Summary of 66-Iwata-CellDynOSNMT


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DOI
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Title
A set of calcium imaging data in the olfactory system of M. musculus adult
Description

Calcium imaging data in the olfactory system of M. musculus adult

Submited Date
2017-10-12
Release Date
2017-11-14
Updated Date
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License
Data size
30.9 GB
Data formats

Organism
M. musculus
Strain
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Cell Line
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Molecular Function (MF)
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Biological Process (BP)
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Cellular Component (CC)
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Study Type
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Imaging Methods
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Method Summary

See details in Ryo Iwata, Hiroshi Kiyonari, Takeshi Imai (2017) Neuron, 96(5): 1139-1152.

Related paper(s)

Ryo Iwata, Hiroshi Kiyonari, Takeshi Imai (2017) Mechanosensory-Based Phase Coding of Odor Identity in the Olfactory Bulb., Neuron, Volume 96, Number 5, pp. 1139-1152.e7

Published in 2017 Dec 6

(Abstract) Mitral and tufted (M/T) cells in the olfactory bulb produce rich temporal patterns of activity in response to different odors. However, it remains unknown how these temporal patterns are generated and how they are utilized in olfaction. Here we show that temporal patterning effectively discriminates between the two sensory modalities detected by olfactory sensory neurons (OSNs): odor and airflow-driven mechanical signals. Sniff-induced mechanosensation generates glomerulus-specific oscillatory activity in M/T cells, whose phase was invariant across airflow speed. In contrast, odor stimulation caused phase shifts (phase coding). We also found that odor-evoked phase shifts are concentration invariant and stable across multiple sniff cycles, contrary to the labile nature of rate coding. The loss of oscillatory mechanosensation impaired the precision and stability of phase coding, demonstrating its role in olfaction. We propose that phase, not rate, coding is a robust encoding strategy of odor identity and is ensured by airflow-induced mechanosensation in OSNs.
(MeSH Terms)

Contact(s)
Takeshi Imai
Organization(s)
Kyushu University, Graduate School of Medical Sciences , Department of Developmental Neurophysiology
Image Data Contributors
Ryo Iwata, Hiroshi Kiyonari, Takeshi Imai
Quantitative Data Contributors

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