Computational neuroscience
Recent articles
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.
Romain Brette reveals fundamental flaws in commonly assumed neuroscience concepts
His new book, “The Brain, In Theory,” offers alternatives to many of the computer science frameworks currently driving theoretical neuroscience.
Romain Brette reveals fundamental flaws in commonly assumed neuroscience concepts
His new book, “The Brain, In Theory,” offers alternatives to many of the computer science frameworks currently driving theoretical neuroscience.
‘The Brain, In Theory,’ an excerpt
In his new book, Brette pushes back against theories that describe the brain as a “biological computer.” In this excerpt from Chapter 4, he challenges equating brain evolution with programming, and the universality of neural network models.
‘The Brain, In Theory,’ an excerpt
In his new book, Brette pushes back against theories that describe the brain as a “biological computer.” In this excerpt from Chapter 4, he challenges equating brain evolution with programming, and the universality of neural network models.
Computational neuroscientist Keith Hengen explains his work through illustrations
The images help him communicate the “big-picture ideas” behind the mathematical principles of neuronal networks.
Computational neuroscientist Keith Hengen explains his work through illustrations
The images help him communicate the “big-picture ideas” behind the mathematical principles of neuronal networks.
Explore more from The Transmitter
Switching neural code may solve ongoing face-recognition debate
Face patch cells in macaque monkeys initially respond to images of any object but rapidly transition to attend to faces exclusively, a new study finds.
Switching neural code may solve ongoing face-recognition debate
Face patch cells in macaque monkeys initially respond to images of any object but rapidly transition to attend to faces exclusively, a new study finds.
Liset de la Prida explains how neuron subtypes may control the activity of large neural populations, from manifolds to ripples
De la Prida's work analyzing the varieties of sharp wave ripples in the hippocampus led to her discovery that specific types of neurons control the properties of neural manifolds.
Liset de la Prida explains how neuron subtypes may control the activity of large neural populations, from manifolds to ripples
De la Prida's work analyzing the varieties of sharp wave ripples in the hippocampus led to her discovery that specific types of neurons control the properties of neural manifolds.
At 25, INSAR needs to bring autism scientists together more than ever
As the International Society for Autism Research’s annual meeting in Prague this week celebrates its quarter-century anniversary, its president reflects on the field’s past successes, current challenges and needs for the future
At 25, INSAR needs to bring autism scientists together more than ever
As the International Society for Autism Research’s annual meeting in Prague this week celebrates its quarter-century anniversary, its president reflects on the field’s past successes, current challenges and needs for the future