Stormy Chamberlain is associate professor of genetics and genome sciences and associate director of the Graduate Program in Genetics and Developmental Biology at the University of Connecticut School of Medicine.
Stormy Chamberlain
Associate professor
University of Connecticut
From this contributor
Angelman syndrome’s silent gene points way forward for autism therapies
Advances in research and help from families have brought scientists to the brink of an effective therapy for Angelman syndrome.
Angelman syndrome’s silent gene points way forward for autism therapies
For accurate results in autism, genetic databases need diversity
We must diversify databases of reference DNA to improve our ability to interpret the consequences of genetic variation.
For accurate results in autism, genetic databases need diversity
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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.