Spike-Timing-Dependent Plasticity and Short-Term Plasticity Jointly Control the Excitation of Hebbian Plasticity without
Weight Constraints in Neural Networks
Figure 4
Network structure with ten synaptic connections. (a) shows the developed fully connected network to test how neurons could balance the excitation after external input was applied to part of it. and are the outputs (the number of active transmitters attached to the neuron at a given time step) of neuron and neuron , respectively. Receptor groups and receptor groups symbolized the number of active receptors in the corresponding receptor groups of postsynaptic neuron A and postsynaptic neuron , respectively. are the synapses where receptor groups of postsynaptic neuron A contact the transmitters of neuron B. Similarly, are the synapses where receptor groups of postsynaptic neuron B contact the transmitters of neuron A. (b) shows how information flows between the two neurons. When signals are passing from A to B, A is called presynaptic neuron and B is called postsynaptic neuron. Similarly, when signals are passing from B to A, B is called presynaptic neuron and A is called postsynaptic neuron. Since external Poisson inputs are applied to neuron A only, neuron A becomes the immediate presynaptic neuron and B becomes the immediate postsynaptic neuron for the external inputs.
