Biased competition in semantic representation during natural visual search

Abstract

Humans divide their attention among multiple visual targets in daily life, and visual search gets more difficult as the number of targets increases. The biased competition hypothesis (BC) has been put forth as an explanation for this phenomenon. BC suggests that brain responses during divided attention are a weighted linear combination of the responses during search for each target individually. Furthermore, this combination is biased by the intrinsic selectivity of cortical regions. Yet, it is unknown whether attentional modulations of semantic representations of cluttered and dynamic natural scenes are consistent with this hypothesis. Here, we investigated whether BC accounts for semantic representation during natural category-based visual search. Human subjects viewed natural movies, and their whole-brain BOLD responses were recorded while they attended to \"humans\", \"vehicles\" (i.e. single-target attention tasks), or \"both humans and vehicles\" (i.e. divided attention) in separate runs. We computed a voxelwise linearity index to assess whether semantic representation during divided attention can be modeled as a weighted combination of representations during the two single-target attention tasks. We then examined the bias in weights of this linear combination across cortical ROIs. We find that semantic representations during divided attention are linear to a substantial degree, and that they are biased toward the preferred target in category-selective areas across ventral temporal cortex. Taken together, these results suggest that the biased competition hypothesis is a compelling account for attentional modulations of semantic representation across cortex.\n\nSignificance Statement\n\nNatural vision is a complex task that involves splitting attention between multiple search targets. According to the biased competition hypothesis (BC), limited representational capacity of the cortex inevitably leads to a competition among representation of these targets and the competition is biased by intrinsic selectivity of cortical areas. Here we examined BC for semantic representation of hundreds of object and action categories in natural movies. We observed that: 1) semantic representation during simultaneous attention to two object categories is a weighted linear combination of representations during attention to each of them alone, and 2) the linear combination is biased toward semantic representation of the preferred object category in strongly category-selective areas. These findings suggest BC as a compelling account for attentional modulations of semantic representation across cortex in natural vision.