AIMC Topic: Brain

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EEG-based motor imagery channel selection and classification using hybrid optimization and two-tier deep learning.

Journal of neuroscience methods Jul 3, 2024
Brain-computer interface (BCI) technology holds promise for individuals with profound motor impairments, offering the potential for communication and control. Motor imagery (MI)-based BCI systems are particularly relevant in this context. Despite the...
Imagination Humans Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Algorithms Brain Deep Learning
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Structure focused neurodegeneration convolutional neural network for modelling and classification of Alzheimer's disease.

Scientific reports Jul 3, 2024
Alzheimer's disease (AD), the predominant form of dementia, is a growing global challenge, emphasizing the urgent need for accurate and early diagnosis. Current clinical diagnoses rely on radiologist expert interpretation, which is prone to human err...
Magnetic Resonance Imaging Alzheimer Disease Neuroimaging Brain Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Deep Learning-based Hierarchical Brain Segmentation with Preliminary Analysis of the Repeatability and Reproducibility.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Jul 2, 2024
PURPOSE: We developed new deep learning-based hierarchical brain segmentation (DLHBS) method that can segment T1-weighted MR images (T1WI) into 107 brain subregions and calculate the volume of each subregion. This study aimed to evaluate the repeatab...
Adult Male Middle Aged Female Reproducibility of Results Young Adult Magnetic Resonance Imaging Gray Matter White Matter Deep Learning Imaging, Three-Dimensional Image Processing, Computer-Assisted Humans Brain
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A Method to Extract Task-Related EEG Feature Based on Lightweight Convolutional Neural Network.

Neuroscience bulletin Jul 2, 2024
Unlocking task-related EEG spectra is crucial for neuroscience. Traditional convolutional neural networks (CNNs) effectively extract these features but face limitations like overfitting due to small datasets. To address this issue, we propose a light...
Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Neural Networks, Computer Brain Female Young Adult Adult Male Humans
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Unraveling Brain Synchronisation Dynamics by Explainable Neural Networks using EEG Signals: Application to Dyslexia Diagnosis.

Interdisciplinary sciences, computational life sciences Jul 2, 2024
The electrical activity of the neural processes involved in cognitive functions is captured in EEG signals, allowing the exploration of the integration and coordination of neuronal oscillations across multiple spatiotemporal scales. We have proposed ...
Humans Neural Networks, Computer Brain Child Electroencephalography Dyslexia Female Male Deep Learning
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Power spectral density-based resting-state EEG classification of first-episode psychosis.

Scientific reports Jul 2, 2024
Historically, the analysis of stimulus-dependent time-frequency patterns has been the cornerstone of most electroencephalography (EEG) studies. The abnormal oscillations in high-frequency waves associated with psychotic disorders during sensory and c...
Humans Machine Learning Brain Electroencephalography Signal Processing, Computer-Assisted Psychotic Disorders Rest Male Adolescent Support Vector Machine Female Young Adult Adult
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Advances in Computational Biology for Diagnosing Neurodegenerative Diseases: A Comprehensive Review.

Zhongguo ying yong sheng li xue za zhi = Zhongguo yingyong shenglixue zazhi = Chinese journal of applied physiology Jul 2, 2024
The numerous and varied forms of neurodegenerative illnesses provide a considerable challenge to contemporary healthcare. The emergence of artificial intelligence has fundamentally changed the diagnostic picture by providing effective and early means...
Computational Biology Magnetic Resonance Imaging Neurodegenerative Diseases Neuroimaging Algorithms Brain Image Processing, Computer-Assisted Humans Artificial Intelligence Machine Learning
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Directly training temporal Spiking Neural Network with sparse surrogate gradient.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2024
Brain-inspired Spiking Neural Networks (SNNs) have attracted much attention due to their event-based computing and energy-efficient features. However, the spiking all-or-none nature has prevented direct training of SNNs for various applications. The ...
Action Potentials Neurons Algorithms Brain Models, Neurological Humans Neural Networks, Computer
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Unsupervised and semi-supervised domain adaptation networks considering both global knowledge and prototype-based local class information for Motor Imagery Classification.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2024
The non-stationarity of EEG signals results in variability across sessions, impeding model building and data sharing. In this paper, we propose a domain adaptation method called GPL, which simultaneously considers global knowledge and prototype-based...
Brain-Computer Interfaces Imagination Unsupervised Machine Learning Electroencephalography Supervised Machine Learning Humans Neural Networks, Computer Algorithms Brain
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Classification of brain tumor types through MRIs using parallel CNNs and firefly optimization.

Scientific reports Jul 1, 2024
Image segmentation is a critical and challenging endeavor in the field of medicine. A magnetic resonance imaging (MRI) scan is a helpful method for locating any abnormal brain tissue these days. It is a difficult undertaking for radiologists to diagn...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Algorithms Brain Brain Neoplasms Humans Neural Networks, Computer
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