2026-10-11T15:39:47Z https://data.mendeley.com/oai

oai:data.mendeley.com/wpzxh93vhx.1 2019-03-11T10:04:28Z

Bogdan, Petruț Antoniu Supporting Data and Software for Event-based computation: Unsupervised elementary motion decomposition Mendeley Data We show that the presented architecture allows for unsupervised learning; that synaptic rewiring enhanced to initialise synapses by drawing from a distribution of delays produces more specialised neurons for the task of motion decomposition; and that a pair of readout neurons is sufficient to correctly classify the input based on the target layer's activity using rank-order encoding, rather than spike-rate encoding. Folder structure: |--- simulation_statistics --> analysis scripts and pre-processed simulation results ---|-- preproc --> pre-processed simulation results |--- synaptogenesis ---|-- moving_bar_simulations --> training and testing results for motion learning phase ---|-- readout_simulations --> training and testing results for readout phase ---|-- spiking_moving_bar_input --> moving bar spiking input used throughout |--- spinnaker_software --> snapshot of SpiNNaker software used to generate the presented results Synaptic Plasticity Computational Neuroscience Computer Simulation Neuronal Plasticity Pineda-Garcia, Garibaldi Davidson, Simon Hopkins, Michael James, Robert Furber, Steve B. Dataset doi:10.17632/wpzxh93vhx.1 oai:data.mendeley.com/wpzxh93vhx.1 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/wpzxh93vhx 2019-03-11T10:04:28Z