Sentence examples for target faces from inspiring English sources

Participants were faster to detect exemplar versus category human target faces, but were faster to detect category versus exemplar non-human target faces (Fig. 1B).

Target faces were either one specific face (exemplar search) or a given category of faces (category search).

But the subjects favored morphed faces halfway between their two previous target faces over the previously seen face on its own.

Target faces with either neutral or fearful emotion were briefly primed by either neutral or fearful faces, or by blank ovals.

Participants viewed angry and happy target faces or neutral distractors for 18, 35, or 53 ms subsequently masked by neutral faces.

A person who wants a password picks out five or more faces; then, to log on, he identifies each of the target faces as it pops up in a grid with eight decoy faces.

Consistent with prior N2pc results23, we hypothesized that target location would be classified from the electrophysiological signal with higher accuracy for exemplar-level than category-level human target faces within the N2pc time window (200 300 ms).

In addition, we aimed to test whether target location would be classified with higher accuracy for category-level vs. exemplar-level non-human target faces, as suggested by the behavioural results, or vice-versa, as suggested by the ERP results.

Multivariate pattern analyses (MVPA) of electrophysiological data during a visual search task suggest similar speed and strength of target selection for human and non-human target faces, consistent with earlier ERP analyses of a specific component (i.e. N2pc).

Fixation event-related potentials (fERPs) to target and distractor stimuli showed the emergence of robust sensory components associated with the perception of stimuli and cognitive components associated with the detection of target faces.

However, the relatively proportion of target and non-target faces captured during operations varies over time.