Saverio Truglia
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Rising star: Ann Kennedy bridges gap between biology, computational theory
A theoretical neuroscientist, Kennedy uses a blend of computational modeling and real-world experiments to understand how brain activity shapes the behaviors of animals that model autism and other conditions.
Rising star: Ann Kennedy bridges gap between biology, computational theory
Elizabeth Berry-Kravis: Running a marathon for fragile X syndrome
Elizabeth Berry-Kravis has spent decades uncovering molecular clues to fragile X syndrome and crafting trials of treatments. Her efforts are paying off.
Elizabeth Berry-Kravis: Running a marathon for fragile X syndrome
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Why neural foundation models work, and what they might—and might not—teach us about the brain
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?
Why neural foundation models work, and what they might—and might not—teach us about the brain
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?
Error equation predicts brain’s ability to generalize
Four statistical measurements of neural network geometry capture how well brains and artificial networks use what they already know to solve new problems, a study suggests.
Error equation predicts brain’s ability to generalize
Four statistical measurements of neural network geometry capture how well brains and artificial networks use what they already know to solve new problems, a study suggests.
Embrace complexity to improve the translatability of basic neuroscience
Researchers must learn to view heterogeneity as an essential feature of the systems they study and a central consideration in experimental design, not a variable to control for or reduce.
Embrace complexity to improve the translatability of basic neuroscience
Researchers must learn to view heterogeneity as an essential feature of the systems they study and a central consideration in experimental design, not a variable to control for or reduce.