Ann N. Topple

21 total papers · 1.1k total citations
19 papers, 962 citations indexed

About

Ann N. Topple is a scholar working on Cellular and Molecular Neuroscience, Neurology and Pharmacology. According to data from OpenAlex, Ann N. Topple has authored 19 papers receiving a total of 962 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cellular and Molecular Neuroscience, 6 papers in Neurology and 4 papers in Pharmacology. Recurrent topics in Ann N. Topple's work include Neuroscience and Neuropharmacology Research (10 papers), Neurotransmitter Receptor Influence on Behavior (6 papers) and Vestibular and auditory disorders (5 papers). Ann N. Topple is often cited by papers focused on Neuroscience and Neuropharmacology Research (10 papers), Neurotransmitter Receptor Influence on Behavior (6 papers) and Vestibular and auditory disorders (5 papers). Ann N. Topple collaborates with scholars based in Australia and United States. Ann N. Topple's co-authors include Charles Watson, George Paxinos, Glenn E. Hunt, Iain S. McGregor, Jonathon C. Arnold, Ian S. Curthoys, G. Michael Hálmagyi, T. Smock, E. Fifková and Paul E. Mallet and has published in prestigious journals such as Brain Research, Neuroscience and Experimental Brain Research.

In The Last Decade

Ann N. Topple

19 papers receiving 947 citations

Hit Papers

Bregma, lambda and the in... 1985 2026 1998 2012 1985 100 200 300 400

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Ann N. Topple 493 212 188 181 145 19 962
Jan N. Keijser 385 0.8× 87 0.4× 253 1.3× 161 0.9× 218 1.5× 24 950
Flavia Carreño 281 0.6× 160 0.8× 273 1.5× 227 1.3× 214 1.5× 29 1.1k
Radmila Manev 422 0.9× 175 0.8× 139 0.7× 161 0.9× 387 2.7× 36 1.2k
Kathryn P. MacPherson 565 1.1× 239 1.1× 394 2.1× 255 1.4× 162 1.1× 16 1.1k
János Fuzik 451 0.9× 191 0.9× 295 1.6× 144 0.8× 360 2.5× 19 1.0k
Elena Dale 363 0.7× 271 1.3× 150 0.8× 176 1.0× 293 2.0× 21 1.1k
J. Brent Kuzmiski 455 0.9× 178 0.8× 126 0.7× 183 1.0× 348 2.4× 18 1.1k
Martine M. Mirrione 684 1.4× 114 0.5× 273 1.5× 144 0.8× 269 1.9× 13 1.2k
Conor D. Cox 501 1.0× 156 0.7× 360 1.9× 136 0.8× 230 1.6× 24 1000
Mala Ananth 517 1.0× 156 0.7× 428 2.3× 125 0.7× 326 2.2× 24 1.1k

Countries citing papers authored by Ann N. Topple

Since Specialization
Citations

This map shows the geographic impact of Ann N. Topple's research. 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 Ann N. Topple with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ann N. Topple more than expected).

Fields of papers citing papers by Ann N. Topple

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ann N. Topple. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ann N. Topple. The network helps show where Ann N. Topple may publish in the future.

Co-authorship network of co-authors of Ann N. Topple

This figure shows the co-authorship network connecting the top 25 collaborators of Ann N. Topple. A scholar is included among the top collaborators of Ann N. Topple based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ann N. Topple. Ann N. Topple is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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.

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