Arthur W. Toga

17.5k total citations · 4 hit papers
144 papers, 9.5k citations indexed

About

Arthur W. Toga is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Arthur W. Toga has authored 144 papers receiving a total of 9.5k indexed citations (citations by other indexed papers that have themselves been cited), including 103 papers in Radiology, Nuclear Medicine and Imaging, 48 papers in Cognitive Neuroscience and 33 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Arthur W. Toga's work include Advanced Neuroimaging Techniques and Applications (95 papers), Functional Brain Connectivity Studies (47 papers) and Advanced MRI Techniques and Applications (36 papers). Arthur W. Toga is often cited by papers focused on Advanced Neuroimaging Techniques and Applications (95 papers), Functional Brain Connectivity Studies (47 papers) and Advanced MRI Techniques and Applications (36 papers). Arthur W. Toga collaborates with scholars based in United States, Australia and Canada. Arthur W. Toga's co-authors include John C. Mazziotta, Jack L. Lancaster, Peter T. Fox, Alan C. Evans, Roger P. Woods, Katherine L. Narr, Susumu Mori, Jiangyang Zhang, Hangyi Jiang and Michael I. Miller and has published in prestigious journals such as Journal of Neuroscience, SHILAP Revista de lepidopterología and Nature Neuroscience.

In The Last Decade

Arthur W. Toga

140 papers receiving 9.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template

2008 1.4k citations Susumu Mori, Kenichi Oishi et al. NeuroImage profile →
A Probabilistic Atlas of the Human Brain: Theory and Rationale for Its Development

1995 1.2k citations John C. Mazziotta, Arthur W. Toga et al. NeuroImage profile →
Construction of a 3D probabilistic atlas of human cortical structures

2007 850 citations Arthur W. Toga et al. NeuroImage profile →
Three-Dimensional MRI Atlas of the Human Cerebellum in Proportional Stereotaxic Space

1999 661 citations Arthur W. Toga, Alan C. Evans et al. NeuroImage profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Arthur W. Toga United States	43	4.9k	4.1k	1.4k	1.1k	902	144	9.5k
Philip A. Cook United States	37	5.7k 1.2×	5.1k 1.3×	1.5k 1.1×	1.2k 1.0×	1.1k 1.2×	93	12.4k
Babak A. Ardekani United States	49	4.3k 0.9×	3.6k 0.9×	1.8k 1.3×	910 0.8×	480 0.5×	104	8.3k
Yongyue Zhang China	12	6.4k 1.3×	6.0k 1.5×	1.8k 1.3×	978 0.9×	1.0k 1.1×	34	13.0k
James Saunders United States	11	5.7k 1.2×	5.7k 1.4×	1.5k 1.1×	919 0.8×	794 0.9×	26	11.2k
Ivana Drobnjak United Kingdom	23	7.2k 1.5×	6.4k 1.6×	1.6k 1.1×	1.1k 1.0×	860 1.0×	41	12.8k
Nicholas J. Tustison United States	33	5.4k 1.1×	3.5k 0.9×	1.1k 0.8×	946 0.8×	1.7k 1.9×	133	12.1k
Rami K. Niazy United Kingdom	8	6.0k 1.2×	6.5k 1.6×	1.5k 1.1×	926 0.8×	808 0.9×	10	11.7k
Evelina Busa United States	12	3.9k 0.8×	5.7k 1.4×	2.8k 2.0×	937 0.8×	942 1.0×	15	10.7k
Gerard R. Ridgway United Kingdom	44	4.0k 0.8×	4.2k 1.0×	2.4k 1.7×	739 0.6×	986 1.1×	107	10.0k
Christian Haselgrove United States	13	2.6k 0.5×	4.1k 1.0×	2.2k 1.5×	630 0.5×	702 0.8×	32	7.9k

Countries citing papers authored by Arthur W. Toga

Since Specialization

Citations

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

Fields of papers citing papers by Arthur W. Toga

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arthur W. Toga. 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 Arthur W. Toga. The network helps show where Arthur W. Toga may publish in the future.

Co-authorship network of co-authors of Arthur W. Toga

This figure shows the co-authorship network connecting the top 25 collaborators of Arthur W. Toga. A scholar is included among the top collaborators of Arthur W. Toga 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 Arthur W. Toga. Arthur W. Toga is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wisch, Julie K., Kalen J. Petersen, Peter R Millar, et al.. (2025). Cross‐Sectional Comparison of Structural MRI Markers of Impairment in a Diverse Cohort of Older Adults. Human Brain Mapping. 46(2). e70133–e70133. 2 indexed citations

Lynch, Kirsten M., et al.. (2025). Perivascular and parenchymal fluid characteristics are related to age and cognitive performance across the lifespan. Imaging Neuroscience. 3. 1 indexed citations

Wen, Junhao, Ioanna Skampardoni, Ye Tian, et al.. (2025). Neuroimaging endophenotypes reveal underlying mechanisms and genetic factors contributing to progression and development of four brain disorders. Nature Biomedical Engineering. 9(11). 1920–1937. 5 indexed citations

Aksman, Leon, Kirsten M. Lynch, Arthur W. Toga, Aparajit Ballav Dey, & Jinkook Lee. (2022). Investigating the factors that explain white matter hyperintensity load in older Indians. Brain Communications. 5(1). fcad008–fcad008.

