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Neuroscience

Hebrew University’s Haim Sompolinsky awarded prestigious Brain Prize for pioneering neuroscience research – The Times of Israel

Prof. Haim Sompolinsky of the Hebrew University of Jerusalem is awarded the Brain Prize for 2024, the largest and most prestigious international prize for brain research. The prize is awarded annually by the Lundbeck Foundation of Denmark.

Sompolinsky, who is also affiliated with Harvard University, is a physicist and pioneer in the field of theoretical and computational neuroscience, particularly in the study of neural circuit dynamics in the brain. His research has significantly contributed to understanding how neural circuits process and encode information, map the external world and participate in learning and memory.

Sompolinsky shares the annual prize totaling 1.3 million euros with Prof. Larry Abbott of Columbia University and Prof. Terrence Sejnowski of the Salk Institute, who are also widely recognized for their groundbreaking work in computational and theoretical neuroscience, which applies physics, mathematics, and statistics as tools for studying the brain and how it functions.

Its a very satisfactory and personal honor for me to receive this award. More so, it is a fantastic recognition of the important contribution of radical computational science at the heart of brain science. This would not have been the case decades ago, he tells The Times of Israel.

His Royal Highness King Frederik of Denmark, will present the Brain Prize medals to the winners at a ceremony in Copenhagen on May 30.

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Hebrew University's Haim Sompolinsky awarded prestigious Brain Prize for pioneering neuroscience research - The Times of Israel

Neuroscience

Harvard neuroscientist Haim Sompolinsky awarded Brain Prize – EurekAlert

image:

Haim Sompolinsky, professor in residence in molecular and cellullar biology and physics at Harvard.

Credit: Anthony Tulliani for the Kempner Institute at Harvard

Haim Sompolinsky, Professor in Residence in Harvards Department of Molecular and Cellular Biology and Department of Physics, has received theBrain Prizefor his pioneering contributions to computational and theoretical neuroscience.

Considered the worlds most prestigious prize for neuroscience research, the Brain Prize 2024 is shared by Sompolinsky, Larry Abbott of Columbia University, and Terrence Sejnowski of the Salk Institute. All three scientists have helped uncover key principles governing the brains structure, function, and the emergence of cognition and behavior, according to the Lundbeck Foundation in Denmark, which awards the annual recognition.

Richard Morris, chair of the Brain Prize Selection Committee, explained the reasoning behind this years awardees.

It is inconceivable to imagine modern brain sciences without the concomitant development of computational and theoretical neuroscience, Morris said. The three scientists have applied novel and sophisticated approaches from physics, mathematics, and statistics to study the brain. They have developed vital tools for the analysis of highly complex datasets acquired by modern-day experimental neuroscientists.

Director of the Swartz Program in Theoretical Neuroscience at Harvards Center for Brain Science and Associate Faculty in the Kempner Institute for the Study of Natural and Artificial Intelligence, Sompolinsky has spent his career developing new theoretical approaches to computational neuroscience. His research has helped establish a deeper understanding of neural processes through rigorous conceptual frameworks found in physics.

Among his most important foundational work is the establishment and theoretical understanding of models of neuronal circuit function, including circuits for long-term memory and recall, as well as elucidating the brains delicate balance between opposing forces orchestrated by excitatory and inhibitory neurons.

The brain is an intrinsically dynamic organ thats whats fascinating about it, Sompolinsky said. Think about sleep, dreaming, wandering thoughts, creative actions in arts or sciences, problem-solving. The theory gives us a framework for conceptualizing, quantifying, and studying the link between circuit dynamics and these types of functionalities in the brain.

Over the last 10 years, Sompolinsky has been captivated by advances in artificial intelligence technologies. His current research focuses on deep learning, language models, and reasoning models in artificial neural network settings. His goal is to adapt these models to be biologically plausible, using them to test new theories about how the brain works.

For the first time in the history of the science of intelligence, we have artificial neural networks with strong similarities to the architecture and operation of the brain, Sompolinsky said. We have distributed, experience-dependent processing with amazing cognitive functions that are similar in many ways to human cognition. For me, this is a game changer, and this is where I am working at the interface between AI and neuroscience.

Venkatesh Murthy, the Paul J. Finnegan Family Director of the Center for Brain Science, said, There are few who lay the foundation for a growing field, but thats what Sompolinsky has done for theoretical neuroscience. He brought approaches from physics to understand various ways a network of neurons can interact, which has led to an understanding of how brains can store and retrieve memories, how a brain knows which direction its head is pointing, and how a proper balance between excitatory and inhibitory neurons can be maintained in our brains. Now, he is bringing his customary rigorous physics approaches (and his unbounded energy) to bear on the many exciting puzzles in high-level animal cognition, as well as to the startlingly sophisticated AI models such as ChatGPT. His presence at Harvard has been transformative to many communities here.

Before joining the faculty of Harvard in 2022, Sompolinsky spent most of his academic career as a professor at Hebrew University in Jerusalem, where he is now emeritus. His Ph.D. is from Bar-Ilan University in Israel, and his first appointment at Harvard was as a physics postdoctoral researcher in 1982, working with Professor Bert Halperin.

