Going from cognitive theory to neural data to ACT‐R models, the authors relate brain activity in a lexical ambiguity priming task to brain processes that resolve ambiguity in word meanings. These detailed data were tested and found compatible to the results of an ACT‐R computational model of reinforcement learning (RL). The model confirms and extends the behavioral findings to provide a RL account of individual differences in lexical ambiguity resolution.

Previous research on the neural basis of cognitive control processes has mainly focused on cortical areas, while the role of subcortical structures in cognitive control is less clear. Models of basal ganglia function as well as clinical studies in neurodegenerative diseases suggest that the striatum (putamen and caudate nucleus) modulates the inhibition of interfering responses and thereby contributes to an important aspect of cognitive control, namely response interference control. To further investigate the putative role of the striatum in the control (...) of response interference, 23 patients with stroke-induced lesions of the striatum and 32 age-matched neurologically healthy controls performed a unimanual version of the Simon task. In the Simon task, the correspondence between stimulus location and response location is manipulated so that control over response interference can be inferred from the reaction time costs in incongruent trials. Results showed that stroke patients responded overall slower and more erroneous than controls. The difference in response times (RTs) between incongruent and congruent trials (known as the Simon effect) was smaller in the ipsilesional/-lateral hemifield, but did not differ significantly between groups. However, in contrast to controls, stroke patients exhibited an abnormally stable Simon effect across the reaction time distribution indicating a reduced efficiency of the inhibition process. Thus, in stroke patients unilateral lesions of the striatum did not significantly impair the general ability to control response interference, but led to less efficient selective inhibition of interfering responses. (shrink)

Several attempts have been made previously to provide a biological grounding for cognitive architectures by relating their components to the computations of specific brain circuits. Often, the architecture's action selection system is identified with the basal ganglia. However, this identification overlooks one of the most important features of the basal ganglia—the existence of a direct and an indirect pathway that compete against each other. This characteristic has important consequences in decision-making tasks, which are brought to light by Parkinson's disease as (...) well as genetic differences in dopamine receptors. This paper shows that a standard model of action selection in a cognitive architecture cannot replicate any of these findings, details an alternative solution that reconciles action selection in the architecture with the physiology of the basal ganglia, and extends the domain of application of cognitive architectures. The implication of this solution for other architectures and existing models are discussed. (shrink)