Synaptic network structure shapes cortically evoked spatio-temporal responses of STN and GPe neurons in a computational model.
Justus A. KromerHemant BokilPeter A. TassPublished in: Frontiers Neuroinformatics (2023)
Keyphrases
- computational model
- network structure
- spatio temporal
- working memory
- single neuron
- sensory inputs
- synaptic plasticity
- neuron model
- learning rules
- spiking neurons
- spiking neural networks
- social networks
- primary visual cortex
- network analysis
- feed forward
- complex networks
- network size
- dynamic networks
- computational models
- online social networks
- hebbian learning
- link prediction
- visual processing
- hidden layer
- neural network
- synaptic weights
- visual cortex
- small world
- biologically inspired
- real world networks
- biologically plausible
- spike trains
- image sequences
- receptive fields
- space time
- cognitive architecture
- computational framework
- cognitive modeling
- long term memory
- activation function
- structure learning
- artificial neural networks
- network evolution
- computational modeling
- social media
- clustering coefficient
- back propagation
- recurrent neural networks
- graph theory