Literature DB >> 3192230

A totally automated system for the detection and classification of neural spikes.

X W Yang, S A Shamma.   

Abstract

Mesh：

Year:  1988        PMID： 3192230     DOI： 10.1109/10.7287

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN： 0018-9294            Impact factor:   4.538


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  7 in total

1.  Automated spike sorting using density grid contour clustering and subtractive waveform decomposition.

Authors:  Carlos Vargas-Irwin; John P Donoghue
Journal:  J Neurosci Methods       Date:  2007-04-12       Impact factor: 2.390

2.  Detection of spontaneous synaptic events with an optimally scaled template.

Authors:  J D Clements; J M Bekkers
Journal:  Biophys J       Date:  1997-07       Impact factor: 4.033

3.  Identification of connectivity in neural networks.

Authors:  X W Yang; S A Shamma
Journal:  Biophys J       Date:  1990-05       Impact factor: 4.033

Review 4.  Continuing progress of spike sorting in the era of big data.

Authors:  David Carlson; Lawrence Carin
Journal:  Curr Opin Neurobiol       Date:  2019-03-08       Impact factor: 6.627

5.  An automatic measure for classifying clusters of suspected spikes into single cells versus multiunits.

Authors:  Ariel Tankus; Yehezkel Yeshurun; Itzhak Fried
Journal:  J Neural Eng       Date:  2009-08-07       Impact factor: 5.379

6.  Development and validation of a spike detection and classification algorithm aimed at implementation on hardware devices.

Authors:  E Biffi; D Ghezzi; A Pedrocchi; G Ferrigno
Journal:  Comput Intell Neurosci       Date:  2010-03-14

7.  High-density microelectrode array recordings and real-time spike sorting for closed-loop experiments: an emerging technology to study neural plasticity.

Authors:  Felix Franke; David Jäckel; Jelena Dragas; Jan Müller; Milos Radivojevic; Douglas Bakkum; Andreas Hierlemann
Journal:  Front Neural Circuits       Date:  2012-12-20       Impact factor: 3.492
  7 in total

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