Neural representation of object-specific attentional priority

Abstract

Humans can flexibly select locations, features, or objects in a visual scene for prioritized processing. Although it is relatively straightforward to manipulate location- and feature-based attention, it is difficult to isolate object-based selection. Because objects are always composed of features, studies of object-based selection can often be interpreted as the selection of a combination of locations and features. Here we examined the neural representation of attentional priority in a paradigm that isolated object-based selection. Participants viewed two superimposed gratings that continuously changed their color, orientation, and spatial frequency, such that the gratings traversed the same exact feature values within a trial. Participants were cued at the beginning of each trial to attend to one or the other grating to detect a brief luminance increment, while their brain activity was measured with fMRI. Using multi-voxel pattern analysis, we were able to decode the attended grating in a set of frontoparietal areas, including anterior intraparietal sulcus (IPS), frontal eye field (FEF), and inferior frontal junction (IFJ). Thus, a perceptually varying object can be represented by patterned neural activity in these frontoparietal areas. We suggest that these areas can encode attentional priority for abstract, high-level objects independent of their locations and features.

Biased neural representation of feature-based attention in the human brain

“…In contrast, the attended feature can be reliably decoded from distributed activity patterns in both visual and frontoparietal areas ( Fig 2F). We obtained similar results from the other experiments; details can be found in previous publications (Liu et al, 2011;Liu, 2016;Jigo et al, 2018, Gong andLiu, 2019). In total, the dataset contained BOLD data from 48 subjects, each containing 22 brain areas (11 areas per hemisphere).…”

“…We re-analyzed data from five previously published fMRI experiments (Liu et al, 2011;Liu, 2016;Jigo et al, 2018;Gong and Liu, 2019). The details of the methods can be found in previous publications, so only an abbreviated description is provided here.…”

“…In the fourth experiment, twelve subjects attended to a linear motion direction in a superimposed up-left/up-right moving dot field (Gong and Liu, 2019). In the fifth experiment (Liu, 2016), twelve subjects attended to a dynamic object in a superimposed display containing two Gabor patches (Object 1 or Object 2) that continuously changed their features in multiple dimensions (color, orientation, and spatial frequency). Data for each subject were collected in a single 1.5 -2 hr scanning session.…”

Left-Hemispheric Asymmetry for Object-Based Attention: an ERP Study

“…Increased phase coherence was also visible in the higher gamma range. The phase lag (20 ms) between frontal and temporal areas indicated the IFJ as a potentially key region for top-down modulation of object-based (and feature-based) attention [18,19]. Using a different approach, Valdes-Sosa and colleagues [20] showed evidence for non-spatial, object-based attention selection at an early stage of vision.…”

Attentional Weighting in the Face Processing Network: A Magnetic Response Image-guided Magnetoencephalography Study Using Multiple Cyclic Entrainments

“…In a prototypical Posner cueing paradigm, participants are instructed to fixate at a central point on the screen and to attend covertly to either side of the fixation point to detect the temporal onset of a target stimulus. There are corresponding variants of the Posner cueing paradigm for other, nonspatial attentional sets such as visual features (Störmer & Alvarez, 2014;Andersen, Fuchs, & Müller, 2011;Zhang & Luck, 2009;Liu, Stevens, & Carrasco, 2007;Maunsell & Treue, 2006;Müller et al, 2006;Hopf, Boelmans, Schoenfeld, Luck, & Heinze, 2004;Saenz, Buracas, & Boynton, 2003) and objects (Marinato & Baldauf, 2019;Kim, Tsai, Ojemann, & Verghese, 2017;Zhang, Mlynaryk, Japee, & Ungerleider, 2017;Liu, 2016;Baldauf & Desimone, 2014), all of which exhibit reliable attentional facilitation effects, that is, cue validity effects. The robust finding of such "cue validity effects" in our study indicates that attention was indeed covertly oriented to the cued aspects of the face stimulus.…”