Computational neuroscience
Recent articles
Transforming AI models into useful model organisms
These systems were not built to explain the brain. But treating them as model organisms that we can perturb and evolve will move us closer to that goal.
Transforming AI models into useful model organisms
These systems were not built to explain the brain. But treating them as model organisms that we can perturb and evolve will move us closer to that goal.
Models at the speed of thought: How AI coding is reshaping theoretical neuroscience
Agentic coding makes it possible to specify a neuroscience model in hours instead of months. Seven neuroscientists weigh in on what that tectonic change may bring to the field.
Models at the speed of thought: How AI coding is reshaping theoretical neuroscience
Agentic coding makes it possible to specify a neuroscience model in hours instead of months. Seven neuroscientists weigh in on what that tectonic change may bring to the field.
This paper changed my life: Appreciating John Hopfield’s brilliant neural network
In a 1982 paper, the Nobel laureate created his namesake recurrent neural network—work that taught Maria Geffen to always ground research questions in biology.
This paper changed my life: Appreciating John Hopfield’s brilliant neural network
In a 1982 paper, the Nobel laureate created his namesake recurrent neural network—work that taught Maria Geffen to always ground research questions in biology.
Why neural foundation models work, and what they might—and might not—teach us about the brain
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?
Why neural foundation models work, and what they might—and might not—teach us about the brain
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?
Error equation predicts brain’s ability to generalize
Four statistical measurements of neural network geometry capture how well brains and artificial networks use what they already know to solve new problems, a study suggests.
Error equation predicts brain’s ability to generalize
Four statistical measurements of neural network geometry capture how well brains and artificial networks use what they already know to solve new problems, a study suggests.
Explore more from The Transmitter
Recording warning: Common brain signal may be misunderstood
High gamma activity in electrophysiologic recordings reflects widespread neural activity, not merely local firing, as previously thought.
Recording warning: Common brain signal may be misunderstood
High gamma activity in electrophysiologic recordings reflects widespread neural activity, not merely local firing, as previously thought.
Fructose silences hunger-driving neurons less than glucose does
Two simple sugars show the complexities of gut-brain communication.
Fructose silences hunger-driving neurons less than glucose does
Two simple sugars show the complexities of gut-brain communication.
A new subtyping model for autism phenotypes late in development, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 29 June.
A new subtyping model for autism phenotypes late in development, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 29 June.