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Stephen J. Smith

Researcher at Allen Institute for Brain Science

Publications -  127
Citations -  22271

Stephen J. Smith is an academic researcher from Allen Institute for Brain Science. The author has contributed to research in topics: Postsynaptic potential & Synapse. The author has an hindex of 59, co-authored 118 publications receiving 20466 citations. Previous affiliations of Stephen J. Smith include Stanford University & Yale University.

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A solution to temporal credit assignment using cell-type-specific modulatory signals

TL;DR: This work re-analyzes the mathematical basis of gradient descent learning in recurrent spiking neural networks (RSNNs) in light of the recent single-cell transcriptomic evidence for cell-type-specific local neuropeptide signaling in the cortex and suggests a computationally efficient on-chip learning method for bio-inspired artificial intelligence.
Journal ArticleDOI

Array tomography: imaging stained arrays

TL;DR: In this protocol, tissue arrays are imaged using conventional wide-field fluorescence microscopy, which makes it possible to visualize and quantify previously inaccessible features of tissue structure and molecular architecture.
Proceedings ArticleDOI

Integrated Semiconductor Optical Sensors for Chronic, Minimally- Invasive Imaging of Brain Function

TL;DR: It is shown that near-infrared IOS imaging at wavelengths compatible with semiconductor devices can produce physiologically significant images in mice, even through skull.
Proceedings ArticleDOI

High throughput integration of optoelectronics devices for biochip fluorescent detection

TL;DR: In this article, the authors used vertical cavity surface emitting lasers (VCSELs), optical emission filters and PIN photodetectors to realize monolithically integrated, near infrared, fluorescence detection systems.
Peer Review

Line Emission Mapper (LEM): Probing the physics of cosmic ecosystems

Ralph P. Kraft, +106 more
TL;DR: The Line Emission Mapper (LEM) as discussed by the authors is an X-ray probe for the 2030s that will answer the outstanding questions of the Universe's structure formation, including stellar and black-hole feedback and flows of baryonic matter into and out of galaxies.