AIMC Topic: Brain
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Roman domination-based spiking neural network for optimized EEG signal classification of four class motor imagery.
Computers in biology and medicine
Jun 10, 2025
The Spiking Neural Network (SNN) is a third-generation neural network recognized for its energy efficiency and ability to process spatiotemporal information, closely imitating the behavioral mechanisms of biological neurons in the brain. SNN exhibit ...
Robust Bayesian brain extraction by integrating structural subspace-based spatial prior into deep neural networks.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 9, 2025
Accurate and robust brain extraction, or skull stripping, is essential for studying brain development, aging, and neurological disorders. However, brain images exhibit substantial data heterogeneity due to differences in contrast and geometric charac...
From code to archetype: Toward a unified theory of biological, neural, and artificial artifacts.
Bio Systems
Jun 9, 2025
Carl Jung's concept of archetypes as innate, universal structures of the human psyche finds surprising resonance with contemporary theories in Code Biology, neuroscience, and artificial intelligence. Archetypes, far from being metaphysical abstractio...
AI-powered remote monitoring of brain responses to clear and incomprehensible speech via speckle pattern analysis.
Journal of biomedical optics
Jun 9, 2025
SIGNIFICANCE: Functional magnetic resonance imaging provides high spatial resolution but is limited by cost, infrastructure, and the constraints of an enclosed scanner. Portable methods such as functional near-infrared spectroscopy and electroencepha...
Causal Discovery Analysis Reveals Insights into Psychosis Proneness, Brain Function, and Environmental Factors among Young Individuals.
Psychiatry research. Neuroimaging
Jun 8, 2025
Experiencing mild symptoms of psychosis, like delusions and hallucinations, occurs sometimes in general, nonclinical populations, often termed psychosis proneness (PP), potentially part of the psychosis continuum. Understanding the neural and environ...
Neuronal dynamics of slow and fast-motion motor imagery.
Neuroscience
Jun 5, 2025
Motor imagery (MI) is a cognitive process requiring mental simulation of physical actions, engaging neural networks that overlap with those activated during actual execution. This study investigated the neural correlates of slow and fast MI in ten he...
Recognition of flight cadets brain functional magnetic resonance imaging data based on machine learning analysis.
PloS one
Jun 5, 2025
The rapid advancement of the civil aviation industry has attracted significant attention to research on pilots. However, the brain changes experienced by flight cadets following their training remain, to some extent, an unexplored territory compared ...
Explainable machine learning model predicting neurological deterioration in Wilson's disease via MRI radiomics and clinical features.
Parkinsonism & related disorders
Jun 4, 2025
BACKGROUND: This study aims to build a machine learning (ML) model to predict the deterioration of neurological symptoms in Wilson's disease (WD) patients during short-term anti-copper therapy. The model combines brain T1WI MRI radiomics with clinica...
Vascular segmentation of functional ultrasound images using deep learning.
Computers in biology and medicine
Jun 4, 2025
Segmentation of medical images is a fundamental task with numerous applications. While MRI, CT, and PET modalities have significantly benefited from deep learning segmentation techniques, more recent modalities, like functional ultrasound (fUS), have...
Dynamically weighted graph neural network for detection of early mild cognitive impairment.
PloS one
Jun 4, 2025
Alzheimer's disease (AD) is a prevalent neurodegenerative disease that primarily affects the elderly population. The early detection of mild cognitive impairment (MCI) holds significant clinical importance for prompt intervention and treatment of AD....
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