Reward and Memory-driven Attentional Networks in Human Vision

Yale University, New Haven CT

Investigators

Linked publications & trials

Abstract

DESCRIPTION (provided by applicant): This project examines reward- and memory-driven attention through an investigation of the brain networks underlying these influences. Recent investigations have shown that prior reward, and memory, can both influence attention. These influences, however, are not well accounted for by a classic top-down versus bottom-up framework. There is consequently current uncertainty over whether these influences are best considered top-down, bottom-up, or their own separate class. This work will seek to bring a neurobiological perspective to this debate, using functional magnetic resonance imaging and novel analysis methods. This work will employ informational connectivity; a method developed by the applicant that combines the sensitivity of multi-voxel pattern analysis with the network approach of connectivity, making it ideal for investigating the dynamic regional interactions that underlie attention. The proposed studies will seek to identify common fluctuations in multivariate information between frontoparietal regions, reward and memory networks, and visual cortex, as participants engage in reward-driven, memory-driven, top-down and bottom-up attention. The first aim of this proposal is to reveal the commonalities and differences in how reward-driven and memory- driven attention results from the brain's connectivity patterns. The second aim is to better understand how these influences relate to classic top-down and bottom-up attention, and how reward and memory information is integrated with attentional processing. The final aim is to examine how the brain's informational networks breakdown during attentional distraction, in order to identify the regional connections that are particularly important to overcoming exogenous attentional capture. This research will help improve our understanding of how reward and memory influence the human attentional system.