Study of Stimulus Waveform Effect on Nerve Excitability and SENN model verification in Lumbricus Terrestris as a Convenient Animal Model

Size: px
Start display at page:

Download "Study of Stimulus Waveform Effect on Nerve Excitability and SENN model verification in Lumbricus Terrestris as a Convenient Animal Model"

Transcription

1 Biomedicine and Molecular Biosciences COST Action BM39 EMF-MED COST EMF-MED European network for innovative uses of EMFs in biomedical applications Study of Stimulus Waveform Effect on Nerve Excitability and SENN model verification in Lumbricus Terrestris as a Convenient Animal Model Prof. Antonio Šarolić, PhD Zlatko Živković, PhD FESB Split

2 Biomedicine and Molecular Biosciences COST Action BM39 EMF-MED Contents. Introduction 2. SENN model 3. Animal model 4. Measurement setup 4. Measurement/simulation results 5. Conclusion 2

3 Biomedicine and Molecular Biosciences COST Action BM39 EMF-MED Contents. Introduction 2. SENN model 3. Animal model 4. Measurement setup 4. Measurement/simulation results 5. Conclusion 3

4 Introduction o single axon studies effects of stimulus parameters computational stimulation model controllable measurements o transition ELF -> higher frequencies (IF range) complex pulses (single or repetitive) optimized biomedical effects (healing, pain relief, ) EMF safety (human exposure) waveform effects (temporal and frequency parameters) 4

5 Terminology Threshold level V th [mv] - the transmembrane voltage level that should be exceeded to excite the action potential. Stimulus threshold level I TH [ma] - the minimum stimulus current magnitude (peak value) just sufficient to excite the nerve and initiate AP propagation. Monopolar stimulation - the type of electrical stimulation with the active electrode positioned near the nerve that wants to be stimulated. Bipolar stimulation - the type of stimulation where both the active and return electrode are placed in the close proximity to an axon Monophasic stimulus - the stimulus with unidirectional current Biphasic stimulus - the stimulus with bidirectional current 5

6 Biomedicine and Molecular Biosciences COST Action BM39 EMF-MED Contents. Introduction 2. SENN model 3. Animal model 4. Measurement setup 4. Measurement/simulation results 5. Conclusion 6

7 McNeal s and SENN model of myelinated axon dv I C I G V 2V V dt n m m i,n i i,n- i,n i,n+ G i 2 π d L 4 i i Li D V n =V i,n -V e,n Ri INTRACELLULAR MEDIUM V i,n- Ri V i,n Ri V i,n+ Ri d.7d dv d n Gi Vn- 2V n Vn+ Ve,n- 2V e,n Ve,n+ Ii,n t C m cm rm Vr cm rm Vr cm rm Vr Second spatial Second spatial difference of difference of unknown extracellural liqid potential transmembrane (activation function): potential Δ 2 V e,n => Δ 2 V e,n /Δx 2 =ΔE e,n /Δx V e,n- V e,n V e,n+ EXTRACELLULAR MEDIUM I π d w J J J J i,n Na K P L J G ( V V ) Na Na n Na J G ( V V ) K K n K J G ( V V ) P P n P J G ( V V ) L L n L SENN model Activation function 7

8 σ e [S/m] SENN model parameters Parameter Value Fiber diameter (D) 2 µm,6 Axon diameter at node (d).7 D Nodal gap (w) 2.5 µm Axoplasmic resistivity (ρ i ) External medium resistivity (ρ e ) Ωm 3 Ωm Membrane capacitance (c m ) 2 µf/cm 2 Membrane conductivity (g m ) Internodal distance (L i ) 3.4 ms/cm 2 D,5,4,3,2, f [khz] y A =5 mm L=2 y A = cm N R =5 nodes 8

9 Equivalent time constant - τ Q I rb rb c ln 2 approximate chronaxie (τ c ) equivalent time constant (τ) relation τ= µs 9

10 Biomedicine and Molecular Biosciences COST Action BM39 EMF-MED Contents. Introduction 2. SENN model 3. Animal model 4. Measurement setup 4. Measurement/simulation results 5. Conclusion

11 Lumbricus terrestris (Earthworm) Earthworm

12 Why Earthworm (lat. Lumbricus Terrestris) 2

13 Biomedicine and Molecular Biosciences COST Action BM39 EMF-MED Contents. Introduction 2. SENN model 3. Animal model 4. Measurement setup 4. Measurement/simulation results 5. Conclusion 3

14 Measurement setup 4

15 Measurement setup (photo) 5

16 Biomedicine and Molecular Biosciences COST Action BM39 EMF-MED Contents. Introduction 2. SENN model 3. Animal model 4. Measurement setup 4. Measurement/simulation results 5. Conclusion 6

17 Single/repetitive monophasic square pulses Transmembrane voltage change [mv] 2 Transmembrane voltage change [mv] Single pulse td=2 µs 2τ ITH=4.5 ma 8 6.*I_TH I_TH 4.8*I_TH 2.5*I_TH td= µs.τ ITH=24.75 ma 8.*I_TH 6 I_TH 4.9*I_TH 2.5*I_TH,2,4 Repetitive pulses td=2 µs 2τ tp=2 µs 2τ Case ITH=3.2mA 2.2 * I_TH I_TH 8.8 * I_TH I_TH.8 * I_TH Case 4.2 * I_TH 8 I_TH 6.8 * I_TH t [ms] td=2 µs 2τ tp=µs.τ ITH=2.2 ma 3 4 Transmembrane voltage change [mv] Transmembrane voltage change [mv].2 * I_TH Case 2 t [ms] 2,8 td= µs.τ 3 tp=2case µs 2τ ITH=5 ma t [ms] -2,6 t [ms] Transmembrane voltage change [mv] Transmembrane voltage change [mv] t [ms] td= µs.τ tp= µs.τ ITH=4.5 ma * I_TH 4 I_TH 2.8 * I_TH -2,2,4,6 t [ms],8 7

