Jonathan Young

1.8k total citations · 1 hit paper
16 papers, 1.2k citations indexed

About

Jonathan Young is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Psychiatry and Mental health. According to data from OpenAlex, Jonathan Young has authored 16 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Cognitive Neuroscience, 4 papers in Experimental and Cognitive Psychology and 4 papers in Psychiatry and Mental health. Recurrent topics in Jonathan Young's work include Functional Brain Connectivity Studies (5 papers), Mental Health Research Topics (4 papers) and Dementia and Cognitive Impairment Research (3 papers). Jonathan Young is often cited by papers focused on Functional Brain Connectivity Studies (5 papers), Mental Health Research Topics (4 papers) and Dementia and Cognitive Impairment Research (3 papers). Jonathan Young collaborates with scholars based in United Kingdom, United States and Spain. Jonathan Young's co-authors include Sébastien Ourselin, M. Jorge Cardoso, Marc Modat, A. Mendelson, David M. Cash, Philip McGuire, Andrea Mechelli, Gary Donohoe, Edward T. Bullmore and Aiden Corvin and has published in prestigious journals such as Journal of Cell Science, Psychological Medicine and Schizophrenia Bulletin.

In The Last Decade

Jonathan Young

16 papers receiving 1.2k citations

Hit Papers

Structure and function in the nervous systems of inverteb... 1966 2026 1986 2006 1966 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonathan Young United Kingdom 10 403 369 222 216 184 16 1.2k
Jeremy F.P. Ullmann Australia 19 204 0.5× 246 0.7× 147 0.7× 67 0.3× 264 1.4× 35 1.2k
Erin L. Rich United States 15 361 0.9× 850 2.3× 293 1.3× 77 0.4× 117 0.6× 24 1.6k
Susan M. Fitzpatrick United States 26 273 0.7× 220 0.6× 488 2.2× 101 0.5× 252 1.4× 66 2.0k
Douglas M. Bowden United States 26 823 2.0× 619 1.7× 150 0.7× 77 0.4× 434 2.4× 91 2.9k
Sandra Esmeralda Dos Santos United States 3 416 1.0× 285 0.8× 125 0.6× 38 0.2× 537 2.9× 3 1.6k
Neil Weisenfeld United States 15 156 0.4× 146 0.4× 73 0.3× 63 0.3× 545 3.0× 18 1.5k
William Corrêa Tavares Brazil 9 408 1.0× 266 0.7× 166 0.7× 35 0.2× 552 3.0× 22 1.7k
Felipe Cunha Canada 5 397 1.0× 267 0.7× 143 0.6× 35 0.2× 526 2.9× 13 1.6k
Stephan Gerhard Switzerland 9 295 0.7× 444 1.2× 74 0.3× 29 0.1× 143 0.8× 11 936
Aaron L. Goldman United States 13 431 1.1× 754 2.0× 52 0.2× 379 1.8× 361 2.0× 25 1.9k

Countries citing papers authored by Jonathan Young

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Young

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonathan Young

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

All Works

16 of 16 papers shown
1.
Lei, Du, Kun Qin, Walter Hugo Lopez Pinaya, et al.. (2022). Graph Convolutional Networks Reveal Network-Level Functional Dysconnectivity in Schizophrenia. Schizophrenia Bulletin. 48(4). 881–892. 42 indexed citations
2.
Morgan, Sarah E., Jonathan Young, Ameera X. Patel, et al.. (2020). Functional Magnetic Resonance Imaging Connectivity Accurately Distinguishes Cases With Psychotic Disorders From Healthy Controls, Based on Cortical Features Associated With Brain Network Development. Biological Psychiatry Cognitive Neuroscience and Neuroimaging. 6(12). 1125–1134. 20 indexed citations
3.
Gifford, George, Nicolás Crossley, Matthew J. Kempton, et al.. (2020). Resting state fMRI based multilayer network configuration in patients with schizophrenia. NeuroImage Clinical. 25. 102169–102169. 53 indexed citations
4.
Lei, Du, Walter Hugo Lopez Pinaya, Thérèse van Amelsvoort, et al.. (2019). Detecting schizophrenia at the level of the individual: relative diagnostic value of whole-brain images, connectome-wide functional connectivity and graph-based metrics. Psychological Medicine. 50(11). 1852–1861. 58 indexed citations
5.
Lei, Du, Walter Hugo Lopez Pinaya, Jonathan Young, et al.. (2019). Integrating machining learning and multimodal neuroimaging to detect schizophrenia at the level of the individual. Human Brain Mapping. 41(5). 1119–1135. 70 indexed citations
6.
Mechelli, Andrea, Ashleigh Lin, Stephen J. Wood, et al.. (2016). Using clinical information to make individualized prognostic predictions in people at ultra high risk for psychosis. Schizophrenia Research. 184. 32–38. 44 indexed citations
7.
Young, Jonathan. (2016). Spatial pyramid match kernels for brain image classification. Research Portal (King's College London). 1 indexed citations
8.
Roberto, Aaron J., et al.. (2016). First-Episode of Synthetic Cannabinoid-Induced Psychosis in a Young Adult, Successfully Managed with Hospitalization and Risperidone. Case Reports in Psychiatry. 2016. 1–4. 19 indexed citations
9.
Manning, Emily N., Kate Macdonald, Kelvin K. Leung, et al.. (2015). Differential hippocampal shapes in posterior cortical atrophy patients: A comparison with control and typical AD subjects. Human Brain Mapping. 36(12). 5123–5136. 16 indexed citations
10.
Young, Jonathan, Marc Modat, M. Jorge Cardoso, et al.. (2013). Accurate multimodal probabilistic prediction of conversion to Alzheimer's disease in patients with mild cognitive impairment. NeuroImage Clinical. 2. 735–745. 176 indexed citations
11.
Young, Jonathan, John Ashburner, & Sébastien Ourselin. (2013). Wrapper Methods to Correct Mislabelled Training Data. 170–173. 9 indexed citations
12.
Young, Jonathan, Marc Modat, M. Jorge Cardoso, John Ashburner, & Sébastien Ourselin. (2012). Classification of Alzheimer's disease patients and controls with Gaussian processes. Research Portal (King's College London). 1523–1526. 6 indexed citations
13.
Young, Jonathan, Gerard R. Ridgway, Kelvin K. Leung, & Sébastien Ourselin. (2012). Classification of Alzheimer's disease patients with hippocampal shape, wrapper based feature selection and support vector machine. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8314. 83140Q–83140Q. 6 indexed citations
14.
Jarman, Kenneth D., et al.. (2010). Integrating System Dynamics and Bayesian Networks with Application to Counter-IED Scenarios. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1 indexed citations
15.
Young, Jonathan. (1966). Structure and function in the nervous systems of invertebrates. Electroencephalography and Clinical Neurophysiology. 20(5). 538–538. 693 indexed citations breakdown →
16.
Young, Jonathan. (1953). Intracellular Membranes. Journal of Cell Science. S3-94(28). 399–406. 2 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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