HB05 Modelling human nerve excitability

Page 1

Axonal Excitability Workshop

Antalya, December 2012

Modelling human nerve excitability and the TROND protocol The MEMFIT program


Multiple measures of nerve excitability (TROND protocol) Plots of multiple excitability data for motor axons of median nerve (wrist-APB) of 30 normal subjects, each recorded in 9-10 minutes (means +/- SD). Threshold electrotonus

A

(I/V)

C Current (% threshold)

Threshold charge (mA.ms)

B

100 Threshold reduction (%)

5

Current- threshold relationship

0

-100

0

0

Recovery cycle

100 Threshold change (%)

Charge-duration relationship

D

0

-100 -1

0 1 Stimulus width (ms)

0

100 Delay (ms)

200

-500 0 Threshold reduction (%)

10 100 Interstimulus interval (ms)


Diagram of myelinate axon structure, illustrating the ion channels, pumps and exchangers responsible for determining axonal excitability. Ion channels are shown in yellow, ion exchangers in orange and energy-dependent pumps in green. Krishnan, Lin, Park & Kiernan 2009


Electrical model of node and internode with addition of sodium pump currents Outside Myelin GBB

CM

Node ENa

ENap

EKf

EKs

EKf

EKs

EH

ELk

CN GNa

GNap

GKf

GKs

CI GKf

Ipump

GKs

GH

GLk

Ipump

Internode Inside


Equivalent circuit of node and internode used to model electrical excitability properties of human axons.


Modelling the membrane potential changes during excitability testing.


Modelling the membrane potential changes during excitability testing.

Threshold Threshold electrotonus electrotonus

Currentthreshold Currentthreshold (I/V) (I/V) relationship relationship

Recovery Recovery cycle cycle

Charge-duration Charge-duration relationship relationship Strengthduration time constant

Circles = mean normal control data. Lines = standard model.


Modelling the membrane potential changes during excitability testing.

Threshold Threshold electrotonus electrotonus

Currentthreshold Currentthreshold (I/V) (I/V) relationship relationship

Recovery Recovery cycle cycle

Charge-duration Charge-duration relationship relationship Strengthduration time constant

Circles = mean normal control data. Lines = standard model.


Modelling the membrane potential changes during excitability testing.

Threshold Threshold electrotonus electrotonus

Currentthreshold Currentthreshold (I/V) (I/V) relationship relationship

Recovery Recovery cycle cycle

Charge-duration Charge-duration relationship relationship Strengthduration time constant

Circles = mean normal control data. Lines = standard model.


Modelling the membrane potential changes during excitability testing.

Threshold Threshold electrotonus electrotonus

Currentthreshold Currentthreshold (I/V) (I/V) relationship relationship

Recovery Recovery cycle cycle

Charge-duration Charge-duration relationship relationship Strengthduration time constant

Circles = mean normal control data. Lines = standard model.


Modelling the membrane potential changes during excitability testing.

Threshold Threshold electrotonus electrotonus

Currentthreshold Currentthreshold (I/V) (I/V) relationship relationship

Recovery Recovery cycle cycle

Charge-duration Charge-duration relationship relationship Strengthduration time constant

Circles = mean normal control data. Lines = standard model.


This model has over 30 independent membrane parameters. If a parameter is changed, is it possible to determine correctly which one was changed?




‘Discrepancy’ is scored as the weighted sums of squares of differences between the recorded and modelled values. The ‘Optimize fit’ function in MEMFIT finds parameter values that minimize discrepancy.




EN -82.9 → -80.5

IPumpNI IPumpNI

PNaN 4.1 → 2.2

GKsN 41→ 80

PNaN PNaN

GKsN GKsN

GBB GBB

PNap(%) PNap(%)

PNap(%) PNap(%)

GKsI GKsI

GKfN GKfN

GKfI GKfI

KO KO

GKsN GKsN

IPumpBoth IPumpNI

GLk GLk

GKfI GKfI

GBB GBB

GH GH

IPumpBoth IPumpNI

GKfN GKfN

GLkN GLkN

KO KO

PNaN PNaN

GKfI GKfI

CAX CAX

GH GH

CAX CAX

GBB GBB

GLk GLk

GKfN GKfN

GLkN GLkN

GLkN GLkN

GKsN GKsI

CMy CMy

CN CN

PNap(%) PNap(%)

