Feature-based attention has a spatial gradient

Journal of Vision(2023)

引用 0|浏览1
暂无评分
摘要
Selective attention to a particular feature is known to be spatially global, with processing of that feature enhanced throughout the visual field. Theoretical accounts of feature-based attention assume that this spread of attentional enhancement is uniform across space. However, underlying empirical studies of spatial profile of feature-based attention have almost exclusively used isoeccentric locations to control for variability in visual processing across retinal eccentricities. Here we used EEG and frequency-tagged stimuli to measure the spread of feature-based attention across a wide range of eccentricities. Participants (n=29) were presented with a stimulus comprised of one central and two peripheral apertures filled with superimposed sets of red and blue randomly moving dots. On each trial they were cued to attend to either red or blue color. Their task was to detect brief episodes of coherent motion in the dots of the cued color in the central aperture. Peripheral apertures were presented simultaneously to the central one in one of three eccentricity conditions: close (spanning 5° to 9° degrees of visual angle), mid (12° to 21°) or far (22° to 38°) with the size of the dots progressively increasing. Attentional selection was measured through steady-state visual evoked potentials (SSVEPs) elicited by the flickering stimuli at each of the locations. The estimates of attentional modulation were then individually adjusted to account for signal-to-noise ratio (SNR) decline of SSVEPs between fovea and periphery. By magnifying stimuli sizes with eccentricity and by using SNR-corrected SSVEP amplitudes we were able to control for variations in visual processing across non-isoeccentric locations. SSVEP modulations analysed as a function of stimulus location showed robust attentional enhancement which, however, decreased with increasing eccentricity. These results suggest that the spread of feature-based attention across the visual field is not uniform and instead has a spatial gradient.
更多
查看译文
关键词
attention,spatial gradient,feature-based
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要