Spatio-temporal Localization And Display Of Focal Epileptic Activity From The Electrocorticogram (ECoG)

Author(s):  
A.B. Barreto ◽  
J.C. Principe ◽  
S.A. Reid
2021 ◽  
Author(s):  
Kristina Belikova ◽  
Aleksandra Zailer ◽  
Svetlana V. Tekucheva ◽  
Sergey N. Ermoljev ◽  
Dmitry V. Dylov

2002 ◽  
Vol 156 (4) ◽  
pp. 725-736 ◽  
Author(s):  
Samuel Y. Cho ◽  
Richard L. Klemke

Initiation of cell migration requires morphological polarization with formation of a dominant leading pseudopodium and rear compartment. A molecular understanding of this process has been limited, due to the inability to biochemically separate the leading pseudopodium from the rear of the cell. Here we examine the spatio-temporal localization and activation of cytoskeletal-associated signals in purified pseudopodia directed to undergo growth or retraction. Pseudopodia growth requires assembly of a p130Crk-associated substrate (CAS)/c-CrkII (Crk) scaffold, which facilitates translocation and activation of Rac1. Interestingly, Rac1 activation then serves as a positive-feedback loop to maintain CAS/Crk coupling and pseudopodia extension. Conversely, disassembly of this molecular scaffold is critical for export and down regulation of Rac1 activity and induction of pseudopodia retraction. Surprisingly, the uncoupling of Crk from CAS during pseudopodium retraction is independent of changes in focal adhesion kinase activity and CAS tyrosine phosphorylation. These findings establish CAS/Crk as an essential scaffold for Rac1-mediated pseudopodia growth and retraction, and illustrate spatio-temporal segregation of cytoskeletal signals during cell polarization.


Brain ◽  
2011 ◽  
Vol 134 (10) ◽  
pp. 2867-2886 ◽  
Author(s):  
Frédéric Grouiller ◽  
Rachel C. Thornton ◽  
Kristina Groening ◽  
Laurent Spinelli ◽  
John S. Duncan ◽  
...  

2020 ◽  
Vol 34 (07) ◽  
pp. 12886-12893
Author(s):  
Xiao-Yu Zhang ◽  
Haichao Shi ◽  
Changsheng Li ◽  
Peng Li

Weakly supervised action recognition and localization for untrimmed videos is a challenging problem with extensive applications. The overwhelming irrelevant background contents in untrimmed videos severely hamper effective identification of actions of interest. In this paper, we propose a novel multi-instance multi-label modeling network based on spatio-temporal pre-trimming to recognize actions and locate corresponding frames in untrimmed videos. Motivated by the fact that person is the key factor in a human action, we spatially and temporally segment each untrimmed video into person-centric clips with pose estimation and tracking techniques. Given the bag-of-instances structure associated with video-level labels, action recognition is naturally formulated as a multi-instance multi-label learning problem. The network is optimized iteratively with selective coarse-to-fine pre-trimming based on instance-label activation. After convergence, temporal localization is further achieved with local-global temporal class activation map. Extensive experiments are conducted on two benchmark datasets, i.e. THUMOS14 and ActivityNet1.3, and experimental results clearly corroborate the efficacy of our method when compared with the state-of-the-arts.


Author(s):  
Xiaohui Gao ◽  
Gauri Patwardhan ◽  
Bonggu Shim ◽  
Tenio Popmintchev ◽  
Henry C. Kapteyn ◽  
...  

NeuroImage ◽  
1996 ◽  
Vol 3 (3) ◽  
pp. S213
Author(s):  
A. Pegna ◽  
C.M. Michel ◽  
R.D. Pascual-Marqui ◽  
M. Seeck ◽  
A. Khateb ◽  
...  

2008 ◽  
Vol 84 (1) ◽  
pp. 35-45 ◽  
Author(s):  
Chong-Jin Feng ◽  
Jun-Bing Guo ◽  
Hong-Wei Jiang ◽  
Shuang-Xi Zhu ◽  
Chun-Yang Li ◽  
...  

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