* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Increased leak conductance alters ISI variability.
Central pattern generator wikipedia , lookup
Holonomic brain theory wikipedia , lookup
Neuroanatomy wikipedia , lookup
Multielectrode array wikipedia , lookup
Action potential wikipedia , lookup
Premovement neuronal activity wikipedia , lookup
Development of the nervous system wikipedia , lookup
Membrane potential wikipedia , lookup
Theta model wikipedia , lookup
Neural oscillation wikipedia , lookup
Neural modeling fields wikipedia , lookup
Neuromuscular junction wikipedia , lookup
Apical dendrite wikipedia , lookup
Activity-dependent plasticity wikipedia , lookup
Neuropsychopharmacology wikipedia , lookup
Resting potential wikipedia , lookup
Optogenetics wikipedia , lookup
Spike-and-wave wikipedia , lookup
Neurotransmitter wikipedia , lookup
Molecular neuroscience wikipedia , lookup
Electrophysiology wikipedia , lookup
Pre-Bötzinger complex wikipedia , lookup
End-plate potential wikipedia , lookup
Stimulus (physiology) wikipedia , lookup
Metastability in the brain wikipedia , lookup
Single-unit recording wikipedia , lookup
Synaptogenesis wikipedia , lookup
Feature detection (nervous system) wikipedia , lookup
Nonsynaptic plasticity wikipedia , lookup
Chemical synapse wikipedia , lookup
Neural coding wikipedia , lookup
Synaptic gating wikipedia , lookup
Nervous system network models wikipedia , lookup
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 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 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 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 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 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 Computational Consequence May fundamentally chance dendrite integration properties Reduced membrane time constant – change in Temporal Processing High conductance State Decrease in integration time constant Increase in spike output variability 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 Model Model ctnd. Parameters Non adapting Cells The ability of a high conductance state to increase ISI variability depends on the subtype of pyramidal cell. High conductance state – Leakier membranes Faster decay rates for synaptic inputs Increases ISI variability 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 Single pulse Excitation Matlab Model- Reproduced Result Decrease in CV Phase Plane Analysis - Control Reproduced Result Blue – Stable fixed point Black – Unstable fixed point Phase Plane Analysis – with leak Reproduced Result Phase Plane Analysis Bifurcation Analysis 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