Cortisol levels during human aging predict hippocampal atrophy and memory deficits

Abstract

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About

This paper, published in 1950, received 1.3k indexed citations. Written by Sonia Lupien, Mony J. de Leon, Susan De Santi, Antonio Convit, Chaim Tarshish, N.P.V. Nair, Bruce S. McEwen, Richard L. Hauger and Michael J. Meaney covering the research area of Neurology, Behavioral Neuroscience and Endocrinology, Diabetes and Metabolism. It is primarily cited by scholars working on Behavioral Neuroscience (706 citations), Endocrinology, Diabetes and Metabolism (260 citations) and Biological Psychiatry (236 citations). Published in Nature Neuroscience.

In The Last Decade

doi.org/10.1038/271 →

Countries where authors are citing Cortisol levels during human aging predict hippocampal atrophy and memory deficits

Since Specialization
Citations

This map shows the geographic impact of Cortisol levels during human aging predict hippocampal atrophy and memory deficits. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Cortisol levels during human aging predict hippocampal atrophy and memory deficits with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cortisol levels during human aging predict hippocampal atrophy and memory deficits more than expected).

Fields of papers citing Cortisol levels during human aging predict hippocampal atrophy and memory deficits

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Cortisol levels during human aging predict hippocampal atrophy and memory deficits. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Cortisol levels during human aging predict hippocampal atrophy and memory deficits.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/10.1038/271.

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