Artificial intelligence
Recent articles
How will neuroscience training need to change in the future?
Training in computational neuroscience, data science and statistics will need to expand, say many of the scientists we surveyed. But that must be balanced with a more traditional grounding in the scientific method and critical thinking. Researchers noted that funding concerns will also affect training, especially for people from underrepresented groups.
How will neuroscience training need to change in the future?
Training in computational neuroscience, data science and statistics will need to expand, say many of the scientists we surveyed. But that must be balanced with a more traditional grounding in the scientific method and critical thinking. Researchers noted that funding concerns will also affect training, especially for people from underrepresented groups.
How will the field’s relationship to industry change over the next decade? Will a larger neurotechnology sector emerge?
Interactions between academic neuroscience and industry will grow, and the neurotech sector will expand, most survey respondents predict. The current funding upheaval in the United States may accelerate this trend as the field searches for new funding models.
How will the field’s relationship to industry change over the next decade? Will a larger neurotechnology sector emerge?
Interactions between academic neuroscience and industry will grow, and the neurotech sector will expand, most survey respondents predict. The current funding upheaval in the United States may accelerate this trend as the field searches for new funding models.
What are the fastest-growing areas in neuroscience?
Respondents pointed to computational neuroscience, systems neuroscience, neuroimmunology and neuroimaging, among other subfields.
What are the fastest-growing areas in neuroscience?
Respondents pointed to computational neuroscience, systems neuroscience, neuroimmunology and neuroimaging, among other subfields.
What should the field prioritize over the next 10 years?
Respondents pointed to a range of challenges in basic neuroscience—such as understanding naturalistic behaviors, intelligence and embodied cognition—and called for more circuit-level research, more precise brain recordings and more work in alternative models. Just as many pushed for a translational pivot.
What should the field prioritize over the next 10 years?
Respondents pointed to a range of challenges in basic neuroscience—such as understanding naturalistic behaviors, intelligence and embodied cognition—and called for more circuit-level research, more precise brain recordings and more work in alternative models. Just as many pushed for a translational pivot.
The state of neuroscience in 2025: An overview
The Transmitter presents a portrait of the field through four lenses: its focus, its output, its people and its funding.
The state of neuroscience in 2025: An overview
The Transmitter presents a portrait of the field through four lenses: its focus, its output, its people and its funding.
What are the most transformative neuroscience tools and technologies developed in the past five years?
Artificial intelligence and deep-learning methods featured prominently in the survey responses, followed by genetic tools to control circuits, advanced neuroimaging, transcriptomics and various approaches to record brain activity and behavior.
What are the most transformative neuroscience tools and technologies developed in the past five years?
Artificial intelligence and deep-learning methods featured prominently in the survey responses, followed by genetic tools to control circuits, advanced neuroimaging, transcriptomics and various approaches to record brain activity and behavior.
Without monkeys, neuroscience has no future
Research in primate brains has been essential for the development of brain-computer interfaces and artificial neural networks. New funding and policy changes put the future of such advances at risk.
Without monkeys, neuroscience has no future
Research in primate brains has been essential for the development of brain-computer interfaces and artificial neural networks. New funding and policy changes put the future of such advances at risk.
How neuroscientists are using AI
Eight researchers explain how they are using large language models to analyze the literature, brainstorm hypotheses and interact with complex datasets.
How neuroscientists are using AI
Eight researchers explain how they are using large language models to analyze the literature, brainstorm hypotheses and interact with complex datasets.
From bench to bot: Why AI-powered writing may not deliver on its promise
Efficiency isn’t everything. The cognitive work of struggling with prose may be a crucial part of what drives scientific progress.
From bench to bot: Why AI-powered writing may not deliver on its promise
Efficiency isn’t everything. The cognitive work of struggling with prose may be a crucial part of what drives scientific progress.
Should neuroscientists ‘vibe code’?
Researchers are developing software entirely through natural language conversations with advanced large language models. The trend is transforming how research gets done—but it also presents new challenges for evaluating the outcomes.
Should neuroscientists ‘vibe code’?
Researchers are developing software entirely through natural language conversations with advanced large language models. The trend is transforming how research gets done—but it also presents new challenges for evaluating the outcomes.
Explore more from The Transmitter
To persist, memories surf molecular waves from thalamus to cortex
During the later stages of learning, the mouse brain progressively activates transcriptional regulators that drive memory consolidation.
To persist, memories surf molecular waves from thalamus to cortex
During the later stages of learning, the mouse brain progressively activates transcriptional regulators that drive memory consolidation.
Sex hormone boosts female rats’ sensitivity to unexpected rewards
During the high-estradiol stages of their estrus cycle, female rats learn faster than they do during other stages—and than male rats overall—thanks to a boost in their dopaminergic response to reward, a new study suggests.
Sex hormone boosts female rats’ sensitivity to unexpected rewards
During the high-estradiol stages of their estrus cycle, female rats learn faster than they do during other stages—and than male rats overall—thanks to a boost in their dopaminergic response to reward, a new study suggests.
SHANK3 deficiency and behavior in mice; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 24 November.
SHANK3 deficiency and behavior in mice; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 24 November.