Statistical Parametric Mapping: The Analysis of Functional Brain Images
- Journal
- UCL Discovery (University College London)
In The Last Decade
doi.org/w11239211 →Countries where authors are citing Statistical Parametric Mapping: The Analysis of Functional Brain Images
This map shows the geographic impact of Statistical Parametric Mapping: The Analysis of Functional Brain Images. 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 Statistical Parametric Mapping: The Analysis of Functional Brain Images with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Statistical Parametric Mapping: The Analysis of Functional Brain Images more than expected).
Fields of papers citing Statistical Parametric Mapping: The Analysis of Functional Brain Images
This network shows the impact of Statistical Parametric Mapping: The Analysis of Functional Brain Images. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Statistical Parametric Mapping: The Analysis of Functional Brain Images.
About Statistical Parametric Mapping: The Analysis of Functional Brain Images
This paper, published in 2007, received 2.5k indexed citations . Written by W.D. Penny, Karl Friston, John Ashburner, Stefan J. Kiebel and Nichols Thomas covering the research area of Cognitive Neuroscience. It is primarily cited by scholars working on Cognitive Neuroscience (1.5k citations), Radiology, Nuclear Medicine and Imaging (810 citations) and Psychiatry and Mental health (242 citations). Published in UCL Discovery (University College London).
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/w11239211.