Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

 
 
DownloadE-Mail
  Cluster analysis of sharp-wave ripple field potential signatures in the macaque hippocampus

Ramirez-Villegas, J. F., Logothetis, N. K., & Besserve, M. (2014). Cluster analysis of sharp-wave ripple field potential signatures in the macaque hippocampus. Poster presented at Computational and Systems Neuroscience Meeting (COSYNE 2014), Salt Lake City, UT, USA.

Item is

Externe Referenzen

einblenden:
ausblenden:
externe Referenz:
http://cosyne.org/cosyne14/Cosyne2014_program_book.pdf (Verlagsversion)
Beschreibung:
-
OA-Status:

Urheber

einblenden:
ausblenden:
 Urheber:
Ramirez-Villegas, Juan Felipe1, 2, Autor           
Logothetis, Nikos K1, 2, Autor           
Besserve, Michel1, 2, Autor           
Affiliations:
1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

Inhalt

einblenden:
ausblenden:
Schlagwörter: -
 Zusammenfassung: Sharp-wave ripple complexes (SPW-Rs), transient episodes of neural activity combining a sharp wave of dendritic depolarization and a high-frequency oscillation, are a major feature of the cortico-hippocampal communication during immobility, consummatory behaviors and sleep. Experimental evidence relates these episodes to offline consolidation of memory traces. In order to allow for the wide range of network reconfigurations required by this process, different SPW-R events certainly reflect a large variety of selective interactions both within the hippocampus and with other brain regions. A better understanding of the underlying mechanisms of these interactions thus requires a finer characterization of the SPW-R events and their associated signatures over the entire brain. Using unsupervised-learning artificial neural networks and clustering techniques, we analyzed peri-event multi-channel local field potential (LFP) recordings of the hippocampus of anesthetized macaques, and extracted the electrophysiological characteristics of SPW-R events dynamics. We combined this analysis with neural event-triggered functional magnetic resonance imaging analysis in order to map the activity of the whole brain during SPW-R events. Our primary findings hint upon differentiated SPW-R complexes, whose signatures come in four classes: high frequency oscillations preceding, following or located in the peak of sharp wave dendritic depolarization, as well as high frequency oscillations without noticeable sharp-wave signature. These differentiated SPW-R LFP signatures were highly reproducible both across different animals and experimental sessions. At a larger scale, ripple-triggered fMRI activation map for most of the cerebral cortex and sub-cortical regions during ripples has been described by Logothetis et al., 2012. On top of this, our preliminary results suggest that the classes of SPWR field potential signatures reflect differentiated cortical activation and sub-cortical deactivation maps. In light of these findings, we hypothesize that these distinct patterns of SPW-R in hippocampal LFP mark differentiated brain-wide dynamical events, possibly reflecting several underlying mechanisms of memory function.

Details

einblenden:
ausblenden:
Sprache(n):
 Datum: 2014-03
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: -
 Art des Abschluß: -

Veranstaltung

einblenden:
ausblenden:
Titel: Computational and Systems Neuroscience Meeting (COSYNE 2014)
Veranstaltungsort: Salt Lake City, UT, USA
Start-/Enddatum: -

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: Computational and Systems Neuroscience Meeting (COSYNE 2014)
Genre der Quelle: Konferenzband
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: - Artikelnummer: III-73 Start- / Endseite: 199 - 199 Identifikator: -