Results 111 to 120 of about 561 (123)

Feasibility of NeuCube SNN architecture for detecting motor execution and motor intention for use in BCIapplications

2014 International Joint Conference on Neural Networks (IJCNN), 2014
The paper is a feasibility analysis of using the recently introduced by one of the authors spiking neural networks architecture NeuCube for modelling and recognition of complex EEG spatio-temporal data related to both physical and intentional (imagined) movements.
Denise Taylor, Nathan Scott, Nikola Kasabov, Elisa Capecci, Enmei Tu, Nicola Saywell, Yixong Chen, Jin Hu, Zeng-Guang Hou   +8 more
openaire   +2 more sources

EEG Comparison Between Normal and Developmental Disorder in Perception and Imitation of Facial Expressions with the NeuCube

International Conference on Neural Information Processing, 2017
This paper is a feasibility study of using the NeuCube spiking neural network (SNN) architecture for modeling EEG brain data related to perceiving versus mimicking facial expressions. We collected EEG patterns during perception and imitation of facial expressions for each emotion.
Yuma Omori, Hideaki Kawano, Akinori Seo, Zohreh Gholami Doborjeh, Nikola Kasabov, Maryam Gholami Doborjeh   +5 more
openaire   +2 more sources

Efficient Recognition of Attentional Bias Using EEG Data and the NeuCube Evolving Spatio-Temporal Data Machine

International Conference on Neural Information Processing, 2016
Modelling of dynamic brain activity for better understanding of human decision making processes becomes an important task in many areas of study. Inspired by importance of the attentional bias principle in human choice behaviour, we proposed a Spiking Neural Network (SNN) model for efficient recognition of attentional bias.
Zohreh Gholami Doborjeh, Maryam Gholami Doborjeh, Nikola Kasabov   +2 more
openaire   +2 more sources

Spatio-temporal EEG Data Classification in the NeuCube 3D SNN Environment: Methodology and Examples

International Conference on Neural Information Processing, 2013
A vast amount of complex spatio-temporal brain data, such as EEG-, have been accumulated. Technological advances in many disciplines rely on the proper analysis, understanding and utilisation of these data. In order to address this great challenge, the paper utilizes the recently introduced by one of the authors 3D spiking neural network environment ...
Nikola Kasabov, Jin Hu, Yixiong Chen, Nathan Scott, Yulia Turkova   +4 more
openaire   +2 more sources

Which method to use for optimal structure and function representation of large spiking neural networks: A case study on the NeuCube architecture

2016 International Joint Conference on Neural Networks (IJCNN), 2016
This study analyses different representations of large spiking neural network (SNN) structures for conventional computers and uses the NeuCube SNN architecture as a case study. The representation includes neuronal connectivity and network's and neurons' states during the learning process.
Anne Abbott, Neelava Sengupta, Nikola Kasabov   +2 more
openaire   +2 more sources

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

Advances in Neural Networks, 2015
The paper presents a feasibility analysis of a novel Spiking Neural Network (SNN) architecture called NeuCube [10] for classification and analysis of functional changes in brain activity of Electroencephalography (EEG) data collected amongst two groups: control and Alzheimer’s Disease (AD).
Elisa Capecci, Francesco Carlo Morabito, Maurizio Campolo, Nadia Mammone, Domenico Labate, Nikola Kasabov   +5 more
openaire   +2 more sources

Analysis of connectivity in NeuCube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: A case study on opiate dependence treatment

Neural Networks, 2015
The paper presents a methodology for the analysis of functional changes in brain activity across different conditions and different groups of subjects. This analysis is based on the recently proposed NeuCube spiking neural network (SNN) framework and more specifically on the analysis of the connectivity of a NeuCube model trained with ...
Elisa Capecci, Nikola Kasabov, Grace Y. Wang   +2 more
openaire   +4 more sources

Analysis of Similarity and Differences in Brain Activities Between Perception and Production of Facial Expressions Using EEG Data and the NeuCube Spiking Neural Network Architecture

International Conference on Neural Information Processing, 2016
This paper is a feasibility study of using the NeuCube spiking neural network (SNN) architecture for modeling EEG brain data related to perceiving versus mimicking facial expressions. It is demonstrated that the proposed model can be used to study the similarity and differences between corresponding brain activities as complex spatio-temporal patterns.
Hideaki Kawano, Akinori Seo, Zohreh Gholami Doborjeh, Nikola Kasabov, Maryam Gholami Doborjeh   +4 more
openaire   +2 more sources

Izhikevich Neurons in NeuCube for Longitudinal Data Classification

International Conference on Neural Information Processing
Balkaran Singh, Sugam Budhraja, Maryam Doborjeh, Zohreh Doborjeh, Edmund Lai, Nikola Kasabov   +5 more
openaire   +2 more sources

Emotion Analysis using Spiking Neural Networks

31th International Conference on Neural Information Processing (ICONIP) abstracts
Emotion analysis is a prominent research area gaining popularity as more researchers are trying to solve questions in fields that require intensive study of emotions like psychology, human-computer interactions, and affective computing. Music can be used
Kirushnaamoni Ramakrishnan
semanticscholar   +1 more source