Artificial intelligence
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Explore how neuroscientists are thinking about—and applying—artificial intelligence.
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Neuroscience gave AI its start. What happens now?
Commentary: Citation graphs may underestimate neuroscience’s influence on AI
Commentary: The rising absolute number of neuro-inspired AI papers represents a substantial footprint
Examining the bridge between neuroscience and AI
The Transmitter’s favorite essays of 2025
Why expertise won’t protect you from AI’s influence
Betting blind on AI and the scientific mind
From bench to bot: Why AI-powered writing may not deliver on its promise
— TIM REQUARTH, DIRECTOR OF GRADUATE SCIENCE WRITING, RESEARCH ASSISTANT PROFESSOR OF NEUROSCIENCE AND PHYSIOLOGY, NYU GROSSMAN SCHOOL OF MEDICINE Read more
AI-assisted coding: 10 simple rules to maintain scientific rigor
How neuroscientists are using AI
How does a control theorist explain cognition?
Maxim Raginsky draws on control theory, engineering and philosophy to explore what makes biological brains intelligent, what artificial intelligence is missing, and what principles underlie biological autonomy.
How does a control theorist explain cognition?
Maxim Raginsky draws on control theory, engineering and philosophy to explore what makes biological brains intelligent, what artificial intelligence is missing, and what principles underlie biological autonomy.
How, when and why to use agentic AI in our neuroscience labs
With agentic AI’s rapid infiltration into science, researchers need to develop AI use policies and practices.
How, when and why to use agentic AI in our neuroscience labs
With agentic AI’s rapid infiltration into science, researchers need to develop AI use policies and practices.
Mass-produced science is coming. What happens to scientists?
Artificial intelligence may soon enable researchers to generate high-quality science at a previously unimaginable speed. For science consumers—the public, medical patients, technology users—the likely effects will be positive. For scientists, the effects will be as disruptive as industrial mass production was for artisan manufacturers.
Mass-produced science is coming. What happens to scientists?
Artificial intelligence may soon enable researchers to generate high-quality science at a previously unimaginable speed. For science consumers—the public, medical patients, technology users—the likely effects will be positive. For scientists, the effects will be as disruptive as industrial mass production was for artisan manufacturers.
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.
Scientists decry conference’s use of hidden prompts to snare AI peer reviews
The invisible messages, which instruct large language models to use telltale phrases in a peer-review report, are effective in catching artificial-intelligence misuse but also erode trust, some say.
Scientists decry conference’s use of hidden prompts to snare AI peer reviews
The invisible messages, which instruct large language models to use telltale phrases in a peer-review report, are effective in catching artificial-intelligence misuse but also erode trust, some say.
Explore more from The Transmitter
The term ‘model organism’ should be reserved for biological systems
By referring to artificial neural networks as model organisms, we run the risk of distorting funding priorities and disregard the explanatory power of a shared evolutionary history across biological organisms.
The term ‘model organism’ should be reserved for biological systems
By referring to artificial neural networks as model organisms, we run the risk of distorting funding priorities and disregard the explanatory power of a shared evolutionary history across biological organisms.
New phase of BRAIN Initiative spawns basal ganglia ‘parts list’
With a standardized cell naming system and infrastructure for data collection and analysis, the basal ganglia project sets the stage for a whole-brain primate atlas.
New phase of BRAIN Initiative spawns basal ganglia ‘parts list’
With a standardized cell naming system and infrastructure for data collection and analysis, the basal ganglia project sets the stage for a whole-brain primate atlas.
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.