetics on single cell and small network models of the reticular nucleus of the thalamus, thalamocortical neurons, hippocampal neurons, a fast spiking interneuron network, and Aplysia. We now seek to expand this effort to incorporate neurons which are more realistic with respect to types of ion channels and morphology. Preliminary results in small networks (2 cells of each neuron type) incorporating 4 different types of neurons, pyramidal neurons (PY) and interneurons (IN) in the cortex and thalamic relay (TC) and reticular nucleus (RE) neurons in the thalamus, have shown that the feedback between the thalamic neurons and the cortical neurons are important in understanding the behavior of the neurons under anesthetic effects. Being able to create large complex networks (100 cells of each neuron type) is essential to discerning the differences in anesthetics on the overall system level behavior and at the cellular level.

National Institute of Health (NIH)
National Center for Research Resources (NCRR)
Biotechnology Resource Grants (P41)
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Special Emphasis Panel (ZRG1-BCMB-Q (40))
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Carnegie-Mellon University
Biostatistics & Other Math Sci
Schools of Arts and Sciences
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