Information processing
Recent articles
Explaining ‘the largest unexplained number in brain science’: Q&A with Markus Meister and Jieyu Zheng
The human brain takes in sensory information roughly 100 million times faster than it can respond. Neuroscientists need to explore this perceptual paradox to better understand the limits of the brain, Meister and Zheng say.
Explaining ‘the largest unexplained number in brain science’: Q&A with Markus Meister and Jieyu Zheng
The human brain takes in sensory information roughly 100 million times faster than it can respond. Neuroscientists need to explore this perceptual paradox to better understand the limits of the brain, Meister and Zheng say.
Explore more from The Transmitter
Error equation predicts brain’s ability to generalize
Four statistical measurements of neural network geometry capture how well brains and artificial networks use what they already know to solve new problems, a study suggests.
Error equation predicts brain’s ability to generalize
Four statistical measurements of neural network geometry capture how well brains and artificial networks use what they already know to solve new problems, a study suggests.
Embrace complexity to improve the translatability of basic neuroscience
Researchers must learn to view heterogeneity as an essential feature of the systems they study and a central consideration in experimental design, not a variable to control for or reduce.
Embrace complexity to improve the translatability of basic neuroscience
Researchers must learn to view heterogeneity as an essential feature of the systems they study and a central consideration in experimental design, not a variable to control for or reduce.
Romain Brette reveals fundamental flaws in commonly assumed neuroscience concepts
His new book, “The Brain, In Theory,” offers alternatives to many of the computer science frameworks currently driving theoretical neuroscience.
Romain Brette reveals fundamental flaws in commonly assumed neuroscience concepts
His new book, “The Brain, In Theory,” offers alternatives to many of the computer science frameworks currently driving theoretical neuroscience.