AIMC Topic: Brain
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Modality-Aware Discriminative Fusion Network for Integrated Analysis of Brain Imaging Genomics.
IEEE transactions on neural networks and learning systems
May 2, 2025
Mild cognitive impairment (MCI) represents an early stage of Alzheimer's disease (AD), characterized by subtle clinical symptoms that pose challenges for accurate diagnosis. The quest for the identification of MCI individuals has highlighted the impo...
SAGN: Sparse Adaptive Gated Graph Neural Network With Graph Regularization for Identifying Dual-View Brain Networks.
IEEE transactions on neural networks and learning systems
May 2, 2025
Due to the absence of a gold standard for threshold selection, brain networks constructed with inappropriate thresholds risk topological degradation or contain noise connections. Therefore, graph neural networks (GNNs) exhibit weak robustness and ove...
Convolutional Dynamically Convergent Differential Neural Network for Brain Signal Classification.
IEEE transactions on neural networks and learning systems
May 2, 2025
The brain signal classification is the basis for the implementation of brain-computer interfaces (BCIs). However, most existing brain signal classification methods are based on signal processing technology, which require a significant amount of manua...
Neuronal correlates of sleep in honey bees.
Neural networks : the official journal of the International Neural Network Society
May 1, 2025
Honey bees Apis mellifera follow the day-night cycle for their foraging activity, entering rest periods during darkness. Despite considerable research on sleep behaviour in bees, its underlying neurophysiological mechanisms are not well understood, p...
Quantitative susceptibility mapping in magnetically inhomogeneous tissues.
Magnetic resonance in medicine
May 1, 2025
PURPOSE: Conventional quantitative susceptibility mapping (QSM) methods rely on simplified physical models that assume isotropic and homogeneous tissue properties, leading to artifacts and inaccuracies in biological tissues. This study aims to develo...
Artifact estimation network for MR images: effectiveness of batch normalization and dropout layers.
BMC medical imaging
May 1, 2025
BACKGROUND: Magnetic resonance imaging (MRI) is an essential tool for medical diagnosis. However, artifacts may degrade images obtained through MRI, especially owing to patient movement. Existing methods that mitigate the artifact problem are subject...
TasteNet: A novel deep learning approach for EEG-based basic taste perception recognition using CEEMDAN domain entropy features.
Journal of neuroscience methods
Apr 30, 2025
BACKGROUND: Taste perception is the process by which the gustatory system detects and interprets chemical stimuli from food and beverages, involving activation of taste receptors on the tongue. Analyzing taste perception is essential for understandin...
NeuroXiv: AI-powered open databasing and dynamic mining of brain-wide neuron morphometry.
Nature methods
Apr 29, 2025
Neuron morphology has been extensively reconstructed at the whole-brain scale by various projects in recent years. Here, to facilitate interactive exploration in a standardized and scalable manner, we introduce NeuroXiv (neuroxiv.org), a large-scale ...
Brain tumor detection empowered with ensemble deep learning approaches from MRI scan images.
Scientific reports
Apr 29, 2025
Brain tumor detection is essential for early diagnosis and successful treatment, both of which can significantly enhance patient outcomes. To evaluate brain MRI scans and categorize them into four types-pituitary, meningioma, glioma, and normal-this ...
Enhanced Brain Functional Interaction Following BCI-Guided Supernumerary Robotic Finger Training Based on Sixth-Finger Motor Imagery.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Apr 29, 2025
Supernumerary robotic finger (SRF) has shown unique advantages in the field of motor augmentation and rehabilitation, while the development of brain computer interface (BCI) technology has provided the possibility for direct control of SRF. However, ...
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