CN CN

CMy CMy

PNaN PNaN

GKsI GKsI

GKsI GKsI

CMy CMy

GLk GLk

CAX CAX

CN CN

GH GH

KO KO

0

100

0

Discrepancyreduction reduction (%) Discrepancy (%)

100

0

Discrepancy reduction (%) (%) Discrepancy reduction

GLk 1.6 → 8

GKfN 20→ 60 GKfN GKfN

CN CN

PNap(%) PNap(%)

GBB GBB

GKsN GKsN

PNaN PNaN

IPumpNI IPumpNI

GLkN GLkN

GKfI GKfI

GH GH

PNap(%) PNap(%)

IPumpBoth IPumpNI

GLkN GLkN

KO KO

GKsI GKsI

GKfI GKfI

GKfI GKfI

GBB GBB

GKsN GKsN

PNaN PNaN

KO KO

GKfN GKfN

GLk GLk

GLkN GLkN

KO KO

GKfN GKfN

GLk GLk

PNap(%) PNap(%)

CAX CAX

GKsN GKsN

PNaN PNaN

CMy CMy

GH GH

CAX CAX

GKsI GKsI

CAX CAx

CN CN

GH GKsI

CN CN

CMy CMy

GBB GBB

CMy CMy

GKsI GKsI

IPumpNI IPumpNI

100 Discrepancyreduction reduction (%) Discrepancy (%)

0

Discrepancy Discrepancy reduction reduction (%)(%)

100

CN 0.5 → 4

GLk GLk

0

Discrepancy (%) Discrepancyreduction reduction (%)

100

0

Discrepancy (%) Discrepancyreduction reduction (%)

100


Provisional conclusions from model testing: If the model were accurate, there would be enough information in a Trond recording to identify many single parameter changes correctly. Model fitting might also identify 2 parameter changes correctly. However, if more than 2 parameters are abnormal it is most unlikely that they could be identified correctly.

BUT:

How accurate is the model??


Nerve excitability measured by the TROND protocol is sensitive to: Membrane potential Polarizing currents * Hyperkalemia Hypokalemia Ischaemia

Ion channel dysfunction Na channels (Nav1.6) *

Kf channels (Kv1.1) * Ih channels (HCN) * Ks channels (Kv7.2 = KCNQ2)*

Demyelination Degeneration Regeneration Some simple changes provide a test of the electrical model and the use of MEMFIT to identify membrane changes


Curre (nA)

.2 .1 0

0

0 -100

0

100 msec

200

100 msec

200

-500

-.5 0

0 Threshold reduction (%) 100

200

-70 100

-80 0 -90 .5 10

100 msec

0

200

0

-100

0

100

0

100 msec

200

101

-20 1 -40 -60 -80 0 .2 .1 0

-1

200

0

-100 0

100

0 msec 100

msec msec Blue: 1 mA Red: controls, Green: 1 mA hyperpolarization, depolarization 100 1 Current (% threshold)

100

0

Current (nA)

-150 -100

100 msec

Membrane potential (mV) Stimulus charge

-100

200

1

101

Stimulus charge

0 -100

100 msec

Current (nA)

0

Membrane potential Threshold(mV) change (%)

200

Membrane potential (mV) Current (% threshold)

100

0

Threshold reduction (%)

Curre (nA)

Curre (nA)

100 msec

Threshold change (%)

Current (nA)

Membrane potential Threshold reduction (mV) (%)

0

-150 .2 0 -.2

0

-.5 0 Effects of changing membrane potential by polarizing currents

Current (nA)

Curre (nA)

.2 0 -.2

0 -500

0 Threshold reduction (%)

10

100 msec

-1

0 msec

1

Data from Kiernan & Bostock (2000)


Best fit by single parameter change is obtained by addition of 29 pA hyperpolarizing current per internode

Fitting standard model to 4 nerves hyperpolarized by 1 mA current Data from Kiernan & Bostock (2000)


Best fit is obtained by addition of 43 pA depolarizing current per internode (but fanning in caused in other ways is very similar)

Fitting standard model to 4 nerves depolarized by 1 mA current Data from Kiernan & Bostock (2000)


-.5

.1 0

Cu (

Cu (

Cu (

Cu (

0 -.2

0

Fitting standard model to nerves in 4 subjects with DC nerve polarization 0

200

100 msec

200 Red:

Current (% threshold)

