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Jung Hoon Lee

Researcher at Allen Institute for Brain Science

Publications -  54
Citations -  1711

Jung Hoon Lee is an academic researcher from Allen Institute for Brain Science. The author has contributed to research in topics: Artificial neural network & Auditory cortex. The author has an hindex of 16, co-authored 52 publications receiving 1250 citations. Previous affiliations of Jung Hoon Lee include Forschungszentrum Jülich & Boston University.

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Survey of spiking in the mouse visual system reveals functional hierarchy

Joshua H. Siegle, +91 more
- 20 Jan 2021 - 
TL;DR: In this paper, a large-scale dataset of tens of thousands of units in six cortical and two thalamic regions in the brains of mice responding to a battery of visual stimuli is presented.
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Neurosystems: brain rhythms and cognitive processing

TL;DR: The contributions of rhythms to basic cognitive computations and to major cognitive functions (such as attention and multi‐modal coordination) are investigated and the premise that the physiology underlying brain rhythms plays an essential role in how these rhythms facilitate some cognitive operations is offered.
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Top-Down Beta Rhythms Support Selective Attention via Interlaminar Interaction: A Model

TL;DR: The simulation results show that top-down beta rhythms can activate ascending synaptic projections from L5 to L4 and L2/3, responsible for biased competition in superficial layers, and provide a potential mechanism by which cholinergic drive can support selective attention.
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Sparse recurrent excitatory connectivity in the microcircuit of the adult mouse and human cortex.

TL;DR: It is found that connections are sparse but present among all excitatory cell classes and layers the authors sampled, and that most mouse synapses exhibited short-term depression with similar dynamics, contributing to a body of evidence describing recurrent exciteatory connectivity as a conserved feature of cortical microcircuits.
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Neuromorphic architectures for nanoelectronic circuits

TL;DR: It is shown that despite the hardware‐imposed limitations, a simple weight import procedure allows the CrossNets using simple two‐terminal nanodevices to perform functions that had been earlier demonstrated in neural networks with continuous, deterministic synaptic weights.