方谬神探
양기대, 국토부서 1인시위…“신천~하안~신림선 제5차 국가철도망 반영해 달라”_我的网站
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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.
。 26일 양기대 전 국회의원이 국토교통부 청사 앞에서 ‘신천~하안~신림선 제5차 국가철도망 구축계획 반영하라’는 피켓을 들고 1인시위를 하고 있다. 양 전 의원 측 제공 재선 광명시장을 지낸 양기대 전 국회의원이 국토교통부 제5차 국가철도망 구축계획에 신천(시흥)~하안(광명)~신림(관악) 지하철 노선을 반영해달라고 촉구했다. 양 전 의원은 26일 국토부 청사 앞에서 ‘신천~하안~신림선 제5차 국가철도망 구축계획 반영하라’는 피켓을 들고 구호를 외치며 1인시위를 벌였다. 그는 “광명시민들이 오랫동안 요구해 온 신천∼하안∼신림선이 이번 제5차 국가철도망 구축계획에 반드시 포함돼야 한다는 절박한 마음을 정부에 전달하기 위해 직접 행동에 나섰다”고 밝혔다. 양 전 의원에 따르면 현재 광명시는 곳곳에서 대규모 재건축·재개발 사업이 진행돼 도심 교통 혼잡이 갈수록 심화하는 상황이다. 특히 하안동 일대는 서울로 직결되는 지하철 노선이 없어 주민들이 출퇴근 시간마다 극심한 불편을 겪고 있다. 여기에 향후 광명·시흥 3기 신도시가 조성되면 인구와 교통 수요가 대폭 늘어날 것으로 예상돼 교통난은 더욱 심각해질 전망이다. 도로 확충만으로는 한계가 뚜렷한 만큼, 광명과 서울을 잇는 새로운 철도망 구축이 시급하다는 것이다. 국토부는 이르면 9월 제5차 국가철도망 구축계획을 발표할 예정이나 신천~하안~신림선의 반영 여부는 아직 불투명하다. 국가철도망 구축계획은 중장기 철도 건설의 기본 방향이자 사업 추진의 근거인 만큼, 이번 계획에 반영되지 않으면 사업 추진이 장기간 지연될 수밖에 없다. 양 전 의원은 “광명시민들이 한마음으로 구로차량기지 광명 이전을 막아냈던 것처럼, 이번에도 광명시장과 국회의원, 시의회가 앞장서고 시민들이 힘을 모아 신천∼하안∼신림선의 국가철도망 구축계획 반영을 반드시 관철해야 한다”고 했다. 이어 “신천∼하안∼신림선은 광명과 시흥, 서울 서남권을 연결하고 수도권의 교통망을 한 단계 발전시키는 광역교통 인프라”라며 “정부가 광명시의 현재와 미래 교통 수요를 종합적으로 고려해 전향적인 결정을 내려야 한다”고 강조했다. 끝으로 양 전 의원은 “광명의 미래 교통 수요를 감안한다면 신천∼하안∼신림선은 더 이상 미룰 수 없는 사업”이라며 “정부가 시민들의 목소리에 귀 기울여 제5차 국가철도망 구축계획에 반드시 반영해 주기를 촉구한다”고 말했다.。
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Published on:02:43:55
