Examining the reliability of brain age algorithms under varying degrees of participant motion [0.03%]
探讨不同程度受试者运动对脑部年龄算法可靠性的影响
Jamie L Hanson,Dorthea J Adkins,Eva Bacas et al.
Jamie L Hanson et al.
Brain age algorithms using data science and machine learning techniques show promise as biomarkers for neurodegenerative disorders and aging. However, head motion during MRI scanning may compromise image quality and influence brain age esti...
Rejuvenating classical brain electrophysiology source localization methods with spatial graph Fourier filters for source extents estimation [0.03%]
利用空间图傅里叶滤波器复兴经典脑电定位方法以估计源范围
Shihao Yang,Meng Jiao,Jing Xiang et al.
Shihao Yang et al.
EEG/MEG source imaging (ESI) aims to find the underlying brain sources to explain the observed EEG or MEG measurement. Multiple classical approaches have been proposed to solve the ESI problem based on different neurophysiological assumptio...
Cross subject emotion identification from multichannel EEG sub-bands using Tsallis entropy feature and KNN classifier [0.03%]
利用Tsallis熵特征和K近邻分类器从多通道EEG子频段进行跨领域情绪识别
Pragati Patel,Sivarenjani Balasubramanian,Ramesh Naidu Annavarapu
Pragati Patel
Human emotion recognition remains a challenging and prominent issue, situated at the convergence of diverse fields, such as brain-computer interfaces, neuroscience, and psychology. This study utilizes an EEG data set for investigating human...
An automatic method using MFCC features for sleep stage classification [0.03%]
使用MFCC特征进行睡眠阶段分类的自动方法
Wei Pei,Yan Li,Peng Wen et al.
Wei Pei et al.
Sleep stage classification is a necessary step for diagnosing sleep disorders. Generally, experts use traditional methods based on every 30 seconds (s) of the biological signals, such as electrooculograms (EOGs), electrocardiograms (ECGs), ...
3D convolutional neural networks uncover modality-specific brain-imaging predictors for Alzheimer's disease sub-scores [0.03%]
三维卷积神经网络揭示用于阿尔茨海默病子分数的模态特定脑部成像预测因素
Kaida Ning,Pascale B Cannon,Jiawei Yu et al.
Kaida Ning et al.
Different aspects of cognitive functions are affected in patients with Alzheimer's disease. To date, little is known about the associations between features from brain-imaging and individual Alzheimer's disease (AD)-related cognitive functi...
The onset of motor learning impairments in Parkinson's disease: a computational investigation [0.03%]
帕金森病运动学习障碍的起始：一项计算研究
Ilaria Gigi,Rosa Senatore,Angelo Marcelli
Ilaria Gigi
The basal ganglia (BG) is part of a basic feedback circuit regulating cortical function, such as voluntary movements control, via their influence on thalamocortical projections. BG disorders, namely Parkinson's disease (PD), characterized b...
Synergistic integration of Multi-View Brain Networks and advanced machine learning techniques for auditory disorders diagnostics [0.03%]
多视角脑网络与先进机器学习技术的协同整合在听觉障碍诊断中的应用
Muhammad Atta Othman Ahmed,Yasser Abdel Satar,Eed M Darwish et al.
Muhammad Atta Othman Ahmed et al.
In the field of audiology, achieving accurate discrimination of auditory impairments remains a formidable challenge. Conditions such as deafness and tinnitus exert a substantial impact on patients' overall quality of life, emphasizing the u...
Deep learning based joint fusion approach to exploit anatomical and functional brain information in autism spectrum disorders [0.03%]
利用自闭症谱系障碍中解剖和功能脑信息的基于深度学习的联合融合方法
Sara Saponaro,Francesca Lizzi,Giacomo Serra et al.
Sara Saponaro et al.
Background: The integration of the information encoded in multiparametric MRI images can enhance the performance of machine-learning classifiers. In this study, we investigate whether the combination of structural and fun...
Addiction-related brain networks identification via Graph Diffusion Reconstruction Network [0.03%]
通过图扩散重建网络识别成瘾相关大脑网络
Changhong Jing,Hongzhi Kuai,Hiroki Matsumoto et al.
Changhong Jing et al.
Functional magnetic resonance imaging (fMRI) provides insights into complex patterns of brain functional changes, making it a valuable tool for exploring addiction-related brain connectivity. However, effectively extracting addiction-relate...
Behavioural relevance of redundant and synergistic stimulus information between functionally connected neurons in mouse auditory cortex [0.03%]
功能连接的鼠标听觉皮层神经元之间的冗余和协同刺激信息的行为相关性研究
Loren Koçillari,Marco Celotto,Nikolas A Francis et al.
Loren Koçillari et al.
Measures of functional connectivity have played a central role in advancing our understanding of how information is transmitted and processed within the brain. Traditionally, these studies have focused on identifying redundant functional co...