ANUP UMRANIKAR A Phantom Bursting Mechanism for Episodic Bursting Richard Bertram, Joseph Rhoads, Wendy Cimbora.

Slides:



Advertisements
Similar presentations
Modeling the Action Potential in a Squid Giant Axon And how this relates to the beating of your heart.
Advertisements

Neural Modeling Suparat Chuechote. Introduction Nervous system - the main means by which humans and animals coordinate short-term responses to stimuli.
The dynamic range of bursting in a network of respiratory pacemaker cells Alla Borisyuk Universityof Utah.
Abstract We investigate the role of the ionic currents expressed in the human pancreatic β-cell in the generation of spiking electrical activity. The depolarization.
Presented by Suganya Karunakaran Reduction of Spike Afterdepolarization by Increased Leak Conductance Alters Interspike Interval Variability Fernando R.
Membrane capacitance Transmembrane potential Resting potential Membrane conductance Constant applied current.
Challenges in Modelling Active Electric Power Networks Dr. S. K. Chakravarthy Department of Elect. Engg., KFUPM.
Neuronal excitability from a dynamical systems perspective Mike Famulare CSE/NEUBEH 528 Lecture April 14, 2009.
XPPAUT Differential Equations Tool B.Ermentrout & J.Rinzel.
Dynamical Systems Analysis II: Evaluating Stability, Eigenvalues By Peter Woolf University of Michigan Michigan Chemical Process Dynamics.
Action potentials of the world Koch: Figure 6.1. Lipid bilayer and ion channel Dayan and Abbott: Figure 5.1.
Mathematical Models in Neural and Neuroendocrine Systems Richard Bertram Department of Mathematics and Programs in Neuroscience and Molecular Biophysics.
A Primer in Bifurcation Theory for Computational Cell Biologists Lecture 2 John J. Tyson Virginia Polytechnic Institute & Virginia Bioinformatics Institute.
Basic Models in Theoretical Neuroscience Oren Shriki 2010 Integrate and Fire and Conductance Based Neurons 1.
Autumn 2008 EEE8013 Revision lecture 1 Ordinary Differential Equations.
Biological Modeling of Neural Networks Week 3 – Reducing detail : Two-dimensional neuron models Wulfram Gerstner EPFL, Lausanne, Switzerland 3.1 From Hodgkin-Huxley.
Introduction to Mathematical Methods in Neurobiology: Dynamical Systems Oren Shriki 2009 Neural Excitability.
Population Modeling Mathematical Biology Lecture 2 James A. Glazier (Partially Based on Brittain Chapter 1)
Tutorial: Electrophysiology of Pancreatic Islets Richard Bertram Department of Mathematics and Programs in Neuroscience and Molecular Biophysics Florida.
TEST 1 REVIEW. Single Species Discrete Equations Chapter 1 in Text, Lecture 1 and 2 Notes –Homogeneous (Bacteria growth), Inhomogeneous (Breathing model)
Bursting Pacemaker Neurons Based on: Models of Respiratory Rhythm Generation in the Pre-Botzinger Complex. I. Bursting Pacemaker Neurons Robert.J. Butera,
BME 6938 Neurodynamics Instructor: Dr Sachin S Talathi.
The Dual Oscillator Model for Pancreatic Islets Richard Bertram Department of Mathematics and Programs in Neuroscience and Molecular Biophysics Florida.
A Hybrid Experimental/Modeling Approach to Studying Pituitary Cell Dynamics Richard Bertram Department of Mathematics and Programs in Neuroscience and.
Quadruped Robot Modeling and Numerical Generation of the Open-Loop Trajectory Introduction We model a symmetric quadruped gait for a planar robot with.
Simplified Models of Single Neuron Baktash Babadi Fall 2004, IPM, SCS, Tehran, Iran
1 MODELING MATTER AT NANOSCALES 4. Introduction to quantum treatments The variational method.
BME 6938 Neurodynamics Instructor: Dr Sachin S Talathi.
Day Problems For each solution write and graph an inequality.
Content: 1) Dynamics of beta-cells. Polynomial model and gate noise. 2) The influence of noise. Phenomenological. 3) The Gaussian method. 4) Wave block.
Halomda Educational Software ( Established 1988) Mathematics and Science for Primary, Intermediate and High schools, Colleges and Universities Computer.
Biological Neural Network & Nonlinear Dynamics Biological Neural Network Similar Neural Network to Real Neural Networks Membrane Potential Potential of.
Differential equations. Many applications of mathematics involve two variables and a relation between them is required. This relation is often expressed.
1 Low Dimensional Behavior in Large Systems of Coupled Oscillators Edward Ott University of Maryland.
Content: 1) Dynamics of beta-cells. Polynomial model and gate noise. 2) The influence of noise. Phenomenological. 3) The Gaussian method. 4) Wave block.
Inhibitory Population of Bursting Neurons Frequency-Domain Order Parameter for Synchronization Transition of Bursting Neurons Woochang Lim 1 and Sang-Yoon.
Hodgkin-Huxley Model and FitzHugh-Nagumo Model. Nervous System Signals are propagated from nerve cell to nerve cell (neuron) via electro-chemical mechanisms.
Warm Up. Solving Differential Equations General and Particular solutions.
Solving a System of Equations in Two Variables By Substitution Chapter 8.2.
MATHEMATICAL MODEL FOR ACTION POTENTIAL
Review Etc.. Modified Tumor-Immune Model Dimensional Analysis Effective growth rate for tumor cells (density) 1/3 /time Carrying capacity for tumor cells.
Tutorial: Converting Between Plateau and Pseudo-Plateau Bursting Richard Bertram Department of Mathematics and Programs in Neuroscience and Molecular Biophysics.
Phase Plane Diagrams ENT 420 Biological System Modeling Lecturer Engr. Mohd Yusof bin Baharuddin MBiomedEng (Melbourne) BBiomedEng (Malaya)
Section 9.4 – Solving Differential Equations Symbolically Separation of Variables.
Michail Stamatakis, Nikos V. Mantzaris  Biophysical Journal 
What weakly coupled oscillators can tell us about networks and cells
Biointelligence Laboratory, Seoul National University
Instability Analysis of Nerve Cell Dynamics in the FitzHugh-Nagumo Model Nasrin Sultana*, Sampad Das and M. Osman Gani** Department of Mathematics, Jahangirnagar.
FEA Introduction.
A Steady State Analysis of a Rosenzweig-MacArthur Predator-Prey System
One- and Two-Dimensional Flows
Bistability, Bifurcations, and Waddington's Epigenetic Landscape
Chapter 14. Dynamical Properties of Excitable Membranes
Spontaneous Synchronization of Coupled Circadian Oscillators
Volume 95, Issue 2, Pages (July 2008)
A method of determining the existence of bursting solutions, and output variables such as burst length and spike number, of multidimensional models using.
Volume 110, Issue 3, Pages (February 2016)
Modeling of Glucose-Induced cAMP Oscillations in Pancreatic β Cells: cAMP Rocks when Metabolism Rolls  Bradford E. Peercy, Arthur S. Sherman, Richard.
Michail Stamatakis, Nikos V. Mantzaris  Biophysical Journal 
X y y = x2 - 3x Solutions of y = x2 - 3x y x –1 5 –2 –3 6 y = x2-3x.
Mathematical Models of Protein Kinase Signal Transduction
Volume 6, Issue 4, Pages e3 (April 2018)
Excitability of the Soma in Central Nervous System Neurons
Effects of Temperature on Heteromeric Kv11.1a/1b and Kv11.3 Channels
Matthew J. Westacott, Nurin W.F. Ludin, Richard K.P. Benninger 
Chapter 3 Modeling in the Time Domain
Evidence for a Novel Bursting Mechanism in Rodent Trigeminal Neurons
Intracellular electrical recordings from islet β-cells exhibiting three types of oscillations. Intracellular electrical recordings from islet β-cells exhibiting.
Balanced scales and equations
Ping Liu, Ioannis G. Kevrekidis, Stanislav Y. Shvartsman 
Presentation transcript:

