Machine learning
Recent articles
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
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.
Remembering Mark Hallett, leader in transcranial magnetic stimulation
The long-time NINDS researcher, best known for studying movement disorders, has died at age 82.
Remembering Mark Hallett, leader in transcranial magnetic stimulation
The long-time NINDS researcher, best known for studying movement disorders, has died at age 82.