BME 6938 Neurodynamics Instructor: Dr Sachin S. Talathi.

Slides:



Advertisements
Similar presentations
Outline Neuronal excitability Nature of neuronal electrical signals Convey information over distances Convey information to other cells via synapses Signals.
Advertisements

BME 6938 Neurodynamics Instructor: Dr Sachin S. Talathi.
Instructor: Dr Sachin S. Talathi
Outline Neuronal excitability Nature of neuronal electrical signals Convey information over distances Convey information to other cells via synapses Signals.
Bioelectromagnetism Exercise #1 – Answers
Bioelectromagnetism Exercise #2 – Answers TAMPERE UNIVERSITY OF TECHNOLOGY Ragnar Granit Institute.
RESTING MEMBRANE POTENTIAL & ACTION POTENTIAL MR. Arjun Maitra Assistant Professor Dept. of Physiology PCMS&RC.
BME 6938 Neurodynamics Instructor: Dr Sachin S Talathi.
Recording of Membrane Potential
Apparatus to Study Action Potentials
Excitable membranes action potential & propagation Basic Neuroscience NBL 120 (2007)
Bioelectricity Provides basis for “irritability” or “excitability Fundamental property of all living cells Related to minute differences in the electrical.
Bioelectromagnetism Exercise #1 – Answers TAMPERE UNIVERSITY OF TECHNOLOGY Institute of Bioelectromagnetism.
C. Establishes an equilibrium potential for a particular ion
ECE602 BME I Ordinary Differential Equations in Biomedical Engineering (Cont’d)
Bio-signals.
Resting membrane potential 1 mV= V membrane separates intra- and extracellular compartments inside negative (-80 to -60 mV) due to the asymmetrical.
Action potentials of the world Koch: Figure 6.1. Lipid bilayer and ion channel Dayan and Abbott: Figure 5.1.
The Integrate and Fire Model Gerstner & Kistler – Figure 4.1 RC circuit Threshold Spike.
Part I: Single Neuron Models BOOK: Spiking Neuron Models, W. Gerstner and W. Kistler Cambridge University Press, 2002 Chapters 2-5 Laboratory of Computational.
Basic Models in Theoretical Neuroscience Oren Shriki 2010 Integrate and Fire and Conductance Based Neurons 1.
BME 6938 Neurodynamics Instructor: Dr Sachin S Talathi.
BME 6938 Neurodynamics Instructor: Dr Sachin S. Talathi.
Computational Biology, Part 20 Neuronal Modeling Robert F. Murphy Copyright  1996, 1999, All rights reserved.
Biological Modeling of Neural Networks Week 3 – Reducing detail : Two-dimensional neuron models Wulfram Gerstner EPFL, Lausanne, Switzerland 3.1 From Hodgkin-Huxley.
Generator Potentials, Synaptic Potentials and Action Potentials All Can Be Described by the Equivalent Circuit Model of the Membrane PNS, Fig 2-11.
Excitable Tissues and Resting Membrane Potential Part 2.
Lecture 3: linearizing the HH equations HH system is 4-d, nonlinear. For some insight, linearize around a (subthreshold) resting state. (Can vary resting.
Biological Modeling of Neural Networks Week 8 – Noisy input models: Barrage of spike arrivals Wulfram Gerstner EPFL, Lausanne, Switzerland 8.1 Variation.
EQUIVALENT CIRCUIT MODEL FOR THE CELL MEMBRANE Reported by: Valerie Chico ECE 5.
ELEC ENG 4BD4: Biomedical Instrumentation
BME 6938 Mathematical Principles in Neuroscience Instructor: Dr Sachin S. Talahthi.
Announcements:. Last lecture 1.Organization of the nervous system 2.Introduction to the neuron Today – electrical potential 1.Generating membrane potential.
1 Bi 1 Lecture 6 Thursday, April 6, 2006 Action Potentials and Single Channels.
Chap. 2 The resting membrane potential chap. 3 Action potential 第三节 细胞的生物电现象 from Berne & Levy Principles of Physiology (4th ed) 2005.
Transmission 1. innervation - cell body as integrator 2. action potentials (impulses) - axon hillock 3. myelin sheath.
Neuroprosthetics Week 4 Neuron Modelling. Implants excite neurons Retina – ganglion or bipolar cells Retina – ganglion or bipolar cells Cochlea/Ear –
Lecture 2 Membrane potentials Ion channels Hodgkin-Huxley model References: Dayan and Abbott, Gerstner and Kistler,
Neural codes and spiking models. Neuronal codes Spiking models: Hodgkin Huxley Model (small regeneration) Reduction of the HH-Model to two dimensions.
Biological Modeling of Neural Networks Week 8 – Noisy output models: Escape rate and soft threshold Wulfram Gerstner EPFL, Lausanne, Switzerland 8.1 Variation.
Nerve Impulse. A nerve impulse is an impulse from another nerve or a stimulus from a nerve receptor. A nerve impulse causes:  The permeability of the.
Nerve Impulse. A nerve impulse is an impulse from another nerve or a stimulus from a nerve receptor. A nerve impulse causes:  The permeability of the.
Major communication systems coordinate parts of animals body 1.Neuronal system: Rapid & Short Burst 2.Endocrine system: Slow & Persistent The Physical.
BME 6938 Neurodynamics Instructor: Dr Sachin S Talathi.
Electrochemical Potentials A. Factors responsible 1. ion concentration gradients on either side of the membrane - maintained by active transport.
Computing in carbon Basic elements of neuroelectronics Elementary neuron models -- conductance based -- modelers’ alternatives Wiring neurons together.
Comparative Vertebrate Physiology Action potentials.
Action Potentials.
Unit 1 Opener neuro4e-unit-01-opener.jpg.
CHAPTER ONE CELL MEMBRANE STRUCTURE. CHAPTER TWO MEMBRANE TRANSPORT.
Nerve Excitation Topic II-2 Biophysics.
Introduction to Mathematical Methods in Neurobiology: Dynamical Systems Oren Shriki 2009 First Order Differential Equations.
Electrophysiology 1.
Joshua Dudman :: 0 mV -80 mV.
Structural description of the biological membrane. Physical property of biological membrane.
1 In the name of God. 2 1-Resting Membrane Potentials 2-Action potential M.Bayat PhD Session 2.
Some problems. Problem #1 A typical mammalian cell has, in mEq/liter [K + ] in = 140; [K + ] out = 5 [Na + ] in = 15; [Na + ] out = 145 [Cl - ] in = 4;
Topics covered 1.Organization of the nervous system 2.Regions / specialization of the neuron 3.Resting membrane potential Especially ionic basis- Nernst,
In the name of God.
MATHEMATICAL MODEL FOR ACTION POTENTIAL
Objectives Basics of electrophysiology 1. Know the meaning of Ohm’s Law 2. Know the meaning of ionic current 3. Know the basic electrophysiology terms.
Biological Modeling of Neural Networks Week 11 – Variability and Noise: Autocorrelation Wulfram Gerstner EPFL, Lausanne, Switzerland 11.1 Variation of.
Epilepsy as a dynamic disease: Musings by a clinical computationalist
How and why neurons fire
HODGKIN–HUXLEY MODEL OF THE ACTION POTENTIAL
Hodgin & Huxley The problem: Explain action potentials
Transport of ions across plasma membranes
Neuroprosthetics Week 4 Neuron Modelling.
The Spark of Life: Electrical Basis of the Action Potential, a Vital Cell Signal IB Physics - 4 Spring 2018 Stan Misler
Resting Membrane Potential
Presentation transcript:

