Enhanced spatial focusing increases feature-based selection in unattended locations

Abstract

Attention is a multifaceted phenomenon, which operates on features (e.g., colour or motion) and over space. A fundamental question is whether the attentional selection of features is confined to the spatially-attended location or operates independently across the entire visual field (global feature-based attention, GFBA). Studies providing evidence for GFBA often employ feature probes presented at spatially unattended locations, which elicit enhanced brain responses when they match a currently-attended target feature. However, the validity of this interpretation relies on consistent spatial focusing onto the target. If the probe were to temporarily attract spatial attention, the reported effects could reflect transient spatial selection processes, rather than GFBA. Here, using magnetoencephalographic recordings (MEG) in humans, we manipulate the strength and consistency of spatial focusing to the target by increasing the target discrimination difficulty (Experiment 1), and by demarcating the upcoming target’s location with a placeholder (Experiment 2), to see if GFBA effects are preserved. We observe that motivating stronger spatial focusing to the target did not diminish the effects of GFBA. Instead, aiding spatial pre-focusing with a placeholder enhanced the feature response at unattended locations. Our findings confirm that feature selection effects measured with spatially-unattended probes reflect a true location-independent neural bias.

Attention expedites target selection by prioritizing the neural processing of distractor features

“…The modulation observed in the N1/N2 time range (here referred to as "late" effect) is well in line with previous literature, where such negative enhancements have been observed for the attended color (Bartsch et al, 2015(Bartsch et al, , 2017(Bartsch et al, , 2018. Also fitting previous observations, this effect is smaller and more transient for a color that is part of the attentional set but not discriminated on a given trial (here: DC) (cf.…”

“…McAdams & Maunsell, 2000;Carrie J. McAdams & Maunsell, 1999;Treue & Martínez Trujillo, 1999) Trujillo, 1999). Consistently, EEG/MEG experiments in humans revealed that GFBA is associated with gain enhancements of the neural population response for the attended feature, starting around 150-200ms after stimulation onset in extrastriate visual cortex areas (Bartsch et al, 2015(Bartsch et al, , 2017(Bartsch et al, , 2018Bondarenko et al, 2012;Garcia-Lazaro et al, 2016;Hopf et al, 2015). It is reasonable to assume that efficient target identification will depend on how rapidly this global biasing can be build up for the attended feature.…”

“…According to previous work (Bartsch et al, 2015(Bartsch et al, , 2017(Bartsch et al, , 2018Bondarenko et al, 2012), we expected to find a negative voltage enhancement for probes containing attended compared to unattended colors at parieto-occipital electrode sites contralateral to the probe location (here: signal averaged across PO3 and PO7). Specifically, when subjects performed the color task, we should observe modulations for both target color alternatives (PC and DC are both part of the attentional set).…”

Parallel attentional facilitation of features and objects in early visual cortex

“…Feature‐based attention prioritizes perceptual processing of stimuli that contain a task‐relevant feature such as a specific color, orientation, or direction of motion, or a combination of such features (Baldassi & Verghese, ; Hayden & Gallant, ; Martinez‐Trujillo & Treue, ; Reynolds & Chelazzi, ). Importantly, feature‐based selection typically spreads across the visual field even to the irrelevant or to‐be‐ignored locations (Andersen, Hillyard, & Müller, ; Bartsch, Donohue, Strumpf, Schoenfeld, & Hopf, ; Liu & Mance, ; Rossi & Paradiso, ; Sàenz, Buraĉas, & Boynton, ). This global selection can benefit certain tasks such as visual search (Treisman, ; Wolfe, ) by restricting the search to a subset of objects containing the attended feature, or it can impede performance in cases when the task‐relevant feature differs across locations (Andersen et al, ; Sàenz, Buraĉas, & Boynton, ).…”

Topics and trends in artificial intelligence assisted human brain research

“…For Virus & Pathology, Hiar et al [74] assessed epidemiological, clinical, and laboratory features of enterovirus infections of central nervous system in children younger than 15 years. For Attention & Vision, with the use of human MEG, Bartsch et al [75] examined whether effects of global feature-based attention were preserved by manipulating the strength and consistency of spatial focusing to the target. For Gene, with the use of unsupervised hierarchical clustering, Perez-Magan [76] identified gene expression profiles and candidate markers related to original and recurrent meningiomas.…”