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Content archived on 2024-05-28

Perceptual load and neural competition. Determinant factors in selective attention

Final Report Summary - LOADATCMC08 (Perceptual load and neural competition. Determinant factors in selective attention)

Attention is important for all cognitive functions. Information that is attended is apparently preferentially processed. However, unattended information sometimes evokes distraction while at other times it seems to be successfully ignored, and what determines which will occur has been an intriguing question in attention research in the last decades. Load theory proposes a model that solves this debate. It proposes that attentional capacity is limited and resource allocation depends on the demands required to process the task relevant information. Tasks that impose low attentional demands on task relevant processing leave spare capacity that spills over resulting in the perception of additional task irrelevant stimuli. However, when demands on task relevant stimuli are increased less spare capacity is available and irrelevant distractor processing is reduced. While there is substantive evidence that load affects processing of distracting information the neural substrate of these capacity limitations is less known. Thus the main goal of this project was to explore the neural sources underlying this limitation as well as additional factors that determine the allocation of neural resources. Specifically we have developed three lines of research. In one line, we investigated the neural signature of perceptual load. We have collected functional brain scans while our participants performed an attentional task in which the level of load was gradually increased. Our results reveal a set of fronto-parietal brain regions that appear to track the level of load and show greater response as load increases. Thus, these regions are sensitive to the amount of resources that the attentional task requires. Also, we see that the neural signal in the retinotopic parts of the brain that represent the attended and unattended information respond to load differentially: load increases the neural signal in the attended locations while neural signal decreases in unattended locations. This is an important empirical contribution to load theory because it demonstrates the strong push-pull relationship between neural activity related to attended versus that related to unattended processing in support of load theory predictions. We also found differential connectivity between the fronto-parietal regions that track the attended processing load and the retinotopic regions of visual cortex that represent the attended and unattended locations. These results suggest that signal change we observe in visual cortex in response to load might be due to differential feedback projections from frontal regions into visual cortex. In another line of research we conducted a series of behavioural studies to address recent criticisms of load theory that argue that distractor processing is reduced in high load (high set size) conditions because non-target letters passively dilute the distractor representation irrespective of the task demands. Our results reveal that reduced distractor effect in high set size conditions is not due to a mere dilution of the distractor representation but rather to the fact that processing resources are devoted to task-relevant stimuli. We have also conducted different lines of experiments where we observe that when task demands are low there is a competition between the stimuli for the spare attentional processing resources. Our results suggest that factors such perceptual saliency dictates the allocation of attentional resources thus affecting what stimuli attentional resources are devoted to. Our conclusions strengthen load theory main tenet that distractor processing is determined by the amount of resources allocation to task relevant stimuli as we describe in a theoretical paper (Lavie & Torralbo, 2010). Finally, in an additional line of experiments, we have investigated the interactions between perceptual demands and the top down factor of expectations in determining the efficiency of selective attention. Specifically, we have tested whether demands imposed on processing task relevant stimuli will impair the processing of a highly unexpected distractor. In different experiments we have manipulated distractor expectancies by changing the probabilities of distractor appearance, the location where it appears and the extent to which it matches or not the target response. When attention demands are low, distractor processing is larger when it is unexpected as compared to expected. However, when attentional demands are high, distractor processing is reduced irrespective of the distractor expectancy. This suggests that load prevents top down expectation processing for distractors. Our results reveal that attention and expectation might share some level of stimulus representation: load reduces distractor representation possibly also affecting the expectation that can be formed from it. Overall, this Marie Curie project has contributed to improve the knowledge of an important and ubiquitous process of human cognition: attention. Our results are valuable to understand the way our brain deals with the large amount of information we often are exposed to in our life.