New study looks at role of sleep disruption in dogs with dementia

Peer-Reviewed Publication

NORTH CAROLINA STATE UNIVERSITY

 

IMAGE: WOOFUS, A PARTICIPANT IN THE SLEEP STUDY, GETS ELECTRODES PLACED. view more 

CREDIT: JOHN JOYNER, NC STATE UNIVERSITY

Dogs with dementia suffer the same sleep disruptions that humans with dementia do. In a new study, researchers from North Carolina State University performed electroencephalography, or EEGs, on elderly dogs to determine whether brain-wave readings during sleep correlated with signs of cognitive decline. They found that dogs with more advanced dementia suffered more sleep disruptions and slept less overall than dogs with normal cognitive function.

The study – part of an ongoing clinical trial on canine aging and cognition at NC State – looked at 28 elderly dogs: 17 females and 11 males. Prior to the sleep study, the dogs had received complete physicals, undergone cognitive testing, and their owners completed the Canine Dementia Scale (CADES) questionnaire, in order to determine the severity of their cognitive decline.

The researchers used non-invasive techniques to gather their data – the dogs weren’t sedated, and the electrodes were affixed to the skull with sticky gel. The dogs did two sleep sessions in the lab – the first one to acclimate them to the surroundings and electrode placement, and the second to record brain activity during a two hour sleep period.

“Past sleep studies in dogs often involved surgically implanted electrodes,” says Alejandra Mondino, postdoctoral researcher at NC State and lead author of the study. “Non-invasive studies are relatively new. We are one of a handful of groups doing this work.”

The EEG measured four stages of sleep: wakefulness, drowsiness, NREM and REM. NREM, or non-REM, is a deep sleep state prior to REM (which stands for rapid eye movement and is associated with dreaming).

“In NREM, the brain clears toxins, including the beta-amyloid proteins that are involved in diseases like Alzheimer’s,” Mondino says. “REM sleep is when dreams happen, and this stage is very important for memory consolidation.”

The researchers correlated the percentage of time spent in each sleep state with the dogs’ scores on cognitive testing and the CADES questionnaire. The higher the dog’s dementia score, the less time they spent in NREM and REM sleep.

“These dogs have dementia and sleep disruption is part of that,” Mondino says. “In addition to the shorter time spent sleeping, when we look at the EEG, we saw their brain activity during sleep was more akin to wakefulness.

“In other words, when they do manage to sleep, their brains aren’t really sleeping.”

The work is an important part of establishing baselines for identifying cognitive decline in dogs. The researchers hope that the work can lead to early diagnosis and intervention for elderly dogs with signs of cognitive decline.

“We now know that EEG signatures are useful indicators of canine cognitive dysfunction,” says Natasha Olby, the Dr. Kady M. Gjessing and Rahna M. Davidson Distinguished Chair in Gerontology at NC State and corresponding author of the study. “The work further establishes the dog as a model for Alzheimer’s disease. Hopefully therapeutic trials in dogs will help to direct our choices of treatment development for people.”

The work appears in Frontiers in Veterinary Science and was supported by the Kady M. Gjessing and Rahna M. Davidson Distinguished Chair in Gerontology, the Sleep Research Society Foundation (Grant 04-SRG-21) and the Company of Biologists (Grant DMMTF2205727).

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Note to editors: An abstract follows.

“Sleep and cognition in aging dogs. A polysomnographic study”

DOI: 10.3389/fvets.2023.1151266

Authors: Alejandra Mondino, Michael Khan, Claire Ludwig, Margaret Elizabeth Gruen and Natasha J. Olby, North Carolina State University; Magaly Catanzariti, Instituto de Matemática Aplicada del Litoral Santa Fe, Argentina; Diego Martin Mateos, Instituto de Matemática Aplicada del Litoral Santa Fe, Argentina and Universidad Autónoma de Entre Ríos (UADER), Entre Ríos, Argentina; Anna Kis, Research Centre for Natural Sciences, Institute of Cognitive Neuroscience and Psychology, Budapest, Hungary
Published: Apr. 28, 2023 in Frontiers in Veterinary Science

Abstract:
Introduction: Sleep is fundamental for cognitive homeostasis, especially in senior populations since clearance of amyloid beta (key in the pathophysiology of Alzheimer’s disease) occurs during sleep. Some electroencephalographic characteristics of sleep and wakefulness have been considered a hallmark of dementia. Owners of dogs with canine cognitive dysfunction syndrome (a canine analog to Alzheimer’s disease) report that their dogs suffer from difficulty sleeping. The aim of this study was to quantify age-related changes in the sleep-wakefulness cycle macrostructure and electroencephalographic features in senior dogs and to correlate them with their cognitive performance.
Methods: We performed polysomnographic recordings in 28 senior dogs during a 2 h afternoon nap. Percentage of time spent in wakefulness, drowsiness, NREM, and REM sleep, as well as latency to the three sleep states were calculated. Spectral power, coherence, and Lempel Ziv Complexity of the brain oscillations were estimated. Finally, cognitive performance was evaluated by means of the Canine Dementia Scale Questionnaire and a battery of cognitive tests. Correlations between age, cognitive performance and sleep-wakefulness cycle macrostructure and electroencephalographic features were calculated.
Results: Dogs with higher dementia scores and with worse performance in a problem-solving task spent less time in NREM and REM sleep. Additionally, quantitative electroencephalographic analyses showed differences in dogs associated with age or cognitive performance, some of them reflecting shallower sleep in more affected dogs.
Discussion: Polysomnographic recordings in dogs can detect sleep-wakefulness cycle changes associated with dementia. Further studies should evaluate its potential clinical use to monitor the progression of canine cognitive dysfunction syndrome.

