Olfactory object recognition, segmentation, adaptation, target seeking, and discrimination by the network of the olfactory bulb and cortex: computational model and experimental data

@article{Zhaoping2016OlfactoryOR,
  title={Olfactory object recognition, segmentation, adaptation, target seeking, and discrimination by the network of the olfactory bulb and cortex: computational model and experimental data},
  author={Li Zhaoping},
  journal={Current Opinion in Behavioral Sciences},
  year={2016},
  volume={11},
  pages={30-39}
}
  • L. Zhaoping
  • Published 1 October 2016
  • Psychology, Biology
  • Current Opinion in Behavioral Sciences
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References

SHOWING 1-10 OF 59 REFERENCES
Modeling the Sensory Computations of the Olfactory Bulb
Two models are presented as examples to discuss the computational tasks, sensory environments, and computational mechanisms in early olfactory processing. One model proposes that the odor inputs…
Olfactory cortical adaptation facilitates detection of odors against background.
TLDR
The results suggest that the aPCX acts as a filter driven most strongly by changing stimuli, providing a potential mechanism for olfactory figure-ground separation and selective reading of Olfactory bulb output.
A model of olfactory adaptation and sensitivity enhancement in the olfactory bulb
  • Z. Li
  • Psychology, Biology
    Biological Cybernetics
  • 2004
TLDR
A mathematical model based on the bulbar anatomy and physiology shows that the inputs from the higher olfactory centers to the inhibitory cells in the bulb are shown to be able to modulate the response, and thus the sensitivity of the bulb to specific odor inputs.
Odour recognition and segmentation by a model olfactory bulb and cortex
TLDR
A model of an olfactory system that performs odour segmentation is presented that consists of a pair of coupled modules, bulb and cortex, which implements o aroma segmentation by suppressing the bulbar response to the pre-existing odour, thereby allowing subsequent odours to be singled out for recognition.
Synaptic adaptation and odor-background segmentation
Odor space and olfactory processing: collective algorithms and neural implementation.
  • J. Hopfield
  • Biology, Psychology
    Proceedings of the National Academy of Sciences of the United States of America
  • 1999
TLDR
A model of the patterns of olfactory receptor responses, based on the broad distribution of Olfactory thresholds, is constructed, which allows a common description of the most important basic problems and shows how to solve them when N is large.
Olfactory computation and object perception.
  • J. Hopfield
  • Biology
    Proceedings of the National Academy of Sciences of the United States of America
  • 1991
TLDR
An adaptive network can solve the essential problem, isolating the quality and intensity of the components within a mixture of several individual unknown odor sources.
Configurational and Elemental Odor Mixture Perception Can Arise from Local Inhibition
TLDR
A computational model shows that inhibitory processes in the olfactory bulb suffice to generate the behaviorally observed inverse relationship between two odorants' perceptual similarities and the perceptual similarities between either of these same odorants and their binary mixture.
An olfactory cocktail party: figure-ground segregation of odorants in rodents
TLDR
The study found that mice could be easily trained to detect target odorants embedded in unpredictable and variable mixtures, and indicated that the olfactory system has powerful analytic abilities that are constrained by the limits of combinatorial neural representation of odorants at the level of the Olfactory receptors.
Profound Context-Dependent Plasticity of Mitral Cell Responses in Olfactory Bulb
TLDR
It is shown that odor responses of the output cells of the OB, mitral cells, change transiently during a go–no-go odor discrimination task, redefining the function of theOB as a transiently modifiable (active) filter, shaping early odor representations in behaviorally meaningful ways.
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