Figure 1.

(A) A common implementation of the biased competition model. Rectangles represent populations of neurons, open arrows signify excitatory connections, filled arrows indicate inhibitory connections, and large shaded boxes, with rounded corners, indicate different cortical areas or processing stages. Within each processing stage nodes compete to be active in response to the current pattern of feedforward activity received from the sensory input or previous processing stage. The outcome of this competition can be influenced by feedback activation received from subsequent processing stages and/or attentional signals. Two possible mechanisms of competition within a processing stage are illustrated in (B) and (C). (B) Lateral inhibition suppressing node outputs. Direct inhibitory connections are shown between two nodes within a neural population, however, functionally equivalent behavior results from inhibition that is pooled via inhibitory interneurons, or from a non-neurally implemented selection mechanism that chooses the most active node(s). (C) Lateral inhibition suppressing node inputs. The bottom-up input to a processing stage is routed via an additional population of nodes. These nodes provide a mechanism through which the output nodes can compete, via feedback inhibition, for the right to respond to inputs. Each inhibitory weight from a node in population y to a node in population e has the same strength as the reciprocal excitatory weight between the same nodes in populations e and y. In both (B) and (C) nodes are shown as circles, thin arrows show connections between individual nodes, while thick arrows illustrate multiple connections between populations of nodes.