Publications by authors named "Yongling Lin"

Navigating social environments is a fundamental challenge for the brain. It has been established that the brain solves this problem, in part, by representing social information in an agent-centric manner; knowledge about others' abilities or attitudes is tagged to individuals such as 'oneself' or the 'other'. This intuitive approach has informed the understanding of key nodes in the social parts of the brain, the dorsomedial prefrontal cortex (dmPFC) and the anterior cingulate cortex (ACC).

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The success of our actions often depends on what others are doing. How does the brain discern predictions of others' actions when situations are ambiguous? Recent work by Ma and colleagues suggests that the brain solves this problem by entertaining multiple predictions of others' actions, ranked by their likelihood.

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Human moral reactions to artificial intelligence (AI) agents' behavior constitute an important aspect of modern-day human-AI relationships. Although previous studies have mainly focused on autonomy ethics, this study investigates how individuals judge AI agents' violations of community ethics (including betrayals and subversions) compared with human violations. Participants' behavioral responses, event-related potentials (ERPs), and individual differences were assessed.

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Background: Maize is one of the world's most important crops, so its stable production and supply is crucial for food security and socioeconomic development. The cotton bollworm, Helicoverpa armigera (Hübner), is one of the major pests in maize. We evaluated the control effect of a bio-bait, an adult attractant, combined with insecticide, a 'toxicant-infused bait', on H.

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Reversal learning is a crucial aspect of behavioral flexibility that plays a significant role in environmental adaptation and development. While previous studies have established a link between anxiety and impaired reversal learning ability, the underlying mechanisms behind this association remain unclear. This study employed a probabilistic reversal learning task with electroencephalographic recording to investigate these mechanisms.

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The process of outcome evaluation effectively navigates subsequent choices in humans. However, it is largely unclear how people evaluate decision outcomes in a sequential scenario, as well as the neural mechanisms underlying this process. To address this research gap, the study employed a sequential decision task in which participants were required to make a series of choices in each trial, with the option to terminate their choices.

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To optimize our decisions, we may change our mind by utilizing social information. Here, we examined how changes of mind were modulated by Social Misalignment Sensitivity (SMS), egocentric tendency, and decision preferences in a decision-making paradigm including both risk and social information. Combining functional magnetic resonance imaging with computational modeling, we showed that both SMS and egocentric tendency modulated changes of mind under the influence of social information.

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Social misalignment occurs when a person's attitudes and opinions deviate from those of others. We investigated how individuals react to social misalignment in risky (outcome probabilities are known) or ambiguous (outcome probabilities are unknown) decision contexts. During each trial, participants played a forced-choice gamble, and they observed the decisions of four other players after they made a tentative decision, followed by an opportunity to keep or change their initial decision.

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Decision making is vital to human behavior and can be divided into multiple stages including option assessment, behavioral output, and feedback evaluation. Studying how people evaluate option characteristics in the option assessment stage would provide important knowledge on human decision making. Using the event-related potential (ERP) method, the present study investigated the neural mechanism of evaluating two types of option characteristics (i.

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Functional near-infrared spectroscopy (fNIRS) is a fast-developing non-invasive functional brain imaging technology widely used in cognitive neuroscience, clinical research and neural engineering. However, it is a challenge to effectively remove the global physiological noise in the fNIRS signal. The global physiological noise in fNIRS arises from multiple physiological origins in both superficial tissues and the brain.

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