2025年1月30日 · With the advancement of artificial intelligence technology, more and more effective methods are being used to identify and classify Electroencephalography (EEG) signals to address challenges in healthcare and brain-computer interface fields.

2024年8月15日 · Conventional node features such as temporal and frequency domain properties of EEG signals prove inadequate for capturing the extensive EEG information. In our investigation, we introduce a novel adaptive method for extracting node features from EEG signals utilizing a distinctive task-induced self-supervised learning technique.

2012年4月25日 · Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks – whose nodes can vary from tens to hundreds – are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size.

2012年4月25日 · Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks – whose nodes can vary from tens to hundreds – are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size.

2015年9月17日 · In this paper, we report a novel software package, called EEGNET, running under MATLAB (Math works, inc), and allowing for analysis and visualization of functional brain networks from M/EEG recordings. EEGNET is developed to analyze networks either at the level of scalp electrodes or at the level of reconstructed cortical sources.

2024年1月24日 · The most effective EEG nodes are typically selected through an EEG channel selection method (Yang et al., 2017). The primary motor cortex is a crucial brain region for classifying motor imagery tasks, and under the widely used 10–20 EEG system placement, the three channels C3, C4, and Cz have been identified as the most informative channels ...

1 天前 · Ji et al. identify an idiopathic generalised epilepsy network that links heterogeneously distributed brain abnormalities to a common brain network and deep brain stimulation sites which reduce ...

2 天之前 · In addition to collecting the regional activity of scalp EEG, this study employed the minimum spanning tree (MST) network to represent neural strategies. The MST network highlights the core properties of the EEG network by including the strongest connections of all nodes without inter-connection loops [6, 15].

3 天之前 · Attention is the cornerstone of effective functioning in a complex and information-rich world. While the neural activity of attention has been extensively studied in the cortex, the brain-wide neural activity patterns are largely unknown. In this study, we conducted a comprehensive analysis of neural activity across the mouse brain during attentional processing using EEG and c …

1 天前 · Brain-computer interfaces (BCIs) represent an emerging technology that facilitates direct communication between the brain and external devices. In recent years, numerous review articles have explored various aspects of BCIs, including their fundamental principles, technical advancements, and applications in specific domains. However, these reviews often focus on signal processing, hardware ...