100

0

-100

-500

-.5

0 Threshold reduction (%)

Current (nA)

0

100 msec

200

-70 100

-80 0 -90 .5 10

100 msec

0

0

100

100 msec

200

101

-20 1 -40 -60 -80 0 .2 .1 0

-1

0 msec 100

1

101

1

0

-100 0

100

0 100 200 hyperpolarization, 0 100 Blue: 200 controls, Green: 1 mA 1 mA msec msec depolarization Threshold change (%)

0

100 msec

Membrane potential (mV) Stimulus charge

0 -100

-150 -100

0

Threshold reduction (%)

200

Current (nA)

-100

100 msec

Stimulus charge

-100 0

-150 .2 0 -.2

0

Membrane potential (mV) Current (% threshold)

100

200

Membrane potential Threshold(mV) change (%)

100 msec

Current (nA)

Current (nA)

Membrane potential Threshold reduction (mV) (%)

0

0 -500

0 Threshold reduction (%)

10

100

-1

msec

0 msec

1

Red: standard model, Green: 5.2 mV hyperpolarization, Blue: 4.5 mV depolarization

Data from Kiernan & Bostock (2000)


Nerve excitability measured by the TROND protocol is sensitive to: Membrane potential Polarizing currents * Hyperkalemia Hypokalemia Ischaemia

Ion channel dysfunction Na channels (Nav1.6) *

Kf channels (Kv1.1) * Ks channels (Kv7.2 = KCNQ2) Ih channels (HCN) * Demyelination Degeneration Regeneration


Puffer Fish Family: Tetraodontidae (Four teeth)


Puffer Fish Family: Tetraodontidae (Four teeth) Tetrodotoxin, synthesized by symbiotic bacteria, is 10,000 times more deadly than cyanide!


Early description of puffer fish poisoning in Captain James Cook's journal from his second voyage in 1774. “…only the liver and roe was dressed which we did but taste. About 3 o’clock in the morning, we were seized with most extraordinary weakness in all our limbs attended with numbness of sensation caused by exposing one’s hand and feet to a fire after having been pinched much by frost. ….nor could I distinguish between light and heavy objects. We each took a vomit. In the morning one of the pigs which had eaten the entrails was found dead.”


.5

Current (nA)

0

.2 .1 0

Abnormal nerve excitability in 4 patients with puffer-fish poisoning -.5 0 200

Current (% threshold)

100

0

0

-100

100 msec

200

0

0

100 msec

200

100

100 msec

200

101

1

0

-100 0

100

Stimulus charge

100 msec

Threshold change (%)

0

Threshold reduction (%)

Current (nA)

Current (nA)

Current (nA)

.2 0 -.2

0 -500

0 Threshold reduction (%)

10

100 msec

-1

0 msec

1

Red: 29 normal controls, Blue: 4 patients

Control data from Kiernan et al. (2000) Patient data from Kiernan et al. (2005)


Best fit is obtained by 48% reduction in all sodium channel currents

Fitting standard model to nerves in 4 patients with puffer-fish poisoning Data from Kiernan et al. (2005)


Current (nA)

.5

.2 .1 0

200

0

0

100 msec

200

100 msec

200

0

-500

-.5

0 Threshold reduction (%)

-80 0

-90 .5 10 0

Current (% threshold)

0

-100

0

100 msec

100 msec

200

-40 -60 -80 0 .2 .1 0

-1

200

0 msec

100

1

101

msec

100

1

0

-100 0

101

1 -20

msec

100

100

100 -70

0 100 200 0 100 Red: 29 normal controls, Blue: 4 patients

Threshold change (%)

0

Current (nA)

-100 -150

200

Membrane potential Stimulus (mV)charge

0 -100

100 msec

Stimulus charge

-100

100 msec

Current (nA)

0

Membrane potential Current(mV) (% threshold)

Threshold reduction Membrane potential (%) (mV)

0 -100

-150 .2 0 -.2

200

Membrane potential Threshold change (%) (mV)

100 msec

100

Current (nA)

Current (nA)

Current (nA)

0

Threshold reduction (%)

0

Fitting standard model to nerves in 4 patients with puffer-fish poisoning -.5 0

Current (nA)

Current (nA)

.2 0 -.2

0 -500

0 Threshold reduction (%)

10

100 msec

-1

0 msec

1

Red: standard model, Blue: PNaN x 0.52 Control data from Kiernan et al. (2000) Patient data from Kiernan et al. (2005)


