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J Neurosci Methods. 2018 Jul 1;304:126-135. doi: 10.1016/j.jneumeth.2018.04.018. Epub 2018 Apr 30.

Mapping of neuron soma size as an effective approach to delineate differences between neural populations.

Author information

1
Department of Psychology & Neuroscience, Dalhousie University, Halifax, NS, B3H 4R2, Canada.
2
Department of Ophthalmology, McGill University, Montreal, PQ, H4A 3S5, Canada.
3
Department of Psychology & Neuroscience, Dalhousie University, Halifax, NS, B3H 4R2, Canada. Electronic address: kevin.duffy@dal.ca.

Abstract

BACKGROUND:

A single histological marker applied to a slice of tissue often reveals myriad cytoarchitectonic characteristics that can obscure differences between neuron populations targeted for study. Isolation and measurement of a single feature from the tissue is possible through a variety of approaches, however, visualizing the data numerically or through graphs alone can preclude being able to identify important features and effects that are not obvious from direct observation of the tissue.

NEW METHOD:

We demonstrate an efficient, effective, and robust approach to quantify and visualize cytoarchitectural features in histologically prepared brain sections. We demonstrate that this approach is able to reveal small differences between populations of neurons that might otherwise have gone undiscovered.

RESULTS & COMPARISON WITH EXISTING METHOD(S):

We used stereological methods to record the cross-sectional soma area and in situ position of neurons within sections of the cat, monkey, and human visual system. The two-dimensional coordinate of every measured cell was used to produce a scatter plot that recapitulated the natural spatial distribution of cells, and each point in the plot was color-coded according to its respective soma area. The final graphic display was a multi-dimensional map of neuron soma size that revealed subtle differences across neuron aggregations, permitted delineation of regional boundaries, and identified small differences between populations of neurons modified by a period of sensory deprivation.

CONCLUSIONS:

This approach to collecting and displaying cytoarchitectonic data is simple, efficient, and provides a means of investigating small differences between neuron populations.

KEYWORDS:

Color maps; Cytoarchitecture; Laminar boundaries; Monocular deprivation; Neural plasticity; Regional boundaries; Soma size; Spatial distribution

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