Neural Correlates of Divided Attention in Natural Scenes

Author:

Fagioli Sabrina1,Macaluso Emiliano12

Affiliation:

1. 1IRCCS Santa Lucia Foundation, Rome, Italy

2. 2Lyon Neuroscience Research Center

Abstract

Abstract Individuals are able to split attention between separate locations, but divided spatial attention incurs the additional requirement of monitoring multiple streams of information. Here, we investigated divided attention using photos of natural scenes, where the rapid categorization of familiar objects and prior knowledge about the likely positions of objects in the real world might affect the interplay between these spatial and nonspatial factors. Sixteen participants underwent fMRI during an object detection task. They were presented with scenes containing either a person or a car, located on the left or right side of the photo. Participants monitored either one or both object categories, in one or both visual hemifields. First, we investigated the interplay between spatial and nonspatial attention by comparing conditions of divided attention between categories and/or locations. We then assessed the contribution of top–down processes versus stimulus-driven signals by separately testing the effects of divided attention in target and nontarget trials. The results revealed activation of a bilateral frontoparietal network when dividing attention between the two object categories versus attending to a single category but no main effect of dividing attention between spatial locations. Within this network, the left dorsal premotor cortex and the left intraparietal sulcus were found to combine task- and stimulus-related signals. These regions showed maximal activation when participants monitored two categories at spatially separate locations and the scene included a nontarget object. We conclude that the dorsal frontoparietal cortex integrates top–down and bottom–up signals in the presence of distractors during divided attention in real-world scenes.

Publisher

MIT Press - Journals

Subject

Cognitive Neuroscience

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