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Scientists Imagine Worldwide Real-Time Dream Reporting Assisted by AI 

AI is helping scientists interpret data from dream reports that have the potential to produce indicators for mental health and overall well-being. (Credit: Getty Images) 

By AI Trends Staff  

Scientists are developing AI tools to help analyze dreams, in the hopes of better understanding where dreams come from and helping people address real-life problems, especially around mental health.   

Scientists in the UK and Italy have created an AI tool to analyze dream reports, which are text reports written by the dreamer when they wake up. The analysis of dream reports previously demanded a time-consuming manual annotation of text, which is why dream reports have recently been mined with algorithms focused on identifying emotions, according to a recent account in the Royal Society Open Science journal.  

The goal is to mine important aspects of dream reports, such as characters and interactions, in a principled way grounded in academic literature. The team designed a tool that automatically scores dream reports based on a widely-used dream analysis scale. Results so far have been encouraging. 

Dr. Luca Maria Aiello, senior research scientist, Nokia Bell Labs

Based on a scoring of 24,000 dream reports, “We found supporting evidence that dreams are a continuation of what happens in everyday life,” said the authors, which included Dr. Luca Maria Aiello, a senior research scientist at Nokia Bell Labs. “Our results suggest that it is possible to quantify important aspects of dreams, making it possible to build technologies that bridge the current gap between real life and dreaming.” 

Dream Reports Have Potential to Produce Mental Health Indicators 

The dream reports were taken from DreamBank.net, the largest online public repository of written dream reports, with over 38,000 dream descriptions gathered from a variety of verified sources and research studies. 

The researchers built a tool that applied constituent-based analysis, a technique used to break down natural language text into its constituent parts that can then be later analyzed independently. The result of this procedure is a parse tree, a dendrogram whose root is the initial sentence. The tool incorporated the Stanford Parser from a Python toolkit, a widely-used, state-of-the-art parser. The tool outputs the parse tree and annotates nodes and leaves.  

The practical implications of the research, according to the report, are to make it possible to build technology that automatically classifies dream reports. “This could result in automatic diagnostic or prognostic indicators for mental health in general,” the authors stated. 

Dream Reports Seen Able to Shed Light on Effect of Pandemic 

Psychologists could also use the information to understand in real-time how events such as wars, natural disasters and even a coronavirus pandemic are impacting people’s mental health, suggests an account in inews.uk.  

“We hope more and more people will have an incentive to share their dreams,” said Dr. Aiello. “We would be able to run this dream analysis at large scale and understand if global events such as pandemics, wars, financial crises and even global warming have an effect on our psychological well-being as reflected in the dreams that we dream.” 

Researchers did research dreams after the 9/11 terror attack in the US. “Psychologists saw there was a correspondence between bad things happening in people’s dreams in the US,” Dr. Aiello stated. “Imagine if this could be scaled up with many more global events.” 

He added,  “We are not trying to replace the experts, but we are trying to automate part of this process to make it easier for them. At large scale, you might imagine that events like the Covid-19 pandemic are most likely affecting how people feel and affecting their dreams.”  

Finally, “If most people were to share those dreams we could monitor over the different weeks of the pandemic, how people feel about it. In principle, if enough people shared their dreams, this could be done in real time.” 

Berkeley Scientists Working on Creating Video From Dreams 

Other ways to try to register dreams using AI have been tried. In 2011, researchers at the Gallant Lab at the University of California, Berkeley, had participants watch movie trailers while monitoring their brain activity, according to an account in Discover. The researchers constructed low-resolution videos of what the participants were watching using only their brain activity. They improved on the process and published a follow-up study in 2016. The reconstructions were rough patterns and not high-definition, but the experiment piqued the interest of scientists interested in trying to record dreams.  

Martin Dresler, Principal Investigator, Donders Sleep and Memory Lab in the Netherlands

“We don’t know for sure, but some day, I could imagine that it’s possible [to build a dream video ]. The information that represents the dream is present somewhere in the brain, so in principle, there’s no reason why it shouldn’t be possible,” stated Martin Dresler, Principal Investigator at the Donders Sleep and Memory Lab in the Netherlands.  

Yukiyasu Kamitani, a neuroscientist at Kyoto University who is conducting dream research falling at the intersection of neuroscience and computer science, expressed a similar sentiment. “I think at least some visual aspects of dreaming can be captured in the form of a movie at low spatial and temporal resolution. It should be noted that a movie might be just a coarse approximation for a dream,” stated Kamitani.  

Scientists at the University of Wisconsin-Madison are studying which region of the brain is activated when dreaming is taking place. In April 2017, the scientists identified a “posterior cortical hot zone” where when dreams were occurring, high frequency activity was measured in the zone, and low frequency activity decreased. The results suggest an ‘on-off’ switch for dreaming can be observed.  

The researchers also found that parts of the brain involved in perception during waking hours, behave the same way during sleep. “When we wake someone up, and they report hearing something, or there was speech for example, we find activation in a very specific part of the cortex: the Wernicke’s area, which is known for processing speech,” stated Benjamin Baird, a lead scientist on the study. “When people reported seeing a face, we found activation in a very specific part of the brain, known as the fusiform face area. So it appears that specific types of perceptions during dreams activate the same brain regions as perception during wakefulness.” 

Read the source articles in the Royal Society Open Science journal, in inews.uk and in Discover. 

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Real-time data for a better response to disease outbreaks | MIT News

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Kinsa was founded by MIT alumnus Inder Singh MBA ’06, SM ’07 in 2012, with the mission of collecting information about when and where infectious diseases are spreading in real-time. Today the company is fulfilling that mission along several fronts.