ANUP UMRANIKAR A Phantom Bursting Mechanism for Episodic Bursting Richard Bertram, Joseph Rhoads, Wendy Cimbora

Introduction Bursting = Periods of electrical spiking followed by periods of rest Bursting is observed in cells such as  R15 neuron of aplysia  Thalamic neurons  Pyramidal neurons  Trigeminal neurons  Pancreatic beta-cells  Pituitary gonadotrophs

Episodic (or Compound) Bursting Complex form of bursting observed in beta-cells of islets of Langerhans in pancreas and GnRH of pituitary gland Episodes of several bursts followed by long silent phases or ‘deserts’ Paper discusses episodic bursting using a minimal model Depending on location in parameter space, model produces fast, slow and episodic bursting

Mathematical Model Two slow variables interact with the fast subsystem Planar fast subsystem given by Expressions for ionic current are given by

Parameter Values In paper, all simulations and bifurcations were calculated using XPPAUT software package; CVODE numerical method used to solve differential equations I’ve used MATLAB for simulations; used ode15s to solve differential equations

Fast Bursting

Fast Bursting – My Results

Fast Bursting – Bifurcation Diagram Fast/slow analysis of fast bursting (s2 = 0.49). The solid portion of the z-curve represents branches of stable steady states. Dashed curves represent unstable steady states. The two branches of filled circles represent the maximum and minimum values of periodic solutions. The green dot-dashed curve is the s1 nullcline. HB=supercritical Hopf bifurcation, HM=homoclinic bifurcation, LK=lower knee, UK=upper knee.

Slow Bursting

Slow Bursting – My Results

Episodic Bursting

Episodic Bursting – My Results

Conclusion Model described in minimal, with two fast and two slow variables Slow variables represent activation variables of hyperpolarizing K+ currents. However, similar behavior could be achieved by defining slow variables in other ways, such as inactivation variables of depolarizing currents or as a combination of activation and deactivation Behaviors not restricted to specific details of this model Also, more complex neurons or endocrine cell models can be achieved using this minimal model, as long as model possesses at least two slow variables with disparate time scales

References Bertram, R., Rhoads, J., Cimbora, W., A phantom bursting mechanism for episodic bursting. Bull. Math. Biol. 70, Bertram, R., Previte, J., Sherman, A., Kinard, T.A., Satin, L.S., The phantom burster model for pancreatic β-cells. Biophys. J. 79, 2880–2892