Figure 6.

All-to-all cross-columnar excitation prohibits learning. (A) Extending the original architecture described in Figure 1B, M→T connections exist between all columns C_i→C_j (i≠j) and are subject to the same plasticity. (B) Firing rates of the excitatory populations during learning and recall of four time intervals (each 700 ms). Initially, learning evolves as in Figure 1C, but the activity becomes degenerated and the sequence can not be recalled correctly (lower panels). (C) Evolution of the cross-columnar (from C₂, top panel) and recurrent Timer synaptic weights (bottom panel). The transition to the next sequence cannot be uniquely encoded as the weights to all columns are strengthened. (D) Sequence recall after 100 training trials in a network with a low background noise (50% of the baseline value, 1/2σ_ξ). (E) Sequence recall after 100 training trials in a network with a higher Hebbian activation threshold for the cross-columnar projections $r_{\text{th}}^{\text{ff}}=30\text{spks}/\text{sec}$ (instead of the baseline 20spks/sec).