90 citations · 313 across the 14 of their papers we have counts for
8 papers · 1 filter
Compiling molecular ultrastructure into neural dynamics
Konrad P. Kording, Anton Arkhipov, Davy Deng +22
High-resolution brain imaging can now capture not just synapse locations but their molecular composition, with the cost of such mapping falling exponentially. Yet such ultrastructu…
The time is ripe to reverse engineer an entire nervous system: simulating behavior from neural interactions
Gal Haspel, Ben Baker, Isabel Beets +34
Just like electrical engineers understand how microprocessors execute programs in terms of how transistor currents are affected by their inputs, neuroscientists want to understand…
Grand Challenges for Global Brain Sciences
Joshua T. Vogelstein, Katrin Amunts, Andreas Andreou +59
The next grand challenges for society and science are in the brain sciences. A collection of 60+ scientists from around the world, together with 10+ observers from national, privat…
Towards an integration of deep learning and neuroscience
Adam Marblestone, Greg Wayne, Konrad Kording
Neuroscience has focused on the detailed implementation of computation, studying neural codes, dynamics and circuits. In machine learning, however, artificial neural networks tend…
Frequently Asked Questions for: The Atoms of Neural Computation
Gary F. Marcus, Adam H. Marblestone, Thomas L. Dean
Based on a survey of the literature, we attempt to answer Frequently Asked Questions on issues of cortical uniformity vs. non-uniformity, the neural mechanisms of symbolic variable…
Rosetta Brains: A Strategy for Molecularly-Annotated Connectomics
Adam H Marblestone, Evan R Daugharthy, Reza Kalhor +9
We propose a neural connectomics strategy called Fluorescent In-Situ Sequencing of Barcoded Individual Neuronal Connections (FISSEQ-BOINC), leveraging fluorescent in situ nucleic a…