Modeling of Structural Plasticity and Synchronization in the Rodent Olfactory Bulb

Meng, Hongyu

doi:https://doi.org/10.21985/n2-8vph-9b10

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Modeling of Structural Plasticity and Synchronization in the Rodent Olfactory Bulb

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To survive, animals, including human beings, have developed an amazing ability to learn the constantly changing environment. Specifically, detecting specific odorants in a noisy, variable background is crucial for finding food and water, mating, and avoiding potential dangers. For this purpose, rodents have developed an olfactory system that is powerful enough to detect even small relative changes in a specific odor in a complex mixture by learning. Recent experiments have shown that part of this learning occurs in the olfactory bulb, which is the first region to receive odor information in the brain. As a result of the learning, the neuronal activity patterns that represent odors in the output of the bulb are more decorrelated than the corresponding patterns in the input. In this dissertation, we try to understand the mechanism behind this discriminability from different aspects. The olfactory bulb is one of the few regions that show prominent structural plasticity even when the animal has fully matured. The reciprocal dendro-dendritic connection between mitral and granule cells, which are the major principal cells and interneurons within the bulb, show around 20% rewiring at a 2-day interval. In addition, this modification of the network depends on the activity of mitral and granule cells. Chapter 1 of this dissertation discusses how a Hebbian-type rule of structural plasticity can explain the learning behavior observed in the olfactory bulb. We further argue that basic memory function is observed in the olfactory bulb and learning of similar but not dissimilar odor pairs leads to the loss of previously learned odors due to interference. We also discuss the impacts of varying the major parameters of the model. The olfactory bulb is also a brain area that displays extensive rhythmic activity, particularly in the beta- (13 to 30 Hz) and gamma-band (30 to 100 Hz). It has also been observed in experiments that the power of gamma-oscillations increases more when a rodent tries to distinguish more similar odorants after learning. During the study of structural plasticity, we observed that as a result of the learning the network of the olfactory bulb model develops a subnetwork structure reflecting the learned odors. This observation makes us wonder under what condition the rhythms in subnetworks can be synchronized. In chapter 2, during the study of this question, we discover and explain an interesting counter-intuitive phenomenon, which is how independent noise can synchronize population rhythms arising in interconnected subnetworks. We show that by including noise, a negative feedback control loop stabilizes synchronization between different rhythms. Further, the results on synchronization by noise are likely to be relevant beyond the olfactory bulb, since gamma-rhythms are arise in many brain areas and can exhibit task-dependent coherence. Finally, we demonstrate the generality of this type of synchronization in different classes of oscillators and network connectivities. Altogether, this dissertation describes two topics that are both motivated by observations in the olfactory system.

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