Kristin Sainani is associate teaching professor of epidemiology and population health at Stanford University in California.
Kristin Sainani
Teaching professor
Stanford University
From this contributor
Journal Club: Meta-analysis oversells popular autism screen
The Modified Checklist for Autism in Toddlers (M-CHAT) accurately flags autistic toddlers, a new systematic review and meta-analysis suggests, contrary to past evidence that the tool’s validity varies depending on a child’s age and traits. Experts weigh in on the discrepancy.
Journal Club: Meta-analysis oversells popular autism screen
Flawed methods undermine study on undiagnosed autism and suicide
The researchers attempted to retroactively identify signs of autism in people who died by suicide, but their analysis is not convincing.
Flawed methods undermine study on undiagnosed autism and suicide
Study links screen time to autism, but problems abound
The paper relied on parent-reported data and adjusted for few potentially confounding variables.
Study links screen time to autism, but problems abound
Explore more from The Transmitter
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?