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.
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‘Brain Flows: How Network Dynamics Compose the Human Mind,’ an excerpt
In his new book, published today, Michael W. Cole examines how the movement of neuronal activity between neuronal populations shapes free will, intelligence and creativity. In this excerpt from Chapter 1, Cole explores why activity flows could unify efforts to map brain functions and connectivity.
‘Brain Flows: How Network Dynamics Compose the Human Mind,’ an excerpt
In his new book, published today, Michael W. Cole examines how the movement of neuronal activity between neuronal populations shapes free will, intelligence and creativity. In this excerpt from Chapter 1, Cole explores why activity flows could unify efforts to map brain functions and connectivity.
Prenatal pruning of neurons with copy number variants; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 2 November.
Prenatal pruning of neurons with copy number variants; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 2 November.
New Stanford initiative aims to build digital twin of human brain
The effort, funded by private donors, seeks to train the model on a trove of MRI and magnetoencephalography data that scientists plan to collect over the next five years—but questions about its scientific utility and feasibility remain.
New Stanford initiative aims to build digital twin of human brain
The effort, funded by private donors, seeks to train the model on a trove of MRI and magnetoencephalography data that scientists plan to collect over the next five years—but questions about its scientific utility and feasibility remain.