Thursday, June 13, 2019

The whisper of schizophrenia: Machine learning finds 'sound' words predict psychosis

"Machine learning technology is advancing so rapidly that it's giving us tools to data mine the human mind," says Emory psychologist Phillip Wolff, senior author of the study.

By Carol Clark

A machine-learning method discovered a hidden clue in people’s language predictive of the later emergence of psychosis — the frequent use of words associated with sound. The journal npj Schizophrenia published the findings by scientists at Emory University and Harvard University.

The researchers also developed a new machine-learning method to more precisely quantify the semantic richness of people’s conversational language, a known indicator for psychosis.

Their results show that automated analysis of the two language variables — more frequent use of words associated with sound and speaking with low semantic density, or vagueness — can predict whether an at-risk person will later develop psychosis with 93 percent accuracy.

Even trained clinicians had not noticed how people at risk for psychosis use more words associated with sound than the average, although abnormal auditory perception is a pre-clinical symptom.

“Trying to hear these subtleties in conversations with people is like trying to see microscopic germs with your eyes,” says Neguine Rezaii, first author of the paper. “The automated technique we’ve developed is a really sensitive tool to detect these hidden patterns. It’s like a microscope for warning signs of psychosis.”

Rezaii began work on the paper while she was a resident at Emory School of Medicine’s Department of Psychiatry and Behavioral Sciences. She is now a fellow in Harvard Medical School’s Department of Neurology.

“It was previously known that subtle features of future psychosis are present in people’s language, but we’ve used machine learning to actually uncover hidden details about those features,” says senior author Phillip Wolff, a professor of psychology at Emory. Wolff’s lab focuses on language semantics and machine learning to predict decision-making and mental health.

“Our finding is novel and adds to the evidence showing the potential for using machine learning to identify linguistic abnormalities associated with mental illness,” says co-author Elaine Walker, an Emory professor of psychology and neuroscience who researches how schizophrenia and other psychotic disorders develop.

The onset of schizophrenia and other psychotic disorders typically occurs in the early 20s, with warning signs — known as prodromal syndrome — beginning around age 17. About 25 to 30 percent of youth who meet criteria for a prodromal syndrome will develop schizophrenia or another psychotic disorder.

Using structured interviews and cognitive tests, trained clinicians can predict psychosis with about 80 percent accuracy in those with a prodromal syndrome. Machine-learning research is among the many ongoing efforts to streamline diagnostic methods, identify new variables, and improve the accuracy of predictions.

Currently, there is no cure for psychosis.

“If we can identify individuals who are at risk earlier and use preventive interventions, we might be able to reverse the deficits,” Walker says. “There are good data showing that treatments like cognitive-behavioral therapy can delay onset, and perhaps even reduce the occurrence of psychosis.”

For the current paper, the researchers first used machine learning to establish “norms” for conversational language. They fed a computer software program the online conversations of 30,000 users of Reddit, a social media platform where people have informal discussions about a range of topics. The software program, known as Word2Vec, uses an algorithm to change individual words to vectors, assigning each one a location in a semantic space based on its meaning. Those with similar meanings are positioned closer together than those with far different meanings.

The Wolff lab also developed a computer program to perform what the researchers dubbed “vector unpacking,” or analysis of the semantic density of word usage. Previous work has measured semantic coherence between sentences. Vector unpacking allowed the researchers to quantify how much information was packed into each sentence.

After generating a baseline of “normal” data, the researchers applied the same techniques to diagnostic interviews of 40 participants that had been conducted by trained clinicians, as part of the multi-site North American Prodrome Longitudinal Study (NAPLS), funded by the National Institutes of Health. NAPLS is focused on young people at clinical high risk for psychosis. Walker is the principal investigator for NAPLS at Emory, one of nine universities involved in the 14-year project.

The automated analyses of the participant samples were then compared to the normal baseline sample and the longitudinal data on whether the participants converted to psychosis.

The results showed that higher than normal usage of words related to sound, combined with a higher rate of using words with similar meaning, meant that psychosis was likely on the horizon.

