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Lauren Williams, Trafton Drew; Electrophysiological Correlates of Individual Differences in Visual Search. Journal of Vision 2017;17(10):1140. doi: https://doi.org/10.1167/17.10.1140.
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© ARVO (1962-2015); The Authors (2016-present)
Which ERP components predict success in visual search? Despite decades of groundbreaking ERP studies in visual search, little is known about the electrophysiological correlates that predict individual differences in search performance. The aim of the current study was to determine which ERP components differentiate the best performing searchers. Participants (n=38) searched for grayscale real world objects in a lateralized circular display. The search array consisted of two, four, or six objects positioned on each side of the fixation cross. On each trial, a novel target was presented for 500 ms followed by an 800-1000 ms cue that indicated which side of the display to search for the object. The search array was presented until the participant indicated if the target was present or absent. The data was divided into the fastest and slowest searchers using a median split of response time. ERP waveforms were time-locked to the onset of the search array. No differences were found in early sensory components. The earliest component that differentiated the two groups was the n2pc, which is thought to reflect the deployment of attention (Woodman & Luck, 1999). In addition, contralateral delay activity (CDA) was greater in amplitude for the high performing group. Contrary to prior research using consistent targets across trials (Clark, et al., 2015; Luria & Vogel, 2011), these results indicate that greater reliance on WM during search predicts faster response times. Together, these results suggest that individual differences in search performance for a target that changes on each trial can largely be attributed to differences in attentional deployment and reliance on WM. Thus, it appears that the predictability of target identity may be an important factor in determining which individuals will excel at a given search task.
Meeting abstract presented at VSS 2017
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