Dresden 2006 – scientific programme
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AKB: Biologische Physik
AKB 10: Neuroscience
AKB 10.4: Talk
Tuesday, March 28, 2006, 12:30–12:45, ZEU 255
Analytical approach to correlation- and feedback-induced oscillations in biological neural networks — •Benjamin Lindner1,2, Brent Doiron2, and Andre Longtin2 — 1MPI fuer Physik komplexer Systeme, Noethnitzer Str. 38, 01187 Dresden — 2Department of*Physics, University of Ottawa, 150 Louis Pasteur, Ottawa, Canada*K1N-6N5
A network of leaky integrate-and-fire neurons with global inhibitory feedback and under the influence of spatially correlated noise is studied. We calculate the spectral statistics of the network (power spectrum of the population activity, cross spectrum between spike trains of different neurons) as well as of a single neuron (power spectrum of spike train, cross spectrum between external noise and spike train) within the network. As shown by comparison with numerical simulations, our theory works well for arbitrary network size if the feedback is weak and the amount of external noise does not exceed that of the internal noise. By means of our analytical results we discuss the quality of the correlation-induced oscillation in a large network as a function of the transmission delay and the internal noise intensity. It is shown that the strongest oscillation is obtained in a system with zero internal noise and adiabatically long delay (i.e. the delay period is longer than any other time scale in the system).
REFS.: Doiron, Lindner, Longtin, Maler, Bastian Phys. Rev. Lett. 93, 048101 (2004), Lindner, Doiron, Longtin Phys. Rev. E (2005, in press)