Evidence map›Paper›PMID 42651451›Full record

ArticleBehavioral sciences (Basel, Switzerland)2026

A Mouse-Tracking Paradigm for Value-Driven Attentional Capture.

Yitong Chen, Fengji Geng, Mengyuan Gong, Hui Zhou, Yuzheng Hu

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Yitong ChenDepartment of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0002-1201-5141
Fengji GengDepartment of Curriculum and Learning Sciences, Zhejiang University, Hangzhou 310058, China.
Mengyuan GongDepartment of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China.
Hui ZhouDepartment of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China.
Yuzheng HuDepartment of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0003-3427-0650

Funding

National Natural Science Foundation of China 81971245National Natural Science Foundation of China 82471511
6 · The paper itself

Abstract

Reward learning is fundamental to adaptive behavior and exhibits substantial individual variability linked to addiction and other psychiatric conditions. Traditional value-driven attentional capture (VDAC) paradigms rely mainly on reaction time (RT) and accuracy, but it remains unknown whether engaging motor control processes could enhance sensitivity for detecting individual differences in reward-induced attentional biases. We developed a novel mouse-tracking VDAC paradigm that engages motor control processes. Two independent samples (n1 = 45, n2 = 59) completed the task and a battery of reward-related psychological scales (reward sensitivity, impulsivity, self-control, digital addiction tendency). A new index, maximum deviation (MD) of mouse trajectories, quantified how reward history biases attention and motor response. The paradigm replicated the classic RT-based VDAC effect. Trajectory-based measures revealed bidirectional effects: high-value distractors increased attraction and reduced active avoidance. The relative angle modulated VDAC strength, with the largest effect at 120°. ΔMD (high-value vs. absent) showed significant positive correlations with reward sensitivity, impulsivity, and addiction tendency, and negative correlations with self-control in both samples, whereas ΔRT showed no significant correlations. The consistent pattern across two independent samples suggests that mouse-tracking provides a complementary, process-sensitive index for detecting individual differences in reward-driven attention. This paradigm may serve as a useful tool for investigating cognitive markers of vulnerability to reward-related disorders, including addiction.

Indexed as

addiction tendencyindividual differencemouse-trackingreward learningreward sensitivityvalue-driven attentional capture

Identifiers

PMID42651451
PMCPMC13509603

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.