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Neural spike sorting using iterative ICA ...
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Document type :
Article dans une revue scientifique
DOI :
10.1088/1741-2560/9/6/066002
Title :
Neural spike sorting using iterative ICA and deflation based approach
Author(s) :
Tiganj, Zoran [Auteur]
Laboratoire d'Ingénierie des Systèmes de Versailles [LISV]
Non-Asymptotic estimation for online systems [NON-A]
Mboup, Mamadou [Auteur]
Centre de Recherche en Sciences et Technologies de l'Information et de la Communication - EA 3804 [CRESTIC]
Non-Asymptotic estimation for online systems [NON-A]
Journal title :
Journal of Neural Engineering
Pages :
066002
Publisher :
IOP Publishing
Publication date :
2012-10-17
ISSN :
1741-2560
HAL domain(s) :
Informatique [cs]/Traitement du signal et de l'image [eess.SP]
Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
English abstract : [en]
We propose a spike sorting method for multi-channel recordings. When applied in neural recordings, the performance of the Independent Component Analysis (ICA) algorithm is known to be limited, since the number of recording ...
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We propose a spike sorting method for multi-channel recordings. When applied in neural recordings, the performance of the Independent Component Analysis (ICA) algorithm is known to be limited, since the number of recording sites is much lower than the number of neurons. The proposed method uses an iterative application of ICA and a deflation technique in two nested loops. In each iteration of the external loop, the spiking activity of one neuron is singled out and then deflated from the recordings. The internal loop implements a sequence of ICA and sorting for removing the noise and all the spikes that are not fired by the targeted neuron. Then a final step is appended to the two nested loops in order to separate simultaneously fired spikes. We solve this problem by taking all possible pairs of the sorted neurons and apply ICA only on the segments of the signal during which at least one of the neurons in a given pair was active. We validate the performance of the proposed method on simulated recordings, but also on a specific type of real recordings: simultaneous extracellular-intracellular. We quantify the sorting results on the extracellular recordings for the spikes that come from the neurons recorded intracellularly. The results suggest that the proposed solution significantly improves the performance of ICA in spike sorting.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
  • Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Source :
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