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JOURNAL

Frontiers in Veterinary Science

DOI

10.3389/fvets.2023.1151266 

ARTICLE TITLE

Sleep and cognition in aging dogs. A polysomnographic study

ARTICLE PUBLICATION DATE

28-Apr-2023

Old dogs with dementia sleep less

deeply, just like people with Alzheimer’s

Dogs with higher dementia scores and worse performance in problem-solving task show changes in brain waves symptomatic of shallow sleep

FRONTIERS

In people with Alzheimer’s, the earliest symptoms are commonly disruptions in sleep rhythms. These include daytime sleepiness, showing agitation or confusion around dusk, staying awake longer, and waking up often at night. These changes are thought to result from damage to sleep-regulating areas in the brain. Alzheimer patients tend to spend less time in both REM (rapid eye movement) sleep, in which most dreaming occurs, and non-REM (NREM) sleep. But they show the greatest reduction in so-called slow-wave sleep (SWS) – a stage of non-dreaming deep sleep, characterized by slow ‘delta’ brain waves (0.1 to 3.5 Hz) – when day-time memories are consolidated.

Now, scientists have shown that the same reduction in sleep time and delta brain waves occurs in dogs with the canine equivalent of dementia, canine cognitive dysfunction syndrome (CCDS). These dogs thus sleep less and less deeply. The results are published in Frontiers in Veterinary Science.

“Our study is the first to evaluate the association between cognitive impairment and sleep using polysomnography – the same technique as used in sleep studies in people – in aged dogs,” said senior author Dr Natasha Olby, a professor of veterinary neurology and neurosurgery at North Carolina State University.

Old dogs with or without dementia

Olby and colleagues studied 28 female and male senior mixed- and full-breed dogs between 10.4 and 16.2 years of age, which corresponds to between 81% and 106% of their average lifespan, depending on size. Their owners were asked to fill in a questionnaire about their canine companions, to rate the severity of symptoms of CCDS like disorientation, poor social interactions, and house soiling. The researchers also examined the dogs for possible orthopedic, neurological, biochemical, and physiological co-morbidities.

Based on the results, eight dogs (28.5%) were classified as normal, while another eight (28.5%), four (14.3%), and eight (28.5%) had mild, moderate, or severe CCDS, respectively.

The researchers then performed a series of cognitive tests on the dogs, to measure their attention, working memory, and executive control. For example, in the ‘detour task’, a dog had to retrieve a treat from a horizontal transparent cylinder by accessing it from either end – this task is then made more difficult by blocking off her or his preferred side so they have to show cognitive flexibility to detour to the other end of the cylinder.

Sleep clinic for dogs

Then, first author Dr Alejandra Mondino (a postdoctoral fellow in Olby’s research group) and colleagues performed a polysomnography studies in a quiet room with dim light and white noise in a ‘sleep clinic’. The dogs were allowed to spontaneously take an afternoon noon nap, while electrodes measured their brain waves, the electrical activity of the muscles and heart, and eye movements. These measurements lasted up to two hours, but were stopped if the dogs became anxious, attempted to leave the room, or removed the electrodes. 26 (93%) dogs entered drowsiness, 24 (86%) entered NREM sleep, while 15 (54%) entered REM sleep.

The results showed that dogs with higher dementia scores, and dogs who did worse on the detour task, took longer to fall asleep and spent less time sleeping, and this was true for both NREM and REM sleep.

Dogs with poorer memory scores showed changes, such as fewer slow oscillations in their electroencephalograms, during REM sleep, indicating that they slept less deeply during this phase.

“In people, slow brain oscillations are characteristic of SWS and linked to the activity of the so-called ‘glymphatic system, a transport system that removes protein waste products from the cerebrospinal fluid,” said Olby.

“The reduction in slow oscillations in people with Alzheimer’s, and the associated reduced removal of these toxins, has been implicated in their poorer memory consolidation during deep sleep.”

In contrast, dogs with poorer memory had more pronounced fast beta waves, between 15.75 and 19 Hz. Strong beta waves are typical of wakefulness in healthy people and dogs, so are not a normal phenomenon during sleep – again indicating that dogs with CCDS sleep less deeply.

Day sleeping versus night sleeping

Dogs which did worse at the ‘sustained gaze’ task, which measures attention span, showed tighter coupling in delta waves between the two brain hemispheres – a result that has also been found in people with dementia.

