Dayan Abbot Ch 5.1-4,9.

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

Neurophysiology. The Resting Membrane Potential Intracellular (soma) Extracellular VV -70 mV.
Why are cortical spike trains irregular? How Arun P Sripati & Kenneth O Johnson Johns Hopkins University.
Chemical synapses: post-synaptic mechanisms. Postsynaptic Membranes and ion channels Ligand gated ion channels – a review a. Resting K + channels: responsible.
Cellular Neuroscience (207) Ian Parker Lecture #13 – Postsynaptic excitation and inhibition.
Effects of Excitatory and Inhibitory Potentials on Action Potentials Amelia Lindgren.
Neural Condition: Synaptic Transmission
The Decisive Commanding Neural Network In the Parietal Cortex By Hsiu-Ming Chang ( 張修明 )
COGNITIVE SCIENCE 17 The Electric Brain Part 1 Jaime A. Pineda, Ph.D.
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.
Copyright © 2008 Pearson Education, Inc., publishing as Pearson Benjamin Cummings PowerPoint ® Lecture Presentations for Biology Eighth Edition Neil Campbell.
Neurons & Neuroanatomy What are the characteristics of neurons important for Cognitive Neuroscience? What is the brain structure important for CogNeuro?
Week 2 Membrane Potential and Nernst Equation. Key points for resting membrane potential Ion concentration across the membrane E ion : Equilibrium potential.
Lecture 9: Introduction to Neural Networks Refs: Dayan & Abbott, Ch 7 (Gerstner and Kistler, Chs 6, 7) D Amit & N Brunel, Cerebral Cortex 7, (1997)
Lecture 2 Membrane potentials Ion channels Hodgkin-Huxley model References: Dayan and Abbott, Gerstner and Kistler,
Membrane Transport1 Not responsible for: Nernst Equation, other than to know what it’s used for. Chapter 12 Membrane Transport Questions in this chapter.
Theoretical Neuroscience Physics 405, Copenhagen University Block 4, Spring 2007 John Hertz (Nordita) Office: rm Kc10, NBI Blegdamsvej Tel (office)
INTRODUCTION OF INTEGRATE AND FIRE MODEL Single neuron modeling By Pooja Sharma Research Scholar LNMIIT-Jaipur.
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.
Galvanism 1790 Luigi Galvani & “animal electricity” Contraction of a muscle that is stimulated by an electric current.
Structural description of the biological membrane. Physical property of biological membrane.
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;
The Action Potential. Four Signals Within the Neuron  Input signal – occurs at sensor or at points where dendrites are touched by other neurons.  Integration.
Do Now 1/9/15 1.Name 3 glial cells and describe their function and location. 2.Which neural pathway transmits a signal when the internal body temperature.
Resting (membrane) Potential
Resting Membrane Potential
Chemical synapses: post-synaptic mechanisms
The Patch Clamp Method 1976 by Erwin Neher and Bert Sakmann at the Max Planck Institute in Goettingen.
Neuron.
Animal Cell Chromatin.
Biological Neural Networks
The Neuron.
What is the part of the neuron that receives signals? Sends them?
Nerve Signals 11.2 (Image from:
Neurons, Synapses, and Signaling
Action Potential Propagation
NOTES - UNIT 5 part 2: Action Potential: Conducting an Impulse
Nerve cell membrane Electrochemical message is created by the movement of ions across the nerve cell membrane The resting nerve membrane has a electrical.
Learning Objectives After this miniclass, you should be able to:
Synaptic integration in single neurons
Do Now Describe what biological psychology is..
Neurons Parts of a Neuron Dendrite Axon Myelin sheath
Animal Cell Chromatin.
Action Potentials and Conduction
Action Potential 6.5.
1. Describe the structures and functions of the animal nervous system
6.5 Nerves, Hormones, and Homeostasis
Resting Potential, Ionic Concentrations, and Channels
Polarity of Long-Term Synaptic Gain Change Is Related to Postsynaptic Spike Firing at a Cerebellar Inhibitory Synapse  Carlos D Aizenman, Paul B Manis,
Neuron Physiology.
Cell Communication: Neuron.
AP Biology Nervous Systems Part 3.
Effects of Excitatory and Inhibitory Potentials on Action Potentials
Neural Condition: Synaptic Transmission
Neuronal Signals.
Carlos D. Brody, J.J. Hopfield  Neuron 
Preceding Inhibition Silences Layer 6 Neurons in Auditory Cortex
Electrochemical Gradient Causing an Action Potential
Biology 211 Anatomy & Physiology I
AP Biology Nervous Systems Part 3.
Action potentials.
AP Biology Nervous Systems Part 3.
Gates + Potentials.
Animal Cell Cell Membrane.
Synaptic Transmission and Integration
Learning Objectives After this class, you should be able to:
Shunting Inhibition Modulates Neuronal Gain during Synaptic Excitation
Neural Condition: Synaptic Transmission
Presentation transcript:

Dayan Abbot Ch 5.1-4,9

Membranes Different ion channels have different Nernst (reversal) potentials. Opening and closing of channels regulates this flow. Na and Ca have positive reversal potentials. Opening these channels depolarizes the membrane. K has negative reversal potential and depolarizes the membrane. Membrane current thus approximately given by I= g(V-E) Where g and E channel specific. G is time dependent conductance. Channels maintain cell resting potential, spike generation, and synaptic contacts Resting potential is given by ratio of ion concentrations by Nernst equation for K. E=RT/F ln [outside]/[inside]

Single comparment model linearizes current voltage relation around resting potential. S is synapse G_l is leak V is voltage dependent conductance

Integrate-and-fire neuron driven by current input I_e. For constant current I, the IF neuron spikes regularly with a rate inverse the ISI time: T_ISI=tau ln(R I + E-V_r)/(RI + E – V_th) C_m dV/dt = -1/R (V-E)+I Tau dV/dt= E-V+R I When V reaches a threshold V_th, V is reset to V_r. Solid: pyramidal cell first ISI Open: pyramidal cell adapted ISI Line: IF model Adaptation can be included (5.14).

Synapes and coupled IF Tau dV/dt = E_l – V - g P (V-E) + R I P=P_max t/tau_s exp(1 - t/tau_s) Is alpha function, has max at t=tau_s V_r = -80 mV E_l=-70 mV V_th= -54 mV Tau=20 ms G=0.05 RI=25 mV Tau_s=10 ms P_max=1 A: Excitatory connection. E=0 mV. Out of phase response B: Inhibitory connection. E=-80 mV. In phase response

IF neuron driven by 1000 excitatory and 200 inhibitory inputs IF neuron driven by 1000 excitatory and 200 inhibitory inputs. Each input is an independent Poisson spike train driving a synaptic conductance. Top. Membrane potential in absence of spike generation mechanism. Bottom, with spike generation mechanism. Left: when total input drives the neuron above the firing threshold, IF fires at high rate and regular (CV=0.3) Right: when total input drives the neuron below or around the threshold, IF fires irregularly. (CV=0.84).