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
Supported by a $40 million NIH grant, Yale brain shuttle technology raises questions
Yale University claims its STEP platform might be able to deliver gene-editing tools into the brain via multiple routes. Researchers are eager to see more.
Supported by a $40 million NIH grant, Yale brain shuttle technology raises questions
Yale University claims its STEP platform might be able to deliver gene-editing tools into the brain via multiple routes. Researchers are eager to see more.
What counts as a ‘naturalistic’ behavior?
Nedah Nemati explains how neuroscience methods and the lived experience of the scientists themselves shape how we define the behaviors we seek to explain.
What counts as a ‘naturalistic’ behavior?
Nedah Nemati explains how neuroscience methods and the lived experience of the scientists themselves shape how we define the behaviors we seek to explain.
Allen Institute sets sights on treatments for five brain diseases
The Brain Health Accelerator program aims to harness single-cell transcriptomics and cell-type-specific genetic tools to develop treatments for Alzheimer’s, Huntington’s and Parkinson’s diseases, Lewy body dementia and ALS.
Allen Institute sets sights on treatments for five brain diseases
The Brain Health Accelerator program aims to harness single-cell transcriptomics and cell-type-specific genetic tools to develop treatments for Alzheimer’s, Huntington’s and Parkinson’s diseases, Lewy body dementia and ALS.