Sompolinsky was the 2022 recipient of the Gruber Neuroscience Prize and was elected a fellow of the Israel Physical Society that same year. He is a Foreign Honorary Member of the American Academy of Arts and Sciences and a former recipient of the EMET Prize in Life Sciences-Brain Research.

The Brain Prize 2024 comes with an award of 1.3 million to be shared by the three recipients.

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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Harvard neuroscientist Haim Sompolinsky awarded Brain Prize - EurekAlert

Neuroscience

Rhythm in the Brain: Music Exposure Influences Rhythmic Interpretation – Neuroscience News

Summary: A new study involving participants from 15 countries, shed light on the universal preference for simple integer ratios in rhythms, revealing significant cultural variations in musical perception.

This research, conducted with 39 groups, including people from traditional societies, indicates that while theres a common bias towards certain rhythmic structures, the specific preferences can differ markedly across cultures. The findings suggest that the brains bias towards these rhythms aids in error correction during music production, ensuring the consistency of musical systems across generations.

This landmark study, which is unparalleled in its scope, emphasizes the need for diverse, global research to fully understand the complexities of music perception.

Key Facts:

Source: MIT

When listening to music, the human brain appears to be biased toward hearing and producing rhythms composed of simple integer ratios for example, a series of four beats separated by equal time intervals (forming a 1:1:1 ratio).

However, the favored ratios can vary greatly between different societies, according to a large-scale study led by researchers at MIT and the Max Planck Institute for Empirical Aesthetics and carried out in 15 countries.

The study included 39 groups of participants, many of whom came from societies whose traditional music contains distinctive patterns of rhythm not found in Western music.

Our study provides the clearest evidence yet for some degree of universality in music perception and cognition, in the sense that every single group of participants that was tested exhibits biases for integer ratios. It also provides a glimpse of the variation that can occur across cultures, which can be quite substantial, saysNori Jacoby, the studys lead author and a former MIT postdoc, who is now a research group leader at the Max Planck Institute for Empirical Aesthetics in Frankfurt, Germany.

The brains bias toward simple integer ratios may have evolved as a natural error-correction system that makes it easier to maintain a consistent body of music, which human societies often use to transmit information.

When people produce music, they often make small mistakes. Our results are consistent with the idea that our mental representation is somewhat robust to those mistakes, but it is robust in a way that pushes us toward our preexisting ideas of the structures that should be found in music, says Josh McDermott,an associate professor of brain and cognitive sciences at MIT and a member of MITs McGovern Institute for Brain Research and Center for Brains, Minds, and Machines.

McDermott is the senior author of the study, which appears today inNature Human Behaviour.The research team also included scientists from more than two dozen institutions around the world.

A global approach

The new study grew out of a smaller analysis that Jacoby and McDermott published in 2017. Inthat paper, the researchers compared rhythm perception in groups of listeners from the United States and the Tsimane, an Indigenous society located in the Bolivian Amazon rainforest.

To measure how people perceive rhythm, the researchers devised a task in which they play a randomly generated series of four beats and then ask the listener to tap back what they heard.

The rhythm produced by the listener is then played back to the listener, and they tap it back again. Over several iterations, the tapped sequences became dominated by the listeners internal biases, also known as priors.

The initial stimulus pattern is random, but at each iteration the pattern is pushed by the listeners biases, such that it tends to converge to a particular point in the space of possible rhythms, McDermott says.

That can give you a picture of what we call the prior, which is the set of internal implicit expectations for rhythms that people have in their heads.

When the researchers first did this experiment, with American college students as the test subjects, they found that people tended to produce time intervals that are related by simple integer ratios. Furthermore, most of the rhythms they produced, such as those with ratios of 1:1:2 and 2:3:3, are commonly found in Western music.

The researchers then went to Bolivia and asked members of the Tsimane society to perform the same task. They found that Tsimane also produced rhythms with simple integer ratios, but their preferred ratios were different and appeared to be consistent with those that have been documented in the few existing records of Tsimane music.

At that point, it provided some evidence that there might be very widespread tendencies to favor these small integer ratios, and that there might be some degree of cross-cultural variation. But because we had just looked at this one other culture, it really wasnt clear how this was going to look at a broader scale, Jacoby says.

To try to get that broader picture, the MIT team began seeking collaborators around the world who could help them gather data on a more diverse set of populations. They ended up studying listeners from 39 groups, representing 15 countries on five continents North America, South America, Europe, Africa, and Asia.

This is really the first study of its kind in the sense that we did the same experiment in all these different places, with people who are on the ground in those locations, McDermott says.

That hasnt really been done before at anything close to this scale, and it gave us an opportunity to see the degree of variation that might exist around the world.

Cultural comparisons

Just as they had in their original 2017 study, the researchers found that in every group they tested, people tended to be biased toward simple integer ratios of rhythm.However, not every group showed the same biases. People from North America and Western Europe, who have likely been exposed to the same kinds of music, were more likely to generate rhythms with the same ratios. However, many groups, for example those in Turkey, Mali, Bulgaria, and Botswana showed a bias for other rhythms.

There are certain cultures where there are particular rhythms that are prominent in their music, and those end up showing up in the mental representation of rhythm, Jacoby says.

The researchers believe their findings reveal a mechanism that the brain uses to aid in the perception and production of music.

When you hear somebody playing something and they have errors in their performance, youre going to mentally correct for those by mapping them onto where you implicitly think they ought to be, McDermott says.

