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
Outside influences on CHD8 variant phenotypes, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 18 May.
Outside influences on CHD8 variant phenotypes, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 18 May.
Reforming neuroscience graduate education for—and with—AI
In disrupting the status quo, artificial intelligence can help us critically reassess and redefine what neuroscience graduate training should look like—and potentially address long-standing training challenges in novel and innovative ways.
Reforming neuroscience graduate education for—and with—AI
In disrupting the status quo, artificial intelligence can help us critically reassess and redefine what neuroscience graduate training should look like—and potentially address long-standing training challenges in novel and innovative ways.
What can AI teach us about ‘emotions’?
Exploring why Anthropic’s AI, Claude, displays something like emotion could ultimately help us better understand the function that emotions serve in humans.
What can AI teach us about ‘emotions’?
Exploring why Anthropic’s AI, Claude, displays something like emotion could ultimately help us better understand the function that emotions serve in humans.