18 Δ SR [db] Single/repetitive monophasic square pulses (2) SR db 2log I I single TH repetitive TH tp= μs tp=3 μs tp=5 μs tp= μs tp=3 μs 4 2 t D [μs] 8

19 Transmembrane voltage change [mv] Transmembrane voltage change [mv] Transmembrane voltage change [mv] Transmembrane voltage change [mv] Single/repetitive biphasic square pulses Single pulse t D = µs t D = µs I_TH=4.68 ma 3.8*I_TH,2,4,6,8-3 t [ms] t D = µs τ 8 6 I_TH=5.5 ma 4.8*I_TH 2-2,2,4,6,8 t [ms] t D = µs.τ Repetitive pulses 2 t D = µs 2 t D = µs I_TH=4.3 ma 8.8*I_TH ,5,5 2 2,5 t [ms] t D = µs τ 9 I_TH=27 ma 6.8*I_TH 3,2,4,6,8-3 t [ms] t D = µs.τ 9

20 I TH [ma] Single/repetitive biphasic square pulses (2) Single monophasic pulse Single biphasic pulse monophasic pulses biphasic pulses 3 2 t D [µs] 2

21 Transmembrane voltage change [mv] Transmembrane voltage change [mv] Transmembrane voltage change [mv] Transmembrane voltage change [mv] Single cycle/continuous sinusoid Single cycle t D = µs.2*i_th I_TH.8*I_TH,5,5 2 t [ms] I TH =6.2 ma t D = µs.2*i_th I_TH.8*I_TH,2,4,6,8 t [ms] I TH =75 ma Continuous t D = µs t [ms] I TH =5.6 ma.2*i_th I_TH.8*I_TH t D = µs,2,4,6,8 t [ms] I TH =36.5mA.2*I_TH I_TH.8*I_TH 2

22 I TH [ma] Single cycle/continuous sinusoid (2) Single monophasic pulse Single sinusoidal cycle monophasic pulses sinusoidal cycles t D [µs] 22

23 Equivalence between repetitive monophasic square pulses and continuous sinusoid - t D =t P I TH [ma] f 2 t D Single monophasic pulse with td=/2fc (peak value) Continuous sinusoid with frequency fc (RMS value) S/P I I sine(rms) TH pulse(peak) TH f /2t c D S/P f c [khz] S/P I I sine(rms) TH pulse(peak) TH f /2t c D S/P cycle 9 5 cycles 8 7 cycles 6 2 cycles 5 5 cycles 4 cycles f [khz].2 fc [khz] 23

24 I TH [ma] Measurement results SD curves Worm Worm 2 Worm 3 Worm 4 Worm 5 Chronaxie - τ c [ms] Time constant - τ [ms] Earthworm.44 Earthworm 2.44 Earthworm Earthworm Earthworm SENN t D [ms]

25 Measurement results monophasic square pulse Worm SENN Worm 2 SENN Worm 3 SENN I TH /I rb I TH /I rb I TH /I rb... ϒ D =t D /τ... ϒ D =t D /τ.. ϒ D =t D /τ Worm 4 SENN Worm 5 SENN I TH /I rb I TH /I rb.. ϒ D =t D /τ.. ϒ D =t D /τ 25

26 I TH [ma] Measurement results continuous sinusoid Worm Worm 2 Worm 3 Worm 4 Worm 5,, f [khz] Worm SENN Worm 2 SENN Worm 3 SENN I TH /I rb I TH /I rb I TH /I rb.. ϒ D =t D /τ.. ϒ D =t D /τ Worm 4 SENN.. ϒ D =t D /τ Worm 5 SENN I TH /I rb I TH /I rb.. ϒ D =t D /τ.. ϒ D =t D /τ 26

27 Comparison of the single monophasic square pulse and continuous sinusoid with equal t D (f c =/2t D ) I TH [ma] S/P Worm Worm 2 Worm 3 Worm 4 Worm 5 SENN,, ϒ D =t D /τ Comparison of the repetitive biphasic square pulses and continuous sinusoid with equal t D (f c =/2t D ) 8, Sinusoid Biphasic square wave S/P,8,6,4,2 Measurements SENN results,, f [khz],, ϒ D =t D /τ 27

28 I TH [ma] P/S (ϒ D,ϒ P ) Comparison of the repetitive monophasic square pulses and continuous sinusoid with equal t D and t P (f c =/2t D ) P/S (ϒ D,ϒ P ) P/S (ϒ D,ϒ P ), t D =t P Single pulse Repetitive pulses (tp=td),, ϒ=t D /τ [ms] Comparison of the repetitive monophasic square pulses with arbitrary phase/pause durations and continuous sinusoid with (f c =/2t D ) S/P t D =t P Measurement results SENN results,, ϒ D =t D /τ,2 t D =3τ,8,6,4 Measurement results,2 SENN results,,, ϒ P =t P /τ t D =τ,8,6,4,2 Measurement results SENN results,,, ϒ P =t P /τ t D =.τ,7,6 Measurement results,5 SENN results,4,3,2,,,, ϒ P =t P /τ 28

29 Conclusion The study produced a set of results that nicely agree both with the theory and with SENN model, proving that this setup could be conveniently used for following studies. 29

30 THANK YOU FOR YOUR ATTENTION! 3

31 3

Electrostimulation Models in Perspective

Electrostimulation Models in Perspective Document MT 16-109 v1.3 18 Feb. 2016 Electrostimulation Models in Perspective J. Patrick Reilly The Johns Hopkins University (Retired) 12516 Davan Drive Silver Spring, MD, USA jpreilly@erols.com Presented

More information

Biomedical Instrumentation

Biomedical Instrumentation ELEC ENG 4BD4: Biomedical Instrumentation Lecture 5 Bioelectricity 1. INTRODUCTION TO BIOELECTRICITY AND EXCITABLE CELLS Historical perspective: Bioelectricity first discovered by Luigi Galvani in 1780s

More information

Supplementary Information

Supplementary Information Supplementary Information Tuning Ranvier node and internode properties in myelinated axons to adjust action potential timing Marc C. Ford, Olga Alexandrova, Lee Cossell, Annette Stange Marten, James Sinclair,

More information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION Supplementary Figure S1. Pulses >3mJ reduce membrane resistance in HEK cells. Reversal potentials in a representative cell for IR-induced currents with laser pulses of 0.74 to

More information

Biomedical Instrumentation

Biomedical Instrumentation Biomedical Instrumentation Winter 1393 Bonab University The Origin of BioPotentials Bioelectric Signals Bioelectrical potential is a result of electrochemical activity across the membrane of the cell.

