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Description
  • The talk covers basic description of stochastic modelling in olfactory neuronal models. Few simple theoretical models are described via random processes. Measures for quantifying how well the input odorant concentration can be determined form the knowledge of the response, concentration of activated receptors in the cell membrane, are introduced. Given methods and computations are illustrated on a biophysical model and empirical data.
  • The talk covers basic description of stochastic modelling in olfactory neuronal models. Few simple theoretical models are described via random processes. Measures for quantifying how well the input odorant concentration can be determined form the knowledge of the response, concentration of activated receptors in the cell membrane, are introduced. Given methods and computations are illustrated on a biophysical model and empirical data. (en)
Title
  • Optimal Odor Intenisty in Simple Olfactory Neuronal Models
  • Optimal Odor Intenisty in Simple Olfactory Neuronal Models (en)
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  • Optimal Odor Intenisty in Simple Olfactory Neuronal Models
  • Optimal Odor Intenisty in Simple Olfactory Neuronal Models (en)
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  • RIV/00216224:14310/09:00039596!RIV10-MSM-14310___
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  • P(LC06024)
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  • 331876
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  • RIV/00216224:14310/09:00039596
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  • sensory neuron; signal optimality; stochastic model; Fisher information (en)
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  • [A7301EB66119]
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  • Lánský, Petr
  • Pokora, Ondřej
http://localhost/t...ganizacniJednotka
  • 14310
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