If you didnt have something like this, and you just faithfully represented what you heard, these errors might propagate and make it much harder to maintain a musical system.

Among the groups that they studied, the researchers took care to include not only college students, who are easy to study in large numbers, but also people living in traditional societies, who are more difficult to reach.

Participants from those more traditional groups showed significant differences from college students living in the same countries, and from people who live in those countries but performed the test online.

Whats very clear from the paper is that if you just look at the results from undergraduate students around the world, you vastly underestimate the diversity that you see otherwise, Jacoby says.

And the same was true of experiments where we tested groups of people online in Brazil and India, because youre dealing with people who have internet access and presumably have more exposure to Western music.

The researchers now hope to run additional studies of different aspects of music perception, taking this global approach.

If youre just testing college students around the world or people online, things look a lot more homogenous. I think its very important for the field to realize that you actually need to go out into communities and run experiments there, as opposed to taking the low-hanging fruit of running studies with people in a university or on the internet, McDermott says.

Funding: The research was funded by the James S. McDonnell Foundation, the Canadian National Science and Engineering Research Council, the South African National Research Foundation, the United States National Science Foundation, the Chilean National Research and Development Agency, the Austrian Academy of Sciences, the Japan Society for the Promotion of Science, the Keio Global Research Institute, the United Kingdom Arts and Humanities Research Council, the Swedish Research Council, and the John Fell Fund.

Author: Sarah McDonnell Source: MIT Contact: Sarah McDonnell MIT Image: The image is credited to Neuroscience News

Original Research: The findings will appear in Nature Human Behavior

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Rhythm in the Brain: Music Exposure Influences Rhythmic Interpretation - Neuroscience News

Neuroscience

Physicist Haim Sompolinsky first Israeli to win largest brain science research prize – The Times of Israel

Prof. Haim Sompolinsky of the Hebrew University of Jerusalem has been awarded the Brain Prize for 2024, the largest and most prestigious international prize for brain research. The prize is awarded annually by the Lundbeck Foundation of Denmark.

Sompolinsky, who is also affiliated with Harvard University, is a physicist and pioneer in the field of theoretical and computational neuroscience, particularly in the study of neural circuit dynamics in the brain. His research has significantly contributed to understanding how neural circuits process and encode information, map the external world, and participate in learning and memory.

Sompolinsky shares the annual prize totaling 1.3 million euros ($1.4 million) with Prof. Larry Abbott of Columbia University and Prof. Terrence Sejnowski of the Salk Institute, who are also widely recognized for their groundbreaking work in computational and theoretical neuroscience, which applies physics, mathematics and statistics as tools for studying the brain and how it functions.

Haims work over more than 40 years has been instrumental in establishing theoretical and computational neuroscience as a cornerstone of modern brain research, said Richard Morris, chair of The Brain Prize selection committee.

Sompolinsky will be presented the Brain Prize medal by King Frederik on May 30 in Copenhagen, where he was born in 1949. The son of Danish and Hungarian Holocaust survivors who met in Sweden after the war, he is the third of 10 children, and the last to be born in Denmark before his family immigrated to Israel.

During the war, his father, Prof. David Sompolinsky, worked with the Danish Resistance to save 700 co-religionists from extermination by the Nazis, by arranging their escape to Sweden in October 1943.

Haim Sompolinsky as a young boy with his teacher, Rishon Lezion, 1954. (Courtesy of Sompolinsky family)

When asked whether his fathers work as a microbiologist inspired him to become a scientist, Sompolinsky said that while it is hard to know why someone goes into one profession or another, his father undoubtedly was an inspiration. The elder Sompolinsky modeled how a person could combine Orthodox Jewish observance with a deep love of science.

My fathers big library in our living room was a complete chaotic mix of Talmud, Torah and books of Jewish law. In the middle of this were books about mathematics, microbiology and physics. To me, it was a place where I could just pick up a book and read, Sompolinsky recalled.

There was no conflict between religious observance and a professional life in the sciences. I think I inherited from him the idea of leading a coherent lifestyle. I think that being a scientist enriches my religious experiences and insights and vice versa, he said.

In the following interview, edited for length and clarity, The Times of Israel asked Sompolinsky about how theoretical and computational neuroscience helps us understand the brain, where he sees the field going and his reaction to receiving the worlds largest prize for brain research.

The Times of Israel: Why did you decide to pursue research in neuroscience in particular?

Prof. Haim Sompolinsky: It was a matter of personal choice. Many of my physicist colleagues who, like me, worked on the theory of spin glasses branched out to problems in the areas of economics and other complex systems in physics. Some went into the fields of biochemistry or biophysics. For me, neuroscience and the brain presented a very attractive set of problems. Throughout my career, I have always chosen problems that I think are intellectually interesting and worthwhile. It was natural for me to go in the direction of neuroscience because there was a mesh between my interest in the problems and my abilities to contribute to [understanding] them.

Haim Sompolinsky and his wife Elisheva with their family on vacation in Holland, 2016. (Courtesy of Sompolinsky family)

Were you motivated by a desire to find cures for specific neurological diseases?

