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
Neuroscientists weigh in on White House proposal for ‘moonshot infrastructure’ for connectomics
A report from the Trump administration calls for a “new golden age” of science, in which the federal government supports mission-driven collaborations to deliver high returns on research investments.
Neuroscientists weigh in on White House proposal for ‘moonshot infrastructure’ for connectomics
A report from the Trump administration calls for a “new golden age” of science, in which the federal government supports mission-driven collaborations to deliver high returns on research investments.
In memoriam: Kevin Dunbar, who traced the neural basis of human reasoning
Using imaging technologies, he transformed our understanding of how creativity and scientific discovery arise in the brain.
In memoriam: Kevin Dunbar, who traced the neural basis of human reasoning
Using imaging technologies, he transformed our understanding of how creativity and scientific discovery arise in the brain.
Neurons engage in risky, DNA-breaking business during migration
The cells later repair the damage, which occurs mostly in transcriptionally silent parts of the genome.
Neurons engage in risky, DNA-breaking business during migration
The cells later repair the damage, which occurs mostly in transcriptionally silent parts of the genome.