Identification of synaptic connections in neural ensembles by graphical models

• Verfasst von: Dahlhaus, Rainer [VerfasserIn]
• Verfasst von: Eichler, Michael [VerfasserIn]
• Verfasst von: Sandkühler, Jürgen [VerfasserIn]
• Titel: Identification of synaptic connections in neural ensembles by graphical models
• Verf.angabe: Rainer Dahlhaus, Michael Eichler, Jürgen Sandkühler
• Jahr: 1997
• Umfang: 15 S.
• Teil: volume:77
• Teil: year:1997
• Teil: number:1
• Teil: pages:93-107
• Teil: extent:15
• Fussnoten: Online 13 January 1998 ; Gesehen am 03.05.2021
• Titel Quelle: Enthalten in: Journal of neuroscience methods
• Ort Quelle: Amsterdam [u.a.] : Elsevier Science, 1979
• Jahr Quelle: 1997
• Band/Heft Quelle: 77(1997), 1, Seite 93-107
• ISSN Quelle: 1872-678X
• DOI: doi:10.1016/S0165-0270(97)00100-3
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Graphical models
• Sach-SW: Multivariate point processes
• Sach-SW: Neuronal net
• Sach-SW: Partial spectral coherence
• Sach-SW: Synaptic connectivity
• K10plus-PPN: 1756907528

Abstract

A method for the identification of direct synaptic connections in a larger neural net is presented. It is based on a conditional correlation graph for multivariate point processes. The connections are identified via the partial spectral coherence of two neurons, given all others. It is shown how these coherences can be calculated by inversion of the spectral density matrix. In simulations with GENESIS, we discuss the relevance of the method for identifying different neural ensembles including an excitatory feedback loop and networks with lateral inhibitions.