When we work on basic research, we all hope that it will contribute in the long run to the benefit of humanity, whether it is health, ecology, climate, energy or whatever. But Im a basic scientist and my area of excellence is thinking more about principles and fundamental problems. I dont think Id be very good at applied research, where the details and the short-term goals dominate the thinking and research. My primary interest has been to contribute to understanding the principles of brain function.

Brain research has different levels. Can you explain what these levels are in laymans terms?

People are more familiar with the experimental and empirical aspects of neuroscience. First, there is the molecular level. People often read about discoveries of genes or molecules in the brain. Then there is cellular neuroscience. There is very active and fascinating research in this area, including on the properties of single nerve cells and other cells in the brain aside from neurons.

Then comes the level of circuits, and above it the level of systems. Most of the work in theoretical and computational neuroscience is at the level of circuits and above. We dont study the theoretical principles of molecular neuroscience because, at the level of principles, molecular neuroscience is very similar to molecular biology. The DNA and the expression of proteins in molecules in brain cells are the same as in any other setting in the body. On the other hand, the circuit level is what is unique about the brain and more directly related to computation.

What are some examples of what we can understand by studying brain circuits and systems?

You can ask how a circuit stores information or how it encodes or retrieves memories. You can ask how the visual system in the brain performs cognitive functions associated with vision perception. How do we recognize somebody simply from visual signals? The primary focus of theoretical and computational neuroscience science is to try to understand the relation between the structure of the neurocircuits and the dynamics of the activation of the neurons and the function that comes out of it.

Hebrew University theoretical and computational neuroscientist professor Haim Sompolinsky with junior colleagues in Jerusalem, 2014. (Courtesy of Sompolinsky family)

Do theoretical and computational neuroscientists work on their own, or do they interact with neuroscientists who work in the lab?

Our goal is to make sense of experimental results and even make predictions about what can be expected based on our theoretical models. If you have a good idea, you have to be able to translate it to a concrete model, which means mathematical equations and algorithms and analyzing them. Then you can approach an experimentalist and say, hey, I have a great idea, and here are the predictions and lets see if they are right. By working this way with the experimentalist, we advanced the understanding of the brain.

What do you think will be the legacy that you and other pioneers in theoretical and computational neuroscience will leave to the next generation?

There are several legacies. Ill mention just a couple. First, I think we succeeded in establishing solid foundations based on physics and mathematics for theoretical neuroscience, which will largely remain relevant for future generations. What we started as research is now part of textbooks in the field.

Second, I believe the interdisciplinary nature of brain science research that developed due to our efforts will remain forever. Brain science is no longer just part of biology studies or medical school. Its too complex and important for humanity not to recruit all the intellectual and technical skills of disciplines in science and maybe also in philosophy. Most neuroscience institutes today are multidisciplinary, not only in terms of research but also education. The Hebrew University made a pioneering contribution to the development of multidisciplinary research in neuroscience, and I am very proud and grateful for that.

What are the more recent developments in computational neuroscience that will help carry the field forward?

An important and extremely active research area in neuroscience is artificial intelligence. It is an exciting new direction. We hope to integrate new ideas, tools and models coming from AI into experimental paradigms. AI is already showing its impact in the research of my group and that of others in the last 10 years.

On the technical side of neuroscience, the toolbox for researchers has grown exponentially in terms of devices, electronics, optics and more. With this, the amount of data that is accumulated in neuroscience has grown exponentially, and now we are talking about international observatories and centers that specialize in generating big data for neuroscience research and are open access.

The Brain Prize medal, designed by Georg Jensen. (The Lundbeck Foundation)

What does it mean to you to be awarded The Brain Prize?

It is very satisfactory and a personal honor. For me and my co-winners, it is an expression of the international national recognition of the central contribution and role that theoretical and computational neuroscience plays in contemporary brain research.

You are the first Israeli to be given this award.

Im humbled by my ability to bring honor to Israeli science, particularly at this time.

What does receiving this award from a Danish foundation at a ceremony in Copenhagen mean to you given your familys background?

We were always told about the king of Denmarks empathy and public expression of support for the Jewish community [during World War II]. My going to Copenhagen in a couple of months to receive the prize from the present king, who is a descendant of the wartime one, is going to be very moving.

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Physicist Haim Sompolinsky first Israeli to win largest brain science research prize - The Times of Israel

Neuroscience

Prestigious 2024 Brain Prize awarded to Hebrew University’s Prof. Haim Sompolinsky by Lundbeck Foundation – EurekAlert

image:

Prof. Haim Sompolinsky

Credit: Kris Snibbe/Harvard File

Prof. Haim Sompolinsky of the Hebrew University and Harvard University has been awarded the Brain Prize for 2024, the largest and most prestigious international prize in neuroscience.

Prof. Haim Sompolinsky a physicist and neuroscience researcher at the Edmond and Lily Safra Center for Neuroscience (ELSC) at the Hebrew University and Professor at the Center for Brain Science (CBS) at Harvard University is the first Israeli scientist to receive this esteemed prize, which is awarded to pioneers in the field of neuroscience. He shares the prize totaling 1.3 million euros with Professor Larry Abbott at Columbia University (USA) and Professor Terrence Sejnowski at the Salk Institute (USA).

Prof. Sompolinsky is renowned for his groundbreaking work in theoretical and computational neuroscience, particularly in the study of neural circuit dynamics in the brain. His research has significantly contributed to our understanding of how neural circuits process and encode information, map the external world, and participate in learning and memory. Through a combination of theoretical and computational approaches, his work has elucidated key computational principles underlying brain function.

