The basal ganglia play a central role in cognition and are involved in such general functions as action selection and reinforcement learning. Here, we present a model exploring the hypothesis that the basal ganglia implement a conditional information-routing system. The system directs the transmission of cortical signals between pairs of regions by manipulating separately the selection of sources and destinations of information transfers. We suggest that such a mechanism provides an account for several cognitive functions of the basal ganglia. The model also incorporates a possible mechanism by which subsequent transfers of information control the release of dopamine. This signal is used to produce novel stimulus–response associations by internalizing transferred cortical representations in the striatum. We discuss how the model is related to production systems and cognitive architectures. A series of simulations is presented to illustrate how the model can perform simple stimulus–response tasks, develop automatic behaviors, and provide an account of impairments in Parkinson’s and Huntington’s diseases.

The human ability to flexibly adapt to novel circumstances is extraordinary. Perhaps the most illustrative yet underappreciated form of this cognitive flexibility is rapid instructed task learning (RITL) – the ability to rapidly reconfigure our minds to perform new tasks from instruction. This ability is important for everyday life (e.g., learning to use new technologies), and is used to instruct participants in nearly every study of human cognition. We review the development of RITL as a circumscribed domain of cognitive neuroscience investigation, culminating in recent demonstrations that RITL is implemented via brain circuits centered on lateral prefrontal cortex. We then build on this and other insights to develop an integrative theory of cognitive flexibility and cognitive control, identifying theoretical principles and mechanisms that may make RITL possible in the human brain. Insights gained from this new theoretical account have important implications for further developments and applications of RITL research.

The methodologies of cognitive architectures and functional magnetic resonance imaging can mutually inform each other. For example, four modules of the ACT-R (adaptive control of thought - rational) cognitive architecture have been associated with four brain regions that are active in complex tasks. Activity in a lateral inferior prefrontal region reflects retrieval of information in a declarative module; activity in a posterior parietal region reflects changes to problem representations in an imaginal module; activity in the anterior cingulate cortex reflects the updates of control information in a goal module; and activity in the caudate nucleus reflects execution of productions in a procedural module. Differential patterns of activation in such central regions can reveal the time course of different components of complex cognition.

Understanding the neurobiological basis of individual differences in second language acquisition (SLA) is important for research on bilingualism, learning, and neural plasticity. The current study used quantitative electroencephalography (qEEG) to predict SLA in college-aged individuals. Baseline, eyes-closed resting-state qEEG was used to predict language learning rate during eight weeks of French exposure using an immersive, virtual scenario software. Individual qEEG indices predicted up to 60% of the variability in SLA, whereas behavioral indices of fluid intelligence, executive functioning, and working-memory capacity were not correlated with learning rate. Specifically, power in beta and low-gamma frequency ranges over right temporoparietal regions were strongly positively correlated with SLA. These results highlight the utility of resting-state EEG for studying the neurobiological basis of SLA in a relatively construct-free, paradigm-independent manner.