More information

Resting Distribution of Ions in Mammalian Neurons. Outside Inside (mm) E ion Permab. K Na Cl

Resting Distribution of Ions in Mammalian Neurons. Outside Inside (mm) E ion Permab. K Na Cl Resting Distribution of Ions in Mammalian Neurons Outside Inside (mm) E ion Permab. K + 5 100-81 1.0 150 15 +62 0.04 Cl - 100 10-62 0.045 V m = -60 mv V m approaches the Equilibrium Potential of the most

More information

Properties of the living organism. Interaction between living organism and the environment. Processing informations. Definitions

Properties of the living organism. Interaction between living organism and the environment. Processing informations. Definitions thermodynamics material energy Interaction between living organism and the environment Open system: free material and energy exchange. Processing informations information processing answer Properties of

More information

Simulating Hodgkin-Huxley-like Excitation using Comsol Multiphysics

Simulating Hodgkin-Huxley-like Excitation using Comsol Multiphysics Presented at the COMSOL Conference 2008 Hannover Simulating Hodgkin-Huxley-like Excitation using Comsol Multiphysics Martinek 1,2, Stickler 2, Reichel 1 and Rattay 2 1 Department of Biomedical Engineering

More information

6.3.4 Action potential

6.3.4 Action potential I ion C m C m dφ dt Figure 6.8: Electrical circuit model of the cell membrane. Normally, cells are net negative inside the cell which results in a non-zero resting membrane potential. The membrane potential

More information

A Model of Nerve-Bundle Fibre-Stimulation using Implantable Cuff Electrodes

A Model of Nerve-Bundle Fibre-Stimulation using Implantable Cuff Electrodes UNSW GSBME 1 A Model of Nerve-Bundle Fibre-Stimulation using Implantable Cuff Electrodes Joseph Radford Abstract The aim of this study is to demonstrate radial selectivity when stimulating axons that innervate

More information

Physiology Unit 2. MEMBRANE POTENTIALS and SYNAPSES

Physiology Unit 2. MEMBRANE POTENTIALS and SYNAPSES Physiology Unit 2 MEMBRANE POTENTIALS and SYNAPSES Neuron Communication Neurons are stimulated by receptors on dendrites and cell bodies (soma) Ligand gated ion channels GPCR s Neurons stimulate cells

More information

Modeling of Retinal Ganglion Cell Responses to Electrical Stimulation with Multiple Electrodes L.A. Hruby Salk Institute for Biological Studies

Modeling of Retinal Ganglion Cell Responses to Electrical Stimulation with Multiple Electrodes L.A. Hruby Salk Institute for Biological Studies Modeling of Retinal Ganglion Cell Responses to Electrical Stimulation with Multiple Electrodes L.A. Hruby Salk Institute for Biological Studies Introduction Since work on epiretinal electrical stimulation

More information

MEMBRANE POTENTIALS AND ACTION POTENTIALS:

MEMBRANE POTENTIALS AND ACTION POTENTIALS: University of Jordan Faculty of Medicine Department of Physiology & Biochemistry Medical students, 2017/2018 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Review: Membrane physiology

More information

Peripheral Nerve II. Amelyn Ramos Rafael, MD. Anatomical considerations

Peripheral Nerve II. Amelyn Ramos Rafael, MD. Anatomical considerations Peripheral Nerve II Amelyn Ramos Rafael, MD Anatomical considerations 1 Physiologic properties of the nerve Irritability of the nerve A stimulus applied on the nerve causes the production of a nerve impulse,

More information

Nervous Tissue. Neurons Neural communication Nervous Systems

Nervous Tissue. Neurons Neural communication Nervous Systems Nervous Tissue Neurons Neural communication Nervous Systems What is the function of nervous tissue? Maintain homeostasis & respond to stimuli Sense & transmit information rapidly, to specific cells and

More information

Νευροφυσιολογία και Αισθήσεις

Νευροφυσιολογία και Αισθήσεις Biomedical Imaging & Applied Optics University of Cyprus Νευροφυσιολογία και Αισθήσεις Διάλεξη 5 Μοντέλο Hodgkin-Huxley (Hodgkin-Huxley Model) Response to Current Injection 2 Hodgin & Huxley Sir Alan Lloyd

More information

BIOELECTRIC PHENOMENA

BIOELECTRIC PHENOMENA Chapter 11 BIOELECTRIC PHENOMENA 11.3 NEURONS 11.3.1 Membrane Potentials Resting Potential by separation of charge due to the selective permeability of the membrane to ions From C v= Q, where v=60mv and

More information

Action Potential Propagation

Action Potential Propagation Action Potential Propagation 2 Action Potential is a transient alteration of transmembrane voltage (or membrane potential) across an excitable membrane generated by the activity of voltage-gated ion channels.