Strengths of the study include the simplicity of using just two variables — both of which have a strong theoretical foundation — the replication of the results in a holdout dataset, and the high accuracy of its predictions, at above 90 percent.

“In the clinical realm, we often lack precision,” Rezaii says. “We need more quantified, objective ways to measure subtle variables, such as those hidden within language usage.”

Rezaii and Wolff are now gathering larger data sets and testing the application of their methods on a variety of neuropsychiatric diseases, including dementia.

“This research is interesting not just for its potential to reveal more about mental illness, but for understanding how the mind works — how it puts ideas together,” Wolff says. “Machine learning technology is advancing so rapidly that it’s giving us tools to data mine the human mind.”

The work was supported by grants from the National Institutes of Health and a Google Research Award.

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Wednesday, June 12, 2019

A focus on fathers: The science of dads

Anthropologist James Rilling with his son Toby, 8, and daughter Mia, 2. (Photo by Becky Stein)

Want to do something special for a father on June 16? Try asking him what he finds most rewarding — and most challenging — about being a dad.

James Rilling, an anthropologist at Emory University, recently completed in-depth interviews on that topic with 120 new fathers. Rilling and his colleague Craig Hadley, also an anthropologist at Emory, are still analyzing data from the interviews for a comprehensive study.

One result, however, is already clear. A positive-and-negative-affect scale administered to the subjects before and after the interviews shows how talking about fatherhood influenced their moods. “Most of them experienced an increase in how enthusiastic, proud and inspired they felt after talking about their experience as a father,” Rilling says. “They seemed to find it therapeutic to talk about their feelings surrounding being a father, particularly if they were struggling with some things. The challenges of being a mother are often much greater. So fathers may think that nobody really wants to hear about the things they are dealing with as a new parent.”

Read more about Rilling's work here, and learn five surprising facts about fathers.

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Tuesday, June 4, 2019

How chronic inflammation may drive down dopamine and motivation

“If our theory is correct, then it could have a tremendous impact on treating cases of depression and other behavioral disorders that may be driven by inflammation,” says co-author Andrew Miller, an Emory professor of psychiatry. (Getty Images)

By Carol Clark

Growing evidence shows that the brain’s dopamine system, which drives motivation, is directly affected by chronic, low-grade inflammation. A new paper proposes that this connection between dopamine, effort and the inflammatory response is an adaptive mechanism to help the body conserve energy.

Trends in Cognitive Sciences published the theoretical framework developed by scientists at Emory University. The authors also provided a computational method to experimentally test their theory.

“When your body is fighting an infection or healing a wound, your brain needs a mechanism to recalibrate your motivation to do other things so you don’t use up too much of your energy,” says corresponding author Michael Treadway, an associate professor in Emory’s Department of Psychology, who studies the relationship between motivation and mental illness. “We now have strong evidence suggesting that the immune system disrupts the dopamine system to help the brain perform this recalibration.”

The computational method will allow scientists to measure the effects of chronic inflammation on energy availability and effort-based decision-making. The method may yield insights into how chronic, low-grade inflammation contributes to motivational impairments in some cases of depression, schizophrenia and other medical disorders.

Co-author Andrew Miller, William P. Timmie Professor of Psychiatry and Behavioral Sciences in Emory’s School of Medicine and the Winship Cancer Institute, is a leader in this field and is pioneering the development of immunotherapeutic strategies for the treatment of psychiatric disorders.

“If our theory is correct, then it could have a tremendous impact on treating cases of depression and other behavioral disorders that may be driven by inflammation,” Miller says. “It would open up opportunities for the development of therapies that target energy utilization by immune cells, which would be something completely new in our field.”

Co-author Jessica Cooper, a post-doctoral fellow in Treadway’s lab, led the development of the computational model.

It has previously been shown that inflammatory cytokines — signaling molecules used by the immune system — impact the mesolimbic dopamine system. And recent research has revealed more insights into how immune cells can shift their metabolic states differently from most other cells.

