Simulations showing how spike time dependent plasticity and heterosynaptic competition spontaneously organize networks to produce long, sparse neural activity sequences, whether the training inputs are sequential or not. This simulation aligns with Figure 2 in the associated paper (summed weight bound). After weights are learned, random bursts are provided to initiate activity and playback is plotted.
Please cite "I. R. Fiete, W. Senn, C. Wang, R. H. R. Hahnloser. Spike time-dependent plasticity and heterosynaptic competition organize networks to produce long scale-free sequences of neural activity. Neuron 65(4): 563-576 (2010)." If this code is used.
- Fig_2_Simulation.m
- README.md
Simulation of long chain network formation through spike time dependent plasticity and heterosynaptic long term depression. This simulation aligns with Figure 2 in the associated paper, imposing binary neuron network dynamics and a summed weight limit. After weights are learned random, bursts are provided to initiate activity and playback is plotted.
- Run the simulation from Matlab or Octave by typing Fig_2_Simulation in the command line.