Characterizing visual performance fields: effects of transient covert attention, spatial frequency, eccentricity, task and set size

Carrasco, Marisa; Talgar, Cigdem P.; Cameron, E. Leslie

doi:10.1163/15685680152692015

Cited by 293 publications

(382 citation statements)

References 38 publications

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“…This effect was observed in both hemifields. This type of visual field asymmetry has been reported previously (19)(20)(21)(22). As a result, two probe locations, even adjacent, might present different report probabilities (i.e., P1 > P2) due to a position bias, rather than the kind of attentional effect under investigation here (one might speculate as to whether the position bias is, in turn, due to an attentional effect or some other spatially variable aspect of visual processing, but this question is beyond the scope of this investigation).…”

Section: Resultssupporting

confidence: 83%

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Attention searches nonuniformly in space and in time

Dugué

McLelland

Lajous

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Difficult search tasks are known to involve attentional resources, but the spatiotemporal behavior of attention remains unknown. Are multiple search targets processed in sequence or in parallel? We developed an innovative methodology to solve this notoriously difficult problem. Observers performed a difficult search task during which two probes were flashed at varying delays. Performance in reporting probes at each location was considered a measure of attentional deployment. By solving a second-degree equation, we determined the probability of probe report at the most and least attended probe locations on each trial. Because these values differed significantly, we conclude that attention was focused on one stimulus or subgroup of stimuli at a time, and not divided uniformly among all search stimuli. Furthermore, this deployment was modulated periodically over time at ∼7 Hz. These results provide evidence for a nonuniform spatiotemporal deployment of attention during difficult search.V isual search tasks (e.g., to find a target embedded among similar looking distracters) have long been used to investigate the deployment of attention (1-6). Certain tasks are performed "efficiently," in which case the search time and accuracy are independent of the number of distracters. Other tasks are more difficult, or "inefficient," characterized by an increase in reaction times (RTs) and/or a decrease in accuracy with the number of distracting elements, a result typically attributed to the need to allocate attention (4-7). For more than 30 y now, since the pioneering study of Treisman and Gelade in 1980 (4), two opposing theories of attention deployment during difficult search have persisted. Attention could either be allocated nonuniformly to the stimuli, such that in some cases it would switch sequentially from one stimulus (or group of stimuli) to another (4, 5), or be divided uniformly to process all of the stimuli in parallel, but with a drop in efficiency for increasing distractor numbers (2,(8)(9)(10). To date, neither of these two theories has been unequivocally disproved. Overall performance in the search task itself is not directly informative, because both theories predict an increase in RT with the number of distracters (11,12). One alternative is to use briefly flashed probes to test for the deployment of attention at a specific location and time. With two probes, it should be possible to differentiate parallel and sequential processing strategies: The strict parallel theory predicts that both probes should receive equal amounts of attention, whereas the sequential theory predicts that one of the probes will receive more attention than the other. Of course, the most attended probe may not be the same one on every trial, but a simple mathematical manipulation, the solution of a quadratic equation, allows us to access this information despite the need to average performance over trials.In recent years, a second, related, debate has arisen in the literature concerning the temporal behavior of attention. It has been p...

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Section: Resultssupporting

confidence: 83%

“…A study in the macaque monkey showed that neurons in the frontal eye field respond sequentially to the items of a difficult search task, at a frequency of [18][19][20][21][22][23][24][25]. This finding was the first strong evidence of a link between attentional periodicity and sequential processing in visual search.…”

Section: Discussionmentioning

confidence: 91%

Attention searches nonuniformly in space and in time

Dugué

McLelland

Lajous

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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“…This lower intensity might be simply explained by the distance from the source to the electrodes, which would be shorter for area V3 compared to VP. However, some evidence suggests a real advantage for the lower hemifield, both in the strength of electrophysiological (Portin et al, 1999) and behavioral (Carrasco et al, 2001;Levine and McAnany, 2005;Liu et al, 2006) responses. This functional benefit might be explained by the anatomical overrepresentation of the lower hemifield in the retina (Perry and Cowey, 1985), the lateral geniculate nucleus (Connolly and Van Essen, 1984) and V1 .…”