Prof. Sompolinsky responded: I am deeply honored to have been recognized with the Brain Prize 2024, an award that underscores the central contribution of theoretical and computational neuroscience to brain science. This distinction also allows me to highlight the pioneering efforts of the Hebrew University in fostering the development of interdisciplinary brain research.

The Brain Prize, initiated in 2011 and awarded annually by the Lundbeck Foundation, is considered the most prestigious award in neuroscience. It recognizes researchers whose work has advanced the field, from fundamental research to clinical applications. Prof. Sompolinsky's research not only deepens our knowledge of the brain's inner workings but also holds promise for applications in brain-inspired artificial intelligence.

Prof. Asher Cohen, President of the Hebrew University commented: "Prof. Sompolinsky's Brain Prize triumph is a testament to his pioneering contributions in computational neuroscience, unraveling neural circuit dynamics and laying the foundation for insights into information processing. His groundbreaking work inspires artificial intelligence, blending experimentation and theory to illuminate fundamental computational principles in brain function. This recognition not only honors his exceptional achievements but serves as a beacon guiding us toward further revelations at the intersection of neuroscience and computation."

The 2024 Brain Prize will be presented on May 30, 2024 to the three winners, Professor Haim Sompolinsky at Hebrew University (Israel) and Harvard University (USA), Professor Larry Abbott at Columbia University (USA), Professor Terrence Sejnowski at the Salk Institute (USA). The Brain Prize recipients are presented with their award by His Royal Highness, King Frederik of Denmark, at a ceremony in the Danish capital, Copenhagen.

Prof. Haim Sompolinsky is the son of the late Prof. David Sompolinsky, who was born in Denmark. Together with friends from the Danish Underground, he saved hundreds of Danish Jews from Nazi persecution in October 1943 by smuggling them by fishing boats to a safe haven in Sweden.

The Hebrew University of Jerusalem is Israels premier academic and research institution. With over 25,000 students from 90 countries, it is a hub for advancing scientific knowledge and holds a significant role in Israels civilian scientific research output, accounting for nearly 40% of it and has registered over 11,000 patents. The universitys faculty and alumni have earned eight Nobel Prizes and a Fields Medal, underscoring their contributions to ground-breaking discoveries. In the global arena, the Hebrew University ranks 86th according to the Shanghai Ranking. To learn more about the universitys academic programs, research initiatives, and achievements, visit the official website at http://new.huji.ac.il/en

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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Prestigious 2024 Brain Prize awarded to Hebrew University's Prof. Haim Sompolinsky by Lundbeck Foundation - EurekAlert

Neuroscience

Pioneering work in computational and theoretical neuroscience is awarded the world’s largest brain research prize – EurekAlert

image:

The Brain Prize medal is awarded to the recipients at a ceremony in Copenhagen. His royal highness, king Frederik of Denmark, attends this ceremony and awards the medals.

Credit: The Lundbeck Foundation

The Lundbeck Foundation has announced the recipients of The Brain Prize 2024, the worlds largest award for outstanding contributions to neuroscience. This years award recognizes the pioneering work of three leading neuroscientists Professor Larry Abbott at Columbia University (USA), Professor Terrence Sejnowski at the Salk Institute (USA), and Professor Haim Sompolinsky at Harvard University (USA) and the Hebrew University (Israel).

Theoretical and computational neuroscience permeates neuroscience today and is of increasingly growing importance. The winners of The Brain Prize 2024 have made pioneering contributions to these scientific areas by uncovering some of the principles that govern the brains structure, function, and the emergence of cognition and behaviour.

Chair of The Brain Prize Selection Committee, Professor Richard Morris, explains the reasoning behind this years award:

It is inconceivable to imagine modern brain sciences without the concomitant development ofn computational and theoretical neuroscience. The three scientists have applied novel and sophisticated approaches from physics, mathematics, and statistics to study the brain. They have developed vital tools for the analysis of highly complex datasets acquired by modern day experimental neuroscientists. The three prize winners have also proposed conceptual frameworks for understanding some of the brains most fundamental processes such as learning, memory, perception and how the brain generates maps of the external world. They have also provided crucial new insights into what may go awry in several devastating disorders of the nervous system, such as epilepsy, Alzheimers disease, and schizophrenia. In addition, their scientific achievements have paved the way for the development of brain-inspired artificial intelligence, one of the emerging and transformational technologies of our time.

On behalf of the Lundbeck Foundation, CEO Lene Skole extends her warmest congratulations to each of the three Brain Prize recipients:

Their pioneering research has created trailblazing knowledge and paved the way for other scientists to better understand critical brain functions, also in relation to diseases. It aligns fully with our purpose of bringing discoveries to lives. Each of their scientific endeavours began in the 70s, and their determination, courage and persistence over decades should serve as inspiration for other scientists, and indeed be rewarded.

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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Organic Chemistry

Advancing Chemistry with AI: New Model for Simulating Diverse Organic Reactions – Lab Manager Magazine

Key Takeaways:

Researchers from Carnegie Mellon University and Los Alamos National Laboratory have used machine learning to create a model that can simulate reactive processes in a diverse set of organic materials and conditions.

