Tracking feature-based attention

Abstract

Objective. Feature-based attention (FBA) helps one detect objects with a particular color, motion, or orientation. FBA works globally; the attended feature is enhanced at all positions in the visual field. This global property of FBA lets one use stimuli presented in the peripheral visual field to track attention in a task presented centrally. The present study explores the use of SSVEPs, generated by flicker presented peripherally, to track attention in a visual search task presented centrally. We evaluate whether this use of EEG to track FBA is robust enough to track attention when performing visual search within a dynamic 3D environment presented with a head-mounted display (HMD). Approach. Observers first performed a visual search task presented in the central visual field within a stationary virtual environment. The purpose of this first experiment was to establish whether flicker presented peripherally can produce SSVEPs during HMD use. The second experiment placed observers in a dynamic virtual environment in which observers moved around a racetrack. Peripheral flicker was again used to track attention to the color of the target in the visual search task. Main results. SSVEPs produced by flicker in the peripheral visual field are influenced strongly by attention in observers with stationary or moving viewpoints. Offline classification results show that one can track an observer’s attended color, which suggests that these methods may provide a viable means for tracking FBA in a real-time task. Significance. Current FBA and brain–computer interface (BCI) studies primarily use foveal flicker to produce SSVEP responses. The present study’s finding that one can use peripherally-presented flicker to track attention in dynamic virtual environments promises a more flexible and practical approach to BCIs based on FBA.

Steady-state visual evoked potential and its applications in studying visual selective attention

“…这些发现引领了随后一系 列的研究 [63~65] . 有趣的是, 最近研究发现, 在虚拟的三 维空间中进行基于特征的目标搜索时, 空间注意焦点 之外的目标特征也有更高的SSVEP的激活 [66] . 可以说,…”

Steady-State Visually Evoked Potentials and Feature-based Attention: Preregistered Null Results and a Focused Review of Methodological Considerations

“…Finally, in the central task with peripheral flicker (Appendix S), participants performed a task near fixation (e.g., visual search), and feature-based attention was measured indirectly via a peripheral flickering stimulus (i.e., this design took advantage of the spatially global spread of feature-based attention; White & Carrasco, 2011;Sàenz, Buraĉas, & Boynton, 2002. Studies using a central task with peripheral flicker include Chu and D'Zmura (2019); Jiang, Wu, and Gao (2017);Painter, Dux, and Mattingley (2015); and Painter, Dux, Travis, and Mattingley (2014).…”

“…Although some studies have argued that feature-based attention effects do not qualitatively appear to vary with frequency (Steinhauser & Andersen, 2019;, the vast majority of reviewed studies only reported statistical significance of an overall attention effect collapsed across frequencies. Only a handful of studies have reported statistical significance of individual frequencies (e.g., Chu & D'Zmura, 2019;Steinhauser & Andersen, 2019;Painter et al, 2014;Quigley & Müller, 2014). As such, future work is needed to systematically investigate the effect of frequency choice on feature-based attention effects, particularly for frequencies > 20 Hz.…”

Steady-state visually evoked potentials and feature-based attention: Pre-registered null results and a focused review of methodological considerations

“…Studies using a hemi-field flicker task include: (Adamian et al, 2019;Andersen et al, 2013;Andersen, Fuchs, et al, 2011;Störmer & Alvarez, 2014) Finally, in the central task with peripheral flicker, participants performed a task near fixation (e.g., visual search), and feature-based attention was measured indirectly via a peripheral flickering stimulus (i.e., this design took advantage of the spatially global spread of feature-based attention, Sàenz et al, 2002Sàenz et al, , 2003White & Carrasco, 2011). Studies using a central task with peripheral flicker include: (Chu & D'Zmura, 2019;Jiang et al, 2017;Painter et al, 2014Painter et al, , 2015.…”

“…Although some studies have argued that feature-based attention effects do not qualitatively appear to vary with frequency Steinhauser & Andersen, 2019), the vast majority of reviewed studies only reported statistical significance of an overall attention effect collapsed across frequencies. Only a handful studies have reported statistical significance of individual frequencies (e.g., Chu & D'Zmura, 2019;Painter et al, 2014;Quigley & Müller, 2014;Steinhauser & Andersen, 2019). As such, future work is needed to systematically investigate the effect of frequency choice on feature-based attention effects, particularly for frequencies >20 Hz.…”