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Extracting functional components of neural dynamics with Independent Component Analysis and inverse Current Source Density

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Abstract

Local field potentials have good temporal resolution but are blurred due to the slow spatial decay of the electric field. For simultaneous recordings on regular grids one can reconstruct efficiently the current sources (CSD) using the inverse Current Source Density method (iCSD). It is possible to decompose the resultant spatiotemporal information about the current dynamics into functional components using Independent Component Analysis (ICA). We show on test data modeling recordings of evoked potentials on a grid of 4×5×7 points that meaningful results are obtained with spatial ICA decomposition of reconstructed CSD. The components obtained through decomposition of CSD are better defined and allow easier physiological interpretation than the results of similar analysis of corresponding evoked potentials in the thalamus. We show that spatiotemporal ICA decompositions can perform better for certain types of sources but it does not seem to be the case for the experimental data studied. Having found the appropriate approach to decomposing neural dynamics into functional components we use the technique to study the somatosensory evoked potentials recorded on a grid spanning a large part of the forebrain. We discuss two example components associated with the first waves of activation of the somatosensory thalamus. We show that the proposed method brings up new, more detailed information on the time and spatial location of specific activity conveyed through various parts of the somatosensory thalamus in the rat.

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Notes

  1. See Hunt et al. (2009, unpublished). Available at http://www.neuroinf.pl/Members/danek/homepage/preprints/Article.2009-10-22.4312

  2. STICA software available at http://jim-stone.staff.shef.ac.uk/

  3. The package is available at http://www.cis.hut.fi/jhimberg/icasso/

  4. http://www.neuroinf.pl/Members/szleski/iCSD_data/ICviewer

  5. http://www.neuroinf.pl/Members/szleski/iCSD_data/ICviewer

  6. The single exception is Rat 6, where the recording grid encompassed the border with cortical tissue. For this rat we found three strong cortical components with long latencies accompanied by moderate strength components typically located at somatosensory thalamus.

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Authors and Affiliations

  1. Department of Neurophysiology, Nencki Institute of Experimental Biology, 3 Pasteur St., 02-093, Warsaw, Poland

    Szymon Łęski, Ewa Kublik, Daniel A. Świejkowski, Andrzej Wróbel & Daniel K. Wójcik

Authors
  1. Szymon Łęski
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  2. Ewa Kublik
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  3. Daniel A. Świejkowski
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  4. Andrzej Wróbel
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  5. Daniel K. Wójcik
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Corresponding author

Correspondence to Szymon Łęski.

Additional information

Action Editor: T. Sejnowski

This work was partly financed from the Polish Ministry of Science and Higher Education grants PBZ/MNiSW/07/2006/11 and 46/N-COST/2007/0.

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Abbreviations

Abbreviations

APT:

anterior pretectal nucleus

DLG:

dorsal lateral geniculate nucleus

Hipp:

hippocampus

LD:

latero-dorsal thalamic nucleus

LP:

lateral posterior thalamic nucleus

MGM:

medial geniculate nucleus, medial part

Po:

posterior thalamic nuclear group

Rt:

reticular thalamic nucleus

SN:

substantia nigra

VPM:

ventral postero-medial thalamic nucleus

VLG:

ventral lateral geniculate nucleus

ZI:

zona incerta

ZIc:

caudal part of zona incerta

cp:

cerebral peduncle

ic:

internal capsule

ml:

medial lemniscus

opt:

optic tract

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Łęski, S., Kublik, E., Świejkowski, D.A. et al. Extracting functional components of neural dynamics with Independent Component Analysis and inverse Current Source Density. J Comput Neurosci 29, 459–473 (2010). https://doi.org/10.1007/s10827-009-0203-1

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  • DOI: https://doi.org/10.1007/s10827-009-0203-1

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