More information

ELECTRICAL STIMULATION OF EXCITABLE TISSUE

ELECTRICAL STIMULATION OF EXCITABLE TISSUE 7 ELECTRICAL STIMULATION OF EXCITABLE TISSUE In designing systems for stimulation, a qualitative understanding together with mathematical descriptions of responses to stimulation are essential. The response

More information

9.01 Introduction to Neuroscience Fall 2007

9.01 Introduction to Neuroscience Fall 2007 MIT OpenCourseWare http://ocw.mit.edu 9.01 Introduction to Neuroscience Fall 2007 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. 9.01 Recitation (R02)

More information

Figure by MIT OCW. After Melcher and Kiang, HST MODELING ISSUES IN HEARING AND SPEECH SPRING Vertex - Ipsilateral Earbar

Figure by MIT OCW. After Melcher and Kiang, HST MODELING ISSUES IN HEARING AND SPEECH SPRING Vertex - Ipsilateral Earbar Harvard-MIT Division of Health Sciences and Technology HST.750: Modeling Issues in Speech and Hearing, Spring 2006 Course Directors: Dr. Christopher Shera and Dr. Jennifer Melcher HST 750 - MODELIG ISSUES

More information

Ch. 5. Membrane Potentials and Action Potentials

Ch. 5. Membrane Potentials and Action Potentials Ch. 5. Membrane Potentials and Action Potentials Basic Physics of Membrane Potentials Nerve and muscle cells: Excitable Capable of generating rapidly changing electrochemical impulses at their membranes

More information

Physiology Unit 2. MEMBRANE POTENTIALS and SYNAPSES

Physiology Unit 2. MEMBRANE POTENTIALS and SYNAPSES Physiology Unit 2 MEMBRANE POTENTIALS and SYNAPSES In Physiology Today Ohm s Law I = V/R Ohm s law: the current through a conductor between two points is directly proportional to the voltage across the

More information

Nervous Tissue. Neurons Electrochemical Gradient Propagation & Transduction Neurotransmitters Temporal & Spatial Summation

Nervous Tissue. Neurons Electrochemical Gradient Propagation & Transduction Neurotransmitters Temporal & Spatial Summation Nervous Tissue Neurons Electrochemical Gradient Propagation & Transduction Neurotransmitters Temporal & Spatial Summation What is the function of nervous tissue? Maintain homeostasis & respond to stimuli

More information

Lecture Notes 8C120 Inleiding Meten en Modelleren. Cellular electrophysiology: modeling and simulation. Nico Kuijpers

Lecture Notes 8C120 Inleiding Meten en Modelleren. Cellular electrophysiology: modeling and simulation. Nico Kuijpers Lecture Notes 8C2 Inleiding Meten en Modelleren Cellular electrophysiology: modeling and simulation Nico Kuijpers nico.kuijpers@bf.unimaas.nl February 9, 2 2 8C2 Inleiding Meten en Modelleren Extracellular

More information

Transport of ions across plasma membranes

Transport of ions across plasma membranes Transport of ions across plasma membranes Plasma Membranes of Excitable tissues Ref: Guyton, 13 th ed: pp: 61-71. 12 th ed: pp: 57-69. 11th ed: p57-71, Electrical properties of plasma membranes Part A:

More information

Introduction to Physiology V - Coupling and Propagation

Introduction to Physiology V - Coupling and Propagation Introduction to Physiology V - Coupling and Propagation J. P. Keener Mathematics Department Coupling and Propagation p./33 Spatially Extended Excitable Media Neurons and axons Coupling and Propagation

More information

All-or-None Principle and Weakness of Hodgkin-Huxley Mathematical Model

All-or-None Principle and Weakness of Hodgkin-Huxley Mathematical Model All-or-None Principle and Weakness of Hodgkin-Huxley Mathematical Model S. A. Sadegh Zadeh, C. Kambhampati International Science Index, Mathematical and Computational Sciences waset.org/publication/10008281

More information

Channels can be activated by ligand-binding (chemical), voltage change, or mechanical changes such as stretch.

Channels can be activated by ligand-binding (chemical), voltage change, or mechanical changes such as stretch. 1. Describe the basic structure of an ion channel. Name 3 ways a channel can be "activated," and describe what occurs upon activation. What are some ways a channel can decide what is allowed to pass through?

More information

BIOL Week 5. Nervous System II. The Membrane Potential. Question : Is the Equilibrium Potential a set number or can it change?

BIOL Week 5. Nervous System II. The Membrane Potential. Question : Is the Equilibrium Potential a set number or can it change? Collin County Community College BIOL 2401 Week 5 Nervous System II 1 The Membrane Potential Question : Is the Equilibrium Potential a set number or can it change? Let s look at the Nernst Equation again.

More information

Modeling the Excitability of Mammalian Nerve Fibers: Influence of Afterpotentials on the Recovery Cycle

Modeling the Excitability of Mammalian Nerve Fibers: Influence of Afterpotentials on the Recovery Cycle J Neurophysiol 87: 995 1006, 2002; 10.1152/jn.00353.2001. Modeling the Excitability of Mammalian Nerve Fibers: Influence of Afterpotentials on the Recovery Cycle CAMERON C. MCINTYRE, ANDREW G. RICHARDSON,

More information

Overview Organization: Central Nervous System (CNS) Peripheral Nervous System (PNS) innervate Divisions: a. Afferent

Overview Organization: Central Nervous System (CNS) Peripheral Nervous System (PNS) innervate Divisions: a. Afferent Overview Organization: Central Nervous System (CNS) Brain and spinal cord receives and processes information. Peripheral Nervous System (PNS) Nerve cells that link CNS with organs throughout the body.

More information

2401 : Anatomy/Physiology

2401 : Anatomy/Physiology Dr. Chris Doumen Week 6 2401 : Anatomy/Physiology Action Potentials NeuroPhysiology TextBook Readings Pages 400 through 408 Make use of the figures in your textbook ; a picture is worth a thousand words!

More information

Electrophysiology of the neuron

Electrophysiology of the neuron School of Mathematical Sciences G4TNS Theoretical Neuroscience Electrophysiology of the neuron Electrophysiology is the study of ionic currents and electrical activity in cells and tissues. The work of

More information

PROPERTIES OF PERIFERAL NERVE EXCITATION IN RESPECT OF LOCATION OF COIL FOR MAGNETIC NERVE STIMULATION

PROPERTIES OF PERIFERAL NERVE EXCITATION IN RESPECT OF LOCATION OF COIL FOR MAGNETIC NERVE STIMULATION PROPERTIES OF PERIFERAL NERVE EXCITATION IN RESPECT OF LOCATION OF COIL FOR MAGNETIC NERVE STIMULATION O. Hiwaki, H. Kuwano Facult of Information Sciences, Hiroshima Cit Universit, Hiroshima, Japan Abstract-