The researchers built on these findings to develop their theoretical framework.

An immune-system mechanism to help regulate the use of energy resources during times of acute stress was likely adaptive in our ancestral environments, rife with pathogens and predators. In modern environments, however, many people are less physically active and may have low-grade inflammation due to factors such as chronic stress, obesity, metabolic syndrome, aging and other factors. Under these conditions, the same mechanism to conserve energy for the immune system could become maladaptive, the authors theorize.

Studies by Miller and others have provided evidence of an association between an elevated immune system, reduced levels of dopamine and motivation, and some diagnoses of depression, schizophrenia and other mental disorders.

“We’re not proposing that inflammation causes these disorders,” Treadway says. “The idea is that a subset of people with these disorders may have a particular sensitivity to the effects of the immune system and this sensitivity could contribute to the motivational impairments they are experiencing.”

The researchers are now using their computational method to test their theory in a clinical trial on depression.

The work for the current paper was supported by the National Institute of Mental Health.

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Study reveals how the brain decides to make an effort

Thursday, May 23, 2019

Civil War plant medicines blast drug-resistant bacteria

Micah Dettweiler gathered samples for the study from Lullwater Forest on the Emory campus. He began the project for his honors thesis as an Emory undergraduate majoring in biology.

During the height of the Civil War, the Confederate Surgeon General commissioned a guide to traditional plant remedies of the South, as battlefield physicians faced high rates of infections among the wounded and shortages of conventional medicines.

A new study of three of the plants from this guide — the white oak, the tulip poplar and the devil’s walking stick — finds that they have antiseptic properties. Scientific Reports published the results of the study led by scientists at Emory University. The results show that extracts from the plants have antimicrobial activity against one or more of a trio of dangerous species of multi-drug-resistant bacteria associated with wound infections: Acinetobacter baumannii, Staphylococcus aureus and Klebsiella pneumoniae.

Read more about the study here.

Tuesday, May 21, 2019

Mathematicians revive abandoned approach to the Riemann Hypothesis

The idea for the paper was sparked by a "toy problem" that Emory mathematician Ken Ono (left) presented as a "gift" to entertain Don Zagier (right), of the Max Planck Institute of Mathematics, to celebrate Zagier's 65th birthday. The toy problem is seen on the whiteboard behind them.

By Carol Clark

Many ways to approach the Riemann Hypothesis have been proposed during the past 150 years, but none of them have led to conquering the most famous open problem in mathematics. A new paper in the Proceedings of the National Academy of Sciences (PNAS) suggests that one of these old approaches is more practical than previously realized.

“In a surprisingly short proof, we’ve shown that an old, abandoned approach to the Riemann Hypothesis should not have been forgotten,” says Ken Ono, a number theorist at Emory University and co-author of the paper. “By simply formulating a proper framework for an old approach we’ve proven some new theorems, including a large chunk of a criterion which implies the Riemann Hypothesis. And our general framework also opens approaches to other basic unanswered questions.”

The paper builds on the work of Johan Jensen and George Pólya, two of the most important mathematicians of the 20th century. It reveals a method to calculate the Jensen-Pólya polynomials — a formulation of the Riemann Hypothesis — not one at a time, but all at once.

“The beauty of our proof is its simplicity,” Ono says. “We don’t invent any new techniques or use any new objects in math, but we provide a new view of the Riemann Hypothesis. Any reasonably advanced mathematician can check our proof. It doesn’t take an expert in number theory.”

Read a commentary on the paper by Fields Medalist Enrico Bombieri.

Although the paper falls short of proving the Riemann Hypothesis, its consequences include previously open assertions which are known to follow from the Riemann Hypothesis, as well as some proofs of conjectures in other fields.

Co-authors of the paper are Michael Griffin and Larry Rolen — two of Ono’s former Emory graduate students who are now on the faculty at Brigham Young University and Vanderbilt University, respectively — and Don Zagier of the Max Planck Institute of Mathematics.

