Subcortical and cortical brain activity during the feeling of self-generated emotions
- Journal
- Nature Neuroscience
In The Last Decade
doi.org/10.1038/79871 →Countries where authors are citing Subcortical and cortical brain activity during the feeling of self-generated emotions
This map shows the geographic impact of Subcortical and cortical brain activity during the feeling of self-generated emotions. 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 Subcortical and cortical brain activity during the feeling of self-generated emotions with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Subcortical and cortical brain activity during the feeling of self-generated emotions more than expected).
Fields of papers citing Subcortical and cortical brain activity during the feeling of self-generated emotions
This network shows the impact of Subcortical and cortical brain activity during the feeling of self-generated emotions. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Subcortical and cortical brain activity during the feeling of self-generated emotions.
About Subcortical and cortical brain activity during the feeling of self-generated emotions
This paper, published in 2000, received 1.5k indexed citations . Written by António R. Damásio, Thomas J. Grabowski, Antoine Bechara, Laura L. Boles Ponto, Josef Parvizi and Richard D. Hichwa covering the research area of Cognitive Neuroscience. It is primarily cited by scholars working on Cognitive Neuroscience (960 citations), Experimental and Cognitive Psychology (462 citations) and Social Psychology (398 citations). Published in Nature Neuroscience.
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/10.1038/79871.