### Abstract

Our goal is to estimate neuronal numbers from counts of nucleolar profiles. The primary difficulty is that a simple way to convert the counts to the numbers, especially when multiple nucleoli are present in a nucleus, is not available. In this paper, we propose a solution. The formula is N = n × [N(c.f.)/n(c.f.)] where N = the true number of neurons, n = the number of nucleolar profiles in these neurons, N(c.f.) = the number of neurons used to estimate the correction factor and n(c.f.) = the number of nucleolar profiles found in the neurons that make up N(c.f.). The constraints are (1) that the neurons identified for N(c.f.) be representative of the entire population, N; (2) that the nucleolar profiles be counted by the same criteria when n(c.f.) is determined as when n is determined, and (3) that when the correction factor [N(c.f.)/n(c.f.)] is calculated, the nucleolar profiles in each neuron be counted only once. The advantages are (1) simplicity, and (2) generality; the latter resulting from the empirical nature of the correction factor which can calibrate for multiple nucleoli, split nucleoli, invisible fragments, nucleolar size changes, section thickness differences and any other factors that cause n to deviate from N.

Original language | English (US) |
---|---|

Pages (from-to) | 125-132 |

Number of pages | 8 |

Journal | Journal of Neuroscience Methods |

Volume | 12 |

Issue number | 2 |

DOIs | |

State | Published - 1984 |

### Fingerprint

### Keywords

- neuronal counts
- nucleoli

### ASJC Scopus subject areas

- Neuroscience(all)

### Cite this

*Journal of Neuroscience Methods*,

*12*(2), 125-132. https://doi.org/10.1016/0165-0270(84)90011-6

**An empirical method for converting nucleolar counts to neuronal numbers.** / Coggeshall, Richard E.; Chung, Kyungsoon; Greenwood, Denise; Hulsebosch, Claire E.

Research output: Contribution to journal › Article

*Journal of Neuroscience Methods*, vol. 12, no. 2, pp. 125-132. https://doi.org/10.1016/0165-0270(84)90011-6

}

TY - JOUR

T1 - An empirical method for converting nucleolar counts to neuronal numbers

AU - Coggeshall, Richard E.

AU - Chung, Kyungsoon

AU - Greenwood, Denise

AU - Hulsebosch, Claire E.

PY - 1984

Y1 - 1984

N2 - Our goal is to estimate neuronal numbers from counts of nucleolar profiles. The primary difficulty is that a simple way to convert the counts to the numbers, especially when multiple nucleoli are present in a nucleus, is not available. In this paper, we propose a solution. The formula is N = n × [N(c.f.)/n(c.f.)] where N = the true number of neurons, n = the number of nucleolar profiles in these neurons, N(c.f.) = the number of neurons used to estimate the correction factor and n(c.f.) = the number of nucleolar profiles found in the neurons that make up N(c.f.). The constraints are (1) that the neurons identified for N(c.f.) be representative of the entire population, N; (2) that the nucleolar profiles be counted by the same criteria when n(c.f.) is determined as when n is determined, and (3) that when the correction factor [N(c.f.)/n(c.f.)] is calculated, the nucleolar profiles in each neuron be counted only once. The advantages are (1) simplicity, and (2) generality; the latter resulting from the empirical nature of the correction factor which can calibrate for multiple nucleoli, split nucleoli, invisible fragments, nucleolar size changes, section thickness differences and any other factors that cause n to deviate from N.

AB - Our goal is to estimate neuronal numbers from counts of nucleolar profiles. The primary difficulty is that a simple way to convert the counts to the numbers, especially when multiple nucleoli are present in a nucleus, is not available. In this paper, we propose a solution. The formula is N = n × [N(c.f.)/n(c.f.)] where N = the true number of neurons, n = the number of nucleolar profiles in these neurons, N(c.f.) = the number of neurons used to estimate the correction factor and n(c.f.) = the number of nucleolar profiles found in the neurons that make up N(c.f.). The constraints are (1) that the neurons identified for N(c.f.) be representative of the entire population, N; (2) that the nucleolar profiles be counted by the same criteria when n(c.f.) is determined as when n is determined, and (3) that when the correction factor [N(c.f.)/n(c.f.)] is calculated, the nucleolar profiles in each neuron be counted only once. The advantages are (1) simplicity, and (2) generality; the latter resulting from the empirical nature of the correction factor which can calibrate for multiple nucleoli, split nucleoli, invisible fragments, nucleolar size changes, section thickness differences and any other factors that cause n to deviate from N.

KW - neuronal counts

KW - nucleoli

UR - http://www.scopus.com/inward/record.url?scp=0021682618&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0021682618&partnerID=8YFLogxK

U2 - 10.1016/0165-0270(84)90011-6

DO - 10.1016/0165-0270(84)90011-6

M3 - Article

VL - 12

SP - 125

EP - 132

JO - Journal of Neuroscience Methods

JF - Journal of Neuroscience Methods

SN - 0165-0270

IS - 2

ER -