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"It's a tool that can be used to investigate more reactions in this field," said Shuhao Zhang, a graduate student in Carnegie Mellon University'sDepartment of Chemistry. "We can offer a full simulation of the reaction mechanisms."

Zhang is the first author on the paper that explains the creation and results of this new machine learning model, "Exploring the Frontiers of Chemistry with a General Reactive Machine Learning Potential," which was published in Nature Chemistry on March 7.

Though researchers have simulated reactions before, previous methods had multiple problems. Reactive force field models are relatively common, but they usually require training for specific reaction types. Traditional models that use quantum mechanics, where chemical reactions are simulated based on underlying physics, can be applied to any materials and molecules, but these models require supercomputers to be used.

This new general machine learning interatomic potential (ANI-1xnr) can perform simulations for arbitrary materials containing the elements carbon, hydrogen, nitrogen, and oxygen and requires significantly less computing power and time than traditional quantum mechanics models. According to Olexandr Isayev, associate professor of chemistry at Carnegie Mellon and head of the lab where the model was developed, this breakthrough is due to developments in machine learning.

"Machine learning is emerging as a powerful approach to construct various forms of transferable atomistic potentials utilizing regression algorithms. The overall goal of this project is to develop a machine learning method capable of predicting reaction energetics and rates for chemical processes with high accuracy, but with a very low computational cost," Isayev said. "We have shown that those machine learning models can be trained at high levels of quantum mechanics theory and can successfully predict energies and forces with quantum mechanics accuracy and an increase in speed of as much as 6-7 orders of magnitude. This is a new paradigm in reactive simulations."

Researchers tested ANI-1xnr on different chemical problems, including comparing biofuel additives and tracking methane combustion. They even recreated the Miller experiment, a famous chemical experiment meant to demonstrate how life originated on Earth. Using this experiment, they found that the ANI-1xnr model produced accurate results in condensed-phase systems.

Zhang said that the model could potentially be used for other areas in chemistry with further training.

"We found out it can be potentially used to simulate biochemical processes like enzymatic reactions," Zhang said. "We didn't design it to be used in such a way, but after modification it may be used for that purpose.

In the future, the team plans to refine ANI-1xnr and allow it to work with more elements and in more chemical areas, and they will try to increase the scale of the reactions it can process. This could allow it to be used in multiple fields where designing new chemical reactions could be relevant, such as drug discovery.

- This press release was originally published on the Carnegie Mellon University website

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Advancing Chemistry with AI: New Model for Simulating Diverse Organic Reactions - Lab Manager Magazine

Cardiology

PA Martine Altieri Brings an Obesity Medicine Clinic to Her Cardiology Patients – AAPA

PAs treat people with obesity every dayit affects every specialty

March 5, 2024

By Jennifer Walker

About nine years ago, when she was practicing in family medicine, Martine Altieri, PA-C, FMG, MHS, now a cardiology PA, was struck by how her collaborating physician addressed obesity with patients. He would tell them the long-held advice about treating this disease: They needed to exercise more; they needed to eat healthier food and less of it; they needed to fill half of their plate with greens. The patients really felt apprehensive about having this conversation because of the way he approached it and mostly blamed them for gaining weight, Altieri said. I always felt bad for them. I thought, Theres got to be another way.

During the pandemic, Altieri began to take courses on obesity medicine, completing the Fundamentals of Obesity Treatment course with the Obesity Medicine Association (OMA) and the Obesity Management in Primary Care Training and Certificate Program with AAPA in collaboration with The Obesity Society. In these programs, she learned how to approach an obesity diagnosis and craft comprehensive, evidence-based plans for patients based on the four pillars of clinical obesity treatment: nutrition therapy, physical activity, behavior modifications, and medical interventions.

Then in 2022, Altieri found a way to formally bring obesity medicine into her work. She was applying for a position with MyCardiologist, a group of private practices in Florida, when interviewers asked what new ideas she could bring to their practice. Altieri expressed a desire to start an obesity medicine clinic tailored to cardiology patients. She was hired and has since been making that dream a reality.

Today, Altieri, who is based in Boca Raton, Florida, is focusing on building up the clinic to address obesity, which was classified as a chronic disease by the American Medical Association in 2013. She is also a leader, advocate, and educator in several special-interest groups and AAPA caucuses, including PAs in Obesity Medicine, for which she is director at large. Altieriwho is also the public relations chair for PAs for Women Empowerment and a co-host for the Journal of the American Academy of PAs (JAAPA) podcastvalues this role because she sees the importance of all PAs learning how to approach obesity with their patients.

Every PA should be interested in obesity medicine, she said. It affects every specialty.

Addressing Obesity in a Cardiology Practice Altieri graduated from medical school in Haiti before moving to the United States in 2008 to be with her husband. To become a physician in the U.S., she would have had to go through the lengthy process of taking the three-step United States Medical Licensing Exam and completing at least a three-year residency program. Then she learned about the PA profession through her sister-in-law, and realized that she could practice more quickly if she became a PA.

After graduating from the PA program at Miami Dade College in 2010, Altieri practiced in family medicine, urgent care, and hospital medicine before transitioning to cardiology. At MyCardiologist, about 80% of her patients are age 70 or older. Altieri has a full schedule in this specialty: She does rounds at the hospital, cares for patients in an outpatient setting, and spends a half-day a week doing implants of loop recorders, a device that looks for causes of cardiac symptoms, such as irregular heartbeats and palpitations.

