Extraction of functional components from multichannel LFP data
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1
Nencki Institute of Experimental Biology, Department of Neuropsychology, Poland
Multi-electrode recordings of extracellular potentials are a useful tool for understanding dynamics of the brain at the population level. However, efficient analysis of such recordings is a challenge. First, the electric signal recorded in one place may reflect distant synaptic currents due to electric field propagation in the tissue. Second, each signal is a mixture of contributions from several populations active at the same time.
We show that the combination of inverse current source density method (iCSD, [1,2]) followed by independent component analysis (ICA) in spatial domain [3,4] constitutes a powerful and stable method for efficient extraction of functional components from multi-electrode recordings of LFP.
We applied this procedure to potentials evoked by deflection of all the vibrissae from one side of rat's snout recorded on a regular three-dimensional grid in the rat's forebrain [1]. The analyzed dataset consists of average evoked responses measured in 140 locations. The proposed method allows to decompose the complex dynamics of the recorded responses into a small number of spatially localized components with simple time courses which can be interpreted physiologically in terms of activity of different nuclei. The decomposition is stable with respect to different starting points of the ICA algorithm. Application of ICA to potentials (instead of CSD) results in components which are less precise in space and the decomposition is not as stable. We have also studied temporal and spatiotemporal ICA decompositions of both raw LFP and CSD and we observed that temporal decompositions produce components which are not meaningful physiologically. Spatiotemporal decompositions are gaining stability and quality with the increase of spatial component with the optimum obtained for purely spatial decompositions.
Acknowledgements: This research has been supported by the Polish Ministry of Science and Higher Education under grants PBZ/MNiSW/07/2006/11 and 46/N-COST/2007/0.
References
1. Łęski S, Wójcik DK, Tereszczuk J, Świejkowski DA, Kublik E, Wróbel A: Inverse Current-Source Density Method in 3D: Reconstruction Fidelity, Boundary Effects, and Influence of Distant Sources. Neuroinformatics 2008, 5: 207-222.
2. Pettersen KH, Devor A, Ulbert I, Dale AM, Einevoll GT: Current-source density estimation based on inversion of electrostatic forward solution: effects of finite extent of neuronal activity and conductivity discontinuities. J Neurosci Methods 2006, 154:116-133.
3. Stone JV and Porrill J: Regularisation Using Spatiotemporal Independence and Predictability. Computational Neuroscience Report 201, Psychology Department, Sheffield University.
4. Stone JV, Porrill J, Porter NR, Wilkinson ID: Spatiotemporal Independent Component Analysis of Event-Related fMRI Data Using Skewed Probability Density Functions. NeuroImage 2002, 15:407-421.
Conference:
Neuroinformatics 2009, Pilsen, Czechia, 6 Sep - 8 Sep, 2009.
Presentation Type:
Poster Presentation
Topic:
Electrophysiology
Citation:
Łęski
S,
Kublik
E,
Świejkowski
DA,
Wróbel
A and
Wójcik
DK
(2019). Extraction of functional components from multichannel LFP data.
Front. Neuroinform.
Conference Abstract:
Neuroinformatics 2009.
doi: 10.3389/conf.neuro.11.2009.08.060
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Received:
22 May 2009;
Published Online:
09 May 2019.
*
Correspondence:
Szymon Łęski, Nencki Institute of Experimental Biology, Department of Neuropsychology, Granz, Poland, s.leski@nencki.gov.pl