Artificial neural networks
Recent articles
This paper changed my life: Appreciating John Hopfield’s brilliant neural network
In a 1982 paper, the Nobel laureate created his namesake recurrent neural network—work that taught Maria Geffen to always ground research questions in biology.
This paper changed my life: Appreciating John Hopfield’s brilliant neural network
In a 1982 paper, the Nobel laureate created his namesake recurrent neural network—work that taught Maria Geffen to always ground research questions in biology.
Kim Stachenfeld on the dance between neuroscience and artificial intelligence
As a researcher at both Google DeepMind and Columbia University, Stachenfeld offers cross-disciplinary insight into how to understand the brain.
Kim Stachenfeld on the dance between neuroscience and artificial intelligence
As a researcher at both Google DeepMind and Columbia University, Stachenfeld offers cross-disciplinary insight into how to understand the brain.
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Finally, a new route for the magnetic-sense field
Researchers have dueled for years over how the magnetic sense works. New data from monarch butterflies could finally help settle the debate.
Finally, a new route for the magnetic-sense field
Researchers have dueled for years over how the magnetic sense works. New data from monarch butterflies could finally help settle the debate.
Sensory over-responsivity tied to autism, anxiety but not other conditions
Negative reactions to sensations track with certain neurodevelopmental traits in more than 15,000 children—pointing to shared neurobiological roots.
Sensory over-responsivity tied to autism, anxiety but not other conditions
Negative reactions to sensations track with certain neurodevelopmental traits in more than 15,000 children—pointing to shared neurobiological roots.
Neuromechanical models deepen our understanding of animal motor control
Thanks to recent progress in physics-based simulators and robotics, it has never been easier for neuroscientists to use neuromechanical modeling to test hypotheses about animal movement.
Neuromechanical models deepen our understanding of animal motor control
Thanks to recent progress in physics-based simulators and robotics, it has never been easier for neuroscientists to use neuromechanical modeling to test hypotheses about animal movement.