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Updated: Jul 23, 2026

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Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Published on: August 25, 2014
Neonatal brain parameters: outstanding tails of normal distribution
1Department of Microbiology and Immunology, UCLA School of Medicine 90024-1747.
Summary
This study examined neonatal rat brain parameters, finding rare extreme values. Litter size and maternal weight influenced these extremes, suggesting different factors for maximal and minimal brain development.
Area of Science:
- Neuroscience
- Developmental Biology
- Quantitative Biology
Background:
- Previous research analyzed neonatal rat brain parameter distributions (weight, DNA, cell number, protein) in 720 individuals.
- These parameters typically followed normal distribution curves, with values exceeding two standard deviations (SD) from the mean (X) considered statistically significant.
Purpose of the Study:
- To investigate rare extreme values (beyond 3 SD) in neonatal rat brain parameters using a larger sample size.
- To identify potential factors influencing maximal and minimal neonatal brain development.
Main Methods:
- Examined a larger sample of 1,948 neonatal rats.
- Focused analysis on individuals with brain parameters exceeding three standard deviations above or below the mean.
- Investigated correlations between litter size, maternal weight, and extreme brain parameter values.
Main Results:
- Extreme deviations in brain parameters were rare and showed some skewness compared to normal distribution expectations.
- For DNA, maximal brain values reached +3.62 SD and minimal values reached -4.33 SD.
- Lower litter size was associated with increased maximal brain parameters, while lower maternal weight at conception was linked to decreased minimal brain parameters.
Conclusions:
- Factors influencing maximal neonatal brain parameters differ from those affecting minimal parameters.
- The identified factors (litter size, maternal weight) provide insights into the variability of neonatal brain development.
- Understanding these extremes is crucial for potential correlations with behavioral performance.
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