Marta Zaraska is a freelance science journalist whose work has appeared in The Washington Post, Scientific American and The Boston Globe, among other publications. She has written two literary novels and contributed to two travel books published by National Geographic. Her nonfiction book “Meathooked: The History and Science of Our 2.5-Million-Year Obsession With Meat,” was published in 2016 by Basic Books and chosen by Nature as one of “the best science picks” in March 2016.
Marta Zaraska
From this contributor
Moving for autism care
Disparities in state services for autism are driving families to relocate. But not everyone can afford to move, and others find that their new home also has faults.
The problems with prenatal testing for autism
As prenatal testing improves, it presents a host of thorny issues — from what to test and how to interpret the results, to what to do about them.
The problems with prenatal testing for autism
Europe’s race to ramp up genetic tests for autism
Many countries in Europe are reckoning with the growing demand for genetic tests for autistic people — and the accompanying ethical and scientific considerations.
Europe’s race to ramp up genetic tests for autism
France faces down its outdated notions about autism
After lagging behind other countries for decades, France is working on a new national plan for autism.
France faces down its outdated notions about autism
Explore more from The Transmitter
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.