Nerve excitability measured by the TROND protocol is sensitive to: Membrane potential Polarizing currents * Hyperkalemia Hypokalemia Ischaemia

Ion channel dysfunction Na channels (Nav1.6) *

Kf channels (Kv1.1) * Ih channels (HCN) * Ks channels (Kv7.2 = KCNQ2)

Demyelination Degeneration Regeneration Some simple changes provide a test of the electrical model and the use of MEMFIT to identify membrane changes


TE +/- 40%

100

TE +/- 20%

100

100

NC

-100

NC

0

Threshold change (%)

EA1

0

Threshold reduction (%)

Threshold reduction (%)

EA1

-100

NC 0

EA1 0

100 Delay (ms)

200

0

100 Delay (ms)

200

10 100 Interstimulus interval (ms)

Brain 2010: 133; 3530-3540


TE +/- 40%

100

TE +/- 20%

100

100

NC

-100

NC

0

Threshold change (%)

Threshold reduction (%)

EA1

0

-100

NC 0

EA1 0

100 Delay (ms)

200

0

100 Delay (ms)

200

10 100 Interstimulus interval (ms)

70

Superexcitability (%)

50

NC

40

EA1

-50

EA1

60 TEd20(peak)

Threshold reduction (%)

EA1

NC

NC 30

0 10

20

30 40 TEd40(Accom)

50

0

10

20 30 Subexcitability (%)

40


GKfRel GBB GKfI GKfN GKsN GLkRel

Best fit is obtained by 51.5% reduction in all fast potassium channel currents

GKsRel PNaN IPumpNI PNap(%) GLk GLkN GH GKsI 0

100 Discrepancy reduction (%)

Fitting standard model to nerves in 3 kindreds with EA1 (Kv1.1 mutations) Data from Tomlinson et al. (2010)


0

.5

Current (nA)

Current (nA)

Current (nA)

Current (nA)

.2 0 -.2

.2 .1 0

Fitting standard model with EA1 (KCNA1 missense) -.5 to nerves in 3 kindreds 0 0

0 -100

100 msec

200

100 msec

200 Red: Current (% threshold)

100

0

-100

0

-500

-.5

0 Threshold reduction (%)

100 msec

200

100 -70

-80 0

-90 .5

0

10 msec

msec

0

100 msec

200

101

1 -20

100

-40 -60 -80 0 .2 .1 0

-1

0 msec 100

1

101

msec

100

1

0

-100 0

100

0 100 200 0 100 29 normal controls, Blue: 11 recordings from 6 200 patients Threshold change (%)

0

Current (nA)

-100 -150

0

Threshold reduction (%)

200

Membrane potential (mV)charge Stimulus

-100

100 msec

Current (nA)

Membrane potential Current(mV) (% threshold)

0 -100

-150 .2 0 -.2

0

Current (nA)

Current (nA)

Membrane potential Threshold reduction (mV) (%)

100

200

Stimulus charge

100 msec

Membrane potential (mV) Threshold change (%)

0

0 -500

0 Threshold reduction (%)

10

100 msec

-1

0 msec

1

Red: standard model, Blue: All GKf x 0.485 Data from Tomlinson et al., 2010


Brain 2012 (in press)

Threshold reduction (%)

100

0

0

100 Delay (ms)

200


Nerve excitability measured by the TROND protocol is sensitive to: Membrane potential Polarizing currents * Hyperkalemia Hypokalemia Ischaemia

Ion channel dysfunction Na channels (Nav1.6) *

Kf channels (Kv1.1) * Ks channels (Kv7.2 = KCNQ2) Ih channels (HCN) * Demyelination Degeneration Regeneration


Koltzenburg (Personal communication)


Koltzenburg (Personal communication)


Best fit to 40 mg Org 34167 responses was obtained by 82% reduction in GH (HCN channel conductance)

Koltzenburg (Personal communication)


Koltzenburg (Personal communication)


Koltzenburg (Personal communication)


Modelling human nerve excitability and the TROND protocol Conclusions: MEMFIT is able to correctly identify selective changes in polarizing current and several individual ion channels. On the other hand, complex changes in excitability involving several membrane parameters are unlikely to be resolved unambiguously. However, because of the complexity of interactions between the electrical components of myelinated axons, MEMFIT provides a useful aid to interpreting changes in excitability.



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