Tunicamycin impairs olfactory learning and synaptic plasticity in the olfactory bulb

Neuroscience ◽  
2017 ◽  
Vol 344 ◽  
pp. 371-379 ◽  
Author(s):  
Jia Tong ◽  
Fumino Okutani ◽  
Yoshihiro Murata ◽  
Mutsuo Taniguchi ◽  
Toshiharu Namba ◽  
...  
Neuroscience ◽  
2010 ◽  
Vol 170 (1) ◽  
pp. 259-267 ◽  
Author(s):  
J.J. Zhang ◽  
F. Okutani ◽  
G.Z. Huang ◽  
M. Taniguchi ◽  
Y. Murata ◽  
...  

Neuroscience ◽  
2013 ◽  
Vol 232 ◽  
pp. 21-31 ◽  
Author(s):  
Y.-J. Wang ◽  
F. Okutani ◽  
Y. Murata ◽  
M. Taniguchi ◽  
T. Namba ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chang Zhao ◽  
Yves F. Widmer ◽  
Sören Diegelmann ◽  
Mihai A. Petrovici ◽  
Simon G. Sprecher ◽  
...  

AbstractOlfactory learning and conditioning in the fruit fly is typically modelled by correlation-based associative synaptic plasticity. It was shown that the conditioning of an odor-evoked response by a shock depends on the connections from Kenyon cells (KC) to mushroom body output neurons (MBONs). Although on the behavioral level conditioning is recognized to be predictive, it remains unclear how MBONs form predictions of aversive or appetitive values (valences) of odors on the circuit level. We present behavioral experiments that are not well explained by associative plasticity between conditioned and unconditioned stimuli, and we suggest two alternative models for how predictions can be formed. In error-driven predictive plasticity, dopaminergic neurons (DANs) represent the error between the predictive odor value and the shock strength. In target-driven predictive plasticity, the DANs represent the target for the predictive MBON activity. Predictive plasticity in KC-to-MBON synapses can also explain trace-conditioning, the valence-dependent sign switch in plasticity, and the observed novelty-familiarity representation. The model offers a framework to dissect MBON circuits and interpret DAN activity during olfactory learning.


2010 ◽  
Vol 1352 ◽  
pp. 108-117 ◽  
Author(s):  
Ambigapathy Ganesh ◽  
Wieslaw Bogdanowicz ◽  
Moritz Haupt ◽  
Ganapathy Marimuthu ◽  
Koilmani Emmanuvel Rajan

2010 ◽  
Vol 56 (6) ◽  
pp. 819-833 ◽  
Author(s):  
Hideto Kaba

Abstract This review examines the organizational principles underlying olfactory learning in three specialized contexts that occur during sensitive periods of enhanced neural plasticity and emphasizes some of their common features. All three forms of olfactory learning are associated with neural changes in the olfactory bulb (OB) at the first stage of sensory processing. These changes require the association of the olfactory and somatosensory signals in the OB. They all depend on somatosensory stimulation- induced release of noradrenaline that induces structural and functional changes at mitral-granule cell reciprocal synapses in the OB, resulting in increases in inhibitory transmission. In the accessory olfactory bulb, this represents the enhanced self-inhibition of mitral cells, which selectively disrupts the transmission of the mating male's pregnancy-blocking signal at this level. In contrast, an extensive network of secondary dendrites of mitral cells in the main olfactory bulb probably results in a sharpening of the odor-induced pattern of activity, due to increases in lateral inhibition, leading to offspring recognition in sheep and neonatal learning in rats and rabbits. These findings show that inhibitory interneurons play a critical role in olfactory learning. Further work on how these neurons shape olfactory circuit function could provide important clues to understand memory functions of interneurons in other systems. Moreover, recent research has suggested that three forms of olfactory learning are controlled by synergistic, redundant, and distributed neural mechanisms. This has general implications regarding the mechanisms that may contribute to the robustness of memories.


2011 ◽  
Vol 71 ◽  
pp. e356
Author(s):  
Keiko Moriya-Ito ◽  
Endoh Kentaroh ◽  
Yoko Tsukamoto ◽  
Masumi Ichikawa

1992 ◽  
Vol 70 (2) ◽  
pp. 279-282 ◽  
Author(s):  
R.M. Sullivan ◽  
D.R. Zyzak ◽  
P. Skierkowski ◽  
D.A. Wilson

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