720 A fMRI study on human brain activity ofthe spatial attention recognition with sight cue

2011 ◽  
Vol 2011.49 (0) ◽  
pp. 203-204
Author(s):  
Yuya Kawata ◽  
Chunlin Li ◽  
Satoshi Takahashi ◽  
Jinglong Wu
Keyword(s):  
Human Brain ◽  
Spatial Attention ◽  
Brain Activity ◽  
Fmri Study

Effects of motor fatigue on human brain activity, an fMRI study

NeuroImage ◽  
2007 ◽  
Vol 35 (4) ◽  
pp. 1438-1449 ◽  
Author(s):  
Hiske van Duinen ◽  
Remco Renken ◽  
Natasha Maurits ◽  
Inge Zijdewind
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
Fmri Study

Human brain activity in the control of fine static precision grip forces: an fMRI study

2001 ◽  
Vol 14 (2) ◽  
pp. 382-390 ◽  
Author(s):  
Johann P. Kuhtz-Buschbeck ◽  
H. Henrik Ehrsson ◽  
Hans Forssberg
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
Precision Grip ◽  
Fmri Study

scholarly journals Is Human Brain Activity During Driving Operations Modulated by the Viscoelastic Characteristics of a Steering Wheel?: An fMRI Study

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 215073-215090
Author(s):  
Yoshihisa Okamoto ◽  
Takafumi Sasaoka ◽  
Norihiro Sadato ◽  
Masaki Fukunaga ◽  
Tetsuya Yamamoto ◽  
...  
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
Steering Wheel ◽  
Fmri Study ◽  
Viscoelastic Characteristics

scholarly journals Age-Dependent Differences in Human Brain Activity Using a Face- and Location-Matching Task: An fMRI Study

2007 ◽  
Vol 24 (4) ◽  
pp. 235-246 ◽  
Author(s):  
G. Leinsinger ◽  
C. Born ◽  
T. Meindl ◽  
A.L.W. Bokde ◽  
S. Britsch ◽  
...  
Keyword(s):  
Human Brain ◽  
Brain Activity ◽  
Matching Task ◽  
Fmri Study ◽  
Age Dependent

The Effects of CCRC on Cognition and Brain Activity in aMCI Patients: A Pilot Placebo Controlled BOLD fMRI Study

2014 ◽  
Vol 11 (5) ◽  
pp. 484-493 ◽  
Author(s):  
Junying Zhang ◽  
Zijing Wang ◽  
Shijun Xu ◽  
Yaojing Chen ◽  
Kewei Chen ◽  
...  
Keyword(s):  
Brain Activity ◽  
Bold Fmri ◽  
Fmri Study

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.

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