scholarly journals Electroencephalogram Source Imaging and Brain Network Based Natural Grasps Decoding

2021 ◽  
Vol 15 ◽  
Author(s):  
Baoguo Xu ◽  
Leying Deng ◽  
Dalin Zhang ◽  
Muhui Xue ◽  
Huijun Li ◽  
...  
Keyword(s):  
Parietal Lobe ◽  
Phase Locking ◽  
Brain Network ◽  
Internal Communication ◽  
Peak Performance ◽  
Source Imaging ◽  
Planning Stage ◽  
Grand Average ◽  
Reach And Grasp ◽  
Phase Locking Value

Studying the decoding process of complex grasping movement is of great significance to the field of motor rehabilitation. This study aims to decode five natural reach-and-grasp types using sources of movement-related cortical potential (MRCP) and investigate their difference in cortical signal characteristics and network structures. Electroencephalogram signals were gathered from 40 channels of eight healthy subjects. In an audio cue-based experiment, subjects were instructed to keep no-movement condition or perform five natural reach-and-grasp movements: palmar, pinch, push, twist and plug. We projected MRCP into source space and used average source amplitudes in 24 regions of interest as classification features. Besides, functional connectivity was calculated using phase locking value. Six-class classification results showed that a similar grand average peak performance of 49.35% can be achieved using source features, with only two-thirds of the number of channel features. Besides, source imaging maps and brain networks presented different patterns between each condition. Grasping pattern analysis indicated that the modules in the execution stage focus more on internal communication than in the planning stage. The former stage was related to the parietal lobe, whereas the latter was associated with the frontal lobe. This study demonstrates the superiority and effectiveness of source imaging technology and reveals the spread mechanism and network structure of five natural reach-and-grasp movements. We believe that our work will contribute to the understanding of the generation mechanism of grasping movement and promote a natural and intuitive control of brain–computer interface.

scholarly journals Different Brain Network Activations Induced by Modulation and Nonmodulation Laser Acupuncture

2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
Author(s):  
Chang-Wei Hsieh ◽  
Jih-Huah Wu ◽  
Chao-Hsien Hsieh ◽  
Qwa-Fun Wang ◽  
Jyh-Horng Chen
Keyword(s):  
Primary Motor Cortex ◽  
Parietal Lobe ◽  
Random Effect ◽  
Sensory Information ◽  
Brain Network ◽  
Laser Acupuncture ◽  
Middle Temporal Gyrus ◽  
Left Frontal Lobe ◽  
External Stimulation ◽  
Acupuncture Stimulation

The aim of this study is to compare the distinct cerebral activation with continued wave (CW) and 10 Hz-modulated wave (MW) stimulation during low-level laser acupuncture. Functional magnetic resonance imaging (fMRI) studies were performed to investigate the possible mechanism during laser acupuncture stimulation at the left foot's yongquan (K1) acupoint. There are 12 healthy right-handed volunteers for each type of laser stimulation (10-Hz-Modulated wave: 8 males and 4 females; continued wave: 9 males and 3 females). The analysis of multisubjects in this experiment was applied by random-effect (RFX) analysis. In CW groups, significant activations were found within the inferior parietal lobule, the primary somatosensory cortex, and the precuneus of left parietal lobe. Medial and superior frontal gyrus of left frontal lobe were also aroused. In MW groups, significant activations were found within the primary motor cortex and middle temporal gyrus of left hemisphere and bilateral cuneus. Placebo stimulation did not show any activation. Most activation areas were involved in the functions of memory, attention, and self-consciousness. The results showed the cerebral hemodynamic responses of two laser acupuncture stimulation modes and implied that its mechanism was not only based upon afferent sensory information processing, but that it also had the hemodynamic property altered during external stimulation.

scholarly journals Abnormal Functional and Structural networks in Rectal Cancer with Depressive symptoms: A Graph Theory Analysis

2019 ◽  
Author(s):  
Wenwen Zhang ◽  
Ying Zou ◽  
Yuan Li ◽  
Yu Fu ◽  
Jie Shi ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Emotional Disorders ◽  
Parietal Lobe ◽  
Diffusion Tensor ◽  
Brain Network ◽  
Imaging Data ◽  
Network Efficiency ◽  
Limbic Lobe ◽  
Random Node ◽  
Brain Network Reorganization

Abstract Background: Surgery and chemotherapy can cause emotional disorders in patients with rectal cancer (RC). However, few comprehensive studies are conducted on RC patients associated alterations in the topological organization of structural and functional networks. Methods: Resting-state functional MRI and Diffusion tensor imaging data were collected from 36 RC patients with surgery and chemotherapy and 32 healthy controls (HC). Functional network (FN) was constructed from extracting average time courses for 246 regions of interest (ROI) and structural network (SN) was established by deterministic tractography. Graph theoretical analysis was used to calculate small-worldness property, clustering coefficients, shortest path length and network efficiency. Additionally, we assess network resilient on FN and SN. Results: Abnormal small-worldness property of FN and SN were found in RC patients. The FN and SN exhibited increased local efficiency and global efficiency respectively in RC patients.The increased nodal efficiency in RC patients were mainly found in the frontal lobe, parietal lobe and limbic lobe for FN and SN, while the decreased nodal efficiency were distributed in subcortical nuclei, parietal lobe and limbic lobe only for SN. In network resilient analysis, the RC patients showed less resilient to targeted or random node deletion in both networks compared with HC. Moreover, FN is more robust than SN for all participants. Conclusions: This study revealed that topological organizations of the FN and SN may be disrupted in RC patients. Brain network reorganization is a compensation mechanism for brain impairment after surgery and chemotherapy.

scholarly journals A note on the phase locking value and its properties

NeuroImage ◽  
2013 ◽  
Vol 74 ◽  
pp. 231-244 ◽  
Author(s):  
Sergul Aydore ◽  
Dimitrios Pantazis ◽  
Richard M. Leahy
Keyword(s):  
Phase Locking ◽  
Phase Locking Value

Experts EEG Cognitive Analysis and Substance Classification in Security Inspection

2019 ◽  
Vol 33 (04) ◽  
pp. 1950006 ◽  
Author(s):  
Yue Yuan ◽  
Hong Wang ◽  
Peixin Yuan
Keyword(s):  
Phase Locking ◽  
Low Frequency ◽  
Brain Network ◽  
Eeg Signals ◽  
Graph Theoretic ◽  
Security Officers ◽  
Detection Technology ◽  
Functional Brain Network ◽  
New Perspective ◽  
Security Inspection

In recent years, the workload of security offers has increased along with the requirement of anti-terrorism. In the paper, a series of evaluation index of security inspection based on the EEG signals of the security officers were proposed to improve the accuracy of dangerous instances detection and decrease the workload of the officers. We performed an experiment to record the EEG data of security officers when they were watching the picture with or without the dangerous item in the uncovered and obscured scenes. Brain network analysis based on graph theory was applied to generate the indexes from the EEG induced by the parcel picture of security inspection, and is a new perspective on the classification of the parcel composition. The paper studied the low-frequency, multi-channel experts EEG signals, calculated the phase locking value (PLV) between every two channels to construct the topological functional brain network (FBN). The appropriate binary FBNs were obtained by setting the thresholds, and then the complex brain network parameters were estimated by the graph-theoretic methods, which were used for classification with 10-fold cross-validation and the average accuracy was 83.3[Formula: see text][Formula: see text][Formula: see text]97.78%. The method was effectively applied to the substance classification and would further improve the recognition accuracy of the target by combining this method with the existing detection technology.

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