Fast spike detection in EEG using eigenvalue analysis and clustering of spatial amplitude distribution

Author(s):  
Tadanori Fukami ◽  
Takamasa Shimada ◽  
Bunnoshin Ishikawa
2018 ◽  
Vol 15 (3) ◽  
pp. 036030 ◽  
Author(s):  
Tadanori Fukami ◽  
Takamasa Shimada ◽  
Bunnoshin Ishikawa

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Richárd Fiáth ◽  
Domokos Meszéna ◽  
Zoltán Somogyvári ◽  
Mihály Boda ◽  
Péter Barthó ◽  
...  

AbstractMultisite, silicon-based probes are widely used tools to record the electrical activity of neuronal populations. Several physical features of these devices are designed to improve their recording performance. Here, our goal was to investigate whether the position of recording sites on the silicon shank might affect the quality of the recorded neural signal in acute experiments. Neural recordings obtained with five different types of high-density, single-shank, planar silicon probes from anesthetized rats were analyzed. Wideband data were filtered to extract spiking activity, then the amplitude distribution of samples and quantitative properties of the recorded brain activity (single unit yield, spike amplitude and isolation distance) were compared between sites located at different positions of the silicon shank, focusing particularly on edge and center sites. Edge sites outperformed center sites: for all five probe types there was a significant difference in the signal power computed from the amplitude distributions, and edge sites recorded significantly more large amplitude samples both in the positive and negative range. Although the single unit yield was similar between site positions, the difference in spike amplitudes was noticeable in the range corresponding to high-amplitude spikes. Furthermore, the advantage of edge sites slightly decreased with decreasing shank width. Our results might aid the design of novel neural implants in enhancing their recording performance by identifying more efficient recording site placements.


2017 ◽  
Vol 128 (1) ◽  
pp. 243-250 ◽  
Author(s):  
Mark L. Scheuer ◽  
Anto Bagic ◽  
Scott B. Wilson

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