Machine learning
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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 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.
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.
Competition seeks new algorithms to classify social behavior in animals
The winner of the competition, which launched today and tests contestants’ models head to head, is set to take home $20,000, according to co-organizer Ann Kennedy.
Competition seeks new algorithms to classify social behavior in animals
The winner of the competition, which launched today and tests contestants’ models head to head, is set to take home $20,000, according to co-organizer Ann Kennedy.
This paper changed my life: Dan Goodman on a paper that reignited the field of spiking neural networks
Friedemann Zenke’s 2019 paper, and its related coding tutorial SpyTorch, made it possible to apply modern machine learning to spiking neural networks. The innovation reinvigorated the field.
This paper changed my life: Dan Goodman on a paper that reignited the field of spiking neural networks
Friedemann Zenke’s 2019 paper, and its related coding tutorial SpyTorch, made it possible to apply modern machine learning to spiking neural networks. The innovation reinvigorated the field.
Xaq Pitkow shares his principles for studying cognition in our imperfect brains and bodies
Pitkow discusses how evolution's messy constraints shape optimal brain algorithms, from Bayesian inference to ecological affordances.
Xaq Pitkow shares his principles for studying cognition in our imperfect brains and bodies
Pitkow discusses how evolution's messy constraints shape optimal brain algorithms, from Bayesian inference to ecological affordances.
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.
Breaking the jar: Why NeuroAI needs embodiment
Brain function is inexorably shaped by the body. Embracing this fact will benefit computational models of real brain function, as well as the design of artificial neural networks.
Breaking the jar: Why NeuroAI needs embodiment
Brain function is inexorably shaped by the body. Embracing this fact will benefit computational models of real brain function, as well as the design of artificial neural networks.
Many students want to learn to use artificial intelligence responsibly. But their professors are struggling to meet that need.
Effectively teaching students how to employ AI in their writing assignments requires clear guidelines—and detailed, case-specific examples.
Many students want to learn to use artificial intelligence responsibly. But their professors are struggling to meet that need.
Effectively teaching students how to employ AI in their writing assignments requires clear guidelines—and detailed, case-specific examples.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.
Explore more from The Transmitter
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.
The leaders we have lost
Learn more about the lives and legacies of the neuroscientists who passed away between 2023 and 2025.
The leaders we have lost
Learn more about the lives and legacies of the neuroscientists who passed away between 2023 and 2025.
What are the most-cited neuroscience papers from the past 30 years?
Highly cited papers reflect the surge in artificial-intelligence research in the field and other technical advances, plus prizewinning work on analgesics, the fusiform face area and ion channels.
What are the most-cited neuroscience papers from the past 30 years?
Highly cited papers reflect the surge in artificial-intelligence research in the field and other technical advances, plus prizewinning work on analgesics, the fusiform face area and ion channels.