Stereological estimation of the number of neurons in the human amygdaloid complex
- 20 September 2005
- journal article
- research article
- Published by Wiley in Journal of Comparative Neurology
- Vol. 491 (4) , 320-329
- https://doi.org/10.1002/cne.20704
Abstract
Pathological changes in neuronal density in the amygdaloid complex have been associated with various neurological disorders. However, due to variable shrinkage during tissue processing, the only way to determine changes in neuron number unambiguously is to estimate absolute counts, rather than neuronal density. As the first stage in evaluating potential neuropathology of the amygdala in autism, the total number of neurons was estimated in the control human amygdaloid complex by using stereological sampling. The intact amygdaloid complex from one hemisphere of 10 brains was frozen and sectioned. One 100‐μm section was selected every 500 μm and stained by the standard Nissl method. The entire amygdaloid complex was outlined and then further partitioned into five reliably defined subdivisions: 1) the lateral nucleus, 2) the basal nucleus, 3) the accessory basal nucleus, 4) the central nucleus, and 5) the remaining nuclei (including anterior cortical, anterior amygdaloid area, periamygdaloid cortex, medial, posterior cortical, nucleus of the lateral olfactory tract, amygdalohippocampal area, and intercalated nuclei). The number of neurons was measured by using an optical fractionator with Stereoinvestigator software. The mean number of neurons (× 106) for each region was as follows: lateral nucleus 4.00, basal nucleus 3.24, accessory basal nucleus 1.28, central nucleus 0.36, remaining nuclei 3.33, and total amygdaloid complex 12.21. The stereological assessment of neuron number in the human amygdala provides an essential baseline for comparison of patient populations, such as autism, in which the amygdala may develop abnormally. To facilitate these types of analyses, this paper provides a detailed anatomical description of the methods used to define subdivisions of the human amygdaloid complex. J. Comp. Neurol. 491:320–329, 2005.Keywords
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