Information processing in the mammalian olfactory bulb

Citation

Bhalla, Upinder Singh (1993) Information processing in the mammalian olfactory bulb. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/3dq4-ad59. https://resolver.caltech.edu/CaltechTHESIS:12092009-100507031

Abstract

A combination of computer modeling and experimental approaches were taken to studying the mammalian olfactory bulb. First, detailed single cell models were developed for the main cell classes in the olfactory bulb. This involved development of simulation techniques and a parameter search method for assigning unknown parameters for neuronal models. This study demonstrated the feasibility of using indirect information, such as spike waveforms, to determine the detailed electrical properties of neurons. The models demonstrated that spikes propagate into the secondary dendrites, which may play a role in long-range spatial interactions in the bulb. Blockage of this spike propagation might be involved in bulbar information processing. Second, a series of recordings were made from neurons in the olfactory bulb of awake unrestrained rats exposed to a cyclical sequence of odorants. These recordings demonstrated a significant amount of variability in the response of individual neurons over time. The neuronal responses were well described as a combination of a consistent component with a component that varied over time. Comparisons made between response properties of the same neuron at different times, between adjacent neurons, between distant neurons and between unrelated neurons showed a clear sequence of increasing difference in the order: same < adjacent < unrelated < distant. However, during sniff periods, the sequence was: adjacent < same < unrelated < distant. This suggests the bulb normally responds evenly to a wide range of odorants, but during sniffing responses to familiar odorants are suppressed so as to preferentially detect novel odorants. The final stage of the study involved the development of detailed models of the bulb as a whole using both the single cell models, and the experimental results previously obtained. It was found that topographical organization of receptor input according to receptor type was not required to produce the range of responses seen in the experiments. The response variability of neurons in the model was much smaller than in experiment. We propose that the bulb can operate in multiple processing modes so as to optimize its responses for different situations and that this leads to variability in single neuron responses.

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