Figure 2. Dynamic representation in a neural network model of semantic processing.

A. Model architecture. B. 3D MDS of hub activation patterns learned in one model run—each line shows the trajectory of a single item over time in the compressed space. C. The same trajectories shown in uncompressed unit activations for nine randomly sampled unit pairs, horizontal and vertical axes each showing activation of one unit. D. Feature-based analysis of each hub unit in one network run. Each square shows one unit. Lines trace, across time, the correlation between unit activation and category labels across items with dashed lines showing significance thresholds. Color indicates different patterns of responding (see text).