Diagnostic biomarker discovery from brain EEG data using LSTM, reservoir-SNN, and NeuCube methods in a pilot study comparing epilepsy and migraine [PDF]
Scientific ReportsThe study introduces a new online spike encoding algorithm for spiking neural networks (SNN) and suggests new methods for learning and identifying diagnostic biomarkers using three prominent deep learning neural network models: deep BiLSTM, reservoir SNN,
Nikola Kasabov +2 more
exaly +7 more sources
A Retinotopic Spiking Neural Network System for Accurate Recognition of Moving Objects Using NeuCube and Dynamic Vision Sensors [PDF]
Frontiers in Computational Neuroscience, 2018 This paper introduces a new system for dynamic visual recognition that combines bio-inspired hardware with a brain-like spiking neural network. The system is designed to take data from a dynamic vision sensor (DVS) that simulates the functioning of the ...
Nikola Kasabov, Kasabov Nikola
exaly +7 more sources
Spiking Neural Networks for Multimodal Neuroimaging: A Comprehensive Review of Current Trends and the NeuCube Brain-Inspired Architecture [PDF]
BioengineeringArtificial intelligence (AI) is revolutionising neuroimaging by enabling automated analysis, predictive analytics, and the discovery of biomarkers for neurological disorders.
Omar Garcia-Palencia +5 more
doaj +5 more sources
Spiking Neural Networks: Background, Recent Development and the NeuCube Architecture [PDF]
Neural Processing Letters, 2020 This paper reviews recent developments in the still-off-the-mainstream information and data processing area of spiking neural networks (SNN) — the third generation of artificial neural networks. We provide background information about the functioning of biological neurons, discussing the most important and commonly used mathematical neural models. Most
Clarence Tan +2 more
exaly +6 more sources
Using EEG Data and NeuCube for the Study of Transfer of Learning [PDF]
2020 International Conference on Computational Science and Computational Intelligence (CSCI), 2020 Deeper and long-lasting learning occurs through a critical review of prior knowledge in the light of the new context, and a transfer of the acquired knowledge to new settings. Attention to the task is one of factors that enable transfer of learning (TL). This study adopts a cognitive neuroscience approach to the study of TL.
Krassie Petrova +2 more
exaly +6 more sources
Brain-Inspired Spatio-Temporal Associative Memories for Neuroimaging Data Classification: EEG and fMRI [PDF]
Bioengineering, 2023 Humans learn from a lot of information sources to make decisions. Once this information is learned in the brain, spatio-temporal associations are made, connecting all these sources (variables) in space and time represented as brain connectivity.
Nikola K. Kasabov +3 more
doaj +2 more sources
Brain-inspired spiking neural networks for decoding and understanding muscle activity and kinematics from electroencephalography signals during hand movements [PDF]
Scientific Reports, 2021 Compared to the abilities of the animal brain, many Artificial Intelligence systems have limitations which emphasise the need for a Brain-Inspired Artificial Intelligence paradigm. This paper proposes a novel Brain-Inspired Spiking Neural Network (BI-SNN)
Kaushalya Kumarasinghe +2 more
doaj +2 more sources
Lightweight Building of an Electroencephalogram-Based Emotion Detection System [PDF]
Brain Sciences, 2020 Brain–computer interface (BCI) technology provides a direct interface between the brain and an external device. BCIs have facilitated the monitoring of conscious brain electrical activity via electroencephalogram (EEG) signals and the detection of human ...
Abeer Al-Nafjan +2 more
doaj +2 more sources
FusionSense: Emotion Classification Using Feature Fusion of Multimodal Data and Deep Learning in a Brain-Inspired Spiking Neural Network [PDF]
Sensors, 2020 Using multimodal signals to solve the problem of emotion recognition is one of the emerging trends in affective computing. Several studies have utilized state of the art deep learning methods and combined physiological signals, such as the ...
Clarence Tan +3 more
doaj +2 more sources
eXCube2: Explainable Brain-Inspired Spiking Neural Network Framework for Emotion Recognition from Audio, Visual and Multimodal Audio–Visual Data [PDF]
BiomimeticsThis paper introduces a biomimetic framework and novel brain-inspired AI (BIAI) models based on spiking neural networks (SNNs) for emotional state recognition from audio (speech), visual (face), and integrated multimodal audio–visual data.
N. K. Kasabov +5 more
doaj +2 more sources