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
Is it time for neuroscience to shift its focus from a computational mind to a navigating mind?
Andrea Hiott explains her navigational approach to the mind, and why now is the time to embrace seemingly paradoxical findings in neuroscience.
Is it time for neuroscience to shift its focus from a computational mind to a navigating mind?
Andrea Hiott explains her navigational approach to the mind, and why now is the time to embrace seemingly paradoxical findings in neuroscience.
Human brain organoids come of age—but still have room to grow
The U.S. government has touted organoids as an alternative to animals for studying the brain. The model has improved since its debut in 2013, but scientists are still working to overcome key limitations: immaturity, consistency and the lack of vascularization.
Human brain organoids come of age—but still have room to grow
The U.S. government has touted organoids as an alternative to animals for studying the brain. The model has improved since its debut in 2013, but scientists are still working to overcome key limitations: immaturity, consistency and the lack of vascularization.
Finding neuroheterogeneity’s sweet spot
Once thought to be detrimental to memory processing, neuronal diversity—at the right ‘Goldilocks’ dose—is a new boon to theoretical neuroscience.
Finding neuroheterogeneity’s sweet spot
Once thought to be detrimental to memory processing, neuronal diversity—at the right ‘Goldilocks’ dose—is a new boon to theoretical neuroscience.