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A New Tool to Detect Viruses in Sequence Data
A new software algorithm developed at Caltech enables researchers to easily search for viruses in RNA sequence data, enabling scientists to detect viruses in samples and study how they impact biological functions. The number of individual viruses on Earth is nearly unfathomable: There are an estimated 10 million individual viruses for each star in the […]
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On the Same Wavelength: Neural “Fingerprints” Indicate Deep Focus Flow States in Teams
Have you ever been so laser focused on a task—playing a video game, reading an engrossing book, and so on—that when you look up, hours have suddenly gone by? This is commonly referred to as flow state: a state of absorbed concentration and a distorted sense of time. Studies have shown that working in the […]
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Ontology-guided machine learning outperforms zero-shot foundation models for cardiac ultrasound text reports
USCF Chen Scholar, Rima Arnout, MD, was part of a team whose research was recently published in the journal Nature focusing on recent innovations in cardiac ultrasound. Big data can revolutionize research and quality improvement for cardiac ultrasound. Text reports are a critical part of such analyses. Cardiac ultrasound reports include structured and free text […]
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Artificial intelligence models using F-wave responses predict ALS
Chen Scholar, Nathan P. Staff, M.D., Ph.D. a Professor of Neurology at the Mayo Clinic College of Medicine and Science, and colleagues recently published research in the journal Brain which focuses on improving the diagnosis and prognosis of amyotrophic lateral sclerosis (ALS), a severe motor neuron disease, using advanced artificial intelligence (AI) techniques. ALS is […]
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How Different Learning Modes May Explain Problem Gambling
Caltech’s John O’Doherty is on a quest to understand how human brains make decisions: how they gather evidence about their environments and their own impacts on these environments and then apply this information to their decision-making. Researchers in his lab examine subjects to find how brains learn from positive and negative feedback, and why some […]
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Thinking Slowly: The Paradoxical Slowness of Human Behavior
Caltech researchers have quantified the speed of human thought: a rate of 10 bits per second. However, our bodies’ sensory systems gather data about our environments at a rate of a trillion bits per second, which is 100 million times faster than our thought processes. This new study raises major new avenues of exploration for […]
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Improving Brain–Machine Interfaces with Machine Learning
Brain–machine interfaces (BMIs) have enabled a handful of test participants who are unable to move or speak to communicate simply by thinking. An implanted device picks up the neural signals associated with a particular thought and converts them into control signals that are fed into a computer or a robotic limb. For example, a quadriplegic […]
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New Study Demonstrates How Autonomic Neurons Control Digestive Functions
The autonomic nervous system orchestrates the functions of internal organs such as the heart and gut, serving as a connection between the brain and the rest of the body. It is classified in two divisions—the sympathetic and parasympathetic systems, often described as the body’s accelerator and brake, respectively. For example, the sympathetic nervous system activates […]
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Decoding the Hidden Signals of Aggression and Arousal in the Brain
Credit: AI-generated image courtesy of Aditya Nair A series of three papers from neuroscientist David J. Anderson’s laboratory, two in the journal Nature and one in the journal Cell, reveal new insights into the neural signals underlying internal emotional states including aggression and sexual arousal. The studies show that the state of aggression in male […]
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Thalamic transcranial ultrasound stimulation in treatment resistant depression
Major depressive disorder (MDD) is a leading cause of disability worldwide with one-third of cases being treatment resistant. Symptom heterogeneity suggests variability across affected brain networks, prompting efforts to personalize circuit-based neuromodulatory interventions. For example, personalized deep brain stimulation (DBS) has been achieved by selecting different treatment targets based on phenotypes or mapping stimulation responses. […]