Emergent properties of interacting populations of spiking neurons

Abstract: Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch
Anmerkungen
Frontiers in Computational Neuroscience. 5 (2011), 59, DOI 10.3389/fncom.2011.00059, issn: 1662-5188
IN COPYRIGHT http://rightsstatements.org/page/InC/1.0 rs

Schlagwort
Volterra-Gleichungen
Punktprozess
Stochastische Resonanz
Gehirn
Zentralnervensystem

Ereignis
Veröffentlichung
(wo)
Freiburg
(wer)
Universität
(wann)
2011
Urheber
Beteiligte Personen und Organisationen
Fakultät für Biologie
Bernstein Center Freiburg
Albert-Ludwigs-Universität Freiburg

DOI
10.3389/fncom.2011.00059
URN
urn:nbn:de:bsz:25-freidok-118441
Rechteinformation
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Letzte Aktualisierung
25.03.2025, 13:56 MEZ

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  • 2011

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