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
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Home makeover helps rats better express themselves: Q&A with Raven Hickson and Peter Kind
The “Habitat”—a complex environment with space for large social groups—expands the behavioral repertoire of rodent models, Hickson and Kind say.
Home makeover helps rats better express themselves: Q&A with Raven Hickson and Peter Kind
The “Habitat”—a complex environment with space for large social groups—expands the behavioral repertoire of rodent models, Hickson and Kind say.
Tatiana Engel explains how to connect high-dimensional neural circuitry with low-dimensional cognitive functions
Neuroscientists have long sought to understand the relationship between structure and function in the vast connectivity and activity patterns in the brain. Engel discusses her modeling approach to discovering the hidden patterns that connect the two.
Tatiana Engel explains how to connect high-dimensional neural circuitry with low-dimensional cognitive functions
Neuroscientists have long sought to understand the relationship between structure and function in the vast connectivity and activity patterns in the brain. Engel discusses her modeling approach to discovering the hidden patterns that connect the two.
Beyond the algorithmic oracle: Rethinking machine learning in behavioral neuroscience
Machine learning should not be a replacement for human judgment but rather help us embrace the various assumptions and interpretations that shape behavioral research.
Beyond the algorithmic oracle: Rethinking machine learning in behavioral neuroscience
Machine learning should not be a replacement for human judgment but rather help us embrace the various assumptions and interpretations that shape behavioral research.