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
Este artigo mudou minha vida: adotando um dos primeiros modelos de neurociência naturalística
Um artigo publicado na PNAS em 1992 mostrou que o canto das aves aumenta a expressão de um gene de resposta imediata no prosencéfalo dessas aves. O estudo revelou a Ribeiro a importância de investigar as respostas moleculares em contextos naturalísticos.
Este artigo mudou minha vida: adotando um dos primeiros modelos de neurociência naturalística
Um artigo publicado na PNAS em 1992 mostrou que o canto das aves aumenta a expressão de um gene de resposta imediata no prosencéfalo dessas aves. O estudo revelou a Ribeiro a importância de investigar as respostas moleculares em contextos naturalísticos.
Este artículo cambió mi vida: Adoptando un modelo temprano de neurociencia naturalista
Un estudio del 1992 publicado en PNAS demostró que el canto de las aves aumenta la expresión de un gen de respuesta temprana inmediata en el prosencéfalo de los pájaros. El trabajo le reveló a Ribeiro la importancia de estudiar las respuestas moleculares en contextos naturalistas.
Este artículo cambió mi vida: Adoptando un modelo temprano de neurociencia naturalista
Un estudio del 1992 publicado en PNAS demostró que el canto de las aves aumenta la expresión de un gen de respuesta temprana inmediata en el prosencéfalo de los pájaros. El trabajo le reveló a Ribeiro la importancia de estudiar las respuestas moleculares en contextos naturalistas.
Scientific talent is global. Access to the world’s scientific stage is not.
Neuroscience in Chile, and across Latin America, does not lack talent or ideas, but the systems that make science visible—prestigious journals, conferences and networks—increasingly price its researchers out.
Scientific talent is global. Access to the world’s scientific stage is not.
Neuroscience in Chile, and across Latin America, does not lack talent or ideas, but the systems that make science visible—prestigious journals, conferences and networks—increasingly price its researchers out.