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Counting sectioned cells via mathematical reconstruction.

R D Rose1, D Rohrlich

  • 1Department of Neurobiology and Behavior, State University of New York, Stony Brook 11794.

The Journal of Comparative Neurology
|September 15, 1987
PubMed
Summary
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This study introduces recursive translation, a novel method for accurately counting neurons in tissue sections. The technique estimates cell numbers from profile size distributions, proving robust and precise across various samples.

Area of Science:

  • Neuroscience
  • Stereology
  • Quantitative Biology

Background:

  • Accurate neuronal counting is crucial for understanding brain structure and function.
  • Existing methods for cell enumeration in sectioned tissue can be labor-intensive and prone to error.
  • A need exists for robust and efficient methods to estimate cell populations from tissue samples.

Purpose of the Study:

  • To present a new mathematical method, termed recursive translation, for determining the number of neurons in sectioned tissue.
  • To develop a computational approach for reconstructing cell populations from profile size histograms.
  • To validate the accuracy and robustness of the recursive translation method.

Main Methods:

  • Estimating mean diameters of neuronal somata sections (profiles) without identifying subcellular structures.

Related Experiment Videos

  • Developing a mathematical model to reconstruct the total cell population from a size histogram of these profiles.
  • Utilizing a computer program to perform the numerous calculations required by the model.

    • Main Results:

    • The recursive translation method achieved estimates within 10% of the actual number of cells in tested samples.
    • The method demonstrated robustness against variations in section thickness, sample size, somal morphology, and observer error.
    • Performance was validated using simulated data, real cell samples, and even sliced potatoes.

    Conclusions:

    • Recursive translation offers a reliable and accurate approach for estimating neuronal populations in sectioned tissues.
    • The method's insensitivity to various factors enhances its practical applicability in neuroscience research.
    • This technique provides a valuable alternative to existing cell counting correction schemes.