Cardinal, Tyler, Dhiraj J. Pangal, Ben A. Strickland, et al.. (2021). Anatomical and topographical variations in the distribution of brain metastases based on primary cancer origin and molecular subtypes: a systematic review. Neuro-Oncology Advances. 4(1). vdab170–vdab170. 13 indexed citations

Lynch, Kirsten M., Ryan P. Cabeen, Arthur W. Toga, & Kristi A. Clark. (2020). Magnitude and timing of major white matter tract maturation from infancy through adolescence with NODDI. NeuroImage. 212. 116672–116672. 56 indexed citations

Sepehrband, Farshid, Ryan P. Cabeen, Jeiran Choupan, et al.. (2019). Perivascular space fluid contributes to diffusion tensor imaging changes in white matter. NeuroImage. 197. 243–254. 69 indexed citations

Aydogan, Dogu Baran, et al.. (2017). Topographic Regularity for Tract Filtering in Brain Connectivity. Lecture notes in computer science. 10265. 263–274. 7 indexed citations

Palacios, Eva, Alastair J. Martin, Michael A. Boss, et al.. (2016). Toward Precision and Reproducibility of Diffusion Tensor Imaging: A Multicenter Diffusion Phantom and Traveling Volunteer Study. American Journal of Neuroradiology. 38(3). 537–545. 75 indexed citations

10.

Toga, Arthur W., Ian Foster, Carl Kesselman, et al.. (2015). Big biomedical data as the key resource for discovery science. Journal of the American Medical Informatics Association. 22(6). 1126–1131. 59 indexed citations

11.

Daianu, Madelaine, Neda Jahanshad, Talia M. Nir, et al.. (2013). Breakdown of Brain Connectivity Between Normal Aging and Alzheimer's Disease: A Structural k -Core Network Analysis. Brain Connectivity. 3(4). 407–422. 131 indexed citations

12.

Zhan, Liang, Bryon A. Mueller, Neda Jahanshad, et al.. (2012). Magnetic Resonance Field Strength Effects on Diffusion Measures and Brain Connectivity Networks. Brain Connectivity. 3(1). 72–86. 29 indexed citations

13.

Braskie, Meredith N., Neda Jahanshad, Jason L. Stein, et al.. (2012). Relationship of a variant in the NTRK1 gene to white matter microstructure in young adults. Queensland's institutional digital repository (The University of Queensland). 2 indexed citations

14.

Oishi, Kenichi, Hao Huang, Takashi Yoshioka, et al.. (2011). Superficially Located White Matter Structures Commonly Seen in the Human and the Macaque Brain with Diffusion Tensor Imaging. Brain Connectivity. 1(1). 37–47. 41 indexed citations

15.

Zhan, Liang, Alex Leow, Neda Jahanshad, et al.. (2010). Genetic analysis of high angular resolution diffusion images (HARDI). Lecture notes in computer science. 61–71. 1 indexed citations

16.

Brun, Christine, Natasha Leporé, Xavier Pennec, et al.. (2008). A new registration method based on Log-Euclidean tensor metrics and its application to genetic studies. Queensland's institutional digital repository (The University of Queensland). 1 indexed citations

17.

Brun, Caroline, Natasha Leporé, Xavier Pennec, et al.. (2007). Comparison of Standard and Riemannian Fluid Registration for Tensor-Based Morphometry in HIV/AIDS. HAL (Le Centre pour la Communication Scientifique Directe). 10 indexed citations

18.

Leporé, Natasha, Caroline Brun, Greig I. de Zubicaray, et al.. (2006). Genetic influences on brain structure and fiber architecture mapped using diffusion tensor imaging and tensor-based morphometry in twins. Nature Neuroscience. 3(9). 873–80. 2 indexed citations

19.

Mazziotta, John C., et al.. (1995). A Probabilistic Atlas of the Human Brain: Theory and Rationale for Its Development. NeuroImage. 2(2). 89–101. 1191 indexed citations breakdown →

20.

Goldberg, Robert A., et al.. (1992). Microanatomy of the Orbital Apex. Ophthalmology. 99(9). 1447–1452. 17 indexed citations

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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