Fig. 1.
Structure of the model network. Each circle stands for a population of neurons with similar receptive fields. Edges and other local features of a figure (black parallelogram) activate edge cells (E) that project to border ownership cells (B) that have the same preferred orientation and position, but opposite side-of-figure preferences (in this example BL on the left side of the figure and BR on the right). B cells have reciprocal excitatory feedback connections with grouping cells (G) that integrate global contour information at multiple scales (only one scale is shown). The grouping cells bias border ownership cell activity according to the location of the figure. Because a border can be owned by only one figure, opposing border ownership cells compete directly via IE cells and indirectly via grouping cells. The B cells excite inhibitory border ownership cells (IB; again with the indexes L and R) of the same preferred side of the figure, which inhibit G cells in all directions except the preferred one. Thus, grouping cells that are activated by inconsistent figures mutually inhibit each other via B and IB cells and unstructured input creates only small activation of G cells. A weaker, broader, and less specific inhibitory interaction has been introduced in an extension of the model to explain the results presented in Fig. 5. This inhibition is realized by direct G to IB connections, depicted as dashed lines. Top–down attention is modeled as a broad and purely spatial input to the grouping cells (top). Blue and red connections are inhibitory and excitatory, respectively. High-contrast symbols indicate cells and connections activated by the shown figure. Blue, red, and orange connections are inhibitory, feedforward excitatory, and feedback excitatory, respectively.