Study maps how brain recognise extensively varied faces at one go

December 27, 2016

Washington, Dec 27: Ever wondered how can you recognise whether your friend is happy or sad, at a glance? Also how can you recognise a friend, even if you haven't seen him/her in a decade?

BrainAnswering to all these, a recent study finds out how the brain recognise familiar faces with efficiency and ease, despite extensive variation in how they appear.

Researchers at Carnegie Mellon University in the US are closer than ever before to understand the neural basis of facial identification.

The study, published in the journal of Proceedings of the National Academy of Sciences (PNAS), used highly sophisticated brain imaging tools and computational methods to measure the real-time brain processes that convert the appearance of a face into the recognition of an individual.

“Our results provide a step towards understanding the stages of information processing that begin when an image of a face first enters a person's eye and unfold over the next few hundred milliseconds, until the person is able to recognize the identity of the face," said study author Mark D. Vida.

To determine, how the brain rapidly distinguishes faces, they researchers scanned the brains of four people using magnetoencephalography (MEG).

MEG allowed them to measure ongoing brain activity throughout the brain on a millisecond-by-millisecond basis while the participants viewed images of 91 different individuals with two facial expressions each: happy and neutral.

The participants indicated that when they recognised that the same individual's face was repeated, regardless of expression.

The MEG scans allowed the researchers to map out, for each of many points in time, which parts of the brain encode appearance-based information and which encode identity-based information.

The team also compared the neural data to behavioral judgments of the face images from humans, whose judgments were based mainly on identity-based information.

Then, they validated the results by comparing the neural data to the information present in different parts of a computational simulation of an artificial neural network that was trained to recognise individuals from the same face images.

“Combining the detailed timing information from MEG imaging with computational models of how the visual system works has the potential to provide insight into the real-time brain processes underlying many other abilities beyond face recognition," said another researcher David C. Plaut.

The researchers are hopeful that the findings might be used in the near future to locate the exact point at which the visual perception system breaks down in different disorders and injuries, ranging from developmental dyslexia to prosopagnosia or face blindness.

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February 27,2020

Washington D.C, Feb 27: New research shows that adults who have low fruit and vegetable intake are more likely to be diagnosed with an anxiety disorder.

"For those who consumed less than 3 sources of fruits and vegetables daily, there was at least at 24% higher odds of anxiety disorder diagnosis," says the lead author of the Canadian Longitudinal Study, Karen Davison, who is a health science faculty member, nutrition informatics lab director at Kwantlen Polytechnic University, (KPU) and North American Primary Care Research Group Fellow.

"This may also partly explain the findings associated with body composition measures. As levels of total body fat increased beyond 36%, the likelihood of anxiety disorder was increased by more than 70%," states co-author Jose Mora-Almanza, a Mitacs Globalink intern who worked with the study at KPU.

"Increased body fat may be linked to greater inflammation. Emerging research suggests that some anxiety disorders can be linked to inflammation," says Davison.

In addition to diet and body composition measures, the prevalence of anxiety disorders also differed by gender, marital status, income, immigrant status and several health issues.

An important limitation of the study was that the assessment of anxiety disorders was mostly based upon self-reporting of a medical diagnosis.

"It is estimated that 10% of the global population will suffer from anxiety disorders which are a leading cause of disability," says Karen Davison

"Our findings suggest that comprehensive approaches that target health behaviours, including diet, as well as social factors, such as economic status, may help to minimize the burden of anxiety disorders among middle-aged and older adults, including immigrants," she concluded.

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February 6,2020

Researchers have found the rates of lung cancer are higher in young women than men.

The study, published in the journal Pediatrics, examined lung cancer rates in young adults in 40 countries across five continents and uncovered a trend of higher lung cancer rates in women compared with men in recent years.

The emerging trend was widespread, affecting countries across varied geographic locations and income levels.

The changes appeared to be driven by a rising rate of adenocarcinoma lung cancer among women, said the study researchers from University of Calgary in Canada.

Lung cancer rates have been higher among men than women because men started smoking in large numbers earlier and smoked at higher rates; however, recent studies have reported converging lung cancer incidence rates between sexes.

Among men, age specific lung cancer incidence rates generally decreased in all countries, while in women the rates varied across countries with the trends in most countries stable or declining, albeit at a slower pace compared to those in men.

For the findings, lung and bronchial cancer cases between 30-64 age group from 1993-2012 were extracted from cancer incidence in five continents.

The study found the higher emerging rates of lung cancer in young women compared to young men.

According to the researchers, future studies are needed to identify reasons for the elevated incidence of lung cancer among young women.

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June 21,2020

Lower neighbourhood socioeconomic status and greater household crowding increase the risk of becoming infected with SARS-CoV-2, the virus that causes COVID-19, warn researchers.

"Our study shows that neighbourhood socioeconomic status and household crowding are strongly associated with risk of infection," said study lead author Alexander Melamed from Columbia University in the US.

"This may explain why Black and Hispanic people living in these neighbourhoods are disproportionately at risk for contracting the virus," Melamed added.

For the findings, published in the journal JAMA, the researchers examined the relationships between COVID-19 infection and neighbourhood characteristics in 396 women who gave birth during the peak of the Covid-19 outbreak in New York City. Since March 22, all women admitted to the hospitals for delivery have been tested for the virus, which gave the researchers the opportunity to detect all infections -- including infections with no symptoms -- in a defined population

The strongest predictor of COVID-19 infection among these women was residence in a neighbourhood where households with many people are common.The findings showed that women who lived in a neighbourhood with high household membership were three times more likely to be infected with the virus. Neighbourhood poverty also appeared to be a factor, the researchers said.Women were twice as likely to get COVID-19 if they lived in neighbourhoods with a high poverty rate, although that relationship was not statistically significant due to the small sample size.

The study revealed that there was no association between infection and population density.

"New York City has the highest population density of any city in the US, but our study found that the risks are related more to density in people's domestic environments rather than density in the city or within neighbourhoods," says co-author Cynthia Gyamfi-Bannerman."

The knowledge that SARS-CoV-2 infection rates are higher in disadvantaged neighbourhoods and among people who live in crowded households could help public health officials target preventive measures," the authors wrote.

Recently, another study published in the Journal of the American Planning Association, showed that dense areas were associated with lower COVID-19 death rates.

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