The authors concluded that the dogs with CCDS showed changes in the sleep-wakefulness cycle during the experiments that resemble those found in people with Alzheimer’s. But they caution that it’s still unknown if these changes also occur during when dogs sleep at night instead of in the afternoon.

“Our next step will be to follow dogs over time during their adult and senior years to determine if there are any early markers in their sleep-wakefulness patterns, or in the electrical activity of their brain during sleep, that could predict the future development of cognitive dysfunction,” said Olby.

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JOURNAL

Frontiers in Veterinary Science

DOI

10.3389/fvets.2023.1151266 

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

Animals

ARTICLE TITLE

Sleep and cognition in aging dogs. A polysomnographic study

ARTICLE PUBLICATION DATE

28-Apr-2023

Study shines light on impact of environment on neurocognitive outcomes

Scientists from St. Jude Children’s Research Hospital investigated neighborhood-level economic hardship and its effect on cognitive outcomes in children treated with radiation for brain tumors.

Peer-Reviewed Publication

ST. JUDE CHILDREN'S RESEARCH HOSPITAL

 

IMAGE: HEATHER CONKLIN, PHD, ST. JUDE DEPARTMENT OF PSYCHOLOGY AND BIOBEHAVIORAL SCIENCES view more 

CREDIT: ST. JUDE CHILDREN'S RESEARCH HOSPITAL

To gain a clearer understanding of the differences between childhood cancer patients when it comes to the impact of radiation therapy on cognition, scientists at St. Jude Children’s Research Hospital studied the effect of their environment. Their work showed that children with supportive environments fared better than children living in neighborhoods with economic hardship. Those in areas with greater economic hardship had worse baseline and long-term cognitive outcomes. The results imply that policies and resources providing support at a neighborhood level may help protect high-risk pediatric brain tumor patients from cognitive decline. The findings were published recently in Neuro-Oncology.

“At the simplest level, we found a patient’s environment matters,” said corresponding author Heather Conklin, Ph.D., St. Jude Department of Psychology and Biobehavioral Sciences. “It's not just the diagnosis or treatment the patient receives. It's also the family, neighborhood and support they can access that predicts cognitive outcomes.”

The study used a framework called the economic hardship index (EHI) to study how a patient’s neighborhood could correlate with cognitive outcomes. The researchers found that higher EHI score was associated with patients who entered treatment with lower cognitive abilities as well as those who had a greater cognitive decline, especially in math skills, after treatment.

“Economic hardship at the neighborhood level predicted how these patients performed cognitively at baseline, before radiation therapy, and then also based on what EHI quartile they were, how much they declined or stayed stable over time,” Conklin said.

This predictive power rivaled that of already known risk factors for cognitive decline in these patients.

“The gaps that were present prior to treatment widened over time and had more of a relative impact than the well-established clinical factors, such as age at radiation therapy,” Conklin said.

Assessing patients at the neighborhood level

While a preliminary analysis, using the EHI is a way to account for the environment surrounding patients. It includes information on six factors: unemployment, dependency, education, income, crowded housing and poverty. That information is collected and presented at the Census block level, groups of 250 and 550 housing units, including almost every neighborhood in the United States.

“This is the first time someone in the oncology space has used a neighborhood level variable rather than a family specific measure to predict cognitive outcomes in children treated for brain tumors,” Conklin said. “The reason that's important is that it gives us more nuanced information about the context in which the child is living. It also opens new areas where we can develop interventions to improve cognitive outcomes.”

The paper follows a growing body of research showing that lower socioeconomic status can predict worse cognitive outcomes in pediatric brain tumor patients treated with radiation. St. Jude patients in the study all received similar state-of-art care at no expense, therefore at least some of the differences in outcomes were likely due to non-treatment factors, such as living in a high poverty area. Within the overall EHI score components, the factor that most correlated with poor outcomes was neighborhood-level poverty.

“Even though St. Jude is at the forefront of pediatric brain tumor care, there are still challenges for our patients,” Conklin said. “St. Jude patients receive physical, occupational and speech therapy while they're here, but they still go back home to their neighborhoods that maybe are higher in crime or have poorer schools or are overcrowded. They may not have access to the same level of resources once their treatment concludes and they return to their community.”

This suggests environmental conditions in high poverty areas, not individual choice, has a strong effect on long-term outcomes. Therefore, patients are likely to benefit if physicians and policymakers come up with solutions to address these factors for current and future pediatric patients with brain tumors.

Changing practice to protect cognitive outcomes

While the research demonstrated that EHI can be used to predict poor cognitive outcomes beyond traditional treatment and clinical risk factors, it is not ready to be widely adopted into clinical practice. There is still more to learn about the drivers of cognitive differences. Therefore, clinicians need to be sensitive and resourceful when trying to help patient families from high EHI areas proactively protect their child’s cognitive health.

“I think in terms of how we practice, as a clinician I have to think about how I bring this to my families,” Conklin said. “Clinicians need to learn how to talk effectively to families about factors related to economic hardship. We should be thinking creatively about how to help families we know are in a riskier category.”

