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.

See also [1], [2], [3], [4], [5], [6].

For details on asynchronicity in spike and firing events with Hodgkin Huxley models see here.

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
t_ref	ms	Duration of refractory period
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://modeldb.science/144566?tab=1

Sends

SpikeEvent

Receives

SpikeEvent, CurrentEvent, DataLoggingRequest

See also

Neuron, Hodgkin-Huxley, Current-Based, Clopath Plasticity

Examples using this model

None