Neural Network Dynamics for Attentional Selection

Natural scenes are cluttered and contain many objects that cannot all be processed simultaneously due to capacity limitations of the visual system. Selective attention refers to a set of mechanisms that route behaviorally relevant information through large-scale cortical networks. I will discuss studies performed in two primate brain models, the human and the macaque monkey, using a variety of different techniques including fMRI, ECoG and single-cell physiology. First, I will discuss how large-scale networks mediating perception and cognition can be identified using functional brain imaging. Second, I will discuss physiology studies revealing temporal dynamics in a distributed large-scale network that mediates the selection of behaviorally relevant information. Particularly, while there is evidence that populations of cortical neurons synchronize their activity to preferentially transmit information about attentional priorities, it is unclear how cortical synchrony across a network is accomplished. I will discuss the unique role of thalamo-cortical interactions in influencing cortical networks to optimize their communication. These studies are complemented by ECoG recordings from human epilepsy patients using identical behavioral paradigms providing a mechanistic understanding of the coding principles that best predict behavior in both primate species.