“For example, we can suggest enriching activities that may fit with caregiver’s schedule and resources to help prevent cognitive decline like going to parks, going to libraries and reading regularly at home,” Conklin explained. “We just need to take into account the family’s context – these activities need to be things families can do that are free, don't require them to take off from work and allow single parents of multiple kids to figure out how to work this into their lifestyle.”

One of the study’s bright spots is the finding that some of these social or policy interventions may help. Patients with a low EHI (those from neighborhoods of higher socioeconomic status) had better baseline and long-term cognitive outcomes. That fact gives some hope – by increasing access to the resources available to families from lower socioeconomic status, clinicians and policymakers may be able to be better protect against cognitive decline in pediatric patients treated with radiation for brain tumors.

Authors and funding

The study’s first author was Taylor Mule, The University of Memphis. The study’s other authors are Jason Hodges, Shengjie Wu, Yimei Li, Jason Ashford and Thomas Merchant, of St. Jude.

The study was supported by grants from the National Cancer Institute (P30 CA21765) and ALSAC, the fundraising and awareness organization of St. Jude.

St. Jude Children's Research Hospital

St. Jude Children's Research Hospital is leading the way the world understands, treats and cures childhood cancer, sickle cell disease and other life-threatening disorders. It is the only National Cancer Institute-designated Comprehensive Cancer Center devoted solely to children. Treatments developed at St. Jude have helped push the overall childhood cancer survival rate from 20% to 80% since the hospital opened more than 60 years ago. St. Jude shares the breakthroughs it makes to help doctors and researchers at local hospitals and cancer centers around the world improve the quality of treatment and care for even more children. To learn more, visit stjude.org, read St. Jude Progress blog, and follow St. Jude on social media at @stjuderesearch. 

JOURNAL

Neuro-Oncology

DOI

10.1093/neuonc/noad080 

METHOD OF RESEARCH

Randomized controlled/clinical trial

SUBJECT OF RESEARCH

People

ARTICLE TITLE

Social Determinants of Cognitive Outcomes in Survivors of Pediatric Brain Tumors Treated with Conformal Radiation Therapy

ARTICLE PUBLICATION DATE

26-Apr-2023

Ohio University professor Nancy Stevens helps uncover ecosystem evolution in Africa in paper published in Science

Peer-Reviewed Publication

OHIO UNIVERSITY

Ohio University’s Nancy J. Stevens Ph.D., distinguished professor in the Department of Biomedical Sciences in the Heritage College of Osteopathic Medicine, is coauthor on a paper published in the journal Science and funded by the National Science Foundation that documents the evolution of grassland ecosystems on continental Africa.  

Collaborating with an extensive team of geologists and paleoanthropologists from universities around the world, led by researchers from Baylor University and the University of Minnesota, the team synthesized data from nine Early Miocene fossil localities in the East African Rift of Kenya and Uganda to determine that the expansion of grassy biomes dominated by grasses with the C4 photosynthetic pathway in Eastern Africa occurred more than 10 million years earlier.

According to the paper, previous reconstructions of early Miocene ecosystems, 15-20 million years ago, have suggested that equatorial Africa was covered by a semi-continuous forest, with open habitats dominated by warm-season, or C4, grasses that were uncommon until 8-10 million years ago. C4 refers to the different pathways that plants use to capture carbon dioxide during photosynthesis. C4 plants produce a four-carbon molecule and are more adapted to warm or hot season condition under moist or dry environments.

As the researchers gathered expertise about geological features, isotopes and fossils found at the sites, the paradigm of a continuous forest blanketing equatorial Africa during the early Miocene shifted to a more complex mosaic of habitats that already included open environments with C4 grasses.  

The result of this research pushes back the oldest evidence of C4 grass-dominated habitats in Africa – and globally – by more than 10 million years, with important implications for primate evolution and the origins of tropical C4 grasslands and savanna ecosystems across the African continent and around the world.  

“We suspected that we would find C4 plants at some sites, but we didn't expect to find them at as many sites as we did, and in such high abundance,” Daniel Peppe, lead author and associate professor at Baylor University, said.

A critical aspect of this work was that the team combined many different lines of evidence together: geology, fossil soils, isotopes and phytoliths (plant silica microfossils) to reach their conclusions.

“This research is a big win for collaborative science and documents the value of looking ever deeper in time, and more synthetically across disciplines, to better understand the ecological backdrop for faunal and floral evolution,” Stevens added. “It’s an exciting time to investigate environmental change, and projects like this one generate pivotal data for charting future decisions about resource use and wellbeing on our planet today.”

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JOURNAL

Science

DOI

10.1126/science.abq2834 

METHOD OF RESEARCH

Observational study

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Oldest evidence of abundant C4 grasses and habitat heterogeneity in eastern Africa

U of T receives $200-million grant to support Acceleration Consortium's ‘self-driving labs’ research

The University of Toronto has been awarded a $200-million grant from the Canada First Research Excellence Fund (CFREF) to revolutionize the speed and impact of scientific discovery through its Acceleration Consortium.

