Learning of Chunking Sequences in Cognition and Behavior
Fig 4
Synaptic weights before and after learning.
(a, b) Initially (tini), the recurrent weight matrices implement all-to-all symmetric inhibition, leading to WTA. After learning tfin the matrices acquire an asymmetric component, leading to WLC. Superimposed white arrows in (b) indicate the resulting order of the recalled states. (c, d) The weights in the matrices Qij and Rji learn which EM belongs to which chunk. The last three columns correspond to the elements that activate during chunk transitions.