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research
Amplification of asynchronous inhibition-mediated synchronization by feedback in recurrent networks
Authors
AD Reyes
AK Engel
+34 more
B Bathellier
Bard Ermentrout
Boris S. Gutkin
C Borgers
DT Gillespie
E Salinas
ED Adrian
ED Adrian
H Kashiwadani
JN Teramae
JW Hinds
LM Kay
M Stopfer
NE Schoppa
NE Schoppa
NE Schoppa
NN Urban
PHE Tiesinga
RF Galan
RF Galan
S Hefft
S Lagier
S Marella
Sashi Marella
SL Bressler
TW Margrie
V Egger
V Kapoor
W Singer
W Singer
WJ Freeman
XJ Wang
Y Kuramoto
Z Nusser
Publication date
1 January 2010
Publisher
'Public Library of Science (PLoS)'
Doi
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PubMed
Abstract
Synchronization of 30-80 Hz oscillatory activity of the principle neurons in the olfactory bulb (mitral cells) is believed to be important for odor discrimination. Previous theoretical studies of these fast rhythms in other brain areas have proposed that principle neuron synchrony can be mediated by short-latency, rapidly decaying inhibition. This phasic inhibition provides a narrow time window for the principle neurons to fire, thus promoting synchrony. However, in the olfactory bulb, the inhibitory granule cells produce long lasting, small amplitude, asynchronous and aperiodic inhibitory input and thus the narrow time window that is required to synchronize spiking does not exist. Instead, it has been suggested that correlated output of the granule cells could serve to synchronize uncoupled mitral cells through a mechanism called "stochastic synchronization", wherein the synchronization arises through correlation of inputs to two neural oscillators. Almost all work on synchrony due to correlations presumes that the correlation is imposed and fixed. Building on theory and experiments that we and others have developed, we show that increased synchrony in the mitral cells could produce an increase in granule cell activity for those granule cells that share a synchronous group of mitral cells. Common granule cell input increases the input correlation to the mitral cells and hence their synchrony by providing a positive feedback loop in correlation. Thus we demonstrate the emergence and temporal evolution of input correlation in recurrent networks with feedback. We explore several theoretical models of this idea, ranging from spiking models to an analytically tractable model. © 2010 Marella, Ermentrout
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