Business Announcement

UNIVERSITY OF TORONTO

 

IMAGE: ALÁN ASPURU-GUZIK POSING WITH A ROBOTIC ARM IN THE MATTER LAB. view more 

CREDIT: PHOTO BY LIZ BEDDALL, COURTESY OF CIFAR

The University of Toronto has been awarded a $200-million grant from the Canada First Research Excellence Fund (CFREF) to revolutionize the speed and impact of scientific discovery through its Acceleration Consortium. The funding – the largest federal research grant ever awarded to a Canadian university – will support the consortium’s work on “self-driving labs” that combine artificial intelligence, robotics and advanced computing to discover new materials and molecules in a fraction of the usual time and cost. Applications include everything from life-saving medications and biodegradable plastics to low-carbon cement and renewable energy.

Researchers in the consortium recently revealed that they used the technology to develop a potential cancer drug in just 30 days – a process that typically takes years, or even decades.

“The University of Toronto is grateful for this significant investment in artificial intelligence-driven research and innovation, which promises to improve the lives of Canadians and those of people around the world,” said U of T President Meric Gertler.

“The federal government’s critical support of this initiative builds on years of strategic planning and decisions in this space by the University and the federal government, including the 2017 launch of the Pan-Canadian Artificial Intelligence Strategy that helped cement Toronto’s status as a global hub for a revolutionary technology.

“This is the next step in achieving that bold vision.”

François-Philippe Champagne, minister of innovation, science and industry, announced the U of T funding alongside 10 other large-scale projects across the country.

“The initiatives announced today will lead to breakthrough discoveries that will improve people’s lives, nourish our innovation ecosystems, and shape Canada’s prosperity for years to come,” he said in a statement. “Such is the value of Canadian institutions and researchers who think outside the box to tackle the greatest challenges of our time.”

Launched as an Institutional Strategic Initiative in 2021, the Acceleration Consortium brings together partners from academia, government and industry who are accelerating the discovery of materials and molecules needed for a sustainable future. The consortium aims to reduce the time and cost of bringing advanced materials to market, from an average of 20 years and $100 million to as little as one year and $1 million.  

“Our goal is to accelerate science,” said Acceleration Consortium Director Alán Aspuru-Guzik, a professor in the departments of chemistry and computer science in the Faculty of Arts & Science who is a CIFAR AI Chair at the Vector Institute for Artificial Intelligence. “To do that, we realized we need to take a cue from self-driving cars and extended that concept to a self-driving lab, which uses AI and automation to carry out more experiments in a smarter way.

“We’ve essentially supercharged the process of scientific discovery.”

A self-driving lab capable of automated liquid dispensing, solid dispensing, and high-throughput batch synthesis which is connected to the automated purification, and optical characterization setup.

CREDIT

Photo by Johnny Guatto © The Matter Lab / Acceleration Consortium, University of Toronto

The CFREF funding, along with additional support from U of T – which includes an investment of $130 million to expand facilities to house the Acceleration Consortium’s state-of-the-art labs at the Lash Miller Chemical Laboratories building on the St. George campus – will help secure the researchers, spaces and partnerships needed to build a world-leading centre for accelerated materials discovery and innovation.

The funding will also help the consortium rapidly create high quality datasets to better train AI models and validate the model’s predictions in real time. That, in turn, will dramatically accelerate the discovery and development of molecules and materials for a wide range of industries.

With a strong plan of equity, diversity and inclusion guiding project implementation and research design, the initiative will commercialize ethically designed technologies and materials to benefit society and train today’s scientists with the skills they need to advance the emerging field of accelerated materials discovery. It will also allow the consortium to examine critical issues regarding the application of the technology, including from environmental and Indigenous perspectives.

“With this funding – which enabled us to obtain matching commitments of about $300 million from all our partners – we are talking about half a billion dollars of investments, said Aspuru-Guzik, who joined U of T from Harvard University in 2018 as a Canada 150 Research Chair in Theoretical and Quantum Chemistry and is one of a growing number of global experts at the Acceleration Consortium.

“This will help us make the Greater Toronto Area and Canada world leaders in AI-frontier discovery – we have no excuse not to be after this project.”

The Acceleration Consortium comprises nearly 100 researchers – and is hiring many more – across a wide variety of disciplines, including AI, computer science, mathematics, chemistry, economics, engineering, materials science, mechatronics, biology, pharmacology, robotics, technoscience and more. It also includes 30 partners from the private and public sector, including the University of British Columbia, a lead partner on the grant.

“What’s unique about this model is that it’s kind of this idea of a university without borders,” said Jason Hein, Acceleration Consortium’s associate director of academic partnerships and an associate professor in the chemistry department in the Faculty of Science at UBC.

“What happens a lot in Canadian research culture is that we’re good at punching above our weight class, but, in the past, other countries have had bigger budgets. What’s great about this is that through the energy of the people at Acceleration Consortium, we’re saying, ‘We’re doing something huge here.’ And to get the vote of confidence back saying, ‘Yes, we believe in you and let’s go forward’ is really important.”