More information

لجنة الطب البشري رؤية تنير دروب تميزكم

لجنة الطب البشري رؤية تنير دروب تميزكم 1) Hyperpolarization phase of the action potential: a. is due to the opening of voltage-gated Cl channels. b. is due to prolonged opening of voltage-gated K + channels. c. is due to closure of the Na +

More information

ACTION POTENTIAL. Dr. Ayisha Qureshi Professor MBBS, MPhil

ACTION POTENTIAL. Dr. Ayisha Qureshi Professor MBBS, MPhil ACTION POTENTIAL Dr. Ayisha Qureshi Professor MBBS, MPhil DEFINITIONS: Stimulus: A stimulus is an external force or event which when applied to an excitable tissue produces a characteristic response. Subthreshold

More information

Microsystems for Neuroscience and Medicine. Lecture 9

Microsystems for Neuroscience and Medicine. Lecture 9 1 Microsystems for Neuroscience and Medicine Lecture 9 2 Neural Microsystems Neurons - Structure and behaviour Measuring neural activity Interfacing with neurons Medical applications - DBS, Retinal Implants

More information

Transmission of Nerve Impulses (see Fig , p. 403)

Transmission of Nerve Impulses (see Fig , p. 403) How a nerve impulse works Transmission of Nerve Impulses (see Fig. 12.13, p. 403) 1. At Rest (Polarization) outside of neuron is positively charged compared to inside (sodium ions outside, chloride and

More information

Errata for Bioelectricity: A Quantitative Approach, 3rd edition by Robert Plonsey and Roger C. Barr (Springer 2007)

Errata for Bioelectricity: A Quantitative Approach, 3rd edition by Robert Plonsey and Roger C. Barr (Springer 2007) Errata for Bioelectricity: A Quantitative Approach, 3rd edition by Robert Plonsey and Roger C. Barr (Springer 2007) Frederick J. Vetter Department of Electrical, Computer and Biomedical Engineering University

More information

Bo Deng University of Nebraska-Lincoln UNL Math Biology Seminar

Bo Deng University of Nebraska-Lincoln UNL Math Biology Seminar Mathematical Model of Neuron Bo Deng University of Nebraska-Lincoln UNL Math Biology Seminar 09-10-2015 Review -- One Basic Circuit By Kirchhoff's Current Law 0 = I C + I R + I L I ext By Kirchhoff s Voltage

More information

Voltage-clamp and Hodgkin-Huxley models

Voltage-clamp and Hodgkin-Huxley models Voltage-clamp and Hodgkin-Huxley models Read: Hille, Chapters 2-5 (best) Koch, Chapters 6, 8, 9 See also Clay, J. Neurophysiol. 80:903-913 (1998) (for a recent version of the HH squid axon model) Rothman

More information

Nerve Signal Conduction. Resting Potential Action Potential Conduction of Action Potentials

Nerve Signal Conduction. Resting Potential Action Potential Conduction of Action Potentials Nerve Signal Conduction Resting Potential Action Potential Conduction of Action Potentials Resting Potential Resting neurons are always prepared to send a nerve signal. Neuron possesses potential energy

More information

Quantitative Electrophysiology

Quantitative Electrophysiology ECE 795: Quantitative Electrophysiology Notes for Lecture #1 Wednesday, September 13, 2006 1. INTRODUCTION TO EXCITABLE CELLS Historical perspective: Bioelectricity first discovered by Luigi Galvani in

More information

Nervous Systems: Neuron Structure and Function

Nervous Systems: Neuron Structure and Function Nervous Systems: Neuron Structure and Function Integration An animal needs to function like a coherent organism, not like a loose collection of cells. Integration = refers to processes such as summation

More information

Kirchhoff s Rules. Survey available this week. $ closed loop. Quiz on a simple DC circuit. Quiz on a simple DC circuit

Kirchhoff s Rules. Survey available this week. $ closed loop. Quiz on a simple DC circuit. Quiz on a simple DC circuit RC Circuits. Start Magnetic Fields Announcement on MTE 1 This Lecture: RC circuits Membrane electrical currents Magnetic Fields and Magnets Wednesday Oct. 4, slightly later start time:5:45 pm - 7:15 pm

More information

Quantitative Electrophysiology

Quantitative Electrophysiology ECE 795: Quantitative Electrophysiology Notes for Lecture #4 Wednesday, October 4, 2006 7. CHEMICAL SYNAPSES AND GAP JUNCTIONS We will look at: Chemical synapses in the nervous system Gap junctions in

More information

Phys 102 Lecture 9 RC circuits

Phys 102 Lecture 9 RC circuits Phys 102 Lecture 9 RC circuits 1 Recall from last time... We solved various circuits with resistors and batteries (also capacitors and batteries) ε R 1 R 2 R 3 R 1 ε 1 ε 2 R 3 What about circuits that

More information

Quantitative Electrophysiology

Quantitative Electrophysiology ECE 795: Quantitative Electrophysiology Notes for Lecture #1 Tuesday, September 18, 2012 1. INTRODUCTION TO EXCITABLE CELLS Historical perspective: Bioelectricity first discovered by Luigi Galvani in 1780s

More information

Nervous & Endocrine System

Nervous & Endocrine System 3/19 HW Day 1 Read pages 897-900 Complete Vocab. on pg 897 Aim: What is Regulation? Do Now: What 2 organ systems are involved in regulation? Nervous & Endocrine System Regulation: The control and coordination

More information

Mathematical Foundations of Neuroscience - Lecture 3. Electrophysiology of neurons - continued

Mathematical Foundations of Neuroscience - Lecture 3. Electrophysiology of neurons - continued Mathematical Foundations of Neuroscience - Lecture 3. Electrophysiology of neurons - continued Filip Piękniewski Faculty of Mathematics and Computer Science, Nicolaus Copernicus University, Toruń, Poland

More information

3 Cables: Electrotonic Length, Attenuation, and Filtering

3 Cables: Electrotonic Length, Attenuation, and Filtering Physics 171/271 - Note 3A - David Kleinfeld - Fall 2005 3 Cables: Electrotonic Length, Attenuation, and Filtering We consider, briefly, the behavior of the transmembrane potential across a long process.

