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Structured dynamics of hierarchical action selection

Abstract

Extensive work has examined how individuals structure information in cognitive representations. However, the dynamics of how these structured representations are implemented in real time and how cognitive and motor processing interact during action selection have received relatively less attention. Here, we use computational modeling to closely examine the dynamics of hierarchical action selection at the scope of individual decisions. We had participants learn eight stimulus-action associations with latent hierarchical structure. They then engaged in a forced response task where we manipulated the amount of time participants had to prepare each response. We find evidence that hierarchical action selection is a top-down, serialized process but appears to occur without bottlenecks between decision-making and movement. Overall, our results highlight a close coupling between cognitive and motor processing during hierarchical action selection.

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