Qualitative and Quantitative Measurement of Human Brain Activity Using Pixel Subtraction Algorithm

2004 ◽  
Vol 51 (2) ◽  
pp. 165 ◽  
Author(s):  
Jin Myoung Lee ◽  
Gwang Woo Jeong ◽  
Hyung Joong Kim ◽  
Seong Hoon Cho ◽  
Heoung Keun Kang ◽  
...  
Keyword(s):  
Human Brain ◽  
Quantitative Measurement ◽  
Brain Activity ◽  
Qualitative And Quantitative

scholarly journals Siamese Reconstruction Network: Accurate Image Reconstruction from Human Brain Activity by Learning to Compare

2019 ◽  
Vol 9 (22) ◽  
pp. 4749
Author(s):  
Lingyun Jiang ◽  
Kai Qiao ◽  
Linyuan Wang ◽  
Chi Zhang ◽  
Jian Chen ◽  
...  
Keyword(s):  
Deep Learning ◽  
Human Brain ◽  
Brain Activity ◽  
Feature Space ◽  
Training Data ◽  
Reconstruction Method ◽  
Learning Method ◽  
Training Samples ◽  
Visual Reconstruction ◽  
Relationship Of

Decoding human brain activities, especially reconstructing human visual stimuli via functional magnetic resonance imaging (fMRI), has gained increasing attention in recent years. However, the high dimensionality and small quantity of fMRI data impose restrictions on satisfactory reconstruction, especially for the reconstruction method with deep learning requiring huge amounts of labelled samples. When compared with the deep learning method, humans can recognize a new image because our human visual system is naturally capable of extracting features from any object and comparing them. Inspired by this visual mechanism, we introduced the mechanism of comparison into deep learning method to realize better visual reconstruction by making full use of each sample and the relationship of the sample pair by learning to compare. In this way, we proposed a Siamese reconstruction network (SRN) method. By using the SRN, we improved upon the satisfying results on two fMRI recording datasets, providing 72.5% accuracy on the digit dataset and 44.6% accuracy on the character dataset. Essentially, this manner can increase the training data about from n samples to 2n sample pairs, which takes full advantage of the limited quantity of training samples. The SRN learns to converge sample pairs of the same class or disperse sample pairs of different class in feature space.

Human brain activity during memory

Science ◽  
2020 ◽  
Vol 367 (6482) ◽  
pp. 1086.8-1087
Author(s):  
Peter Stern
Keyword(s):  
Human Brain ◽  
Brain Activity

Mathematical dipoles are adequate to describe realistic generators of human brain activity

1988 ◽  
Vol 35 (11) ◽  
pp. 960-966 ◽  
Author(s):  
J.C. de Munck ◽  
B.W. van Dijk ◽  
H. Spekreijse
Keyword(s):  
Human Brain ◽  
Brain Activity

scholarly journals Time-Invariant Person-Specific Frequency Templates in Human Brain Activity

2006 ◽  
Vol 96 (25) ◽  
Author(s):  
Itai Doron ◽  
Eyal Hulata ◽  
Itay Baruchi ◽  
Vernon L. Towle ◽  
Eshel Ben-Jacob
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
Specific Frequency ◽  
Time Invariant

scholarly journals Molecular Species of the Alcohol Biomarker Phosphatidylethanol in Human Blood Measured by LC-MS

2009 ◽  
Vol 55 (7) ◽  
pp. 1395-1405 ◽  
Author(s):  
Anders Helander ◽  
Yufang Zheng
Keyword(s):  
Fatty Acid ◽  
Human Blood ◽  
Molecular Species ◽  
Quantitative Measurement ◽  
Selected Ion Monitoring ◽  
Blood Samples ◽  
Qualitative And Quantitative ◽  
Ms Analysis ◽  
Alcohol Biomarker ◽  
Product Ions

Abstract Background: The alcohol biomarker phosphatidylethanol (PEth) comprises a group of ethanol-derived phospholipids formed from phosphatidylcholine by phospholipase D. The PEth molecular species have a common phosphoethanol head group onto which 2 fatty acid moieties are attached. We developed an electrospray ionization (ESI) LC-MS method for qualitative and quantitative measurement of different PEth species in human blood. Methods: We subjected a total lipid extract of whole blood to HPLC gradient separation on a C4 column and performed LC-ESI-MS analysis using selected ion monitoring of deprotonated molecules for the PEth species and phosphatidylpropanol (internal standard). Identification of individual PEth species was based on ESI–tandem mass spectrometry (MS/MS) analysis of product ions. Results: The fatty acid moieties were the major product ions of PEth, based on comparison with PEth-16:0/16:0, 18:1/18:1, and 16:0/18:1 reference material. For LC-MS analysis of different PEth species in blood, we used a calibration curve covering 0.2–7.0 μmol/L PEth-16:0/18:1. The lower limit of quantitation of the method was <0.1 μmol/L, and intra- and interassay CVs were <9% and <11%. In blood samples collected from 38 alcohol patients, the total PEth concentration ranged between 0.1 and 21.7 μmol/L (mean 8.9). PEth-16:0/18:1 and 16:0/18:2 were the predominant molecular species, accounting for approximately 37% and 25%, respectively, of total PEth. PEth-16:0/20:4 and mixtures of 18:1/18:1 plus 18:0/18:2 (not separated using selected ion monitoring because of identical molecular masses) and 16:0/20:3 plus 18:1/18.2 made up approximately 13%, 12%, and 8%. Conclusions: This LC-MS method allows simultaneous qualitative and quantitative measurement of several PEth molecular species in whole blood samples.

Theory of the Relation between Human Brain Activity (MEG) and Hand Movements

NeuroImage ◽  
2000 ◽  
Vol 11 (5) ◽  
pp. 359-369 ◽  
Author(s):  
Armin Fuchs ◽  
Viktor K. Jirsa ◽  
J.A.Scott Kelso
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
Hand Movements
Sign in / Sign up

Export Citation Format

Share Document