Index of papers in March 2015 that mention

**normal distribution**

Functional connectivity as a network of pairwise interactions | Assuming that the population response follows a multivariate normal distribution , the conditional dependencies between pairs of neurons are expressed by the partial correlations between them. |

Model selection | We evaluated the covariance matriX estimators using a loss function derived from the normal distribution . |

Model selection | However, this does not limit the applicability of its conclusions to normal distributions . |

Simulation | Here, in the role of the loss function we adopted the Kullback-Leibler divergence between multivariate normal distributions with equal means, scaled by; to make its values comparable across different population sizes: |

Simulation | For simulation, ground truth covariance matrices were produced by taking 150 independent samples from an artificial population of 50 independent, identically normally distributed units. |

Simulation | Samples were then drawn from multivariate normal distributions models with the respective true covariance matrices to be estimated by each of the estimators. |

normal distribution is mentioned in 6 sentences in this paper.

Topics mentioned in this paper:

Analysis of the tomogram via graph theory | As discussed in Methods, we attributed tomographic density to each of the 25 long edges of the polyhedral cage representing the icosahedrally-averaged density considered in this analysis and fitted it to a normal distribution . |

Analysis of the tomogram via graph theory | A ranking of the level of density associated with these edges was achieved using the mean of the fitted normal distribution . |

The density profiles of the long edges | We computed fitted normal distributions using the normfit function from the scipy.stats python library, since for a sparse dataset the mean of a fitted normal distribution is less affected by outliers than the raw data. |

The density profiles of the long edges | The normal fitting function automatically calculated the best positioning of a unimodal normal distribution for the dataset. |

normal distribution is mentioned in 4 sentences in this paper.

Topics mentioned in this paper:

- X-ray (8)
- binding sites (7)
- normal distribution (4)

Derivation of the linear characteristic equations | Then, § (given 5) is normally distributed , and eq. |

Experimental statistics of neural activity and choice | We obtain them as the best (MSE) fit to the following formula: where (I) is the standard cumulative normal distribution . |

Sensitivity and CC signals as a function of K | (Actually, we postulate that E[PlK] is exactly diagonal when the random vectors x.- follow a normal distribution . |

normal distribution is mentioned in 3 sentences in this paper.

Topics mentioned in this paper:

- spike trains (12)
- experimental data (10)
- decision-making (8)