Yet, Altieri still has undertaken additional responsibilities to support her patients who have obesity and other chronic conditions that can increase the risk of cardiovascular diseases. She recently finished developing a template and resources for the obesity medicine clinic, including prioritizing the medication list and working with a dietician to create food plans that are specific for cardiac patients. When creating these resources, she thinks about her patients backgrounds. If you tell a Haitian patient they need to follow a Mediterranean diet, they dont know what that is, she said. We have to be specific. I give patients specific food lists so they know what they can buy and eat.

[For more information on obesity, check out AAPAs Obesity Toolkit]

When treating obesity, Altieri has also stuck to one approach that she learned in the beginning of her courses: She asks permission before starting the conversation. Not everyone is available or willing to talk about obesity, she said. You cant just offer obesity management. They have to be ready. Altieri likes to ask, May I talk to you about obesity? If her patients say no, she knows it is not the right time to address this topic.

Altieri also manages the Ambulatory Patient Monitoring Program to offer earlier interventions for patients who have high blood pressure, heart failure, and/or obesity. This initiative focuses on at-home monitoring of blood pressure, oxygen, pulse, and weight. Patients use a blood pressure device and a digital scale that transfer their readings to their charts via the cloud. Based on these metrics, which Altieri checks monthly, she will schedule virtual visits for patients if changes need to be made to their treatment plans for hypertension or heart failure. Altieri estimates there are more than 170 patients enrolled in the program.

We are looking for opportunities to add patients who have recurrent hospitalizations for heart failure or repeated ED visits with uncontrolled hypertension, and who we feel would benefit from more care at home, she said. Our goal is to prevent hospitalization and reduce ER visits. And patients like the idea of someone looking after them.

Educating Communities About Obesity and More Altieri is involved with several groups and activities that focus on various aspects of medicine. For PAs for Women Empowermentwhich focuses on advocating and promoting leadership roles for women in the PA profession and healthcare in generalAltieri manages the groups social media accounts. She educates the community about initiatives like The Pump Act, which states that mothers in the workplace have a right to break time and a secure spot to express milk for up to one year after their childs birth, and highlights women who hold or have held prominent positions within healthcare.

In 2023, Altieri also became a co-host for the JAAPA podcast. Previously, each episode of this show was focused on summarizing and reviewing JAAPA articles. But Altieri and her fellow co-host, PA Kim Ketchersid, introduced a new concept: They started to interview the authors who published the articles.

And since 2021, Altieriwho is currently working on a certification in cardiometabolic healthhas been a founding member of PAs in Obesity Medicine (PAOM). This group offers periodic information sessions that highlight obesity medicine education programs for PAs. PAOM also hosts webinars on obesity medicine topics throughout the year, such as a recent CME presentation on approaching and treating obesity from the endocrine perspective.

PAOM, whose membership has grown by 32% in three years, also plans to hold a meeting at AAPA 2024 in Houston, Texas, where several board members will present on obesity medicine. The groups goal is to reach as many PAs as possible with education and resources about the growing specialty.

PAs treat people with obesity every day, Altieri said. The more PAs know about obesity as a disease, the more we can help our patients.

Jennifer Walker is a freelance writer in Baltimore, MD. Contact Jennifer at[emailprotected].

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PA Martine Altieri Brings an Obesity Medicine Clinic to Her Cardiology Patients - AAPA

Cardiology

WEGOVY APPROVED FOR HEART RISK: U-Mich cardiology, obesity medicine experts available for interview – Newswise

BYLINE: Noah Fromson

On March 8, the U.S. Food and Drug Administration approved a new indication for the use of semaglutide (brand Wegovy) to reduce the risk of cardiovascular death, heart attack and stroke in adults with cardiovascular disease and either obesity or overweight. The FDA notes it should be used in addition to reduced calorie diet and increased physical activity. As you cover this, University of Michigan has experts in both prevention of cardiovascular disease and weight management/obesity medicine available for interview related to this development: Eric J. Brandt, M.D., M.H.S., is the director of preventive cardiology at the University of Michigan Health Frankel Cardiovascular Center. Brandt is a cardiologist/lipidologist and a clinical lecturer of internal medicine-cardiology at U-M Medical School.

Andrew Kraftson, M.D., is the director of the Weight Navigation Program and the Post-bariatric endocrinology clinic at the University of Michigan. Kraftson is an endocrinologist/obesity medicine specialist and a clinical associate professor of internal medicine-endocrinology at U-M Medical School. I am happy to facilitate an interview if you are interested. Noah Fromson (He/Him/His)Senior Public Relations Specialist & Medical Content ProducerFrankel Cardiovascular Center, Neurosciences, Kahn Pavilion, Broadcast ClipsC: (216) 509-8604

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WEGOVY APPROVED FOR HEART RISK: U-Mich cardiology, obesity medicine experts available for interview - Newswise

Cardiology

AHA Sums Up AI’s Potential in Cardiology, but Also the Hurdles Ahead – TCTMD

Questions about the impact of artificial intelligence (AI) on cardiovascular medicine should be qualified with a when rather than if, according to a new American Heart Association (AHA) scientific statement. Much work remains, though, before these tools can be widely trusted to improve patient care, the authors stress.

