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Presented by Suganya Karunakaran Reduction of Spike Afterdepolarization by Increased Leak Conductance Alters Interspike Interval Variability Fernando R. Fernandez and John A.White The Journal of Neuroscience, January 28, 2009 • 29(4):973–986 • 973

Presented by Suganya Karunakaran

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Reduction of Spike Afterdepolarization by Increased Leak Conductance Alters Interspike Interval Variability. Fernando R. Fernandez and John A.White The Journal of Neuroscience, January 28, 2009 • 29(4):973–986 • 973. Presented by Suganya Karunakaran. Spike Afterdepolarization. - PowerPoint PPT Presentation

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Page 1: Presented by  Suganya Karunakaran

Presented by Suganya Karunakaran

Reduction of Spike Afterdepolarization by Increased Leak Conductance Alters Interspike Interval Variability

Fernando R. Fernandez and John A.WhiteThe Journal of Neuroscience, January 28, 2009 • 29(4):973–986 • 973

Page 2: Presented by  Suganya Karunakaran

Spike Afterdepolarization

Membrane potential depolarization that follows an action potential

May occur before (early) or after (delayed) full repolarization

Common in cardiac muscles Sometimes occurs in tissues not

normally excitable

Page 3: Presented by  Suganya Karunakaran

Leak Conductance

Leak conductance is generated by membrane damage surrounding an electrode and an increase in K+ permeability evoked by cytosolic elevations of Sodium and Calcium

Page 4: Presented by  Suganya Karunakaran

Interspike Interval Variability Inter-spike Interval Variability of neuronal spike train –

important indicator of the type of processing a neuron performs on its synaptic inputs

Simplest measure – Coefficient of Variability

CV = standard deviation of ISI distribution/mean ISI Refractory period lowers the CV at high

firing rates when it tends to force regularity in the ISI duration

Page 5: Presented by  Suganya Karunakaran

High-Conductance state

State of neurons in an active network Total synaptic conductance received by

the neuron (over a period of time) is larger than its resting conductance

Found in thalamocortical system especially cerebral cortex

Neurons can integrate differently in this state

Can be reproduced by dynamic-clamp experiments

Page 6: Presented by  Suganya Karunakaran

Computational Consequence Neuronal responses in high-conductance

states are probabilistic because of the high variability of responses due to the presence of fluctuating background activity

Change the response properties of neurons

Red- deterministic neuron

Green- probabilistic neuron

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Computational Consequence May fundamentally chance dendrite

integration properties Reduced membrane time constant –

change in Temporal Processing

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Previous Results

Effects of background synaptic conductance activity on ISI variability depends on neuron type

For a conductance based stimulus, In pyramidal cells lacking spike frequency

adaptation, variability increased In pyramidal cells displaying spike frequency

adaptation, variability decreased

(τ differs between two subtypes) Leak – bifurcation parameter

Reduces afterdepolarization (ADP) Decrease the gain of frequency-current

relationship

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Model

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Model ctnd.

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Parameters

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Non adapting Cells

The ability of a high conductance state to increase ISI variability depends on the subtype of pyramidal cell.

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Model

3 Dimensions V h (INa inactivation ) n (IKCa activation)

Single pulse-excited spike produces a larger ADP under control conditions than with added leak conductance

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Single pulse Excitation

Matlab Model- Reproduced Result

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Decrease in CV

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Phase Plane Analysis - Control

Blue – Stable fixed pointBlack – Unstable fixed point

Reproduced Result

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Reproduced Result

Phase Plane Analysis – with leak

Page 18: Presented by  Suganya Karunakaran

Phase Plane Analysis

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Bifurcation Analysis

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Conclusion

The decrease in CV of the model with added leak conductance can be explained as a consequence of a lower gain in the F-I relationship resulting from the changes in the ADP and bifurcation in the fast subsystem of the model

Page 21: Presented by  Suganya Karunakaran