More information

2. Building a Passive Neuron Batteries, Resistors, and Capacitors

2. Building a Passive Neuron Batteries, Resistors, and Capacitors pass 2. Building a Passive Neuron brc 2. 1. Batteries, Resistors, and Capacitors The signals in the brain arise from the motion of charged particles - typically ions of sodium, Na +, chloride,, potassium,

More information

Hodgkin-Huxley model simulator

Hodgkin-Huxley model simulator University of Tartu Faculty of Mathematics and Computer Science Institute of Computer Science Hodgkin-Huxley model simulator MTAT.03.291 Introduction to Computational Neuroscience Katrin Valdson Kristiina

More information

Circuit Analysis-II. Circuit Analysis-II Lecture # 5 Monday 23 rd April, 18

Circuit Analysis-II. Circuit Analysis-II Lecture # 5 Monday 23 rd April, 18 Circuit Analysis-II Capacitors in AC Circuits Introduction ü The instantaneous capacitor current is equal to the capacitance times the instantaneous rate of change of the voltage across the capacitor.

More information

Voltage-clamp and Hodgkin-Huxley models

Voltage-clamp and Hodgkin-Huxley models Voltage-clamp and Hodgkin-Huxley models Read: Hille, Chapters 2-5 (best Koch, Chapters 6, 8, 9 See also Hodgkin and Huxley, J. Physiol. 117:500-544 (1952. (the source Clay, J. Neurophysiol. 80:903-913

More information

NEURONS, SENSE ORGANS, AND NERVOUS SYSTEMS CHAPTER 34

NEURONS, SENSE ORGANS, AND NERVOUS SYSTEMS CHAPTER 34 NEURONS, SENSE ORGANS, AND NERVOUS SYSTEMS CHAPTER 34 KEY CONCEPTS 34.1 Nervous Systems Are Composed of Neurons and Glial Cells 34.2 Neurons Generate Electric Signals by Controlling Ion Distributions 34.3

More information

Phys498BIO; Prof. Paul Selvin Hw #9 Assigned Wed. 4/18/12: Due 4/25/08

Phys498BIO; Prof. Paul Selvin Hw #9 Assigned Wed. 4/18/12: Due 4/25/08 1. Ionic Movements Across a Permeable Membrane: The Nernst Potential. In class we showed that if a non-permeable membrane separates a solution with high [KCl] from a solution with low [KCl], the net charge

More information

Neurons, Synapses, and Signaling

Neurons, Synapses, and Signaling Chapter 48 Neurons, Synapses, and Signaling PowerPoint Lecture Presentations for Biology Eighth Edition Neil Campbell and Jane Reece Lectures by Chris Romero, updated by Erin Barley with contributions

More information

BME 5742 Biosystems Modeling and Control

BME 5742 Biosystems Modeling and Control BME 5742 Biosystems Modeling and Control Hodgkin-Huxley Model for Nerve Cell Action Potential Part 1 Dr. Zvi Roth (FAU) 1 References Hoppensteadt-Peskin Ch. 3 for all the mathematics. Cooper s The Cell

More information

Introduction to electrophysiology. Dr. Tóth András

Introduction to electrophysiology. Dr. Tóth András Introduction to electrophysiology Dr. Tóth András Topics Transmembran transport Donnan equilibrium Resting potential Ion channels Local and action potentials Intra- and extracellular propagation of the

More information

Resting potential, action potential and electrotonic potentials. - Ionic mechanisms -

Resting potential, action potential and electrotonic potentials. - Ionic mechanisms - Resting potential, action potential and electrotonic potentials - Ionic mechanisms - Learning objectives: 4-6 Péter SÁNTHA 11.9.2017. Transmembrane potential Resting membrane potential (E 0 ): Transmembrane

More information

Ch 8: Neurons: Cellular and Network Properties, Part 1

Ch 8: Neurons: Cellular and Network Properties, Part 1 Developed by John Gallagher, MS, DVM Ch 8: Neurons: Cellular and Network Properties, Part 1 Objectives: Describe the Cells of the NS Explain the creation and propagation of an electrical signal in a nerve

More information

QUESTION? Communication between neurons depends on the cell membrane. Why is this so?? Consider the structure of the membrane.

QUESTION? Communication between neurons depends on the cell membrane. Why is this so?? Consider the structure of the membrane. QUESTION? Communication between neurons depends on the cell membrane Why is this so?? Consider the structure of the membrane. ECF ICF Possible ANSWERS?? Membrane Ion Channels and Receptors: neuron membranes

More information

Control and Integration. Nervous System Organization: Bilateral Symmetric Animals. Nervous System Organization: Radial Symmetric Animals

Control and Integration. Nervous System Organization: Bilateral Symmetric Animals. Nervous System Organization: Radial Symmetric Animals Control and Integration Neurophysiology Chapters 10-12 Nervous system composed of nervous tissue cells designed to conduct electrical impulses rapid communication to specific cells or groups of cells Endocrine

More information

Neurons. The Molecular Basis of their Electrical Excitability

Neurons. The Molecular Basis of their Electrical Excitability Neurons The Molecular Basis of their Electrical Excitability Viva La Complexity! Consider, The human brain contains >10 11 neurons! Each neuron makes 10 3 (average) synaptic contacts on up to 10 3 other

More information

Electrical Signaling. Lecture Outline. Using Ions as Messengers. Potentials in Electrical Signaling

Electrical Signaling. Lecture Outline. Using Ions as Messengers. Potentials in Electrical Signaling Lecture Outline Electrical Signaling Using ions as messengers Potentials in electrical signaling Action Graded Other electrical signaling Gap junctions The neuron Using Ions as Messengers Important things

More information

Iván De La Pava Panche. Director Álvaro Ángel Orozco Gutiérrez - MEng, PhD Co-director Óscar Alberto Henao Gallo - M.Sc, PhD