“The result established here may be viewed as offering further evidence toward the Riemann Hypothesis, and in any case, it is a beautiful stand-alone theorem,” says Kannan Soundararajan, a mathematician at Stanford University and an expert on the Riemann Hypothesis.

"Math at a research level is often more art than calculation and that was certainly the case here," says co-author Michael Griffin, an Emory grad who is now on the faculty at Brigham Young University.

The idea for the paper was sparked two years ago by a “toy problem” that Ono presented as a “gift” to entertain Zagier during the lead-up to a math conference celebrating his 65th birthday. A toy problem is a scaled-down version of a bigger, more complicated problem that mathematicians are trying to solve. Zagier described the one that Ono gave him as “a cute problem about the asymptotic behavior of certain polynomials involving Euler’s partition function, which is an old love of mine and of Ken’s — and of about pretty much any classical number theorist.”

“I found the problem intractable and I didn’t really expect Don to get anywhere with it,” Ono recalls. “But he thought the challenge was super fun and soon he had crafted a solution.”

Ono’s hunch was that such a solution could be crafted into a more general theory. That’s what the mathematicians ultimately achieved.

“It’s been a fun project to work on, a really creative process,” Griffin says. “Math at a research level is often more art than calculation and that was certainly the case here. It required us to look at an almost 100-year-old idea of Jensen and Pólya in a new way.”

The Riemann Hypothesis is one of seven Millennium Prize Problems, identified by the Clay Mathematics Institute as the most important open problems in mathematics. Each problem carries a $1 million bounty for its solvers.

The method outlined in the PNAS paper "has a shocking sense of being universal, in that it applies to problems that are seemingly unrelated," says co-author Larry Rolen, an Emory grad now on the faculty at Vanderbilt University.

The hypothesis debuted in an 1859 paper by German mathematician Bernhard Riemann. He noticed that the distribution of prime numbers is closely related to the zeros of an analytical function, which came to be called the Riemann zeta function. In mathematical terms, the Riemann Hypothesis is the assertion that all of the nontrivial zeros of the Zeta function have real part ½.

“His hypothesis is a mouthful, but Riemann’s motivation was simple,” Ono says. “He wanted to count prime numbers.”

Bernhard Riemann
The hypothesis is a vehicle to understand one of the greatest mysteries in number theory — the pattern underlying prime numbers. Although prime numbers are simple objects defined in elementary math (any number greater than 1 with no positive divisors other than 1 and itself) their distribution remains hidden.

The first prime number, 2, is the only even one. The next prime number is 3, but primes do not follow a pattern of every third number. The next is 5, then 7, then 11. As you keep counting upwards, prime numbers rapidly become less frequent.

“It’s well known that there are infinitely many prime numbers, but they become rare, even by the time you get to the 100s,” Ono explains. “In fact, out of the first 100,000 numbers, only 9,592 are prime numbers, or roughly 9.5 percent. And they rapidly become rarer from there. The probability of picking a number at random and having it be prime is zero. It almost never happens.”

In 1927, Jensen and Pólya formulated a criterion for confirming the Riemann Hypothesis, as a step toward unleashing its potential to elucidate the primes and other mathematical mysteries. The problem with the criterion — establishing the hyperbolicity of the Jensen-Pólya polynomials — is that it is infinite. During the past 90 years, only a handful of the polynomials in the sequence have been verified, causing mathematicians to abandon this approach as too slow and unwieldy.

For the PNAS paper, the authors devised a conceptual framework that combines the polynomials by degrees. This method enabled them to confirm the criterion for each degree 100 percent of the time, eclipsing the handful of cases that were previously known.

“The method has a shocking sense of being universal, in that it applies to problems that are seemingly unrelated,” Rolen says. “And at the same time, its proofs are easy to follow and understand. Some of the most beautiful insights in math are ones that took a long time to realize, but once you see them, they appear simple and clear.”

Despite their work, the results don’t rule out the possibility that the Riemann Hypothesis is false and the authors believe that a complete proof of the famous conjecture is still far off.

The work was supported by grants from the National Science Foundation and the Asa Griggs Candler Fund.

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