D. Blackburn

30.9k total citations
124 papers, 2.1k citations indexed

About

D. Blackburn is a scholar working on Cognitive Neuroscience, Psychiatry and Mental health and Artificial Intelligence. According to data from OpenAlex, D. Blackburn has authored 124 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Cognitive Neuroscience, 30 papers in Psychiatry and Mental health and 15 papers in Artificial Intelligence. Recurrent topics in D. Blackburn's work include Dementia and Cognitive Impairment Research (25 papers), Neurobiology of Language and Bilingualism (17 papers) and Functional Brain Connectivity Studies (15 papers). D. Blackburn is often cited by papers focused on Dementia and Cognitive Impairment Research (25 papers), Neurobiology of Language and Bilingualism (17 papers) and Functional Brain Connectivity Studies (15 papers). D. Blackburn collaborates with scholars based in United Kingdom, United States and Italy. D. Blackburn's co-authors include Markus Reuber, Annalena Venneri, Pamela J. Shaw, Heidi Christensen, Bahman Mirheidari, Ptolemaios G. Sarrigiannis, Simon Bell, Siranush Sargsyan, Peter N. Monk and Kirsty Harkness and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Molecular Biology.

In The Last Decade

D. Blackburn

112 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. Blackburn United Kingdom 26 618 576 329 307 294 124 2.1k
Mohamad Habes United States 24 807 1.3× 587 1.0× 588 1.8× 576 1.9× 226 0.8× 93 2.5k
Gwénaëlle Catheline France 28 670 1.1× 578 1.0× 702 2.1× 461 1.5× 126 0.4× 84 2.4k
David B. Keator United States 27 400 0.6× 910 1.6× 386 1.2× 158 0.5× 146 0.5× 89 2.5k
Guofan Xu United States 18 719 1.2× 1.3k 2.3× 521 1.6× 429 1.4× 135 0.5× 31 3.0k
Curtis Tatsuoka United States 28 831 1.3× 209 0.4× 255 0.8× 180 0.6× 149 0.5× 141 2.6k
Stéphane Epelbaum France 24 903 1.5× 646 1.1× 818 2.5× 347 1.1× 77 0.3× 67 2.2k
Shifu Xiao China 30 931 1.5× 427 0.7× 558 1.7× 451 1.5× 62 0.2× 148 2.9k
Pablo Martínez‐Lage Spain 28 855 1.4× 436 0.8× 861 2.6× 244 0.8× 132 0.4× 89 2.2k
Ives Cavalcante Passos Brazil 29 1.3k 2.0× 499 0.9× 149 0.5× 327 1.1× 81 0.3× 108 3.5k
Jordi A. Matías‐Guiu Spain 33 946 1.5× 687 1.2× 497 1.5× 424 1.4× 86 0.3× 191 3.1k

Countries citing papers authored by D. Blackburn

Since Specialization
Citations

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

Fields of papers citing papers by D. Blackburn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. Blackburn

This figure shows the co-authorship network connecting the top 25 collaborators of D. Blackburn. A scholar is included among the top collaborators of D. Blackburn 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 D. Blackburn. D. Blackburn 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.
Al‐Ismaily, Said, et al.. (2026). Biochar raises soil health and reduces greenhouse gas emissions in arid lands. Frontiers in Soil Science. 6.
2.
Pahar, Madhurananda, et al.. (2025). Automatic Detection of Early Cognitive Decline Using Multimodal Feature Fusion and Transfer Learning on Real-World Conversational Speech. IEEE Journal of Biomedical and Health Informatics. 29(12). 8727–8734.
3.
Bell, Simon, et al.. (2024). Spoken language-based automatic cognitive assessment of stroke survivors. 2(1). 32–38. 3 indexed citations
4.
Rose, Amy D., et al.. (2024). Bringing the English Curriculum to Life.
5.
Blackburn, D., et al.. (2022). Interview: the global challenge for unions. 29(2). 16–18. 1 indexed citations
6.
Manca, Riccardo, Matteo De Marco, Vanessa Raymont, et al.. (2022). The impact of social isolation due to the COVID-19 pandemic on patients with dementia and caregivers. Acta Neuropsychiatrica. 34(5). 276–281. 7 indexed citations
7.
Marco, Matteo De, D. Blackburn, Iain D. Wilkinson, et al.. (2021). Obesity and Brain Vulnerability in Normal and Abnormal Aging: A Multimodal MRI Study. Journal of Alzheimer s Disease Reports. 5(1). 65–77. 11 indexed citations
8.
Courtney, Ellie, D. Blackburn, & Markus Reuber. (2021). Neurologists’ perceptions of utilising tele-neurology to practice remotely during the COVID-19 pandemic. Patient Education and Counseling. 104(3). 452–459. 32 indexed citations
9.
Mirheidari, Bahman, et al.. (2021). Characterising spoken interactions of healthy ageing adults with CognoSpeak, a web‐based cognitive assessment tool. Alzheimer s & Dementia. 17(S5). 1 indexed citations
10.
Venneri, Annalena, et al.. (2020). Age-Related Hearing Loss an Under-Recognised Cause of Memory Difficulties Mimicking Early Alzheimer’s Disease. Research Explorer (The University of Manchester). 7(1). 1 indexed citations
11.
Saxon, Jennifer A., J. C. Thompson, Jennifer Harris, et al.. (2020). Cognition and behaviour in frontotemporal dementia with and without amyotrophic lateral sclerosis. Journal of Neurology Neurosurgery & Psychiatry. 91(12). 1304–1311. 20 indexed citations
12.
Zhao, Yifan, Liangyu Chen, Panagiotis Zis, et al.. (2019). A Dementia Classification Framework Using Frequency and Time-Frequency Features Based on EEG Signals. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 27(5). 826–835. 106 indexed citations
13.
Sarrigiannis, Ptolemaios G., Panagiotis Zis, Zoe Unwin, et al.. (2019). Tremor after long term lithium treatment; is it cortical myoclonus?. SHILAP Revista de lepidopterología. 6(1). 5–5. 5 indexed citations
14.
15.
Blackburn, D., et al.. (2016). Convenient synthesis of phosphonohydrazines from arylamines. Tetrahedron Letters. 57(19). 2097–2099. 4 indexed citations
16.
Scutt, Polly, D. Blackburn, Kailash Krishnan, et al.. (2015). Baseline characteristics, analysis plan and report on feasibility for the Prevention Of Decline in Cognition After Stroke Trial (PODCAST). Trials. 16(1). 509–509. 5 indexed citations
17.
Elsey, Christopher, Paul Drew, Danielle Jones, et al.. (2015). Towards diagnostic conversational profiles of patients presenting with dementia or functional memory disorders to memory clinics. Patient Education and Counseling. 98(9). 1071–1077. 67 indexed citations
18.
19.
Sargsyan, Siranush, D. Blackburn, Siân C. Barber, et al.. (2011). A comparison of in vitro properties of resting SOD1 transgenic microglia reveals evidence of reduced neuroprotective function. BMC Neuroscience. 12(1). 91–91. 19 indexed citations
20.
Blackburn, D., Siranush Sargsyan, Peter N. Monk, & Pamela J. Shaw. (2009). Astrocyte function and role in motor neuron disease: A future therapeutic target?. Glia. 57(12). 1251–1264. 141 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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