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Tools for modeling state-dependent sensory encoding by neural populations across spatial and temporal scales
David, Stephen
(PI)
Mesgarani, Nima
(CoPI)
Zuckerman Institute
Project
:
Research project
Overview
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Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
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Computer Science
Artificial Neural Network
100%
Coherent Activity
100%
Explanatory Power
100%
Learning System
100%
Machine Learning
100%
Neural Network Model
100%
Open Source
100%
Population Level
100%
Software Library
100%
State Variable
100%
Statistical Regularity
100%
Neuroscience
Artificial Neural Network
50%
Auditory System
50%
Calcium Imaging
50%
Central Auditory Processing
50%
Hearing Loss
50%
Magnetoencephalography
50%
Nerve Potential
50%
Neural Coding
50%
Peripheral Hearing Loss
50%
Sensation of Hearing
100%
Sensory Processing
100%
Signal Processing
50%