Mark Zylka
Associate Professor
University of North Carolina at Chapel Hill
From this contributor
Few autism researchers control for the ‘litter effect’ — this needs to change
Anyone who uses multiple animals from a small number of litters to increase sample size is making a serious mistake. The similarities within individual litters will heavily skew the results.
Few autism researchers control for the ‘litter effect’ — this needs to change
Length matters: Disease implications for long genes
A gene’s length may influence its expression, and this has implications for autism, which tends to be linked to particularly long genes, says Mark Zylka.
Length matters: Disease implications for long genes
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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.