Shafaq Zia is a science journalist and a graduate student in the Graduate Program in Science Writing at the Massachusetts Institute of Technology. Previously, she was a reporting intern at STAT, covering the COVID-19 pandemic and the latest research in health technology.
Shafaq Zia
From this contributor
Spotted around the web: COVID-19 during pregnancy, sleep problems, eugenics
Here is a roundup of news and research for the week of 6 June.
Spotted around the web: COVID-19 during pregnancy, sleep problems, eugenics
New resource tracks genetic variations in Han Chinese populations
An online database called NyuWa catalogs genetic variations among nearly 3,000 individuals and provides a comprehensive reference genome for the Han people.
New resource tracks genetic variations in Han Chinese populations
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Autism-linked genes alter sleep behavior, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 13 April.
Autism-linked genes alter sleep behavior, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 13 April.
This paper changed my life: Erin Calipari ponders the nuances of rewarding and aversive stimuli
A 1960s study by Kelleher and Morse found that lever pressing in squirrel monkeys depended not on whether they received a reward or shock, but on the rules of the task. This taught Calipari to think deeply about factors that influence how behavior is generated and maintained.
This paper changed my life: Erin Calipari ponders the nuances of rewarding and aversive stimuli
A 1960s study by Kelleher and Morse found that lever pressing in squirrel monkeys depended not on whether they received a reward or shock, but on the rules of the task. This taught Calipari to think deeply about factors that influence how behavior is generated and maintained.
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?