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Talking shop: The Transmitter’s top quotes of 2025
Find out what “may be one of the brain’s most underappreciated superpowers” and why it’s so crucial to “talk about our research in our everyday lives.”
Talking shop: The Transmitter’s top quotes of 2025
Find out what “may be one of the brain’s most underappreciated superpowers” and why it’s so crucial to “talk about our research in our everyday lives.”
Say what? The Transmitter’s top quotes of 2024
“We’ve cured mouse-heimer’s thousands of times...”—find out who said this to a Transmitter reporter, and read our other favorite quotes from the past year.
Say what? The Transmitter’s top quotes of 2024
“We’ve cured mouse-heimer’s thousands of times...”—find out who said this to a Transmitter reporter, and read our other favorite quotes from the past year.
Explore more from The Transmitter
The term ‘model organism’ should be reserved for biological systems
By referring to artificial neural networks as model organisms, we run the risk of distorting funding priorities and disregard the explanatory power of a shared evolutionary history across biological organisms.
The term ‘model organism’ should be reserved for biological systems
By referring to artificial neural networks as model organisms, we run the risk of distorting funding priorities and disregard the explanatory power of a shared evolutionary history across biological organisms.
New phase of BRAIN Initiative spawns basal ganglia ‘parts list’
With a standardized cell naming system and infrastructure for data collection and analysis, the basal ganglia project sets the stage for a whole-brain primate atlas.
New phase of BRAIN Initiative spawns basal ganglia ‘parts list’
With a standardized cell naming system and infrastructure for data collection and analysis, the basal ganglia project sets the stage for a whole-brain primate atlas.
Machine-learning model spots autism-linked variants that scramble splicing
The model provides a way to investigate genetic variation in regions of the genome whose functions have been difficult to interpret.
Machine-learning model spots autism-linked variants that scramble splicing
The model provides a way to investigate genetic variation in regions of the genome whose functions have been difficult to interpret.