stdp_dopamine_synapse – Synapse type for dopamine-modulated spike-timing dependent plasticity
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Description
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``stdp_dopamine_synapse`` is a connection to create synapses with
dopamine-modulated spike-timing dependent plasticity (used as a
benchmark model in [1]_, based on [2]_). The dopaminergic signal is a
low-pass filtered version of the spike rate of a user-specific pool
of neurons. The spikes emitted by the pool of dopamine neurons are
delivered to the synapse via the assigned volume transmitter. The
dopaminergic dynamics is calculated in the synapse itself.
.. warning::
This synaptic plasticity rule does not take
:ref:`precise spike timing ` into
account. When calculating the weight update, the precise spike time part
of the timestamp is ignored.
Parameters
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**Common properties**
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volume_transmitter NodeCollection volume_transmitter collecting the spikes from the
pool of dopamine releasing neurons and transmitting
the spikes to the synapse.
A_plus real Multiplier applied to weight changes caused by
pre-before-post spike pairings. If b (dopamine
baseline concentration) is zero, then A_plus
is simply the multiplier for facilitation (as in the
stdp_synapse model). If b is not zero, then A_plus
will be the multiplier for facilitation only if n - b
is positive, where n is the instantenous dopamine
concentration in the volume transmitter. If n - b is
negative, A_plus will be the multiplier for
depression.
A_minus real Multiplier applied to weight changes caused by
post-before-pre spike pairings. If b (dopamine
baseline concentration) is zero, then A_minus
is simply the multiplier for depression (as in the
stdp_synapse model). If b is not zero, then A_minus
will be the multiplier for depression only if n - b
is positive, where n is the instantenous dopamine
concentration in the volume transmitter. If n - b is
negative, A_minus will be the multiplier for
facilitation.
tau_plus ms STDP time constant for weight changes caused by
pre-before-post spike pairings.
tau_c ms Time constant of eligibility trace
tau_n ms Time constant of dopaminergic trace
b real Dopaminergic baseline concentration
Wmin real Minimal synaptic weight
Wmax real Maximal synaptic weight
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The common properties can only be set by :py:func:`.SetDefaults` and apply
to all instances of the synapse model.
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**Individual properties**
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c real Eligibility trace
n real Neuromodulator concentration
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References
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.. [1] Potjans W, Morrison A, Diesmann M (2010). Enabling functional neural
circuit simulations with distributed computing of neuromodulated
plasticity. Frontiers in Computational Neuroscience, 4:141.
DOI: https://doi.org/10.3389/fncom.2010.00141
.. [2] Izhikevich EM (2007). Solving the distal reward problem through linkage
of STDP and dopamine signaling. Cerebral Cortex, 17(10):2443-2452.
DOI: https://doi.org/10.1093/cercor/bhl152
Transmits
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SpikeEvent
See also
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:doc:`Synapse `, :doc:`Spike-Timing-Dependent Plasticity `
Examples using this model
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.. listexamples:: stdp_dopamine_synapse