Computation
Recent articles
David Krakauer reflects on the foundations and future of complexity science
In his book “The Complex World,” Krakauer explores how complexity science developed, from its early roots to the four pillars that now define it—entropy, evolution, dynamics and computation.
David Krakauer reflects on the foundations and future of complexity science
In his book “The Complex World,” Krakauer explores how complexity science developed, from its early roots to the four pillars that now define it—entropy, evolution, dynamics and computation.
Future watch: What should neuroscience prioritize during the next 10 to 20 years?
For The Transmitter’s first annual book, five contributing editors reflect on what subfields demand greater focus in the near future—from dynamical systems and computation to technologies for studying the human brain.
Future watch: What should neuroscience prioritize during the next 10 to 20 years?
For The Transmitter’s first annual book, five contributing editors reflect on what subfields demand greater focus in the near future—from dynamical systems and computation to technologies for studying the human brain.
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.
Hessameddin Akhlaghpour outlines how RNA may implement universal computation
Could the brain’s computational abilities extend beyond neural networks to molecular mechanisms? Akhlaghpour describes how natural universal computation may have evolved via RNA mechanisms.
Hessameddin Akhlaghpour outlines how RNA may implement universal computation
Could the brain’s computational abilities extend beyond neural networks to molecular mechanisms? Akhlaghpour describes how natural universal computation may have evolved via RNA mechanisms.
Explore more from The Transmitter
Why neural foundation models work, and what they might—and might not—teach us about the brain
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?
Why neural foundation models work, and what they might—and might not—teach us about the brain
These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?
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.