- Poster presentation
- Open Access
Learning experience facilitates sparse coding of new odors in a large-scale olfactory bulb model
© Zhou et al. 2015
- Published: 18 December 2015
- Olfactory Bulb
- Sparse Code
- Network Response
- Mitral Cell
- Odor Signal
Furthermore, for the most of total 16 prior odor training tests, the mean correlation coefficients between MT cells within the network measured at the end of after-learning process (i.e. No.14-15s) are less than the native situation (Figure 1e), suggesting a more decorrelated state. Correspondingly, the similarity of the MT network responses for most of the tests is lower significantly than the naïve case (Figure 1f). This strongly suggests prior odor experience could significantly promote odor discrimination ability of the olfactory bulb network. In sum, odor experience could accelerate the formation of network response sparseness, decorrelation, and promote signal discrimination.
This project is funded by NNSF of China (31271170) and Shanghai Eastern Scholar program SHH1140004).
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