Iván De La Pava Panche. Director Álvaro Ángel Orozco Gutiérrez - MEng, PhD Co-director Óscar Alberto Henao Gallo - M.Sc, PhD A Gaussian Process Emulator for Estimating the Volume of Tissue Activated During Deep Brain Stimulation Iván De La Pava Panche Director Álvaro Ángel Orozco Gutiérrez - MEng, PhD Co-director Óscar Alberto

More information

PROPERTY OF ELSEVIER SAMPLE CONTENT - NOT FINAL. The Nervous System and Muscle

PROPERTY OF ELSEVIER SAMPLE CONTENT - NOT FINAL. The Nervous System and Muscle The Nervous System and Muscle SECTION 2 2-1 Nernst Potential 2-2 Resting Membrane Potential 2-3 Axonal Action Potential 2-4 Neurons 2-5 Axonal Conduction 2-6 Morphology of Synapses 2-7 Chemical Synaptic

More information

Nervous System Organization

Nervous System Organization The Nervous System Nervous System Organization Receptors respond to stimuli Sensory receptors detect the stimulus Motor effectors respond to stimulus Nervous system divisions Central nervous system Command

More information

General Physics. Nerve Conduction. Newton s laws of Motion Work, Energy and Power. Fluids. Direct Current (DC)

General Physics. Nerve Conduction. Newton s laws of Motion Work, Energy and Power. Fluids. Direct Current (DC) Newton s laws of Motion Work, Energy and Power Fluids Direct Current (DC) Nerve Conduction Wave properties of light Ionizing Radiation General Physics Prepared by: Sujood Alazzam 2017/2018 CHAPTER OUTLINE

More information

Particles with opposite charges (positives and negatives) attract each other, while particles with the same charge repel each other.

Particles with opposite charges (positives and negatives) attract each other, while particles with the same charge repel each other. III. NEUROPHYSIOLOGY A) REVIEW - 3 basic ideas that the student must remember from chemistry and physics: (i) CONCENTRATION measure of relative amounts of solutes in a solution. * Measured in units called

More information

Adaptive Estimation of the Neural Activation Extent in Computational Volume Conductor Models of Deep Brain Stimulation

Adaptive Estimation of the Neural Activation Extent in Computational Volume Conductor Models of Deep Brain Stimulation 1 Adaptive Estimation of the Neural Activation Extent in Computational Volume Conductor Models of Deep Brain Stimulation Christian Schmidt, Ursula van Rienen arxiv:1705.10478v3 [q-bio.nc] 7 Aug 2017 Abstract

More information

Biophysical Foundations

Biophysical Foundations Biophysical Foundations BENG/BGGN 260 Neurodynamics University of California, San Diego Week 1 BENG/BGGN 260 Neurodynamics (UCSD Biophysical Foundations Week 1 1 / 15 Reading Material B. Hille, Ion Channels

More information

Lecture 17 Push-Pull and Bridge DC-DC converters Push-Pull Converter (Buck Derived) Centre-tapped primary and secondary windings

Lecture 17 Push-Pull and Bridge DC-DC converters Push-Pull Converter (Buck Derived) Centre-tapped primary and secondary windings ecture 17 Push-Pull and Bridge DC-DC converters Push-Pull Converter (Buck Derived) Centre-tapped primary and secondary windings 1 2 D 1 i v 1 v 1s + v C o R v 2 v 2s d 1 2 T 1 T 2 D 2 Figure 17.1 v c (

More information

3.3 Simulating action potentials

3.3 Simulating action potentials 6 THE HODGKIN HUXLEY MODEL OF THE ACTION POTENTIAL Fig. 3.1 Voltage dependence of rate coefficients and limiting values and time constants for the Hodgkin Huxley gating variables. (a) Graphs of forward

More information

4. Active Behavior of the Cell Membrane 4.1 INTRODUCTION

4. Active Behavior of the Cell Membrane  4.1 INTRODUCTION 1 of 50 10/17/2014 10:48 PM 4.1 INTRODUCTION When a stimulus current pulse is arranged to depolarize the resting membrane of a cell to or beyond the threshold voltage, then the membrane will respond with

More information

Membrane Potentials, Action Potentials, and Synaptic Transmission. Membrane Potential

Membrane Potentials, Action Potentials, and Synaptic Transmission. Membrane Potential Cl Cl - - + K + K+ K + K Cl - 2/2/15 Membrane Potentials, Action Potentials, and Synaptic Transmission Core Curriculum II Spring 2015 Membrane Potential Example 1: K +, Cl - equally permeant no charge

More information

LECTURE 380 TWO-STAGE OPEN-LOOP COMPARATORS - II (READING: AH ) Trip Point of an Inverter

LECTURE 380 TWO-STAGE OPEN-LOOP COMPARATORS - II (READING: AH ) Trip Point of an Inverter Lecture 380 Two-Stage Open-Loop Comparators-II (4/5/02) Page 380-1 LECTURE 380 TWO-STAGE OPEN-LOOP COMPARATORS - II (READING: AH 445-461) Trip Point of an Inverter V DD In order to determine the propagation

More information

Math in systems neuroscience. Quan Wen

Math in systems neuroscience. Quan Wen Math in systems neuroscience Quan Wen Human brain is perhaps the most complex subject in the universe 1 kg brain 10 11 neurons 180,000 km nerve fiber 10 15 synapses 10 18 synaptic proteins Multiscale

More information

Nervous System Organization

Nervous System Organization The Nervous System Chapter 44 Nervous System Organization All animals must be able to respond to environmental stimuli -Sensory receptors = Detect stimulus -Motor effectors = Respond to it -The nervous

More information

Classical Biophysics of the Squid Giant Axon

Classical Biophysics of the Squid Giant Axon Chapter 2 Classical Biophysics of the Squid Giant Axon Scientific work proceeds at many levels of complexity. Scientists assume that all observable phenomena can ultimately be accounted for by a small

More information

Nervous System: Part II How A Neuron Works

Nervous System: Part II How A Neuron Works Nervous System: Part II How A Neuron Works Essential Knowledge Statement 3.E.2 Continued Animals have nervous systems that detect external and internal signals, transmit and integrate information, and

More information

Dendrites - receives information from other neuron cells - input receivers.

