Melinda Wenner Moyer (@Lindy2350) is a science writer based in New York’s Hudson Valley. She is a visiting scholar at NYU’s Arthur L. Carter Journalism Institute and an Alicia Patterson fellow. Moyer writes a column for Slate and is a contributing editor at Scientific American. Her work has also appeared in the New York Times, Mother Jones, and a number of women’s magazines.
Melinda Wenner Moyer
From this contributor
When autistic people commit sexual crimes
Many first-time sex offenders on the spectrum may not understand the laws they break. How should their crimes be treated?
When autistic people commit sexual crimes
How pregnancy may shape a child’s autism
Autism is predominantly genetic in origin, but a growing list of prenatal exposures for mother and baby may sway the odds.
How pregnancy may shape a child’s autism
Explore more from The Transmitter
Single-gene systems-level effects, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 6 April.
Single-gene systems-level effects, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 6 April.
‘The Brain, In Theory,’ an excerpt
In his new book, Brette pushes back against theories that describe the brain as a “biological computer.” In this excerpt from Chapter 4, he challenges equating brain evolution with programming, and the universality of neural network models.
‘The Brain, In Theory,’ an excerpt
In his new book, Brette pushes back against theories that describe the brain as a “biological computer.” In this excerpt from Chapter 4, he challenges equating brain evolution with programming, and the universality of neural network models.
Computational neuroscientist Keith Hengen explains his work through illustrations
The images help him communicate the “big-picture ideas” behind the mathematical principles of neuronal networks.
Computational neuroscientist Keith Hengen explains his work through illustrations
The images help him communicate the “big-picture ideas” behind the mathematical principles of neuronal networks.