Brain Neuron Preparations for the Study of Aging Changes in Calcium Potentials and Currents

1994 ◽  
Vol 4 (3) ◽  
pp. 177-181 ◽  
Author(s):  
Olivier Thibault ◽  
Mary L. Mazzanti ◽  
Eric M. Blalock ◽  
Nada M. Porter ◽  
Philip W. Landfield
Keyword(s):  
2000 ◽  
Vol 28 (5) ◽  
pp. A395-A395
Author(s):  
N. M. Vladimirova ◽  
N. A. Potapenko ◽  
T. V. Ovchinnikova
Keyword(s):  

1983 ◽  
Vol 96 (1) ◽  
pp. 892-894
Author(s):  
V. V. Semchenko ◽  
L. V. Polu�ktov ◽  
V. D. Konvai

2008 ◽  
Vol 32 (3) ◽  
pp. S8-S8 ◽  
Author(s):  
Bo Dong ◽  
Huang Xu ◽  
Yong Xia Zheng ◽  
Xun Xu ◽  
Fu Jun Wan ◽  
...  

2020 ◽  
Author(s):  
Gang Liu

In recent years, artificial neural networks (ANNs) have won numerous contests in pattern recognition, machine learning, and artificial intelligence. The basic unit of an ANN is to mimic neurons in the brain. Neuron in ANNs is expressed as f(wx+b) or f(wx).This structure does not consider the information processing capabilities of dendrites. However, recently, studies shown that dendrites participate in pre-calculation in the brain. Concretely, biological dendrites play a role in the pre-processing to the interaction information of input data. Therefore, it's time to perfect the neuron of the neural network. This paper, add dendrite processing section, presents a novel artificial neuron, according to our previous studies (CR-PNN or Gang transform). The dendrite processing section can be expressed as WA.X. Because I perfected the basic unit of ANNs-neuron, there are so many networks to try, this article gives the basic architecture for reference in future research.


2016 ◽  
Vol 2016 (0) ◽  
pp. G2300104
Author(s):  
Hiromichi NAKADATE ◽  
Shigeru AOMURA ◽  
Akira KAKUTA
Keyword(s):  

Neuroreport ◽  
1998 ◽  
Vol 9 (10) ◽  
pp. 2353-2357 ◽  
Author(s):  
Masatomo Watanabe ◽  
Yoshihide Ohe ◽  
Kenji Katakai ◽  
Kenji Kabeya ◽  
Yukihito Fukumura ◽  
...  

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