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
Explore more from The Transmitter
‘Brain Flows: How Network Dynamics Compose the Human Mind,’ an excerpt
In his new book, published today, Michael W. Cole examines how the movement of neuronal activity between neuronal populations shapes free will, intelligence and creativity. In this excerpt from Chapter 1, Cole explores why activity flows could unify efforts to map brain functions and connectivity.
‘Brain Flows: How Network Dynamics Compose the Human Mind,’ an excerpt
In his new book, published today, Michael W. Cole examines how the movement of neuronal activity between neuronal populations shapes free will, intelligence and creativity. In this excerpt from Chapter 1, Cole explores why activity flows could unify efforts to map brain functions and connectivity.
Prenatal pruning of neurons with copy number variants; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 2 November.
Prenatal pruning of neurons with copy number variants; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 2 November.
New Stanford initiative aims to build digital twin of human brain
The effort, funded by private donors, seeks to train the model on a trove of MRI and magnetoencephalography data that scientists plan to collect over the next five years—but questions about its scientific utility and feasibility remain.
New Stanford initiative aims to build digital twin of human brain
The effort, funded by private donors, seeks to train the model on a trove of MRI and magnetoencephalography data that scientists plan to collect over the next five years—but questions about its scientific utility and feasibility remain.