Functional balanced networks with synaptic plasticity (Sadeh et al, 2015)

The model investigates the impact of learning on functional sensory networks. It uses large-scale recurrent networks of excitatory and inhibitory spiking neurons equipped with synaptic plasticity. It explains enhancement of orientation selectivity and emergence of feature-specific connectivity in visual cortex of rodents during development, as reported in experiments.

Model Type: Realistic Network

Cell Type(s): Abstract integrate-and-fire leaky neuron

Transmitters: Gaba; Glutamate

Model Concept(s): Synaptic Plasticity; Long-term Synaptic Plasticity; Learning; Sensory processing; Homeostasis; Orientation selectivity; Vision

Simulation Environment: Python

Implementer(s): Sadeh, Sadra [s.sadeh at ucl.ac.uk]

References:

Sadeh S, Clopath C, Rotter S. (2015). Emergence of Functional Specificity in Balanced Networks with Synaptic Plasticity. PLoS computational biology. 11 [PubMed]