Quantitative analysis of neurons and glial cells in the rat somatosensory cortex, with special reference to GABAergic neurons and parvalbumin-containing neurons
Abstract
The number of neuronal and glial cells in the rat somatosensory cortex (barrel area) has been estimated by a stereological method, the disector, using pairs of toluidine blue-stained, plastic-embedded 0.5-microns-thick sections, 1.5 microns distant from each other. Chemical properties of those disector-counted cells were further analyzed by postembedding immunocytochemical methods on adjacent semithin sections. Thus we were able to analyze quantitatively number, distribution, and proportion of five cell types: (1) gamma-aminobutyric acid-(GABA)-negative neurons; (2) GABA-like immunoreactive (GABA-LIR) neurons; (3) a specific calcium-binding protein parvalbumin-immunoreactive (PV-IR) neurons, a subpopulation of GABA-LIR neurons; (4) S-100 beta-LIR glial cells (astrocytes); and (5) S-100 beta-negative glial cells (oligodendrocytes and microglia). The densities of total cells, glial cells, and neurons in the rat somatosensory cortex were 85.4 +/- 10(3)/mm3, 30.5 x 10(3)/mm3, and 54.9 x 10(3)/mm3, respectively. Of all neurons 25% and 14% were GABA-LIR and PV-IR, respectively; all PV-IR neurons are GABA-LIR, and thus about 54% of GABA-LIR neurons are PV-positive. The number of total cells under a unit surface area of 1 mm2 through the thickness of the somatosensory cortex was 171.6 x 10(3); the number of neurons and glial cells were 110.2 x 10(3) and 61.4 x 10(3), respectively. There were 27.7 x 10(3) GABA-LIR neurons and 15.0 x 10(3) and 12.7 x 10(3) PV-IR neurons and PV-negative GABA-LIR neurons, respectively. The laminar distribution of each group of cells shows prominent differences, indicating that the cellular composition was different from layer to layer. The density of GABA-LIR neurons was highest in layer IV. The numerical density of PV-IR neurons was 2-4 times higher in layer IV than in layers II/III, V, and VI, whereas that of PV-negative GABA-LIR neurons was almost constant throughout the layers.
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Approximately 10% of all NeuN+ neurons in cortex are PV+.
“In agreement with the literature24–26, ~10% of all NeuN+ neurons in cortex were PV+ (Fig. 1b, c)”
From Perineuronal nets decrease membrane capacitance of peritumoral fast spiking interneurons in a model of epilepsy (2018) · cites this paper as [24]
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- Authors
- Ren, J. Q., Aika, Y., Heizmann, C. W., & Kosaka, T.
- Affiliations
- Kyushu University (JP)
- University of Zurich (CH)
- Venue
- Experimental Brain Research
- Published
- 1992-12
- Volume
- 92
- Issue
- 1
- Pages
- 1-14
- ISSN
- 0014-4819 (ISSN-L)
- 1432-1106
- OpenAlex
- W2086657106
- Cited by
- 148
- References
- 38
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 4 · 2022: 3 · 2021: 6 · 2020: 2 · 2019: 6 · 2018: 8 · 2017: 4 · 2016: 4 · 2015: 3 · 2014: 8 · 2013: 6 · 2012: 3
- FWCI
- 0.95
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Experimental Brain Research (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- somatosensory cortex, barrel cortex, GABAergic neurons, parvalbumin neurons, S100β, astrocytes, oligodendrocytes, microglia, neuronal density, glial density, laminar distribution, cell types, rat brain, stereology, immunocytochemistry
- MeSH terms
- Animals, gamma-Aminobutyric Acid, Immunohistochemistry, Male, Neuroglia, Neurons, Oxazines, Parvalbumins, Somatosensory Cortex, Tolonium Chloride, Plastic Embedding, Rats, Wistar, Benzoxazines, Rats
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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