Emily Brooks is a writer, consultant and graduate student in disability studies at the CUNY School of Professional Studies in New York City.
Emily Brooks
Graduate student
City University of New York
From this contributor
Focus on autism must broaden to include non-binary genders
It’s past time for mainstream discussions of ‘women with autism’ to recognize that a significant portion of the autistic community identifies as gender-queer or non-binary.
Focus on autism must broaden to include non-binary genders
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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.