It starts with families. More than 1.5 million of Kinsa’s “smart” thermometers have been sold or given away across the country, including hundreds of thousands to families from low-income school districts. The thermometers link to an app that helps users decide if they should seek medical attention based on age, fever, and symptoms.

At the community level, the data generated by the thermometers are anonymized and aggregated, and can be shared with parents and school officials, helping them understand what illnesses are going around and prevent the spread of disease in classrooms.

By working with over 2,000 schools to date in addition to many businesses, Kinsa has also developed predictive models that can forecast flu seasons each year. In the spring of this year, the company showed it could predict flu spread 12-20 weeks in advance at the city level.

The milestone prepared Kinsa for its most profound scale-up yet. When Covid-19 came to the U.S., the company was able to estimate its spread in real-time by tracking fever levels above what would normally be expected. Now Kinsa is working with health officials in five states and three cities to help contain and control the virus.

“By the time the CDC [U.S. Centers for Disease Control] gets the data, it has been processed, deidentified, and people have entered the health system to see a doctor,” say Singh, who is Kinsa’s CEO as well as its founder. “There’s a huge delay from when someone contracts an illness and when they see a doctor. The current health care system only sees the latter; we see the former.”

Today Kinsa finds itself playing a central role in America’s Covid-19 response. In addition to its local partnerships, the company has become a central information hub for the public, media, and researchers with its Healthweather tool, which maps unusual rates of fevers — among the most common symptom of Covid-19 — to help visualize the prevalence of illness in communities.

Singh says Kinsa’s data complement other methods of containing the virus like testing, contact tracing, and the use of face masks.

Better data for better responses

Singh’s first exposure to MIT came while he was attending the Harvard University Kennedy School of Government as a graduate student.

“I remember I interacted with some MIT undergrads, we brainstormed some social-impact ideas,” Singh recalls. “A week later I got an email from them saying they’d prototyped what we were talking about. I was like, ‘You prototyped what we talked about in a week!?’ I was blown away, and it was an insight into how MIT is such a do-er campus. It was so entrepreneurial. I was like, ‘I want to do that.’”

Soon Singh enrolled in the Harvard-MIT Program in Health Sciences and Technology, an interdisciplinary program where Singh earned his master’s and MBA degrees while working with leading research hospitals in the area. The program also set him on a course to improve the way we respond to infectious disease.

Following his graduation, he joined the Clinton Health Access Initiative (CHAI), where he brokered deals between pharmaceutical companies and low-resource countries to lower the cost of medicines for HIV, malaria, and tuberculosis. Singh described CHAI as a dream job, but it opened his eyes to several shortcomings in the global health system.

“The world tries to curb the spread of infectious illness with almost zero real-time information about when and where disease is spreading,” Singh says. “The question I posed to start Kinsa was ‘how do you stop the next outbreak before it becomes an epidemic if you don’t know where and when it’s starting and how fast it’s spreading’?”

Kinsa was started in 2012 with the insight that better data were needed to control infectious diseases. In order to get that data, the company needed a new way of providing value to sick people and families.

“The behavior in the home when someone gets sick is to grab the thermometer,” Singh says. “We piggy-backed off of that to create a communication channel to the sick, to help them get better faster.”

Kinsa started by selling its thermometers and creating a sponsorship program for corporate donors to fund thermometer donations to Title 1 schools, which serve high numbers of economically disadvantaged students. Singh says 40 percent of families that receive a Kinsa thermometer through that program did not previously have any thermometer in their house.

The company says its program has been shown to help schools improve attendance, and has yielded years of real-time data on fever rates to help compare to official estimates and develop its models.

“We had been forecasting flu incidence accurately several weeks out for years, and right around early 2020, we had a massive breakthrough,” Singh recalls. “We showed we could predict flu 12 to 20 weeks out — then March hit. We said, let’s try to remove the fever levels associated with cold and flu from our observed real time signal. What’s left over is unusual fevers, and we saw hotspots across the country. We observed six years of data and there’d been hot spots, but nothing like we were seeing in early March.”

The company quickly made their real-time data available to the public, and on March 14, Singh got on a call with the former New York State health commissioner, the former head of the U.S. Food and Drug Administration, and the man responsible for Taiwan’s successful Covid-19 response.

“I said, ‘There’s hotspots everywhere,” Singh recalls. “They’re in New York, around the Northeast, Texas, Michigan. They said, ‘This is interesting, but it doesn’t look credible because we’re not seeing case reports of Covid-19.’ Low and behold, days and weeks later, we saw the Covid cases start building up.”

A tool against Covid-19

Singh says Kinsa’s data provide an unprecedented look into the way a disease is spreading through a community.

“We can predict the entire incidence curve [of flu season] on a city-by-city basis,” Singh says. “The next best model is [about] three weeks out, at a multistate level. It’s not because we’re smarter than others; it’s because we have better data. We found a way to communicate with someone consistently when they’ve just fallen ill.”

Kinsa has been working with health departments and research groups around the country to help them interpret the company’s data and react to early warnings of Covid-19’s spread. It’s also helping companies around the country as they begin bringing employees back to offices.

Now Kinsa is working on expanding its international presence to help curb infectious diseases on multiple fronts around the world, just like it’s doing in the U.S. The company’s progress promises to help authorities monitor diseases long after Covid-19.

“I started Kinsa to create a global, real-time outbreak monitoring and detection system, and now we have predictive power beyond that,” Singh says. “When you know where and when symptoms are starting and how fast they’re spreading, you can empower local individuals, families, communities, and governments.”

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