stdp_dopamine_synapse – Synapse type for dopamine-modulated spike-timing dependent plasticity

Description

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.

Parameters

Common properties

vt

integer

ID of volume_transmitter collecting the spikes from the pool of dopamine releasing neurons and transmitting the spikes to the synapse. A value of -1 indicates that no volume transmitter has been assigned.

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

Individual properties

c

real

Eligibility trace

n

real

Neuromodulator concentration

Remarks:

The common properties can only be set by SetDefaults and apply to all synapses of the model.

References

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

SpikeEvent