Figure 1.

The complete network model (A) with thalamocortical circuit where thalamic afferents from the LGN activate the principal cells of layer 4 of V1 via geniculocortical synapses. The layer 4 and LGN are both modeled as an E-I network. There are two inhibitory populations in layer 4: the feedback inhibitory population I₁, which does not receive any inputs from LGN but only from the E neurons of layer 4 and the feedforward inhibitory population I₂, which does. The LGN receives spikes from retinal ganglion cells (RGC). The LGN and layer 4 neurons in the model are separated by the dashed line in the figure. This complete model is used for simulating the experience-dependent phase of development. For each network layer, 60% of randomly chosen neurons are injected with background noise in form of currents (I_inj) for 30 ms. A new of set of 60% randomly chosen neurons at all layers are selected again after that and are injected with background noise. This process is repeated throughout all three phases of development. For simulating early experience-independent phase (Phase 1) the complete network is purely driven by the background noise at both LGN and layer 4. For simulating late experience-independent phase (Phase 2) the LGN is activated by spikes due to retinal waves from RGC.