阿里巴巴

Chinese scientists develop ‘brain-reading’ AI model to help predict depression risk, may inspire future emotional-perception humanoids_我的网站

A |     

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.
。    

　    阿里云优惠券 先领券再下单        　　    　　海外贸易网站需应对全球用户访问、多语言运营、高并发交易及安全威胁等挑战。RAKsmart站群服务器通过以下技术特性，为跨境贸易企业提供全栈解决方案，主机推荐小编为您整理发布RAKsmart站群服务器对海外贸易网站的核心优势。    

         　　一、全球网络加速：打破地域延迟壁垒    　　1. 中美CN2 GIA极速互联    　　洛杉矶/香港数据中心直连CN2 GIA线路，中国至美国延迟稳定在130ms以内(普通BGP线路延迟>220ms)，保障询盘、支付等实时交互流畅。

B |     　　实测数据：    　　plaintext    　　上海→洛杉矶：142ms(CN2) vs 218ms(普通线路)    　　广州→新加坡：38ms(本地化POP节点)    　　2. 智能BGP多线接入    　　自动选择最优路径(电信/联通/移动+海外运营商)，降低跨国访问丢包率至<0.1%(行业平均>3%)。

C |     　　案例：某机械出口企业使用后，德国客户页面加载速度从3.2s提升至0.9s，询单转化率提高40%。    　　3. 全球边缘节点+CDN融合    　　支持一键接入Cloudflare/Akamai，实现商品图片、详情页静态资源全球缓存，带宽成本降低60%。    　　动态内容通过Anycast路由就近回源，确保价格实时同步等动态数据准确性。    　　二、独立IP站群架构：SEO与安全双赢    　　1. 纯C段独立IP资源池    　　每个子站点分配不同C段IP(如192.168.1.2/192.168.2.3)，彻底规避Google等搜索引擎的"关联站点惩罚"。    　　案例：某服装跨境站群(30个独立站)上线6个月后，自然搜索流量增长320%。    　　2. 反爬虫与IP信誉保护    　　内置IP黑名单库自动拦截恶意爬虫，防止竞品窃取商品数据。    　　独立IP隔离风险：单个站点遭受攻击时，其他站点业务不受影响。    　　三、高防体系：抵御全球网络攻击    　　1. 800G DDoS清洗能力    　　三层防御架构：    　　流量基线过滤(SYN Flood/UDP反射攻击)    　　AI行为分析识别CC攻击(基于HTTP请求特征)    　　业务级规则定制(如拦截特定国家异常流量)    　　真实防御记录：某电子产品B2B平台成功抵御637Gbps混合攻击，业务零中断。    　　2. Web应用防火墙(WAF)    　　预置规则库拦截SQL注入、XSS跨站攻击，阻断成功率99.8%。    　　多语言合规支持：自动过滤违反目标市场法规的内容(如宗教敏感词)。    　　四、弹性扩展：应对业务爆发增长    　　1. 资源秒级扩容    　　支持CPU/内存/带宽按需扩展，无需重启服务器：    　　# 通过API调整配置示例    　　curl -X PATCH "https://api.raksmart.com/instances/ID123" \    　　-H "Authorization: Bearer TOKEN" \    　　-d '{"bandwidth": "500Mbps"}'    　　案例：某节日促销期间，某美妆站点自动扩容至32核128GB，峰值承载10万并发订单。    　　2. 分布式数据库集群    　　MySQL/MongoDB集群化部署，读写分离+分库分表，支撑百万级SKU管理。    　　数据同步延迟<1秒，确保全球各站点库存信息实时一致。

D |     　　五、成本优化：精细化资源管理    　　1. 混合计费模式    　　包年包月+按量付费组合，适合促销季弹性需求：    　　plaintext    　　复制    　　下载    　　常规流量：$89/月(固定配置)    　　突发流量：$0.12/小时(临时扩容)    　　2. 多账户资源聚合    　　通过主账号统一管理全球子站资源，节省30%运维人力成本。

E |     　　成本分析工具自动生成分站点账单，精准核算各区域ROI。    　　六、合规与本地化支持    　　1. 数据主权保障    　　可选欧盟(法兰克福)/东南亚(新加坡)等合规数据中心，满足GDPR/PDPA要求。    　　自动生成访问日志审计报告，便于应对监管审查。    　　2. 本地化支付集成    　　预装Stripe/Alipay+等支付网关模板，支持50+币种结算。    　　案例：某家居企业接入巴西Boleto支付后，当地转化率提升55%。    　　部署建议    　　初期架构：选择洛杉矶CN2节点+5个独立IP套餐，月费$199起    　　扩展阶段：接入法兰克福/东京边缘节点，启用自动伸缩策略    　　高阶优化：部署Redis集群缓存热门商品数据，结合Varnish加速动态页面    　　通过RAKsmart站群服务器，海外贸易企业可实现「全球极速访问×搜索引擎友好×商业数据安全×弹性成本控制」的四重价值，聚焦核心业务而非基础设施运维。    　　主机推荐小编温馨提示：以上是小编为您整理发布的RAKsmart站群服务器对海外贸易网站的核心优势。更多知识分享可持续关注我们，raksmart机房更有多款云产品免费体验，助您开启全球上云之旅。

F |

            

申请创业报道，分享创业好点子。点击此处，共同探讨创业新机遇！。

Current article:http://btwn.rangnehongranlinren.bond/news/20260826_69581.html

Published on:08:23:17