Abstract The Study of depression and its effects on the brain is essential since this common mental health disorder affects millions. In addition to disturbing emotional and cognitive processes, depression also disrupts activity in discrete brain regions. Identifying these distortions is important for expanding the diagnosis and treatment plans.
Ali Sam +3 more
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The paper explores how deep LSTM and deep spiking neural networks (SNN) can be used to extract meaningful features from spatio-temporal EEG brain data for early, on-line diagnosis. It introduces a new online spike encoding algorithm for Izhikevich neural networks and new methods for learning and diagnostic biomarker discovery for ...
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From Brain Models to Robotic Embodied Cognition: How Does Biological Plausibility Inform Neuromorphic Systems? [PDF]
Pham MD +3 more
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Prediction and detection of virtual reality induced cybersickness: a spiking neural network approach using spatiotemporal EEG brain data and heart rate variability. [PDF]
Yang AHX, Kasabov NK, Cakmak YO.
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Spiking neural networks for predictive and explainable modelling of multimodal streaming data with a case study on financial time series and online news. [PDF]
AbouHassan I +3 more
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Design of MRI structured spiking neural networks and learning algorithms for personalized modelling, analysis, and prediction of EEG signals. [PDF]
Saeedinia SA +3 more
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Neuromorphic computing facilitates deep brain-machine fusion for high-performance neuroprosthesis. [PDF]
Qi Y, Chen J, Wang Y.
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An overview of brain-like computing: Architecture, applications, and future trends. [PDF]
Ou W, Xiao S, Zhu C, Han W, Zhang Q.
europepmc +1 more source
Application of a Brain-Inspired Spiking Neural Network Architecture to Odor Data Classification. [PDF]
Vanarse A +4 more
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Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network. [PDF]
Doborjeh M +4 more
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