Guang Zhao

Dr. Guang Zhao


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 August 2024 in Brain Sciences
Verified
Journal Article
Open access
PDF file
GZGuang Zhao
Guang Zhao
RWRongtao Wu
Rongtao Wu
HWHuijun Wang
Huijun Wang
JCJiahuan Chen
Jiahuan Chen
SLShiyi Li
Shiyi Li
HSHong-jin Sun
Hong-jin Sun
Selection history is widely accepted as a vital source in attention control. Reward history indicates that a learned association captures attention even when the reward is no longer presented, while statistical learning indicates that a learned probability exerts its influence on attentional control (facilitation or inhibition). Existing research has shown that the effects of the reward history and statistical learning are additive, suggesting that these two components influence attention priority through different pathways. In the current study, leveraging the temporal resolution advantages of EEG, we explored whether these two components represent independent sources of attentional bias. The results revealed faster responses to the target at the high-probability location compared to low-probability locations. Both the target and distractor at high-probability locations elicited larger early Pd (50–150 ms) and Pd (150–250 ms) components. The reward distractor slowed the target search and elicited a larger N2pc (180–350 ms). Further, no interaction between statistical learning and the reward history was observed in RTs or N2pc. The different types of temporal progression in attention control indicate that statistical learning and the reward history independently modulate the attention priority map.

21 January 2025 in Brain Sciences
Verified
Journal Article
Open access
PDF file
GZGuang Zhao
Guang Zhao
HWHuijun Wang
Huijun Wang
RWRongtao Wu
Rongtao Wu
ZZZixin Zhao
Zixin Zhao
SLShiyi Li
Shiyi Li
HSHong-jin Sun
Hong-jin Sun
Background/Objectives: Switching between different tasks incurs switch costs. Previous research has demonstrated that rewards can enhance performance in cognitive tasks. However, prior studies have primarily focused on the overall improvement in cognitive task performance, with limited research on how different types of rewards function under various task conditions. This study aims to investigate the distinct effects of immediate and delayed rewards on cognitive task performance in different task conditions (repeated trials and task-switching trials) and to explore the underlying neural mechanisms, particularly focusing on how rewards influence attention allocation during the concurrent processing of multiple cues. Methods: This study recruited 27 college students (average age 19 years old, 10 males and 17 females). A cue-based task-switching paradigm incorporating immediate and delayed rewards was employed. The study examined the effects of immediate and delayed rewards on cognitive task performance in repeated trials and task-switching trials. Event-related potentials (ERPs) were recorded to investigate the neural mechanisms underlying reward effects on attention allocation. Results: Behavioral results indicated that immediate rewards significantly enhanced performance in repeated trials compared to delayed rewards. In contrast, no significant difference between immediate and delayed rewards was observed in task-switching trials. ERP results showed that immediate rewards induced a larger P300 amplitude than delayed rewards under the task repetition condition. No P300 difference was found between immediate and delayed rewards under the task-switching condition. Conclusions: The findings suggest that rewards enhance task performance by optimizing the allocation of attention to the ongoing task when multiple cues are processed concurrently. When additional resources are required to process task-related cues, there may be insufficient remaining capacity to effectively process reward cues, which could be essential for the optimal completion of the task. These results support the Expected Value of Control (EVC) theory in task-switching scenarios.