Charles DeCarli

23.7k total citations · 3 hit papers
106 papers, 8.9k citations indexed

About

Charles DeCarli is a scholar working on Psychiatry and Mental health, Physiology and Cognitive Neuroscience. According to data from OpenAlex, Charles DeCarli has authored 106 papers receiving a total of 8.9k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Psychiatry and Mental health, 31 papers in Physiology and 22 papers in Cognitive Neuroscience. Recurrent topics in Charles DeCarli's work include Dementia and Cognitive Impairment Research (54 papers), Alzheimer's disease research and treatments (26 papers) and Functional Brain Connectivity Studies (17 papers). Charles DeCarli is often cited by papers focused on Dementia and Cognitive Impairment Research (54 papers), Alzheimer's disease research and treatments (26 papers) and Functional Brain Connectivity Studies (17 papers). Charles DeCarli collaborates with scholars based in United States, Japan and United Kingdom. Charles DeCarli's co-authors include Philip A. Wolf, Bruce Reed, Dorit Carmelli, William J. Jagust, Dan Mungas, Bruce L. Miller, Gary E. Swan, Barry Horwitz, Alexa Beiser and Rhoda Au and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Brain and Neurology.

In The Last Decade

Charles DeCarli

104 papers receiving 8.8k citations

Hit Papers

Midlife vascular risk factor exposure accelerates structu... 2004 2026 2011 2018 2011 2004 2008 100 200 300 400 500

Peers

Charles DeCarli
Victor W. Henderson United States
Niels D. Prins Netherlands
Duk L. Na South Korea
C. Munro Cullum United States
Michael A. Kraut United States
Owen Carmichael United States
Charles DeCarli
Citations per year, relative to Charles DeCarli Charles DeCarli (= 1×) peers Mirjam I. Geerlings

Countries citing papers authored by Charles DeCarli

Since Specialization
Citations

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

Fields of papers citing papers by Charles DeCarli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Charles DeCarli. 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 Charles DeCarli. The network helps show where Charles DeCarli may publish in the future.

Co-authorship network of co-authors of Charles DeCarli

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

All Works

20 of 20 papers shown
1.
Landau, Susan, Theresa M. Harrison, Suzanne L. Baker, et al.. (2024). Positron emission tomography harmonization in the Alzheimer's Disease Neuroimaging Initiative: A scalable and rigorous approach to multisite amyloid and tau quantification. Alzheimer s & Dementia. 21(1). e14378–e14378. 12 indexed citations
2.
González, Héctor M., Wassim Tarraf, Kevin A. González, et al.. (2024). Association of Epigenetic Aging with Plasma Biomarkers of Amyloid, Tau, Neurodegeneration and Neuroinflammation in Diverse Hispanic/Latino Adults. Alzheimer s & Dementia. 20(S2). 1 indexed citations
3.
Harrison, Theresa M., Susan Landau, Suzanne L. Baker, et al.. (2023). Harmonization of amyloid and tau PET tracers in a multi‐center cohort from NIA Alzheimer’s disease research centers in the United States. Alzheimer s & Dementia. 19(S16). 1 indexed citations
4.
Soldan, Anja, Corinne Pettigrew, Yuxin Zhu, et al.. (2019). White matter hyperintensities and CSF Alzheimer disease biomarkers in preclinical Alzheimer disease. Neurology. 94(9). e950–e960. 60 indexed citations
5.
Lockhart, Samuel N. & Charles DeCarli. (2014). Structural Imaging Measures of Brain Aging. Neuropsychology Review. 24(3). 271–289. 189 indexed citations
6.
Bai, Zhouxian, Boryana Stamova, Huichun Xu, et al.. (2014). Distinctive RNA Expression Profiles in Blood Associated With Alzheimer Disease After Accounting for White Matter Hyperintensities. Alzheimer Disease & Associated Disorders. 28(3). 226–233. 40 indexed citations
7.
Marchant, Natalie L., Bruce Reed, Nerses Sanossian, et al.. (2013). The Aging Brain and Cognition. JAMA Neurology. 70(4). 488–488. 103 indexed citations
8.
Toledo, Jon B., Hugo Vanderstichele, Michal Figurski, et al.. (2011). Factors affecting Aβ plasma levels and their utility as biomarkers in ADNI. Acta Neuropathologica. 122(4). 401–13. 145 indexed citations
9.
Farias, Sarah Tomaszewski, Dan Mungas, Bruce Reed, et al.. (2011). Maximal brain size remains an important predictor of cognition in old age, independent of current brain pathology. Neurobiology of Aging. 33(8). 1758–1768. 39 indexed citations
10.
Xie, Jing, Dan A. Alcantara, Nina Amenta, et al.. (2009). Spatially localized hippocampal shape analysis in late‐life cognitive decline. Hippocampus. 19(6). 526–532. 13 indexed citations
11.
Chui, Helena C., Chris Zarow, Wendy J. Mack, et al.. (2006). Cognitive impact of subcortical vascular and Alzheimer's disease pathology. Annals of Neurology. 60(6). 677–687. 192 indexed citations
12.
DeCarli, Charles. (2004). Vascular factors in dementia: an overview. Journal of the Neurological Sciences. 226(1-2). 19–23. 64 indexed citations
13.
DeCarli, Charles. (2003). Magnetic Resonance in Dementia. Alzheimer Disease & Associated Disorders. 17(4). 243–243. 1 indexed citations
14.
Seshadri, Sudha, Philip A. Wolf, Alexa Beiser, et al.. (2001). Stroke Risk Profile Predicts Brain Volume and Cognitive Function in Stroke-free Subjects: The Framingham Study. Stroke. 32. 321–321. 3 indexed citations
15.
DeCarli, Charles, Bruce L. Miller, Gary E. Swan, et al.. (2001). Cerebrovascular and Brain Morphologic Correlates of Mild Cognitive Impairment in the National Heart, Lung, and Blood Institute Twin Study. Archives of Neurology. 58(4). 643–7. 217 indexed citations
16.
Ostuni, John, R.L. Levin, Joseph A. Frank, & Charles DeCarli. (1997). Correspondence of closest gradient Voxels—A robust registration algorithm. Journal of Magnetic Resonance Imaging. 7(2). 410–415. 42 indexed citations
17.
DeCarli, Charles, Anthony R. McIntosh, & Teresa A. Blaxton. (1995). USE OF POSITRON EMISSION TOMOGRAPHY FOR THE EVALUATION OF EPILEPSY. Neuroimaging Clinics of North America. 5(4). 623–645. 14 indexed citations
18.
Brouwers, Pim, Charles DeCarli, Lucy Civitello, et al.. (1995). Correlation Between Computed Tomographic Brain Scan Abnormalities and Neuropsychological Function in Children With Symptomatic Human Immunodeficiency Virus Disease. Archives of Neurology. 52(1). 39–44. 40 indexed citations
19.
Murphy, Declan, Charles DeCarli, Mark B. Schapiro, S I Rapoport, & Barry Horwitz. (1992). Age-Related Differences in Volumes of Subcortical Nuclei, Brain Matter, and Cerebrospinal Fluid in Healthy Men as Measured With Magnetic Resonance Imaging. Archives of Neurology. 49(8). 839–845. 189 indexed citations
20.
DeCarli, Charles, et al.. (1992). Method for Quantification of Brain, Ventricular, and Subarachnoid CSF Volumes from MR Images. Journal of Computer Assisted Tomography. 16(2). 274–284. 223 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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