Nicolas Honnorat

1.0k total citations
30 papers, 548 citations indexed

About

Nicolas Honnorat is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Nicolas Honnorat has authored 30 papers receiving a total of 548 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Cognitive Neuroscience, 17 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Nicolas Honnorat's work include Functional Brain Connectivity Studies (21 papers), Advanced Neuroimaging Techniques and Applications (12 papers) and Advanced MRI Techniques and Applications (9 papers). Nicolas Honnorat is often cited by papers focused on Functional Brain Connectivity Studies (21 papers), Advanced Neuroimaging Techniques and Applications (12 papers) and Advanced MRI Techniques and Applications (9 papers). Nicolas Honnorat collaborates with scholars based in United States, France and Germany. Nicolas Honnorat's co-authors include Christos Davatzikos, Theodore D. Satterthwaite, Jimit Doshi, Kilian M. Pohl, Qingyu Zhao, Harini Eavani, Ehsan Adeli, Erdem Varol, David A. Wolk and Aristeidis Sotiras and has published in prestigious journals such as NeuroImage, Brain and Scientific Reports.

In The Last Decade

Nicolas Honnorat

28 papers receiving 538 citations

Peers

Nicolas Honnorat

PMH

RNMI

PHYSI

Weikai Li China

Pradeep Reddy Raamana Canada

Marisa Koini Austria

Dimosthenis Tsagkrasoulis Greece

Pauline Mouchès Canada

Nikhil Bhagwat Canada

Qiongling Li China

Mehdi Rahim France

Seyed Hani Hojjati United States

Frank de Vos Netherlands

Weikai Li China

Nicolas Honnorat

384 ×1.4

130 ×0.8

PMH

169 ×1.1

RNMI

42 ×0.5

PHYSI

67 ×1.0

Citations per year, relative to Nicolas Honnorat Nicolas Honnorat (= 1×) peers Weikai Li

Countries citing papers authored by Nicolas Honnorat

Since Specialization

Citations

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

Fields of papers citing papers by Nicolas Honnorat

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicolas Honnorat

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

All Works

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20 of 20 papers shown

Honnorat, Nicolas, Jon B. Toledo, Sokratis Charisis, et al.. (2024). Deep learning reveals pathology-confirmed neuroimaging signatures in Alzheimer’s, vascular and Lewy body dementias. Brain. 148(6). 1963–1977. 1 indexed citations

Honnorat, Nicolas, Sudha Seshadri, Ronald Killiany, et al.. (2023). Riemannian frameworks for the harmonization of resting-state functional MRI scans. Medical Image Analysis. 91. 103043–103043. 2 indexed citations

Honnorat, Nicolas & Mohamad Habes. (2022). Covariance shrinkage can assess and improve functional connectomes. NeuroImage. 256. 119229–119229. 4 indexed citations

Zahr, Natalie M., Manojkumar Saranathan, Nicolas Honnorat, et al.. (2021). Altered Cerebro-Cerebellar Dynamic Functional Connectivity in Alcohol Use Disorder: a Resting-State fMRI Study. The Cerebellum. 20(6). 823–835. 15 indexed citations

Honnorat, Nicolas, Manojkumar Saranathan, Edith V. Sullivan, et al.. (2021). Performance ramifications of abnormal functional connectivity of ventral posterior lateral thalamus with cerebellum in abstinent individuals with Alcohol Use Disorder. Drug and Alcohol Dependence. 220. 108509–108509. 5 indexed citations

Honnorat, Nicolas, et al.. (2020). Alcohol Use Disorder and Its Comorbidity With HIV Infection Disrupts Anterior Cingulate Cortex Functional Connectivity. Biological Psychiatry Cognitive Neuroscience and Neuroimaging. 7(11). 1127–1136. 3 indexed citations

Zhao, Qingyu, Nicolas Honnorat, Ehsan Adeli, & Kilian M. Pohl. (2019). Variational Autoencoder with Truncated Mixture of Gaussians for Functional Connectivity Analysis. arXiv (Cornell University). 1 indexed citations

Zhao, Qingyu, Nicolas Honnorat, Ehsan Adeli, et al.. (2019). Variational Autoencoder with Truncated Mixture of Gaussians for Functional Connectivity Analysis. Lecture notes in computer science. 11492. 867–879. 12 indexed citations

Zhao, Qingyu, et al.. (2019). Variational AutoEncoder for Regression: Application to Brain Aging Analysis. Lecture notes in computer science. 11765. 823–831. 48 indexed citations

10.

Yang, Zhen, Shi Gu, Nicolas Honnorat, et al.. (2018). Network changes associated with transdiagnostic depressive symptom improvement following cognitive behavioral therapy in MDD and PTSD. Molecular Psychiatry. 23(12). 2314–2323. 34 indexed citations

11.

Eavani, Harini, Mohamad Habes, Theodore D. Satterthwaite, et al.. (2018). Heterogeneity of structural and functional imaging patterns of advanced brain aging revealed via machine learning methods. Neurobiology of Aging. 71. 41–50. 56 indexed citations

12.

Honnorat, Nicolas, Drew Parker, Birkan Tunç, Christos Davatzikos, & Ragini Verma. (2017). Subject-Specific Structural Parcellations Based on Randomized AB-divergences. Lecture notes in computer science. 10433. 407–415. 3 indexed citations

13.

Honnorat, Nicolas, et al.. (2017). Neuroanatomical heterogeneity of schizophrenia revealed by semi-supervised machine learning methods. Schizophrenia Research. 214. 43–50. 31 indexed citations

14.

Honnorat, Nicolas & Christos Davatzikos. (2017). Riccati-Regularized Precision Matrices for Neuroimaging. Lecture notes in computer science. 10265. 275–286. 2 indexed citations

15.

Honnorat, Nicolas, Theodore D. Satterthwaite, Raquel E. Gur, Ruben C. Gur, & Christos Davatzikos. (2016). sGraSP: A graph-based method for the derivation of subject-specific functional parcellations of the brain. Journal of Neuroscience Methods. 277. 1–20. 8 indexed citations

16.

Gross, Polina, Nicolas Honnorat, Erdem Varol, et al.. (2016). Nuquantus: Machine learning software for the characterization and quantification of cell nuclei in complex immunofluorescent tissue images. Scientific Reports. 6(1). 23431–23431. 13 indexed citations

17.

Toledo, Jon B., Nicolas Honnorat, Jimit Doshi, et al.. (2016). Heterogeneity of neuroanatomical patterns in prodromal Alzheimer’s disease: links to cognition, progression and biomarkers. Brain. 140(3). aww319–aww319. 117 indexed citations

18.

Honnorat, Nicolas, Harini Eavani, Theodore D. Satterthwaite, Ruben C. Gur, & Christos Davatzikos. (2014). GraSP: Geodesic Graph-based Segmentation with Shape Priors for the functional parcellation of the cortex. NeuroImage. 106. 207–221. 46 indexed citations

19.

Honnorat, Nicolas, et al.. (2012). Graph-based guide-wire segmentation through fusion of contrast-enhanced and fluoroscopic images. SPIRE - Sciences Po Institutional REpository.

20.

Honnorat, Nicolas, Régis Vaillant, & Nikos Paragios. (2011). Graph-Based Geometric-Iconic Guide-Wire Tracking. Lecture notes in computer science. 14(Pt 1). 9–16. 13 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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