Richard E. Daws

1.2k total citations · 2 hit papers
17 papers, 739 citations indexed

About

Richard E. Daws is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Neurology. According to data from OpenAlex, Richard E. Daws has authored 17 papers receiving a total of 739 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cognitive Neuroscience, 5 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Neurology. Recurrent topics in Richard E. Daws's work include Functional Brain Connectivity Studies (6 papers), Advanced Neuroimaging Techniques and Applications (4 papers) and EEG and Brain-Computer Interfaces (3 papers). Richard E. Daws is often cited by papers focused on Functional Brain Connectivity Studies (6 papers), Advanced Neuroimaging Techniques and Applications (4 papers) and EEG and Brain-Computer Interfaces (3 papers). Richard E. Daws collaborates with scholars based in United Kingdom, United States and France. Richard E. Daws's co-authors include Robin Carhart‐Harris, Christopher Timmermann, Leor Roseman, Adam Hampshire, David Erritzøe, James Sexton, Bruna Giribaldi, Matthew B. Wall, David Nutt and Mendel Kaelen and has published in prestigious journals such as Nature Medicine, Nature Communications and NeuroImage.

In The Last Decade

Richard E. Daws

16 papers receiving 728 citations

Hit Papers

Predicting Responses to Psychedelics: A Prospective Study 2018 2026 2020 2023 2018 2022 50 100 150 200 250
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.

  1. Predicting Responses to Psychedelics: A Prospective Study
    2018 287 citations Eline Haijen, Mendel Kaelen et al. Frontiers in Pharmacology profile →
  2. Increased global integration in the brain after psilocybin therapy for depression
    2022 257 citations Richard E. Daws, Christopher Timmermann et al. Nature Medicine profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Richard E. Daws United Kingdom 9 519 295 285 134 69 17 739
Cory R. Weissman Canada 13 437 0.8× 260 0.9× 153 0.5× 90 0.7× 73 1.1× 32 643
Joseph P. Barsuglia United States 14 424 0.8× 215 0.7× 205 0.7× 73 0.5× 50 0.7× 18 570
Lysia Demetriou United Kingdom 13 627 1.2× 368 1.2× 438 1.5× 148 1.1× 78 1.1× 20 961
F.X. Vollenweider Switzerland 9 443 0.9× 198 0.7× 353 1.2× 82 0.6× 43 0.6× 23 597
Theo Huber Switzerland 8 821 1.6× 257 0.9× 558 2.0× 293 2.2× 98 1.4× 8 1.3k
Dominique Holstein Switzerland 5 514 1.0× 310 1.1× 281 1.0× 84 0.6× 83 1.2× 5 637
Anya K. Bershad United States 16 477 0.9× 174 0.6× 326 1.1× 96 0.7× 62 0.9× 33 805
Ben Sessa United Kingdom 17 918 1.8× 369 1.3× 466 1.6× 143 1.1× 160 2.3× 31 1.1k
Brendan Adkinson United States 7 359 0.7× 158 0.5× 334 1.2× 422 3.1× 77 1.1× 13 855
Luke A. Jelen United Kingdom 12 271 0.5× 146 0.5× 253 0.9× 92 0.7× 31 0.4× 23 691

Countries citing papers authored by Richard E. Daws

Since Specialization
Citations

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

Fields of papers citing papers by Richard E. Daws

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Richard E. Daws. 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 Richard E. Daws. The network helps show where Richard E. Daws may publish in the future.

Co-authorship network of co-authors of Richard E. Daws

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

All Works

17 of 17 papers shown
1.
Parkin, Beth, Richard E. Daws, Gregory Scott, et al.. (2025). The optimisation of functional brain network dynamics when learning to perform complex tasks. Neuropsychologia. 216. 109188–109188.
2.
Girn, Manesh, Fernando E. Rosas, Richard E. Daws, et al.. (2023). A complex systems perspective on psychedelic brain action. Trends in Cognitive Sciences. 27(5). 433–445. 34 indexed citations
3.
Cole, James H., Richard E. Daws, Vincent Giampietro, et al.. (2022). Tissue volume estimation and age prediction using rapid structural brain scans. Scientific Reports. 12(1). 11 indexed citations
4.
Daws, Richard E., Christopher Timmermann, Bruna Giribaldi, et al.. (2022). Increased global integration in the brain after psilocybin therapy for depression. Nature Medicine. 28(4). 844–851. 257 indexed citations breakdown →
5.
Soreq, Eyal, Inês R. Violante, Richard E. Daws, & Adam Hampshire. (2021). Neuroimaging evidence for a network sampling theory of individual differences in human intelligence test performance. Nature Communications. 12(1). 2072–2072. 15 indexed citations
6.
Parkin, Beth, Richard E. Daws, Inês R. Violante, et al.. (2021). Dissociable effects of age and Parkinson’s disease on instruction-based learning. Brain Communications. 3(3). fcab175–fcab175. 1 indexed citations
7.
Váša, František, Richard E. Daws, Vincent Giampietro, et al.. (2021). Rapid processing and quantitative evaluation of structural brain scans for adaptive multimodal imaging. Human Brain Mapping. 43(5). 1749–1765. 6 indexed citations
8.
Li, Weihua, Nicholas P Lao–Kaim, Andreas–Antonios Roussakis, et al.. (2020). Longitudinal functional connectivity changes related to dopaminergic decline in Parkinson’s disease. NeuroImage Clinical. 28. 102409–102409. 28 indexed citations
9.
10.
Haijen, Eline, Mendel Kaelen, Leor Roseman, et al.. (2018). Predicting Responses to Psychedelics: A Prospective Study. Frontiers in Pharmacology. 9. 897–897. 287 indexed citations breakdown →
11.
Grant, Jon E., Richard E. Daws, Adam Hampshire, & Samuel R. Chamberlain. (2018). An fMRI Pilot Study of Cognitive Flexibility in Trichotillomania. Journal of Neuropsychiatry. 30(4). 318–324. 7 indexed citations
12.
Barry, Erica F., Sofía Cerdá-González, Wen‐Ming Luh, et al.. (2018). Normal diffusivity of the domestic feline brain. The Journal of Comparative Neurology. 527(5). 1012–1023. 3 indexed citations
13.
Mason, Sarah, Richard E. Daws, Eyal Soreq, et al.. (2018). Predicting clinical diagnosis in Huntington's disease: An imaging polymarker. Annals of Neurology. 83(3). 532–543. 29 indexed citations
14.
15.
Dautricourt, Sophie, Inês R. Violante, Emma‐Jane Mallas, et al.. (2017). Reduced information processing speed and event-related EEG synchronization in traumatic brain injury (P6.149). Neurology. 88(16_supplement). 2 indexed citations
16.
Chamberlain, Samuel R., Katherine Derbyshire, Richard E. Daws, et al.. (2016). White matter tract integrity in treatment-resistant gambling disorder. The British Journal of Psychiatry. 208(6). 579–584. 8 indexed citations
17.

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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