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Neural decoding with visual attention using sequential Monte Carlo for leaky integrate- and-fire neurons
Kang Li
*
,
Susanne Ditlevsen
*
Corresponding author for this work
Department of Mathematical Sciences
1
Citation (Scopus)
21
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Dive into the research topics of 'Neural decoding with visual attention using sequential Monte Carlo for leaky integrate- and-fire neurons'. Together they form a unique fingerprint.
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Keyphrases
Brain Response
33%
Computational Methods
33%
External Stimuli
33%
First-passage Probability
33%
Fokker-Planck Equation
33%
Leaky Integrate-and-fire Model
33%
Leaky Integrate-and-fire Neuron
100%
Model Complexity
33%
Model Estimation
33%
Multiple Stimuli
33%
Neural Coding
33%
Neural Data
33%
Neural Model
33%
Neural Spike Trains
33%
Neuronal Output
66%
Neuronal Responses
33%
Ornstein-Uhlenbeck Process
33%
Parallel Processing
33%
Parameter Estimation
33%
Particle Method
33%
Single Stimulus
33%
Spike Trains
66%
Theories of Attention
33%
Visual Attention
100%
Visual Search
33%
Neuroscience
Neural Coding
100%
Visual Search
100%
Computer Science
Planck Equation
33%
Search Mechanism
33%
Serial Processing
33%