Magnetic control of cortical pyramidal neuron activity using a micro-coil

Author(s):  
Seung Woo Lee ◽  
Shelley I. Fried
2020 ◽  
pp. 107197
Author(s):  
Benneth Ben-Azu ◽  
Adegbuyi Oladele Aderibigbe ◽  
Abayomi Mayowa Ajayi ◽  
Aya-Ebi Okubo Eneni ◽  
Itivere Adrian Omogbiya ◽  
...  

2000 ◽  
Vol 32-33 ◽  
pp. 181-187 ◽  
Author(s):  
Adam Kepecs ◽  
Xiao-Jing Wang

2019 ◽  
Vol 70 ◽  
pp. 338-353 ◽  
Author(s):  
Benneth Ben-Azu ◽  
Adegbuyi Oladele Aderibigbe ◽  
Abayomi Mayowa Ajayi ◽  
Aya-Ebi Okubo Eneni ◽  
Itivere Adrian Omogbiya ◽  
...  

Author(s):  
Clément Vitrac ◽  
Sophie Péron ◽  
Isabelle Frappé ◽  
Pierre-Olivier Fernagut ◽  
Mohamed Jaber ◽  
...  

2011 ◽  
Vol 5 (3) ◽  
pp. 241-251 ◽  
Author(s):  
Xiumin Li ◽  
Kenji Morita ◽  
Hugh P. C. Robinson ◽  
Michael Small

2015 ◽  
pp. bhv245 ◽  
Author(s):  
Luping Yin ◽  
Malte J. Rasch ◽  
Quansheng He ◽  
Si Wu ◽  
Fei Dou ◽  
...  

2018 ◽  
Author(s):  
Yelena Kolezeva

AbstractAppropriately classifying neuronal subgroups is critical to numerous downstream procedures in several disciplines of biomedical research. The cortical pyramidal neuron characterization technology has achieved rapid development in recent years. However, capturing true neuronal features for accurate pyramidal neuron characterization and segmentation has remained elusive. In the current study, a novel global preserving estimate algorithm is used to capture the non-linearity in the features of cortical pyramidal neuron after Factor Algorithm. Our results provide evidence for the effective integration of the original linear and nonlinear neuronal features and achieves better characterization performance on multiple cortical pyramidal neuron databases through array matching.


2017 ◽  
Vol 37 (25) ◽  
pp. 6075-6086 ◽  
Author(s):  
Andrea L. Gutman ◽  
Kelle E. Nett ◽  
Caitlin V. Cosme ◽  
Wensday R. Worth ◽  
Subhash C. Gupta ◽  
...  

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