Hansen, Elizabeth

English

Kenyon College: Digital Kenyon - Research, Scholarship, and Creative Exchange

Digital Kenyon: Research, Scholarship, and Creative ExchangeKenyon Summer Science Scholars Program Summer Student Research ScholarshipSummer 2007Computational Modeling of Astrocytic GlutamateInput to NeuronsElizabeth HansenFollow this and additional works at: https://digital.kenyon.edu/summerscienceprogramPart of the Chemistry CommonsThis Poster is brought to you for free and open access by the Summer Student Research Scholarship at Digital Kenyon: Research, Scholarship, andCreative Exchange. It has been accepted for inclusion in Kenyon Summer Science Scholars Program by an authorized administrator of Digital Kenyon:Research, Scholarship, and Creative Exchange. For more information, please contact noltj@kenyon.edu.Recommended CitationHansen, Elizabeth, "Computational Modeling of Astrocytic Glutamate Input to Neurons" (2007). Kenyon Summer Science ScholarsProgram. Paper 377.https://digital.kenyon.edu/summerscienceprogram/377Computational Modeling of Astrocytic Glutamate Input to NeuronsElizabeth Hansen with Dr. Sheryl HemkinQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.QuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.IntroductionThis project initiated the creation of a physiologically sound model of thecommunication between neurons and astrocytes. Astrocytes are small, star-shaped glial cells that are located next to the neurons in the brain. Glutamateis an excitatory neurotransmitter that is released from the astrocyte and candiffuse to the membrane of the neuron. The focus of this study was the affectof astrocytic glutamate on the membrane potential of the neuron.The ModelTo initiate the study of a “dressed” neuron system, the interaction of oneastrocyte and one neuron, experimentally derived information was taken fromthe literature and used to create a model.The model simulates the changes in the neuron’s membrane potential as it isbeing stimulated by external inputs, ex. glutamate, background “noise.”Vmembranepotential(t)       Nnoise(t)     Gglutamate(t)  Stimuli to the Neuron (both new and accumulated signal affects membrane potential) -Nnoise = background noise, guides spontaneous firing rateGglutamate = extra-neural glutamate signal, excitatory neurotransmitterThe noise term is representative of the inputs acting on the neuron that act asbackground. They are not signaling, they simply the “noise” associated withthe activity in the brain.The glutamate is the gliotransmitter that we are focusing on. This termrepresents the potential of the input of glutamate coming to the neuron fromthe astrocyte. The final part of this equation is the membrane potential. Thisis the amount of depolarization the neuronal membrane undergoes whenexternal signaling molecules are acting on it.Another important part of the model is the refractory period. There are, in fact,two refractory periods associated with each input. The absolute refractoryperiod is a time right after the firing of an action potential where anotheraction potential cannot be fired, regardless of its level above threshold. Thisperiod can be 1-3 ms in length. Following the absolute refractory period is therelative refractory period. In the relative refractory period an action potentialcan be\ fired, but it must be a specific amount above threshold. Relativerefractory periods can last 3-5 ms. This addition to the model is reflected inthe spiking patterns for each input (Fig 1b, Fig 2b, Fig 3c).Figure 2 (a) Represents the change in membrane potential thatcorrelates to the sinusoidal model of glutamateinput over 3000 ms. The sinusoidal model wasused to mimic the oscillatory nature of theglutamate input. The resting potential of this modelis scaled to zero ( the actual resting potential being-65 mV for a CA1 pyramidal neuron) and thethreshold potential has been scaled to one. (b)When the scaled potential reaches threshold orsurpasses threshold an action potential is fired.(a)(b)Figure 1(a) The scaled membrane potential for the noise termover 1000 ms. The noise term was found usingthe equation:Ncurrent Nold e(1/D)  RNpresent = the membrane potential at the present timeNold = the membrane potential a millisecond beforeD = the decay constant specific to the neuronR = a random number(b) When the noise potential reaches the threshold anaction potential is fired. The spacing between thespikes is due not only to the potential, but also to therefractory periods.(a)(b)References:J, Dudel. "Kinetics of Postsynaptic Action of Glutamate Pulses Applied Iontophoretically Through High Resistance Micropipettes." Pflugers Arch. (1975): 329-345.R, Parri, and Crunelli V. "An Astrocyte Bridge From Synapse to Blood Flow." Natural Neuroscience 6.1 (2003): 587-6.Reynolds, Glenn. "Hyperstition." Hyperstition: Neutronic News. 11 Apr. 2007. 10 Oct. 2007 <http://hyperstition.abstractdynamics.org/archives/009244.html>.  Shin, J. Y., Z X. Yu, C E. Wang, S H. Li,  and X J. Li. "Expression of Mutant Huntingtin in Glial Cells Contributes to Neuronal Excitotoxicity." Huntington's Disease Advocacy Center. 29 Dec. 2005. Huntington's Disease Advocacy Center. 5 Oct. 2007 <http://www.hdac.org/features/article.php?p_articleNumber=212>. AM Benediktsson1, GS Marrs, JC Tu, PF Worley, JD Rothstein, DE Bergles, and ME Dailey, (2003) Clustering and dynamic remodeling of a glutamate transporter, Glt-1a, in hippocampal astrocytes.Acknowledgments:I would first and foremost like to thank Dr. Sheryl Hemkin for her guidance,knowledge, patience, and assistance. I would like to thank Nora Pencheva forher prior work on the project and her advice. I owe a lot of gratitude to KenyonCollege for providing the funding and resources for the Summer ScienceScholars program.Reynolds, 2007Shin, 2005Bedictssen, 2003Figure 4A fluorescent confocal imagein live brain tissue slices ofthe astrocyte and neuronsystem.Figure 6A pryamidal neuron imaged using fluorescent confocal imaging.Figure 5Astrocytes imaged using fluorescent confocal imaging.Figure 3(a) The inset is a recorded EPSP from a neruon.This EPSP was used to model the input ofglutamate shown above. Though, not an exactmodel it is more physiologically sound. (b) Theglutamate (in red) seems to be a small, straightline, but when comparing the noise input (ingreen) to the total change in potential (in blue) itis clear that the glutamate has a marked effecton the total potentiation. (c) This can also beinferred from the spiking of action potentials forthe glutamate model.(a)(b)(c)

Computational Modeling of Astrocytic Glutamate Input to Neurons

https://digital.kenyon.edu/cgi/viewcontent.cgi?article=1332&amp;context=summerscienceprogram

Computational Modeling of Astrocytic Glutamate Input to Neurons

Abstract

Similar works

Full text

Available Versions

Kenyon College: Digital Kenyon - Research, Scholarship, and Creative Exchange