Machine learning
Recent articles
How to teach programming in the age of AI
Scientists and educators are concerned about students using artificial intelligence to shortcut their learning. But there are also opportunities, especially when it comes to teaching neuroscience students how to code.
How to teach programming in the age of AI
Scientists and educators are concerned about students using artificial intelligence to shortcut their learning. But there are also opportunities, especially when it comes to teaching neuroscience students how to code.
Trading places: What happens when neuroscience turns into machine learning, and machine learning turns into neuroscience?
Neuroscience has become increasingly concerned with prediction, and machine learning with causal explanation, with each field adopting methods from the other. I asked eight experts to weigh in on what we stand to learn from this exchange.
Trading places: What happens when neuroscience turns into machine learning, and machine learning turns into neuroscience?
Neuroscience has become increasingly concerned with prediction, and machine learning with causal explanation, with each field adopting methods from the other. I asked eight experts to weigh in on what we stand to learn from this exchange.
David Sussillo on persistence, luck and the bonds between life and work
In a Q&A about his new book, “Emergence,” Sussillo shares why he wrote it and how challenging circumstances shaped his journey into neuroscience.
David Sussillo on persistence, luck and the bonds between life and work
In a Q&A about his new book, “Emergence,” Sussillo shares why he wrote it and how challenging circumstances shaped his journey into neuroscience.
Large-scale neuroimaging datasets often lack information specific to women’s health, constraining AI’s analysis potential
Addressing this gap will require collecting widespread data on pregnancy, menopause and other life events women experience—and could bring us closer to the “holy grail” of linking brain and behavior.
Large-scale neuroimaging datasets often lack information specific to women’s health, constraining AI’s analysis potential
Addressing this gap will require collecting widespread data on pregnancy, menopause and other life events women experience—and could bring us closer to the “holy grail” of linking brain and behavior.
Modern AI is simply no match for the complexity likely required for harboring consciousness, says Jaan Aru
He argues that our brain’s computations are of a completely different nature than any artificial intelligence because they take place across many spatial and temporal scales and are inextricably entwined with biological materials.
Modern AI is simply no match for the complexity likely required for harboring consciousness, says Jaan Aru
He argues that our brain’s computations are of a completely different nature than any artificial intelligence because they take place across many spatial and temporal scales and are inextricably entwined with biological materials.
The Transmitter’s favorite essays of 2025
Throughout a tumultuous year in science, researchers opined on policy changes and funding uncertainty, as well as scientific trends and the impact of artificial-intelligence tools on the field.
The Transmitter’s favorite essays of 2025
Throughout a tumultuous year in science, researchers opined on policy changes and funding uncertainty, as well as scientific trends and the impact of artificial-intelligence tools on the field.
Exclusive: Springer Nature retracts, removes nearly 40 publications that trained neural networks on ‘bonkers’ dataset
The dataset contains images of children’s faces downloaded from websites about autism, which sparked concerns at Springer Nature about consent and reliability.
Exclusive: Springer Nature retracts, removes nearly 40 publications that trained neural networks on ‘bonkers’ dataset
The dataset contains images of children’s faces downloaded from websites about autism, which sparked concerns at Springer Nature about consent and reliability.
Beyond the algorithmic oracle: Rethinking machine learning in behavioral neuroscience
Machine learning should not be a replacement for human judgment but rather help us embrace the various assumptions and interpretations that shape behavioral research.
Beyond the algorithmic oracle: Rethinking machine learning in behavioral neuroscience
Machine learning should not be a replacement for human judgment but rather help us embrace the various assumptions and interpretations that shape behavioral research.
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.
Explore more from The Transmitter
Single-gene systems-level effects, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 6 April.
Single-gene systems-level effects, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 6 April.
‘The Brain, In Theory,’ an excerpt
In his new book, Brette pushes back against theories that describe the brain as a “biological computer.” In this excerpt from Chapter 4, he challenges equating brain evolution with programming, and the universality of neural network models.
‘The Brain, In Theory,’ an excerpt
In his new book, Brette pushes back against theories that describe the brain as a “biological computer.” In this excerpt from Chapter 4, he challenges equating brain evolution with programming, and the universality of neural network models.
Computational neuroscientist Keith Hengen explains his work through illustrations
The images help him communicate the “big-picture ideas” behind the mathematical principles of neuronal networks.
Computational neuroscientist Keith Hengen explains his work through illustrations
The images help him communicate the “big-picture ideas” behind the mathematical principles of neuronal networks.