A Feasibility Study of Using the NeuCube Spiking Neural Network Architecture for Modelling Alzheimer’s Disease EEG Data

Elisa Capecci; Francesco Carlo Morabito; Maurizio Campolo; Nadia Mammone; Domenico Labate; Nikola Kasabov

doi:10.1007/978-3-319-18164-6_16

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A Feasibility Study of Using the NeuCube Spiking Neural Network Architecture for Modelling Alzheimer’s Disease EEG Data

Elisa Capecci Francesco Carlo Morabito Maurizio Campolo Nadia Mammone Domenico Labate Nikola Kasabov

Year: 2015 Smart innovation, systems and technologies Pages: 159-172 Publisher: Springer Nature

DOI: 10.1007/978-3-319-18164-6_16

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Keywords:

Electroencephalography Artificial neural network Artificial intelligence Computer science Cognitive impairment Neuroscience Machine learning Pattern recognition (psychology) Cognition Psychology

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Advanced Memory and Neural Computing

Physical Sciences → Engineering → Electrical and Electronic Engineering

Neural dynamics and brain function

Life Sciences → Neuroscience → Cognitive Neuroscience

EEG and Brain-Computer Interfaces

Life Sciences → Neuroscience → Cognitive Neuroscience

A Feasibility Study of Using the NeuCube Spiking Neural Network Architecture for Modelling Alzheimer’s Disease EEG Data

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