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Autapses enable temporal pattern recognition in spiking neural networks
Muhammad Yaqoob
,
Volker Steuber
, Borys Wróbel
Department of Computer Science
School of Physics, Engineering & Computer Science
Biocomputation Research Group
Centre of Data Innovation Research
Centre for AI and Robotics Research
Research output
:
Working paper
30
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Keyphrases
Autapses
100%
Temporal Action Detection
100%
Spiking Neural Networks
100%
Network State
100%
Spiking Network
75%
Minimal Networks
50%
Recognition Task
50%
Input Signals
50%
Sensory Stimuli
50%
Neuroscience
25%
Finite State Transducer
25%
Structure Function
25%
Subsequence
25%
Precise Timing
25%
Formal Models of Computation
25%
Functional Behavior
25%
Recognizing Patterns
25%
Signal Pattern
25%
Structural Connectivity
25%
Network Information Processing
25%
Functional Role
25%
Working Mechanism
25%
Action Potential
25%
Output Neurons
25%
Computer Science
Minimal Network
100%
Pattern Recognition
100%
Neural Network
100%
Sensory Stimulus
100%
Positive Correlation
50%
Structure Function
50%
Model of Computation
50%
Functional Role
50%
Function Mapping
50%
Output Symbol
50%
Information Processing
50%
Research Question
50%
Structural Connectivity
50%
Neuroscience
Neural Network
100%
Pattern Recognition
100%
Behavior (Neuroscience)
100%
Information Processing
50%
Neurobiology
50%
Action Potential
50%
Biochemistry, Genetics and Molecular Biology
Spike
100%
Pattern Recognition
100%
Sensory Stimulation
50%
Functional Behavior
25%
Action Potential
25%