Dendrites - receives information from other neuron cells - input receivers. The Nerve Tissue Neuron - the nerve cell Dendrites - receives information from other neuron cells - input receivers. Cell body - includes usual parts of the organelles of a cell (nucleus, mitochondria)

More information

A NOVEL DUAL MODELING METHOD FOR CHARACTERIZING HUMAN NERVE FIBER ACTIVATION. A Thesis. presented to

A NOVEL DUAL MODELING METHOD FOR CHARACTERIZING HUMAN NERVE FIBER ACTIVATION. A Thesis. presented to A NOVEL DUAL MODELING METHOD FOR CHARACTERIZING HUMAN NERVE FIBER ACTIVATION A Thesis presented to the Faculty of California Polytechnic State University, San Luis Obispo In Partial Fulfillment of the

More information

Passive Membrane Properties

Passive Membrane Properties Passive Membrane Properties Communicating through a leaky garden hose... Topics I Introduction & Electrochemical Gradients Passive Membrane Properties Action Potentials Voltage-Gated Ion Channels Topics

More information

Lecture 310 Open-Loop Comparators (3/28/10) Page 310-1

Lecture 310 Open-Loop Comparators (3/28/10) Page 310-1 Lecture 310 Open-Loop Comparators (3/28/10) Page 310-1 LECTURE 310 OPEN-LOOP COMPARATORS LECTURE ORGANIZATION Outline Characterization of comparators Dominant pole, open-loop comparators Two-pole, open-loop

More information

9 Generation of Action Potential Hodgkin-Huxley Model

9 Generation of Action Potential Hodgkin-Huxley Model 9 Generation of Action Potential Hodgkin-Huxley Model (based on chapter 12, W.W. Lytton, Hodgkin-Huxley Model) 9.1 Passive and active membrane models In the previous lecture we have considered a passive

More information

Vertebrate Physiology 437 EXAM I 26 September 2002 NAME

Vertebrate Physiology 437 EXAM I 26 September 2002 NAME 437 EXAM1.DOC Vertebrate Physiology 437 EXAM I 26 September 2002 NAME 0. When you gaze at the stars, why do you have to look slightly away from the really faint ones in order to be able to see them? (1

More information

Lecture 2. Excitability and ionic transport

Lecture 2. Excitability and ionic transport Lecture 2 Excitability and ionic transport Selective membrane permeability: The lipid barrier of the cell membrane and cell membrane transport proteins Chemical compositions of extracellular and intracellular

More information

A Dynamical Model of Fast Intrinsic Optical Signal of Neural Burstings

A Dynamical Model of Fast Intrinsic Optical Signal of Neural Burstings A Dymical Model of Fast Intrinsic Optical Sigl of Neural Burstings Jianzhong Su Hanli Liu Yuanbo Peng Technical Report 2007-20 http://www.uta.edu/math/preprint/ A Dymical Model of Fast Intrinsic Optical

More information

Nervous system. 3 Basic functions of the nervous system !!!! !!! 1-Sensory. 2-Integration. 3-Motor

Nervous system. 3 Basic functions of the nervous system !!!! !!! 1-Sensory. 2-Integration. 3-Motor Nervous system 3 Basic functions of the nervous system 1-Sensory 2-Integration 3-Motor I. Central Nervous System (CNS) Brain Spinal Cord I. Peripheral Nervous System (PNS) 2) Afferent towards afferent

More information

Figure Circuit for Question 1. Figure Circuit for Question 2

Figure Circuit for Question 1. Figure Circuit for Question 2 Exercises 10.7 Exercises Multiple Choice 1. For the circuit of Figure 10.44 the time constant is A. 0.5 ms 71.43 µs 2, 000 s D. 0.2 ms 4 Ω 2 Ω 12 Ω 1 mh 12u 0 () t V Figure 10.44. Circuit for Question

More information

Cell membrane resistance and capacitance

Cell membrane resistance and capacitance Cell membrane resistance and capacitance 1 Two properties of a cell membrane gives rise to two passive electrical properties: Resistance: Leakage pathways allow inorganic ions to cross the membrane. Capacitance:

More information

Lecture 10 : Neuronal Dynamics. Eileen Nugent

Lecture 10 : Neuronal Dynamics. Eileen Nugent Lecture 10 : Neuronal Dynamics Eileen Nugent Origin of the Cells Resting Membrane Potential: Nernst Equation, Donnan Equilbrium Action Potentials in the Nervous System Equivalent Electrical Circuits and

More information

Introduction and the Hodgkin-Huxley Model

Introduction and the Hodgkin-Huxley Model 1 Introduction and the Hodgkin-Huxley Model Richard Bertram Department of Mathematics and Programs in Neuroscience and Molecular Biophysics Florida State University Tallahassee, Florida 32306 Reference:

More information

Neurons and Nervous Systems

Neurons and Nervous Systems 34 Neurons and Nervous Systems Concept 34.1 Nervous Systems Consist of Neurons and Glia Nervous systems have two categories of cells: Neurons, or nerve cells, are excitable they generate and transmit electrical

More information

TSP10N60M / TSF10N60M

TSP10N60M / TSF10N60M TSP10N60M / TSF10N60M 600V N-Channel MOSFET General Description This Power MOSFET is produced using Truesemi s advanced planar stripe DMOS technology. This advanced technology has been especially tailored

More information

Action Potentials & Nervous System. Bio 219 Napa Valley College Dr. Adam Ross

Action Potentials & Nervous System. Bio 219 Napa Valley College Dr. Adam Ross Action Potentials & Nervous System Bio 219 Napa Valley College Dr. Adam Ross Review: Membrane potentials exist due to unequal distribution of charge across the membrane Concentration gradients drive ion

More information

Neural Conduction. biologyaspoetry.com

Neural Conduction. biologyaspoetry.com Neural Conduction biologyaspoetry.com Resting Membrane Potential -70mV A cell s membrane potential is the difference in the electrical potential ( charge) between the inside and outside of the cell. The

More information