Document Detail


Optimal band separation of extracellular field potentials.
MedLine Citation:
PMID:  22101145     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Local Field Potentials (LFPs) exhibit a broadband spectral structure that is traditionally partitioned into distinct frequency bands which are thought to originate from different types of neural events triggered by different processing pathways. However, the exact frequency boundaries of these processes are not known and, as a result, the frequency bands are often selected based on intuition, previous literature or visual inspection of the data. Here, we address these problems by developing a rigorous method for defining LFP frequency bands and their boundaries. The criterion introduced for determining the boundaries delimiting the bands is to maximize the information about an external correlate carried jointly by all bands in the partition. The method first partitions the LFP frequency range into two bands and then successively increases the number of bands in the partition. We applied the partitioning method to LFPs recorded from primary visual cortex of anaesthetized macaques, and we determined the optimal band partitioning that describes the encoding of naturalistic visual stimuli. The first optimal boundary partitioned the LFP response at 60Hz into low-and high-frequencies, which had been previously found to convey independent information about the natural movie correlate. The second optimal boundary divided the high-frequency range at approximately 100Hz into gamma and high-gamma frequencies, consistent with recent reports that these two bands reflect partly distinct neural processes. A third important boundary was at 25Hz and it split the LFP range below 50Hz into a stimulus-informative and a stimulus-independent band.
Authors:
Cesare Magri; Alberto Mazzoni; Nikos K Logothetis; Stefano Panzeri
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-11-9
Journal Detail:
Title:  Journal of neuroscience methods     Volume:  -     ISSN:  1872-678X     ISO Abbreviation:  -     Publication Date:  2011 Nov 
Date Detail:
Created Date:  2011-11-21     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7905558     Medline TA:  J Neurosci Methods     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2011. Published by Elsevier B.V.
Affiliation:
Max Planck Institute for Biological Cybernetics, 38 Spemannstrasse, 72076 Tübingen, Germany; Bernstein Center for Computational Neuroscience Tübingen, Germany.
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