熊猫tv
Parineeti Chopra shares unseen BTS moments from Amar Singh Chamkila in new vlog_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.
。 Parineeti Chopra has opened a vibrant window into the world of Amar Singh Chamkila, sharing unseen photos, videos and deeply personal memories from the set in a new vlog. From singing live with Diljit Dosanjh to emotional breakdowns and unexpected real-life love, the actor revisited the moments that made Imtiaz Ali’s film one of the most transformative experiences of her career.Parineeti revealed that Imtiaz Ali enforced a raw, theatre-like approach to the musical sequences. Instead of traditional lip-syncing, both she and Diljit actually sang live on camera. “Our mics recorded everything we sang, no studio dubbing,” she said. “It was nerve-wracking because it had never been done like this before.”She laughed as she recalled Diljit telling her, “You become Rihanna,” while she tried, and hilariously failed to imitate the pop star during rehearsals. The duo’s off-camera chemistry quickly became a source of joy for the entire crew.
The movie also holds sentimental value for Parineeti for an unexpected reason. During early recce meetings in Punjab, Imtiaz Ali crossed paths with Raghav Chadha, then a local MP handling shoot permissions. “Back then, we didn’t know each other,” she shared. “But when we shot in Punjab in 2023, Raghav and I met, and everything changed.” She credits Chamkila for bringing them together.Parineeti described the wrap as “spiritual.” After the final song, Imtiaz hugged her and shared heartfelt words, leaving her in tears. “I couldn’t stop crying,” she recalled, while Diljit continued to tease her lovingly. “It felt like a family parting.”The assassination sequence, she revealed, was the hardest challenge. Acting lifeless for extended shots, eyes open, body still, no blinking, led to multiple retakes. “It was extremely uncomfortable,” she said. But seeing the final cut gave her goosebumps.
View this post on Instagram
A post shared by @parineetichopra
Despite gaining 16 kilos and wearing deliberately unglamorous looks, Parineeti and Diljit often squeezed in impromptu “photoshoots” between takes just to amuse themselves. “We looked nothing like ourselves but kept posing like we were on a magazine cover,” she laughed.Imtiaz Ali’s Amar Singh Chamkila, starring Diljit Dosanjh as the legendary musician and Parineeti as his wife Amarjot, earned widespread acclaim and two International Emmy nominations, cementing its place as one of the standout films of the year.Also Read: Priyanka Chopra and Nick Jonas Shower Parineeti Chopra’s Son Neer With Wholesome Gifts。
Current article:http://rnq2sn.shouyouxumianpouluanteng.shop/news/20260826_8223181.html
Published on:09:15:05
