Salience, relevance, and firing: a priority map for target selection
- Authors
- Jillian H. FecteauDavid G. Muñoz
- Journal
- Trends in Cognitive Sciences
In The Last Decade
doi.org/10.1016/j.tics.2006.06.011 →Countries where authors are citing Salience, relevance, and firing: a priority map for target selection
This map shows the geographic impact of Salience, relevance, and firing: a priority map for target selection. 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 Salience, relevance, and firing: a priority map for target selection with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Salience, relevance, and firing: a priority map for target selection more than expected).
Fields of papers citing Salience, relevance, and firing: a priority map for target selection
This network shows the impact of Salience, relevance, and firing: a priority map for target selection. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Salience, relevance, and firing: a priority map for target selection.
About Salience, relevance, and firing: a priority map for target selection
This paper, published in 2006, received 667 indexed citations . Written by Jillian H. Fecteau and David G. Muñoz covering the research area of Cognitive Neuroscience and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Cognitive Neuroscience (602 citations), Computer Vision and Pattern Recognition (163 citations) and Sensory Systems (101 citations). Published in Trends in Cognitive Sciences.
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/10.1016/j.tics.2006.06.011.