A 3D Physiological Model of a Synapse During the Neural Response to Pain by Stefan Marcus

Introduction A well studied gene regulation system in E. coli Turns on certain gene only when lactose is present so as to not waste energy Various mathematical and computational simulations established The lac operon (

Agent based modelling Able to show the emerging big picture that results from several agents interacting Natural model of a system and more suitable for random movement of particles like neurotransmitters Flexible and allows for a addition of several agents as well as simple changes to the simulation

LINDSAY Virtual Human An interactive model of human anatomy and physiology Several systems will be modeled and implemented over time

Rationale Useful tool for learning the complexities of physiological processes Ability to reproduce results in literature will establish LINDSAY as a tool for researchers as well Blood clotting

The LINDSAY Composer

Simulation of the nervous system Simulating the nervous system is a daunting task Simple reflex arc as a starting point Main focus: The synapse

Some review Information is conveyed through the nervous system as nerve impulses (action potentials) This electrical current travels from neuron to neuron through a synapse

The synapse The action potential stimulates the neuron to release neurotransmitters Neurotransmitters attach to the receptors on the other neuron which then opens ion channels, allowing the signal to propagate

Big Picture My focus will only be on modelling the synapses between the neurons

Components -Neurotransmitters -Synaptic Vesicles -Ion Channels -Receptors -Pumps -Presynaptic neuron -Postsynaptic neuron The following will be constructed using MAYA

The simulation First step Use agent-based modelling to create an abstract synaptic model which will allow for propagation of signal from one neuron to the next 1. Action potential opens calcium channels in presynaptic membrane 2. Neurotransmitter release into synapse when vesicles are activated by calcium influx 3. Movement through synaptic space 4. Binding to receptor 5. Gates open allowing for positive ions to move through 6. Threshold that would initiate an action potential

The simulation Further develop the subsystems within the simulation. Second step 1. Specific diffusion rates for certain neurotransmitters 2. Neurotransmitter-receptor kinetics 3. Accounting for reuptake/breakdown of neurotransmitters

Third step Validating the model by comparing results to literature values and making necessary adjustments The simulation Similar previous studies using mathematical models (6, 9) have compared their results to patch clamp experiments on CA3 pyramidal neurons in mice (8)

The simulation Fourth step Adding parameters so users will be able to manipulate number of agents, time, distances between receptors, etc., and then observe the results

Future directions Synaptic plasticity Painkillers Different neurotransmitters Summary -Neuron simulation as part of the LINDSAY Virtual Human -A series of steps making the simulation complex and accurate -Possibilities for future development

References [1] E. Bonabeau. Agent-based modeling: methods and techniques for simulating human systems. PNAS, 99:7280–7287, [2] W. Boron and E. Boulpaep. Medical Physiology. Elsevier Saunders Inc, updated edition, [3] C. Jacob, S. von Mammen, S. Novakowski, V. Sarpe, and T. Davison. LINDSAY: Building a Virtual Human for Medical Education, Exploration and Consultation, [4] C. Jacob, and I. Burleigh. Biomolecular swarms - an agent based model of the lactose operon. Natural Computing, 3: , [5] D. Julius and A. I. Basbaum. Molecular mechanics of nociception. Nature, 413:203–210, [6] D. Kullman, M.-Y. Min, F. Asztely, and D. A. Rusakov. Extracellular glutamate diffusion determines the occupancy of glutamate receptors at ca1 synapses in the hippocampus. Molecular and Cellular Aspects of Exocytosis, 354(1381):395–402, [6] W. Senn, H. Markram, and M. Tsodyks. An algorithm for modifying neurotransmitter release probability based on pre- and postsynaptic spike timing. Neural computation, 13(1):35– 67, [8] N. Spruston, Jonas, P., and Sakmann, B. Dendritic glutamate receptor channels in rat hippocampal CA3 and CA1 pyramidal neurons. J. Physiol. Lond. 482: , [9] L. M. Wahl, C. Pouzat, and K. J. Stratford. Monte carlo simulation of fast excitatory synaptic transmission monte carlo simulation of fast exciatory synaptic transmission at a hippocampal synapse. Journal of Neurophysiology, 75(2):597–608, 1996.

Acknowledgements Dr. Christian Jacob Sebastian von Mammen Tanya Karaman Iman Yazdanbod Abbas Sarraf Afshin Esmaeili Vlad Sarpe Timothy Davison

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