Natalia de Marco is a postdoctoral associate in Gordon Fishell’s laboratory at New York University Langone Medical Center in the departments of cell biology and neural science.
Natalia de Marco
Postdoctoral associate
NYU Langone Medical Center
From this contributor
A case for the importance of interneurons in autism
The etiology of autism may be best understood as an impairment of neuronal circuits, specifically interneurons that dampen signals in the brain, says neuroscientist Gordon Fishell.
A case for the importance of interneurons in autism
By
Gordon Fishell, Natalia de Marco
22 November 2011 | 5 min read
Explore more from The Transmitter
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.
By
Holly Barker
4 December 2025 | 0 min watch
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.
By
Paul Middlebrooks
3 December 2025 | 1 min read
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.
By
Nedah Nemati, Matthew Whiteway
3 December 2025 | 7 min read