CFREF aims to boost the strengths of Canadian postsecondary institutions so that they can achieve global success in research areas that create long-term social and economic advantages for Canada. It invests approximately $200 million per year (or approximately $1.4 billion over a competition cycle of seven years) through a highly competitive peer review process.

“We named this a consortium and not an institute for a reason,” Aspuru-Guzik said. “We are a global effort with its homebase in Toronto that involves academia, government and industry.

“A core goal of our efforts is to spin out the next generation of companies that will develop the materials for the 21st century here in Canada. This, in turn, will help make the GTA the economic epicentre for this field.”

Leah Cowen, U of T’s vice-president, research and innovation, and strategic initiatives, said the impact of the CFREF grant will be felt far beyond Acceleration Consortium itself.

“This level of investment can really transform how universities do innovation,” she said. “It allows us to not only drive forward discovery, but also improve adoption by Canadian companies and foster an ethical approach to technology development that’s guided by principles of equity, diversity and inclusion, benefiting all segments of society.”

Structured exploration allows biological brains to learn faster than AI

Scientists discover exploratory actions make learning more efficient

Peer-Reviewed Publication

SAINSBURY WELLCOME CENTRE

 

IMAGE: MOUSE EXPLORING THE ENVIRONMENT TO LEARN HOW TO NAVIGATE AROUND AN OBSTACLE IN THE WAY TO A SHELTER view more 

CREDIT: SAINSBURY WELLCOME CENTRE

Neuroscientists have uncovered how exploratory actions enable animals to learn their spatial environment more efficiently. Their findings could help build better AI agents that can learn faster and require less experience.

Researchers at the Sainsbury Wellcome Centre and Gatsby Computational Neuroscience Unit at UCL found the instinctual exploratory runs that animals carry out are not random. These purposeful actions allow mice to learn a map of the world efficiently. The study, published today in Neuron, describes how neuroscientists tested their hypothesis that the specific exploratory actions that animals undertake, such as darting quickly towards objects, are important in helping them learn how to navigate their environment.

“There are a lot of theories in psychology about how performing certain actions facilitates learning. In this study, we tested whether simply observing obstacles in an environment was enough to learn about them, or if purposeful, sensory-guided actions help animals build a cognitive map of the world,” said Professor Tiago Branco, Group Leader at the Sainsbury Wellcome Centre and corresponding author on the paper.

In previous work, scientists at SWC observed a correlation between how well animals learn to go around an obstacle and the number of times they had run to the object. In this study, Philip Shamash, SWC PhD student and first author of the paper, carried out experiments to test the impact of preventing animals from performing exploratory runs. By expressing a light-activated protein called channelrhodopsin in one part of the motor cortex, Philip was able to use optogenetic tools to prevent animals from initiating exploratory runs towards obstacles.

The team found that even though mice had spent a lot of time observing and sniffing obstacles, if they were prevented in running towards them, they did not learn. This shows that the instinctive exploratory actions themselves are helping the animals learn a map of their environment.

To explore the algorithms that the brain might be using to learn, the team worked with Sebastian Lee, a PhD student in Andrew Saxe’s lab at SWC, to run different models of reinforcement learning that people have developed for artificial agents, and observe which one most closely reproduces the mouse behaviour.

There are two main classes of reinforcement learning models: model-free and model-based. The team found that under some conditions mice act in a model-free way but under other conditions, they seem to have a model of the world. And so the researchers implemented an agent that can arbitrate between model-free and model-based. This is not necessarily how the mouse brain works, but it helped them to understand what is required in a learning algorithm to explain the behaviour.

“One of the problems with artificial intelligence is that agents need a lot of experience in order to learn something. They have to explore the environment thousands of times, whereas a real animal can learn an environment in less than ten minutes. We think this is in part because, unlike artificial agents, animals’ exploration is not random and instead focuses on salient objects. This kind of directed exploration makes the learning more efficient and so they need less experience to learn,” explain Professor Branco.   

The next steps for the researchers are to explore the link between the execution of exploratory actions and the representation of subgoals. The team are now carrying out recordings in the brain to discover which areas are involved in representing subgoals and how the exploratory actions lead to the formation of the representations.

Graphical depiction of a mouse navigating to shelter

CREDIT

Julia Kuhl

This research was funded by a Wellcome Senior Research Fellowship (214352/Z/18/Z) and by the Sainsbury Wellcome Centre Core Grant from the Gatsby Charitable Foundation and Wellcome (090843/F/09/Z), the Sainsbury Wellcome Centre PhD Programme and a Sir Henry Dale Fellowship from the Wellcome Trust and Royal Society (216386/Z/19/Z).

