Sophisticated decision-making mechanisms and complex experimental paradigms can be modeled, simulated, and fit to empirical response time data, using a flexible and efficient computational modeling framework.
Regulatory success operates by goal-consistent increases and decreases of distinct attribute representations in generic neural hubs and in domain-specific brain regions, explaining when and why regulatory success generalizes across domains and contexts.
In monkeys making decisions that balance noisy evidence and reward expectation, frontal cortical and caudate activity reflect different computational components that are related to the monkeys' strategy.
Combined antigenic and genetic analysis shows that different strains of the human influenza virus display dramatically different rates of antigenic drift, and that these differences have a significant impact on the number of new infections in each flu season.
The readiness potential—a long-established neural precursor of voluntary action claimed to precede the onset of the conscious decision to move—is absent, or at least significantly reduced, for deliberate decisions.