本报讯（海河传媒中心记者张璐璐）北京时间7月23日晚，世界乒乓球职业大联盟（WTT）冠军赛布达佩斯站落幕。中国选手未能包揽冠军，王曼昱在女单决赛中以4比2力克队友王艺迪，夺得冠军，而林高远却在随后的男单决赛中浪费六个赛点，以3比4遭日本选手张本智和逆转，丢掉冠军。
与上周进行的WTT球星挑战赛不同，WTT冠军赛只设男、女单打项目比赛，且积分奖励丰厚。中国女单选手占据四强，最终王曼昱和王艺迪在分别淘汰陈梦和孙颖莎后进入了决赛这场中国选手的“内战”中。比赛一开始，双方就展开激烈对攻，王曼昱先声夺人，以11比9和11比4先赢两局。
Brain-reading AI model reveals how different brain regions are linked to cognitive functions. Photo: Courtesy of Lu Han
Chinese scientists have developed a “brain-reading” AI model that could help predict the risk of depression among adolescents up to four years in advance by analyzing how humans respond to facial expressions, a technology expected to inspire future development of embodied intelligent humanoids capable of perceiving human emotion and thoughts through nuanced facial cues.
WHO data show that around 332 million people worldwide have depression, about one-third of whom have treatment-resistant forms of the condition. In China, an estimated 95 million people suffer from depression, National Business Daily reported, citing statistics from the China Mental Health Survey.
Using data from a population-based longitudinal adolescent cohort recruited across several European countries, the research team led by Lu Han, assistant professor at the School of Artificial Intelligence, Shenzhen University, has built an AI model that predicted which 19-year-olds were more likely to develop depression at the age of 23. The predictions were backed up by an independent clinical cohort of individuals with depression. The team’s paper was published in the journal Science Advances this month.
According to Lu, the study used brain scans taken at age 19 to predict depression-related symptoms at age 23. The study focuses on adolescence because the transition from adolescence to early adulthood is a key developmental period when depressive symptoms can increase rapidly. The earlier risks are identified, the greater the opportunity for prevention, Lu told the Global Times on Monday, adding that the findings need to be further validated in middle-aged and older adults and across different ethnic groups in future research.
In this study, the researchers analyzed data from adolescents in the IMAGEN, a population-based longitudinal cohort recruited across several European countries. At age 19, participants underwent an fMRI emotional-face task, and their emotional symptoms were assessed using standardized questionnaires. Genetic data obtained from blood samples were also analyzed, and participants were followed up at age 23. The researchers examined whether neural representations of angry faces at age 19 were associated with emotional symptoms and could predict elevated emotional symptoms four years later.
According to Lu, people without depression can more easily distinguish emotional changes based on others’ facial expressions and respond accordingly – for example, responding with friendliness to a smiling expression. But people with depression cannot do this, and are more likely to assume people are angry with them.
A brain-aligned deep-learning model developed by Lu’s team suggested that those participants whose brains were less able to distinguish between different facial emotions and tended to perceive others as angry were more likely to develop symptoms of depression and anxiety in adulthood.
The hypothesis that adolescents at risk of depression may respond differently to other people’s facial expressions than those without such risk based on the negative information processing bias long observed in depression research: people at risk of depression are more likely to notice, interpret, or remember negative social information, Lu said.
The researchers focused on angry facial expressions because they signal social threat and rejection, which are closely linked to interpersonal difficulties and negativity bias associated with depression. They hope to further understand how this bias develops within the visual system.
Building on this, they created a deep learning model, which mimics how the brain processes visual information, to predict how the brain encodes abstract emotional concepts such as anger.
They found that 19-year-olds whose response to facial expressions was skewed in favour of negative emotions or memories were the most likely to develop some form of depression.
Based on these findings, Lu’s team then developed a marker that can identify possible warning signs.
According to Lu, the study found that the computational biomarker was linked to the depression-related variant rs11123030 and polygenic risk for depression, suggesting that genetic susceptibility may affect emotional perception. It also provided predictive information beyond family stress and socioeconomic factors, complementing rather than replacing environmental risk factors. Therefore, depression is neither purely genetic nor purely psychological, but a complex mental disorder arising from the interplay of genetic susceptibility, brain development, emotional and cognitive processes, and life experiences.
According to Lu, the study is also expected to advance AI by aligning deep neural networks with human brain activity and using parameter perturbations to probe neural mechanisms, allowing models to both predict and explain how biases may arise.
The findings suggest that future affective computing and embodied AI should go beyond simply labeling facial expressions, incorporating visual details while preventing prior assumptions from overriding real-time sensory input, Lu said, adding that the findings could provide valuable insights for developing more interpretable robotic perception systems that more closely emulate the way humans process emotions.
。第三局，王艺迪以11比9扳回一局。
B | 接下来的比赛双方战况胶着，王曼昱以11比7赢下第四局后，王艺迪在第五局同样以11比7还以颜色。第六局，王曼昱稳扎稳打，以11比7锁定整场比赛的胜利。“心态上比较坚决果断，技战术方面处理得不错是赢球的关键，这次在布达佩斯比赛对自己的锻炼非常大，收获很多。
C | ”王曼昱赛后表示。
D | 男单决赛则更具戏剧性。
E | 林高远是唯一进入四强的中国选手，比赛伊始林高远火力全开，以11比3、11比7和14比12连下三城。但随后他却突然“哑火”，以两个6比11被对手连追两局。第六局，林高远更是在手握六个赛点的情况下，以11比13遭到逆转。关键的决胜局，林高远率先达到9分，而后又出现心态变化，最终以9比11输掉整场比赛。
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Published on:12:15:57
