Functional classification of neurons in mouse hippocampus based on spike waveforms in extracellular recordings

Author(s):  
Mehrdad Oghazian ◽  
Ali Khadem ◽  
Moein Esghaei
Author(s):  
Mehrdad Oghazian ◽  
Farzad Saffari ◽  
Ali Khadem

Purpose: Inhibitory and excitatory neurons play an essential role in brain function, and we aim to introduce an automatic method to discriminate these two populations based on features of the shape of their spikes. Consequently, we will explain the spike extraction from raw data of a single shank electrode and determine the best features of spike waveforms for the classification of neurons. It is noteworthy that, to the best of our knowledge, classification of inhibitory and excitatory neurons using the shape features extracted from their spike waveforms has not been done before. Materials and Methods: In this paper, we use a dataset of mouse hippocampus neurons in which the neuron types (inhibitory or excitatory) have been verified optogenetically. For the classification of mouse hippocampus neurons, we extracted eight shape features of their spike waveforms in addition to their firing rates and used three types of classifiers: K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), and Support Vector Machine (SVM) to analyze the discriminatory power of features based on the accuracy of the classifications. Results: We showed that Spike asymmetry, Peak-to-trough ratio, Recovery slope, and Duration between peaks were four shape features of spike waveforms participated in the optimum feature subsets that resulted in maximum classification accuracy. Moreover, the SVM classifier with RBF kernel resulted in maximum accuracy of %96.91 ± %13.03 and was identified as the best classifier. Conclusion: In this study, we found that shape features of spike waveforms can accurately classify inhibitory and excitatory neurons of mouse hippocampus. Also, we found an optimum subset of shape features of spike waveforms that resulted in better classification performance than previously proposed subsets of features used for clustering of neurons. Our findings open a promising way toward a functional classification of neurons automatically.


Physiotherapy ◽  
2013 ◽  
Vol 21 (3) ◽  
Author(s):  
Natalia Uścinowicz ◽  
Wojciech Seidel ◽  
Paweł Zostawa ◽  
Sebastian Klich

AbstractThe recent Olympic Games in London incited much interest in the competition of disabled athletes. Various people connected with swimming, including coaches and athletes, have speculated about the fairness of competitions of disabled athletes. A constant problem are the subjective methods of classification in disabled sport. Originally, athletes with disabilities were classified according to medical diagnosis. Due to the injustice which still affects the competitors, functional classification was created shortly after. In the present review, the authors show the anomalies in the structure of the classification. The presented discovery led to the suggestion to introduce objective methods, thanks to which it would be no longer necessary to rely on the subjective assessment of the classifier. According to the authors, while using objective methods does not completely rule out the possibility of fraud by disabled athletes in the classification process, it would certainly reduce their incidence. Some of the objective methods useful for the classification of disabled athletes are: posturography, evaluation of the muscle parameters, electrogoniometric assessment, surface electromyography, and analysis of kinematic parameters. These methods have provide objective evaluation in the diagnostic sense but only if they are used in tandem. The authors demonstrate the undeniable benefits of using objective methods. Unfortunately, there are not only advantages of such solution, there also several drawbacks to be found. The conclusion of the article is the statement by the authors that it is right to use objective methods which allow to further the most important rule in sport: fair-play.


2020 ◽  
Vol 73 (3) ◽  
pp. 358-367
Author(s):  
Júlio Cezar Rebés Azambuja Filho ◽  
Paulo Cesar de Faccio Carvalho ◽  
Olivier Jean François Bonnet ◽  
Denis Bastianelli ◽  
Magali Jouven

2000 ◽  
Vol 302 (1) ◽  
pp. 189-203 ◽  
Author(s):  
John R Cort ◽  
Adelinda Yee ◽  
Aled M Edwards ◽  
Cheryl H Arrowsmith ◽  
Michael A Kennedy

Author(s):  
Jan Willem Gorter ◽  
Peter L Rosenbaum ◽  
Steven E Hanna ◽  
Robert J Palisano ◽  
Doreen J Bartlett ◽  
...  

2018 ◽  
Vol 33 (3) ◽  
pp. 3784-3794 ◽  
Author(s):  
Qian Shi ◽  
Fei Zhuang ◽  
Ji-Ting Liu ◽  
Na Li ◽  
Yuan-Xiu Chen ◽  
...  

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