Source:

Read the full paper in Neuron: ‘Mice identify subgoal locations through an action-driven mapping process’ DOI: 10.1016/j.neuron.2023.03.034

Media contact:

For more information or to speak to the researchers involved, please contact:

April Cashin-Garbutt
Head of Research Communications and Engagement, Sainsbury Wellcome Centre
E: a.cashin-garbutt@ucl.ac.uk T: +44 (0)20 3108 8028

About the Sainsbury Wellcome Centre
The Sainsbury Wellcome Centre (SWC) brings together world-leading neuroscientists to generate theories about how neural circuits in the brain give rise to the fundamental processes underpinning behaviour, including perception, memory, expectation, decisions, cognition, volition and action. Funded by the Gatsby Charitable Foundation and Wellcome, SWC is located within UCL and is closely associated with the Faculties of Life Sciences and Brain Sciences. For further information, please visit: www.sainsburywellcome.org

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JOURNAL

Neuron

DOI

10.1016/j.neuron.2023.03.034 

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

Animals

ARTICLE TITLE

Mice identify subgoal locations through an action-driven mapping process

ARTICLE PUBLICATION DATE

28-Apr-2023

Disclaimer: A

Comparing physician and AI chatbot responses to patient questions

Peer-Reviewed Publication

JAMA NETWORK

About The Study: In this study of 195 randomly drawn patient questions from a social media forum, a team of licensed health care professionals compared physician’s and chatbot’s responses. The chatbot responses were preferred over physician responses and rated significantly higher for both quality and empathy. Further exploration of this technology is warranted in clinical settings, such as using chatbot to draft responses that physicians could then edit. Randomized trials could assess further if using AI assistants might improve responses, lower clinician burnout, and improve patient outcomes. 

Authors: John W. Ayers, Ph.D., M.A., of the University of California San Diego, La Jolla, is the corresponding author.

(doi:10.1001/jamainternmed.2023.1838)

Editor’s Note: Please see the article for additional information, including other authors, author contributions and affiliations, conflict of interest and financial disclosures, and funding and support.

 https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/10.1001/jamainternmed.2023.1838?guestAccessKey=cc017939-cb8d-4cf0-bf64-11492a83ade0&utm_source=For_The_Media&utm_medium=referral&utm_campaign=ftm_links&utm_content=tfl&utm_term=042823

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JOURNAL

JAMA Internal Medicine

Study finds ChatGTP outperforms physicians in providing high-quality, empathetic advice to patient questions

While AI won’t replace your doctor, the JAMA Internal Medicine paper suggests physicians working together with technologies like ChatGPT may revolutionize medicine

Peer-Reviewed Publication

UNIVERSITY OF CALIFORNIA - SAN DIEGO

La Jolla, Calif. (April 28, 2023) — There has been widespread speculation about how advances in artificial intelligence (AI) assistants like ChatGPT could be used in medicine. 

A new study published in JAMA Internal Medicine led by Dr. John W. Ayers from the Qualcomm Institute within the University of California San Diego provides an early glimpse into the role that AI assistants could play in medicine. The study compared written responses from physicians and those from ChatGPT to real-world health questions. A panel of licensed healthcare professionals preferred ChatGPT’s responses 79% of the time and rated ChatGPT’s responses as higher quality and more empathetic. 

“The opportunities for improving healthcare with AI are massive,” said Ayers, who is also vice chief of innovation in the UC San Diego School of Medicine Division of Infectious Disease and Global Public Health. “AI-augmented care is the future of medicine.” 

Is ChatGPT Ready for Healthcare?

In the new study, the research team set out to answer the question: Can ChatGPT respond accurately to questions patients send to their doctors? If yes, AI models could be integrated into health systems to improve physician responses to questions sent by patients and ease the ever-increasing burden on physicians.

“ChatGPT might be able to pass a medical licensing exam," said study co-author Dr. Davey Smith, a physician-scientist, co-director of the UC San Diego Altman Clinical and Translational Research Institute and professor at the UC San Diego School of Medicine, “but directly answering patient questions accurately and empathetically is a different ballgame.” 

“The COVID-19 pandemic accelerated virtual healthcare adoption,” added study co-author Dr. Eric Leas, a Qualcomm Institute affiliate and assistant professor in the UC San Diego Herbert Wertheim School of Public Health and Human Longevity Science. “While this made accessing care easier for patients, physicians are burdened by a barrage of electronic patient messages seeking medical advice that have contributed to record-breaking levels of physician burnout.”

Designing a Study to Test ChatGPT in a Healthcare Setting

To obtain a large and diverse sample of healthcare questions and physician answers that did not contain identifiable personal information, the team turned to social media where millions of patients publicly post medical questions to which doctors respond: Reddit’s AskDocs. 

r/AskDocs is a subreddit with approximately 452,000 members who post medical questions and verified healthcare professionals submit answers. While anyone can respond to a question, moderators verify healthcare professionals’ credentials and responses display the respondent’s level of credentials. The result is a large and diverse set of patient medical questions and accompanying answers from licensed medical professionals.

While some may wonder if question-answer exchanges on social media are a fair test, team members noted that the exchanges were reflective of their clinical experience. 

The team randomly sampled 195 exchanges from AskDocs where a verified physician responded to a public question. The team provided the original question to ChatGPT and asked it to author a response. A panel of three licensed healthcare professionals assessed each question and the corresponding responses and were blinded to whether the response originated from a physician or ChatGPT. They compared responses based on information quality and empathy, noting which one they preferred.

