Perceptual decision-making performance depends on several cognitive and neural processes. Here, we fit Ratcliff's diffusion model to accuracy data and reaction-time distributions from one numerical and one verbal two-choice perceptual-decision task to deconstruct these performance measures into the rate of evidence accumulation (i.e., drift rate), response criterion setting (i.e., boundary separation), and peripheral aspects of performance (i.e., nondecision time). These theoretical processes are then related to individual differences in brain activation by means of multiple regression. The sample consisted of 24 younger and 15 older adults performing the task in fMRI before and after 100 daily 1-hr behavioral training sessions in a multitude of cognitive tasks. Results showed that individual differences in boundary separation were related to striatal activity, whereas differences in drift rate were related to activity in the inferior parietal lobe. These associations were not significantly modified by adult age or perceptual expertise. We conclude that the striatum is involved in regulating response thresholds, whereas the inferior parietal lobe might represent decision-making evidence related to letters and numbers.

The present fMRI study tested the assumption that a single pairing of a stimulus and a logically unrelated response is sufficient for binding the corresponding stimulus and response codes into an event representation (event file) that is automatically retrieved upon processing of at least one of its components. In particular, we investigated whether repeating a face or a house stimulus and/or a left or a right manual response induces the automatic retrieval of the response or stimulus that it previously accompanied. ROI analyses of fusiform face area, parahippocampal place area, and right and left motor cortex revealed that repeating one component of a previously encountered stimulus-response episode leads to the suppression of cortical areas processing the other components, suggesting that these components were indeed automatically retrieved and conflicted with ongoing processing. The particular pattern obtained is consistent with predictions from diffusion models of decision making, which suggest a crucial role of local competition in response selection.

Ideomotor theory claims that actions are cognitively represented and accessed via representations of the sensory effects they evoke. Previous studies provide support for this claim by showing that the presentation of action effects primes activation in corresponding motor structures. However, whether people actually use action-effect representations to control their motor behavior is not yet clear. In our fMRI study, we had participants prepare for manual or facial actions on a trial-by-trial basis, and hypothesized that preparation would be mediated by the cortical areas that code for the perceptual effects of these actions. Preparing for manual action induced higher activation of hand-related areas of motor cortex (demonstrating actual preparation) and of the extrastriate body area, which is known to mediate the perception of body parts. In contrast, preparing for facial action induced higher activation of face-related motor areas and of the fusiform face area, known to mediate face perception. These observations provide further support for the ideomotor theory and suggest that visual imagery might play a role in voluntary action control.