Waxun Su

Ms. Waxun Su

orcid

Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

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

Representative Publications

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1 November 2025 in Journal of Psychiatric Research
Verified
Journal Article
Closed access
WSWaxun Su
Waxun Su
XLXiao Lin
Xiao Lin
WLWeijian Liu
Weijian Liu
TLTak Kwan Lam
Tak Kwan Lam
PLPeng Li
Peng Li
QWQiandong Wang
Qiandong Wang

8 November 2023 in International Journal of Behavioral Development
Verified
Journal Article
Closed access
WSWaxun Su
Waxun Su
TLTak Kwan Lam
Tak Kwan Lam
ZYZhennan Yi
Zhennan Yi
NANigela Ahemaitijiang
Nigela Ahemaitijiang
ZHZhuo Rachel Han
Zhuo Rachel Han
QWQiandong Wang
Qiandong Wang
Affect-biased attention is an important predictive factor of children’s early socio-emotional development, possibly shaped by the family environment. Our study aimed to reveal children’s temporal dynamic patterns of affect-biased attention by looking at time series of attention to emotional faces, individual differences in temporal dynamics, and their relations with parenting practices. Sixty Chinese children (27 girls; mean age: 7.92 ± 1.09 years) viewed emotional–neutral face pairs (angry, sad, and happy) for 3,000 ms while their eye movements were recorded. First, results showed that overall looking time rather than manual reaction time revealed affect-biased attention: children looked more at angry and happy faces than neutral faces, although they looked at sad and neutral faces approximately the same amount of time. Temporal course analysis revealed further differences in visual attention to emotional faces: attention bias to emotional faces emerged early after the stimuli onset (before 400 ms), even for sad faces. This bias did not hold for the entire stimulus presentation time, and only the attention bias to happy faces appeared again in the later period. Second, we applied a data-driven cluster approach to the time series of attention to emotional faces and revealed three subgroups of dynamic affect-biased attention. Finally, the machine learning method revealed that positive parenting was related to the temporal dynamic patterns of children’s attention to sad faces.

Verified
Journal Article
Open access
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HWHanliang Wei
Hanliang Wei
TLTak Kwan Lam
Tak Kwan Lam
WLWei-Jian Liu
Wei-Jian Liu
WSWaxun Su
Waxun Su
ZWZheng Wang
Zheng Wang
PLPeng Li
Peng Li
Major depressive disorder (MDD) represents a prevalent mental health condition characterized by prominent attentional biases, particularly toward negative stimuli. While extensive research has established the significance of negative attentional bias in depression, critical gaps remain in understanding the temporal dynamics and valence-specificity of these biases. This study employed eye-tracking technology to systematically examine the attentional processing of emotional faces (happy, fearful, sad) in MDD patients (n = 61) versus healthy controls (HC, n = 47), assessing both the initial orientation (initial gaze preference) and sustained attention (first dwell time). Key findings revealed the following: (1) while both groups showed an initial vigilance toward threatening faces (fearful/sad), only MDD patients displayed an additional attentional capture by happy faces; (2) a significant emotion main effect (F (2, 216) = 10.19, p < 0.001) indicated a stronger initial orientation to fearful versus happy faces, with Bayesian analyses (BF < 0.3) confirming the absence of group differences; and (3) no group disparities emerged in sustained attentional maintenance (all ps > 0.05). These results challenge conventional negativity-focused models by demonstrating valence-specific early-stage abnormalities in MDD, suggesting that depressive attentional dysfunction may be most pronounced during initial automatic processing rather than later strategic stages. The findings advance the theoretical understanding of attentional bias in depression while highlighting the need for stage-specific intervention approaches.