Outlining the ways AI, machine learning, and deep learning have already been engrained in medical practice as well as the tools in development, the authors express optimism about their potential to improve diagnosis and treatment as well as prevention, but had some words of caution. Despite enormous academic interest and industry financing, AI-based tools, algorithms, and systems of care have yet to improve patient outcomes at scale, the authors state.

As with any technology, we get excited about its impact, but I believe this is a technology where the impact is unknown, writing committee chair Antonis Armoundas, PhD (Massachusetts General Hospital, Boston, MA), told TCTMD.

Armoundas stressed the commitment of physicians to do no harm and pointed out that improper use of AI-based tools has the potential to adversely affect patients.

It feels like an Oppenheimer moment as we are trying to seek out how to improve outcomes for our patients, whether these are healthcare outcomes or quality of life, he explained. The speed at which this technology evolves makes us humble in being able to ground ourselves and think of the implications of what we are trying to accomplish, how we are going to achieve these goals, and being mindful of the potential negative effects that it could have.

The statement, published online last week in Circulation, is the AHAs second addressing AI this year, with the first directed specifically at its role in cardiac imaging.

What we should be seeking in the future is to build trust for these technologies, as with every other use of technology in medicine.Antonis Armoundas

With a wide variety of AI-based algorithms now available, including for reducing cath lab activation time in STEMI, detecting cardiomyopathy in pregnancy, and identifying heart failure or hypertrophic cardiomyopathy, the impact of these tools is already being felt by cardiologists. In compiling a statement of best practices and associated challenges, Armoundas said the AHA statement aimed to focus both on whats worked as well as identifying gaps and challenges, providing a framework for future efforts.

From clinicians to researchers, IT executives, and government entities, he said all invested stakeholders can take something away from the statement. This manuscript aims to provide a motive: a reason to go deeper and to look for more issues of interest, Armoundas said.

Best Practices and Associated Challenges

The authors identify six main uses and clinical applications of AI within the field of cardiology: cardiac imaging, electrocardiology, continuous bedside monitoring, mobile and wearable technologies, genetics, and electronic health records (EHR). Along with best practices for each of these categories, they list specific gaps and challenges as well. The biggest ones surround patient safety and data protection, bias and fairness, accountability and reliability, regulations and liability, cybersecurity and system upgrades, and clinical decision-making.

With in-hospital monitoring, for example, remote sensors may help improve the accuracy of alarms as well as reduce alarm fatigue. However, the authors point out that while this might sound appealing, limited data exist for these tools and the research that has been done shows that their effect can be altered by patient behavior.

Additionally, they cite the potential for AI to mine EHR data to make diagnoses and predict outcomes like in-hospital mortality. Again, though, challenges around EHR data curation and consistency have been shown to directly affect the potential for AI-based tools in this space, and the authors advise waiting until those issues are corrected before putting any algorithm into routine practice.

As exciting as many of these algorithms sound, Armoundas cautioned that there is a broad shortage of prospective data at this time, and among the studies that do have prospective designs, many are limited by narrow demographics. Increasing the generalizability of these algorithms will give these tools the chance to have a greater impact, he said. What we should be seeking in the future is to build trust for these technologies, as with every other use of technology in medicine.

This can only be done gradually, Armoundas continued, through prospective clinical trials. But the US Food and Drug Administration will also play a role in the way it labels these tools for use. If an algorithm is used as labeled by the FDA, perhaps that would provide the level of security and the level of trust when it is used by clinicians and when it has to be adopted by patients, he said, adding that this will be especially important as these tools start to be used in broader populations of patients than those in the initial studies.

Another issue, he explained, is how physicians can best incorporate their own opinions with the algorithm output when making clinical decisions. We argue that algorithms at this point are more likely to be used in conjunction with expert clinician opinion, albeit we do have evidence today, especially in imaging studies, that an algorithm can perform better than an expert clinician, Armoundas said. Going back to the point of using an algorithm on an as-labeled basis, that provides not only guidance to clinicians, but provides also a level of comfort in terms of liability.

Assigning a level of probability to these algorithms will also be imperative for incorporating them into clinical care so that clinicians can make informed judgements on how to act on the data provided, he added.

Keep an Eye on AI

In a commentary published on the AHAs Professional Heart Daily website, Caroline Marra, PhD, Joseph B. Franklin, JD, PhD, and Amy P. Abernethy, MD, PhD (all from Verily Life Sciences; South San Francisco, CA), write that though there is growing consensus on the need for adequate monitoring of AI tools, agreement on the right level of monitoring is lacking and figuring out how to accomplish monitoring across so many domains is a daunting challenge.

They argue for the creation of infrastructure to be able to simultaneously analyze multiple data sources but also acknowledge that thus far efforts to do this have generated more questions than answers.

Marra et al conclude that AI tools provide an incredible opportunity to enable continuous improvement, innovation, and equity in our healthcare systems and hold the potential to optimize health for all, with the caveat that this will only be possible and responsibly done if the performance of AI tools can be tracked as theyre deployed in practice.

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AHA Sums Up AI's Potential in Cardiology, but Also the Hurdles Ahead - TCTMD