Advance Preparation in Task-Switching: Converging Evidence from Behavioral, Brain Activation, and Model-Based Approaches

The prefrontal cortex subserves executive control--that is, the ability to select actions or thoughts in relation to internal goals. Here, we propose a theory that draws upon concepts from information theory to describe the architecture of executive control in the lateral prefrontal cortex. Supported by evidence from brain imaging in human subjects, the model proposes that action selection is guided by hierarchically ordered control signals, processed in a network of brain regions organized along the anterior-posterior axis of the lateral prefrontal cortex. The theory clarifies how executive control can operate as a unitary function, despite the requirement that information be integrated across multiple distinct, functionally specialized prefrontal regions.

A hybrid blocked and event-related functional magnetic resonance imaging (fMRI) study decomposed brain activity during task switching into sustained and transient components. Contrasting task-switching blocks against single-task blocks revealed sustained activation in right anterior prefrontal cortex (PFC). Contrasting task-switch trials against task-repeat and single-task trials revealed activation in left lateral PFC and left superior parietal cortex. In both sets of regions, activation dynamics were strongly modulated by trial-by-trial fluctuations in response speed. In addition, right anterior PFC activity selectively covaried with the magnitude of mixing cost (i.e., task-repeat versus single-task trial performance), and left superior parietal activity selectively covaried with the magnitude of the switching cost (i.e., task-switch versus task-repeat trial performance). These results indicate a functional double dissociation in brain regions supporting different components of cognitive control during task switching and suggest that both sustained and transient control processes mediate the behavioral performance costs of task switching.

Magnetic resonance imaging (MRI) has rapidly become an important tool in clinical medicine and biological research. Its functional variant (functional magnetic resonance imaging; fMRI) is currently the most widely used method for brain mapping and studying the neural basis of human cognition. While the method is widespread, there is insufficient knowledge of the physiological basis of the fMRI signal to interpret the data confidently with respect to neural activity. This paper reviews the basic principles of MRI and fMRI, and subsequently discusses in some detail the relationship between the blood-oxygen-level-dependent (BOLD) fMRI signal and the neural activity elicited during sensory stimulation. To examine this relationship, we conducted the first simultaneous intracortical recordings of neural signals and BOLD responses. Depending on the temporal characteristics of the stimulus, a moderate to strong correlation was found between the neural activity measured with microelectrodes and the BOLD signal averaged over a small area around the microelectrode tips. However, the BOLD signal had significantly higher variability than the neural activity, indicating that human fMRI combined with traditional statistical methods underestimates the reliability of the neuronal activity. To understand the relative contribution of several types of neuronal signals to the haemodynamic response, we compared local field potentials (LFPs), single- and multi-unit activity (MUA) with high spatio-temporal fMRI responses recorded simultaneously in monkey visual cortex. At recording sites characterized by transient responses, only the LFP signal was significantly correlated with the haemodynamic response. Furthermore, the LFPs had the largest magnitude signal and linear systems analysis showed that the LFPs were better than the MUAs at predicting the fMRI responses. These findings, together with an analysis of the neural signals, indicate that the BOLD signal primarily measures the input and processing of neuronal information within a region and not the output signal transmitted to other brain regions.