The Neural Dynamics of Attentional Selection in Natural Scenes

Abstract

The human visual system can only represent a small subset of the many objects present in cluttered scenes at any given time, such that objects compete for representation. Despite these processing limitations, the detection of object categories in cluttered natural scenes is remarkably rapid. How does the brain efficiently select goal-relevant objects from cluttered scenes? In the present study, we used multivariate decoding of magneto-encephalography (MEG) data to track the neural representation of within-scene objects as a function of top-down attentional set. Participants detected categorical targets (cars or people) in natural scenes. The presence of these categories within a scene was decoded from MEG sensor patterns by training linear classifiers on differentiating cars and people in isolation and testing these classifiers on scenes containing one of the two categories. The presence of a specific category in a scene could be reliably decoded from MEG response patterns as early as 160 ms, despite substantial scene clutter and variation in the visual appearance of each category. Strikingly, we find that these early categorical representations fully depend on the match between visual input and top-down attentional set: only objects that matched the current attentional set were processed to the category level within the first 200 ms after scene onset. A sensor-space searchlight analysis revealed that this early attention bias was localized to lateral occipitotemporal cortex, reflecting top-down modulation of visual processing. These results show that attention quickly resolves competition between objects in cluttered natural scenes, allowing for the rapid neural representation of goal-relevant objects.

The time-course of component processes of selective attention

“…Distinction between an early, parallel processing stage and a later capacity-limited stage is central to most models of attention (Duncan, 1980;Treisman & Gelade, 1980). Target decoding in 3-item displays peaked at 252 ms with first significance at 196 ms, similar to attentional modulation of stimulus category processing in cluttered scenes observed from 180 ms (Kaiser et al, 2016), and to demonstration of feature-binding during integrated competition (Schoenfeld et al 2003). The later stage indexed by single-item decoding may correspond to capacity-limited individuation of the integrated target object, allowing its bound properties to become accessible for further processing and goal-directed action (Duncan, 1980;Bichot et al, 2005;Mitchell and Cusack 2008;Christie et al, 2015), in this case likely including the brightness judgement.…”

Preparatory attention in visual cortex

“…1,12 In this way, preparatory attention would bias visual processing in favor of objects sharing this attribute once the scene appears. 13 The existence of preparatory attention-related activity in the visual cortex has been relatively well established and accepted in doi: 10.1111/nyas.13320 the domain of spatial attention: focusing attention on a location in space is accompanied by increased baseline activity in parts of the visual cortex that are visually responsive to input at the attended location. 14,15 In daily life, however, our goals are typically related to nonspatial attributes, such as when looking out for cars or when searching for our keys.…”

MEG sensor patterns reflect perceptual but not categorical similarity of animate and inanimate objects

“…Replicating previous reports, MEG sensor patterns could be used to accurately decode individual objects (Carlson et al, 2011;Carlson et al, 2013;van de Nieuwenhuijzen et al, 2013;Cichy et al, 2014;Isik et al, 2014;Clarke et al, 2015;Ritchie et al, 2015;Coggan et al, 2016;Kaiser et al, 2016a). Using representational similarity analysis, we then related MEG neural similarity to the objects' perceptual and categorical similarity.…”