Computational neuroscience
Recent articles
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.
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.
Explore more from The Transmitter
‘Push-pull’ recipe for neural wiring used in multiple brain regions
A versatile pair of proteins steers neurons toward their targets and helps establish the brain’s sensory maps, new studies suggest.
‘Push-pull’ recipe for neural wiring used in multiple brain regions
A versatile pair of proteins steers neurons toward their targets and helps establish the brain’s sensory maps, new studies suggest.
Reward-learning algorithm hardwired into dopamine circuit
The finding bolsters the canonical model of reward prediction error, which has come under scrutiny in recent years.
Reward-learning algorithm hardwired into dopamine circuit
The finding bolsters the canonical model of reward prediction error, which has come under scrutiny in recent years.
Exclusive: Brain and spinal cord institute halts research, citing funding problems
The Burke Neurological Institute, which calls itself “the only research institute in the U.S. dedicated to finding treatments to repair the brain and spinal cord,” ceased research operations on 22 May.
Exclusive: Brain and spinal cord institute halts research, citing funding problems
The Burke Neurological Institute, which calls itself “the only research institute in the U.S. dedicated to finding treatments to repair the brain and spinal cord,” ceased research operations on 22 May.