The panel of healthcare professional evaluators preferred ChatGPT responses to physician responses 79% of the time. 

“ChatGPT messages responded with nuanced and accurate information that often addressed more aspects of the patient’s questions than physician responses,” said Jessica Kelley, a nurse practitioner with San Diego firm Human Longevity and study co-author.   

Additionally, ChatGPT responses were rated significantly higher in quality than physician responses: good or very good quality responses were 3.6 times higher for ChatGPT than physicians (physicians 22.1% versus ChatGPT 78.5%). The responses were also more empathic: empathetic or very empathetic responses were 9.8 times higher for ChatGPT than for physicians (physicians 4.6% versus ChatGPT 45.1%). 

“I never imagined saying this,” added Dr. Aaron Goodman, an associate clinical professor at UC San Diego School of Medicine and study coauthor, “but ChatGPT is a prescription I’d like to give to my inbox. The tool will transform the way I support my patients.”

Harnessing AI Assistants for Patient Messages  

“While our study pitted ChatGPT against physicians, the ultimate solution isn’t throwing your doctor out altogether,” said Dr. Adam Poliak, an assistant professor of Computer Science at Bryn Mawr College and study co-author. “Instead, a physician harnessing ChatGPT is the answer for better and empathetic care.”

“Our study is among the first to show how AI assistants can potentially solve real world healthcare delivery problems,” said Dr. Christopher Longhurst, Chief Medical Officer and Chief Digital Officer at UC San Diego Health. “These results suggest that tools like ChatGPT can efficiently draft high quality, personalized medical advice for review by clinicians, and we are beginning that process at UCSD Health.” 

Dr. Mike Hogarth, a physician-bioinformatician, co-director of the Altman Clinical and Translational Research Institute at UC San Diego, professor in the UC San Diego School of Medicine and study co-author, added, “It is important that integrating AI assistants into healthcare messaging be done in the context of a randomized controlled trial to judge how the use of AI assistants impact outcomes for both physicians and patients.”  

In addition to improving workflow, investments into AI assistant messaging could impact patient health and physician performance. 

Dr. Mark Dredze, the John C Malone Associate Professor of Computer Science at Johns Hopkins and study co-author, noted: “We could use these technologies to train doctors in patient-centered communication, eliminate health disparities suffered by minority populations who often seek healthcare via messaging, build new medical safety systems, and assist doctors by delivering higher quality and more efficient care.” 

In addition to Ayers, Poliak, Dredze, Leas, Kelley, Goodman, Longhurst, Hogarth and Smith, authors of the JAMA Internal Medicine paper, “Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum” (JAMA Intern Med. doi:10.1001/jamainternmed.2023.1838), are Zechariah Zhu of  UC San Diego and Dr. Dennis J. Faix of the Naval Health Research Center. 

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JOURNAL

JAMA Internal Medicine

DOI

10.1001/jamainternmed.2023.1838 

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

People

ARTICLE TITLE

Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum

ARTICLE PUBLICATION DATE

28-Apr-2023

COI STATEMENT

Disclosures as reported in the paper: Dr Ayers reported owning equity in companies focused on data analytics, Good Analytics, of which he was CEO until June 2018, and Health Watcher. Dr Dredze reported personal fees from Bloomberg LP and Sickweather outside the submitted work and owning an equity position in Good Analytics. Dr Leas reported personal fees from Good Analytics during the conduct of the study. Dr Goodman reported personal fees from Seattle Genetics outside the submitted work. Dr Hogarth reported being an advisor for LifeLink, a health care chatbot company. Dr Longhurst reported being an advisor and equity holder at Doximity. Dr Smith reported stock options from Linear Therapies, personal fees from Arena Pharmaceuticals, Model Medicines, Pharma Holdings, Bayer Pharmaceuticals, Evidera, Signant Health, Fluxergy, Lucira, and Kiadis outside the submitted work. No other disclosures were reported.

Treatment of children with ADHD

Peer-Reviewed Publication

JAMA NETWORK

About The Study: The results of this study of children with parent-reported attention-deficit/hyperactivity disorder (ADHD) suggest that most were not receiving ADHD medications and had never received outpatient mental health care. Gaps in treatment, which were not directly associated with socioeconomic disadvantage, underscore the challenges of improving communication and access to outpatient mental health care for children with ADHD. 

Authors: Mark Olfson, M.D., M.P.H., of Columbia University and the New York State Psychiatric Institute in New York, is the corresponding author. 

(doi:10.1001/jamanetworkopen.2023.10999)

Editor’s Note: Please see the article for additional information, including other authors, author contributions and affiliations, conflict of interest and financial disclosures, and funding and support.

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About JAMA Network Open: JAMA Network Open is an online-only open access general medical journal from the JAMA Network. On weekdays, the journal publishes peer-reviewed clinical research and commentary in more than 40 medical and health subject areas. Every article is free online from the day of publication.

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JOURNAL

JAMA Network Open