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hh_psc_alpha_clopath – Hodgkin-Huxley neuron model with support for Clopath plasticity

Description

hh_psc_alpha_clopath is an implementation of a spiking neuron using the Hodgkin-Huxley formalism and that is capable of connecting to a Clopath synapse.

(1) Postsynaptic currents Incoming spike events induce a postsynaptic change of current modelled by an alpha function. The alpha function is normalized such that an event of weight 1.0 results in a peak current of 1 pA.

(2) Spike Detection Spike detection is done by a combined threshold-and-local-maximum search: if there is a local maximum above a certain threshold of the membrane potential, it is considered a spike.

Parameters

The following parameters can be set in the status dictionary.

Dynamic state variables

V_m

mV

Membrane potential

u_bar_plus

mV

Low-pass filtered Membrane potential

u_bar_minus

mV

Low-pass filtered Membrane potential

u_bar_bar

mV

Low-pass filtered u_bar_minus

Membrane Parameters

E_L

mV

Leak reversal potential

C_m

pF

Capacity of the membrane

g_L

nS

Leak conductance

tau_ex

ms

Rise time of the excitatory synaptic alpha function

tau_in

ms

Rise time of the inhibitory synaptic alpha function

E_Na

mV

Sodium reversal potential

g_Na

nS

Sodium peak conductance

E_K

mV

Potassium reversal potential

g_K

nS

Potassium peak conductance

Act_m

real

Activation variable m

Inact_h

real

Inactivation variable h

Act_n

real

Activation variable n

I_e

pA

External input current

Clopath rule parameters

A_LTD

1/mV

Amplitude of depression

A_LTP

1/mV^2

Amplitude of facilitation

theta_plus

mV

Threshold for u

theta_minus

mV

Threshold for u_bar_[plus/minus]

A_LTD_const

boolean

Flag that indicates whether A_LTD_ should be constant (true, default) or multiplied by u_bar_bar^2 / u_ref_squared (false).

delay_u_bars

real

Delay with which u_bar_[plus/minus] are processed to compute the synaptic weights.

U_ref_squared

real

Reference value for u_bar_bar_^2.

Problems/Todo

  • better spike detection

  • initial wavelet/spike at simulation onset

References

1

Gerstner W and Kistler WM (2002). Spiking neuron models: Single neurons, populations, plasticity. New York: Cambridge university press.

2

Dayan P and Abbott L (2001). Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. Cambridge, MA: MIT Press. https://pure.mpg.de/pubman/faces/ViewItemOverviewPage.jsp?itemId=item_3006127

3

Hodgkin AL and Huxley A F (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. The Journal of Physiology 117. DOI: https://doi.org/10.1113/jphysiol.1952.sp004764

4

Clopath et al. (2010). Connectivity reflects coding: a model of voltage-based STDP with homeostasis. Nature Neuroscience 13(3):344-352. DOI: https://doi.org/10.1038/nn.2479

5

Clopath and Gerstner (2010). Voltage and spike timing interact in STDP – a unified model. Frontiers in Synaptic Neuroscience. 2:25 DOI: https://doi.org/10.3389/fnsyn.2010.00025

6

Voltage-based STDP synapse (Clopath et al. 2010) connected to a Hodgkin-Huxley neuron on ModelDB: https://senselab.med.yale.edu/ModelDB/showmodel.cshtml?model=144566&file =%2fmodeldb_package%2fstdp_cc.mod

Sends

SpikeEvent

Receives

SpikeEvent, CurrentEvent, DataLoggingRequest