Section: P1-n1 Complexmentioning

confidence: 99%

Retinotopic mapping of visual event-related potentials

Capilla

Melcón

Kessel

et al. 2016

Biological Psychology

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Esta es la versión de autor del artículo publicado en: This is an author produced version of a paper published in:Biological Psychology 118 (2016) ABSTRACTVisual stimulation is frequently employed in electroencephalographic (EEG) research.However, despite its widespread use, no studies have thoroughly evaluated how the morphology of the visual event-related potentials (ERPs) varies according to the spatial location of stimuli. Hence, the purpose of this study was to perform a detailed retinotopic mapping of visual ERPs. We recorded EEG activity while participants were visually stimulated with 60 pattern-reversing checkerboards placed at different polar angles and eccentricities. Our results show five pattern-reversal ERP components. C1and C2 components inverted polarity between the upper and lower hemifields. P1 and N1 showed higher amplitudes and shorter latencies to stimuli located in the contralateral lower quadrant. In contrast, P2 amplitude was enhanced and its latency was reduced by stimuli presented in the periphery of the upper hemifield. The retinotopic maps presented here could serve as a guide for selecting optimal visuo-spatial locations in future ERP studies. HIGHLIGHTS Extensive and multichannel retinotopic mapping of major visual ERP components. C1 and C2 components showed inverted polarity for upper and lower hemifields. P1 and N1 components were larger when the contralateral lower field was stimulated. P2 showed higher amplitude and shorter latency for peripheral upper field stimuli. Present results can be used to select optimal stimulus locations in ERP designs.

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“…Using an orientation-defined target we recently encountered evidence seemingly at odds with both Korte's and Kooi and colleagues' ideas (Solomon, Felisberti & Morgan, 2004). In this now-popular paradigm (Baldassi & Burr, 2000, Cameron, Tai, Eckstein & Carrasco, 2004, Carrasco, Talgar & Cameron, 2001, Felisberti & Morgan, 2001, Morgan, Ward & Castet, 1998 observers must identify the orientation (as clockwise or anticlockwise of some reference orientation, usually vertical or horizontal) of a parafoveally presented Gabor target, when flanked by iso-eccentric Gabor distractors. We found that orientation identification was most difficult when distractor and target orientations differed by 22.5 -45 degrees (Solomon et al, 2004), contrary to the expectation that target salience would counteract crowding.…”

Section: Introductionmentioning

confidence: 99%

The Role of Target Salience in Crowding

2005

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We studied 'crowding' in the parafovea using orientation identification of a Gabor target as the task, and flanking Gabors on an iso-eccentric circle as distractors.Orientation-discrimination thresholds were raised by nearby flanking distractors. This 'crowding' effect was increased by the number of distractors and decreased by the spatial separation between target and distractors. Crowding was greatest when the target was in the centre of the distractor array and smallest when the target was on the edge of the array. A cue indicating the position of the target improved performance when the position was otherwise unknown and the spatial separation between target and distractors was large, but the cue had no significant effect when separation was small.Increasing the contrast of the target relative to the distractors reduced crowding, but targets of smaller contrast than the distractors are even harder to identify than those of the same contrast. Putting the target and distractors in different depth planes decreased crowding for some observers, but there were qualitative individual differences. A large (e.g. 45 deg) difference in orientation between target and distractors caused the target to 'pop out' in a presence/absence task, despite the evidence from other studies that crowding is still found in these conditions. We conclude that salience has--at best--modest effects on crowding.

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Characterizing visual performance fields: effects of transient covert attention, spatial frequency, eccentricity, task and set size

Cited by 293 publications

References 38 publications

Attention searches nonuniformly in space and in time

Attention searches nonuniformly in space and in time

Retinotopic mapping of visual event-related potentials

The Role of Target Salience in Crowding

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