BME 6938 Neurodynamics Instructor: Dr Sachin S. Talathi

Recap Fundamental laws of cellular neurophysiology Nernst Plank Equation Nernst Equation (Reversal potential for ion channel) Active and passive ion transport (and Donnan equilibrium potential) Constant Field Assumption Goldman Hodgkin Katz Model Goldman Voltage Equation

Ionic currents and conductances Current across cell membrane resulting from flow of ion X: GHK Current Eq. In equilibrium : V=E X, current vanishes, i.e., I X (E X )=0 Linearize I X (V) around E X ; we get from GHK Eq. conductance Reversal (Nernst) potential Driving force (in general function of V and t) Note: Convention +ve driving force=> Current flowing out of cell Note:

The Equivalent circuit model for cell membrane Total membrane current I, is given as sum of all ionic currents and the capacitive current caused by the bi- lipid layer capacitance Note Ordinary differential equation model for neuron carrying current via flow of Na +,K + and Cl - ions across its cell membrane At rest (Inward current) (Outward current)

Resting Potential and Input Resistance Resting potential V rest,corresponds to steady state conditions i.e., With total input conductance Input resistance measures the sensitivity of the asymptotic membrane potential to input current Define Note: In general g inp, R inp and depend on time and voltage

Integrate and Fire (IF) model for nerve cell (Lapicque model) Assume V rest =0 and membrane resistance R inp does not depend on time and voltage General Solution: where And H(t) is the Heaviside step function G(t) is the Greens function Models the subthreshold dynamics of cell membrane voltage

Examples of sub threshold behavior Example 1: Example 2:Alpha function

IF model with threshold As we saw earlier, the IF model is only appropriate for subthreshold responses In order for IF model to mimic neuron that produces action potential, a threshold condition needs to be superimposed. Spiking IF model is complete by assuming that the nerve cell generates an action potential everytime V(t) reaches threshold levels. A simple threshold condition is t i is the sequence of times when spikes occur and t R is the absolute refractory period

Sub threshold repetitive excitation What is the minimum frequency of repetitive stimulation necessary to make the cell generate action potential? Assume ; sequence of delta pulse impulses with strength k and pulse freq 1/T From Greens function analysis, we know that every time a pulse arrives, the voltage will rise to k and then decay exponential per In steady state if V max and V min are the range of subthreshold voltage we have For neuron to spike

Exercise Derive expression for T crit when Hint

Frequency Current Relationship (Gain Function) Super threshold excitation Rheobase current I Rh : The membrane current at which the cell reaches threshold potential Change of variables: IF model follows linear F-I curve

Graphical analysis of IF neuron dynamics Subthreshold membrane activity Superthreshold membrane activity

Nonlinear IF model Extension to the IF model have been proposed to allow neurons to exhibit richer dynamics (i.e. bistability; we will study this in details at later date) Quadratic integrate and fire Exponential integrate and fire Subthreshold Dynamics: Superthreshold Dynamics:

Comparison to real neural dynamics in presence of noisy input current Trocme et al, 2003