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.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
3P41RR006009-20S1
Application #
8364228
Study Section
Special Emphasis Panel (ZRG1-BCMB-Q (40))
Project Start
2011-09-15
Project End
2013-07-31
Budget Start
2011-09-15
Budget End
2013-07-31
Support Year
20
Fiscal Year
2011
Total Cost
$1,094
Indirect Cost
Name
Carnegie-Mellon University
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
052184116
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Simakov, Nikolay A; Kurnikova, Maria G (2018) Membrane Position Dependency of the pKa and Conductivity of the Protein Ion Channel. J Membr Biol 251:393-404
Yonkunas, Michael; Buddhadev, Maiti; Flores Canales, Jose C et al. (2017) Configurational Preference of the Glutamate Receptor Ligand Binding Domain Dimers. Biophys J 112:2291-2300
Hwang, Wonmuk; Lang, Matthew J; Karplus, Martin (2017) Kinesin motility is driven by subdomain dynamics. Elife 6:
Earley, Lauriel F; Powers, John M; Adachi, Kei et al. (2017) Adeno-associated Virus (AAV) Assembly-Activating Protein Is Not an Essential Requirement for Capsid Assembly of AAV Serotypes 4, 5, and 11. J Virol 91:
Subramanian, Sandeep; Chaparala, Srilakshmi; Avali, Viji et al. (2016) A pilot study on the prevalence of DNA palindromes in breast cancer genomes. BMC Med Genomics 9:73
Ramakrishnan, N; Tourdot, Richard W; Radhakrishnan, Ravi (2016) Thermodynamic free energy methods to investigate shape transitions in bilayer membranes. Int J Adv Eng Sci Appl Math 8:88-100
Zhang, Yimeng; Li, Xiong; Samonds, Jason M et al. (2016) Relating functional connectivity in V1 neural circuits and 3D natural scenes using Boltzmann machines. Vision Res 120:121-31
Lee, Wei-Chung Allen; Bonin, Vincent; Reed, Michael et al. (2016) Anatomy and function of an excitatory network in the visual cortex. Nature 532:370-4
Murty, Vishnu P; Calabro, Finnegan; Luna, Beatriz (2016) The role of experience in adolescent cognitive development: Integration of executive, memory, and mesolimbic systems. Neurosci Biobehav Rev 70:46-58
Shafee, Rebecca; Buckner, Randy L; Fischl, Bruce (2015) Gray matter myelination of 1555 human brains using partial volume corrected MRI images. Neuroimage 105:473-85

Showing the most recent 10 out of 292 publications