AI in neuroscience: Promise,
friction, progress
Recent articles
Neuroscientists reckon with the gap between artificial intelligence’s potential and the field’s reality.
How to use artificial intelligence to strengthen scientific processes and scholarly output
As AI-driven systems are integrated into all aspects of science, we need to make sure that they read and write to a shared data and knowledge space.
How to use artificial intelligence to strengthen scientific processes and scholarly output
As AI-driven systems are integrated into all aspects of science, we need to make sure that they read and write to a shared data and knowledge space.
AI can’t solve the brain without data that fit together
The brain's first foundation models exist because some areas of neuroscience did the slow work of developing and adopting standards to help integrate data. Artificial intelligence cannot do that work for us.
AI can’t solve the brain without data that fit together
The brain's first foundation models exist because some areas of neuroscience did the slow work of developing and adopting standards to help integrate data. Artificial intelligence cannot do that work for us.
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.
Writing science that humans and machines can read
Large language models are now routinely used to search, summarize and synthesize the literature at scales impossible for any individual researcher—yet scientific publishing has not adapted to that reality.
Writing science that humans and machines can read
Large language models are now routinely used to search, summarize and synthesize the literature at scales impossible for any individual researcher—yet scientific publishing has not adapted to that reality.
Explore more from The Transmitter
Machine-learning model spots autism-linked variants that scramble splicing
The model provides a way to investigate genetic variation in regions of the genome whose functions have been difficult to interpret.
Machine-learning model spots autism-linked variants that scramble splicing
The model provides a way to investigate genetic variation in regions of the genome whose functions have been difficult to interpret.
Future of AI brain models sparks debate
Neuroscientists are divided about whether foundation models that predict brain responses will help the field understand how brains work.
Future of AI brain models sparks debate
Neuroscientists are divided about whether foundation models that predict brain responses will help the field understand how brains work.
Language development during the first 1,000 days; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 9 November.
Language development during the first 1,000 days; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 9 November.