英国达人秀

一 |     

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.
。    사당동 305-35 일대 재개발 신통기획 확정청소년수련시설 등 맞춤시설로 생활환경 개선                   사당동 305-35 지역 정비사업 후 예상 이미지. [서울시][헤럴드경제=김희량 기자] 서울시 동작구 사당동 305-35 일대가 재개발 신속통합기획을 통해 최고 34층, 약 970세대 규모의 주거단지로 탈바꿈한다. 시는 교통 수요 대응을 위해 사당로16길을 단계적으로 폭 16m·4차로까지 확폭하고 생활기반시설을 배치하기로 했다.26일 서울시는 동작구 사당동 305-35 일대 재개발 신속통합기획을 확정했다고 밝혔다. 대상지는 용도지역을 상향(제2종 일반주거지역→제3종일반주거지역)하고 사업성 보정계수(1.17)을 적용 받아 약 970세대의 단지 계획이 가능하게 됐다.해당 지역은 지하철 7호선 남성역 도보 10분 거리에 있다. 시는 남북으로 430m에 이르는 장방형 대지 형상과 최대 22m의 높이차가 있어 경사 지형인 탓에 이를 고려한 단지계획을 검토했다.시 관계자는 “대상지 일대인 사당로16길을 중심으로 역세권 활성화사업, 역세권 장기전세주택사업 등이 추진되고 있어 향후 교통량 증가 등 지역 여건 변화가 예상된다”면서 “대상지는 장래 교통수요 대응과 지역의 도로·보행체계 개선도 필요한 상황”이라고 설명했다.                   사당동 305-35일대 위치도. [서울시]이에 시는 ▷주변 개발사업과 연계한 단계적 도로체계 정비 ▷주민 생활동선 고려한 보행·외부공간 조성 ▷가로 특성을 고려한 맞춤형 시설배치 ▷주변 지역과 조화로운 경관창출 ▷지역 맞춤형 인센티브 적용을 중심으로 기획을 진행했다.도로의 경우 북측 역세권활성화사업과 연계해 우선 폭 14m의 3차로와 양측 보도를 확보하고, 향후 서측 역세권 장기전세주택사업 등 추진을 통해 진입부를 폭 16m, 4차로까지 넓힌다.또 남북으로 긴 장방형 대지(430m×90m)와 주민 보행동선을 고려해 동서방향 공공보행통로를 조성하기로 했다. 동측 주거지쪽 급격한 단차(8~9m)로 인한 옹벽구간은 계단식 조경공간 조성으로 시각적 위압감을 완화하고 급경사 계단은 안전하게 재조성하면서 엘리베이터를 설치해 보행 편의성과 안전성을 갖추도록 한다.기존 협소한 사당4동 구립 청소년독서실은 확대·재배치하여 청소년수련시설로 바꾼다. 대상지 북측 진입부에는 최고 34층을 계획하고 남측 저층주거지 및 남성중학교 방향으로 점차 낮아지도록 계획해 주변과 조화를 이루는 스카이라인이 형성될 예정이다.김창규 서울시 도시공간본부장은 “대상지 일대는 다양한 개발사업이 추진되고 있어 지역 일대 변화를 종합적으로 고려한 도로·보행체계 정비가 필요한 곳”이라며 “지역 생활가로를 중심으로 기반시설을 정비하고 생활동선을 연계해 지역 변화를 이끄는 주거단지가 조성될 수 있도록 지원하겠다”고 했다.。