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Cited by 210

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Gender differences in human cortical synaptic density

Open access
Alonso-Nanclares, L., Gonzalez-Soriano, J., Rodriguez, J. R., DeFelipe, J.·2008·Proceedings of the National Academy of Sciences

Abstract

Certain cognitive functions differ in men and women, although the anatomical and functional substrates underlying these differences remain unknown. Because neocortical activity is directly related with higher brain function, numerous studies have focused on the cerebral cortex when searching for possible structural correlates of cognitive gender differences. However, there are no studies on possible gender differences at the synaptic level. In the present work we have used stereological and correlative light and electron microscopy to show that men have a significantly higher synaptic density than women in all cortical layers of the temporal neocortex. These differences may represent a microanatomical substrate contributing to the functional gender differences in brain activity.

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Crossref · 10.1073/pnas.0803652105

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Metadata

Authors
Alonso-Nanclares, L., Gonzalez-Soriano, J., Rodriguez, J. R., & DeFelipe, J.
Venue
Proceedings of the National Academy of Sciences
Published
2008-09-23
Volume
105
Issue
38
Pages
14615-14619
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2086629023
Cited by
210
References
7
FWCI
6.82
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Gender differences in human cortical synaptic density. https://app.cochat.ai/papers/10.1073/pnas.0803652105
The paper
Alonso-Nanclares, L., Gonzalez-Soriano, J., Rodriguez, J. R., & DeFelipe, J. (2008). Gender differences in human cortical synaptic density. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0803652105

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.