Daniel E. Payne

720 total citations
9 papers, 444 citations indexed

About

Daniel E. Payne is a scholar working on Cognitive Neuroscience, Psychiatry and Mental health and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Daniel E. Payne has authored 9 papers receiving a total of 444 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cognitive Neuroscience, 8 papers in Psychiatry and Mental health and 2 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Daniel E. Payne's work include Epilepsy research and treatment (8 papers), EEG and Brain-Computer Interfaces (8 papers) and Functional Brain Connectivity Studies (2 papers). Daniel E. Payne is often cited by papers focused on Epilepsy research and treatment (8 papers), EEG and Brain-Computer Interfaces (8 papers) and Functional Brain Connectivity Studies (2 papers). Daniel E. Payne collaborates with scholars based in Australia, United States and United Kingdom. Daniel E. Payne's co-authors include Mark Cook, Dean R. Freestone, David B. Grayden, Philippa J. Karoly, Ewan S. Nurse, Benjamin H. Brinkmann, Susmita Saha, Isabell Kiral-Kornek, Steven N. Baldassano and Terence J. O’Brien and has published in prestigious journals such as Annals of Neurology, Epilepsia and EBioMedicine.

In The Last Decade

Daniel E. Payne

9 papers receiving 431 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel E. Payne Australia	8	348	243	73	49	41	9	444
Johannes Koren Austria	12	350 1.0×	268 1.1×	82 1.1×	63 1.3×	50 1.2×	42	461
Jay Pathmanathan United States	12	422 1.2×	222 0.9×	118 1.6×	60 1.2×	19 0.5×	28	592
Mona Nasseri United States	12	409 1.2×	298 1.2×	81 1.1×	52 1.1×	36 0.9×	35	603
Rima El Atrache United States	12	373 1.1×	296 1.2×	44 0.6×	63 1.3×	30 0.7×	20	502
Yogatheesan Varatharajah United States	10	240 0.7×	161 0.7×	70 1.0×	23 0.5×	24 0.6×	24	328
Evy Cleeren Belgium	12	368 1.1×	227 0.9×	101 1.4×	39 0.8×	47 1.1×	22	517
Kaat Vandecasteele Belgium	10	337 1.0×	202 0.8×	48 0.7×	30 0.6×	43 1.0×	12	416
Mustafa Aykut Kural Denmark	10	287 0.8×	228 0.9×	99 1.4×	39 0.8×	16 0.4×	21	453
Matthias Ihle Germany	8	493 1.4×	236 1.0×	106 1.5×	38 0.8×	132 3.2×	11	567
Beth A. Lopour United States	15	408 1.2×	192 0.8×	125 1.7×	49 1.0×	20 0.5×	44	524

Countries citing papers authored by Daniel E. Payne

Since Specialization

Citations

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

Fields of papers citing papers by Daniel E. Payne

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel E. Payne

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

All Works

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9 of 9 papers shown

Naim‐Feil, Jodie, Rachel E. Stirling, Philippa J. Karoly, et al.. (2024). Pro‐Ictal EEG Scheduling Improves the Yield of Epilepsy Monitoring: Validating the Use of Multiday Seizure Cycles to Optimize Video‐EEG Timing. Annals of Neurology. 96(6). 1148–1159. 5 indexed citations

Stirling, Rachel E., Daniel E. Payne, Ewan S. Nurse, et al.. (2023). Forecasting seizure likelihood from cycles of self-reported events and heart rate: a prospective pilot study. EBioMedicine. 93. 104656–104656. 17 indexed citations

Chen, Zhuying, Wenhua Yu, Rongbin Xu, et al.. (2022). Ambient air pollution and epileptic seizures: A panel study in Australia. Epilepsia. 63(7). 1682–1692. 16 indexed citations

Stirling, Rachel E., David B. Grayden, Wendyl D’Souza, et al.. (2021). Forecasting Seizure Likelihood With Wearable Technology. Frontiers in Neurology. 12. 704060–704060. 58 indexed citations

Dell, Katrina L., Daniel E. Payne, Václav Křemen, et al.. (2021). Seizure likelihood varies with day-to-day variations in sleep duration in patients with refractory focal epilepsy: A longitudinal electroencephalography investigation. EClinicalMedicine. 37. 100934–100934. 42 indexed citations

Karoly, Philippa J., Mark Cook, Matias I. Maturana, et al.. (2020). Forecasting cycles of seizure likelihood. Epilepsia. 61(4). 776–786. 81 indexed citations

Payne, Daniel E., Katrina L. Dell, Philippa J. Karoly, et al.. (2020). Identifying seizure risk factors: A comparison of sleep, weather, and temporal features using a Bayesian forecast. Epilepsia. 62(2). 371–382. 22 indexed citations

Payne, Daniel E., Philippa J. Karoly, Dean R. Freestone, et al.. (2018). Postictal suppression and seizure durations: A patient‐specific, long‐term iEEG analysis. Epilepsia. 59(5). 1027–1036. 12 indexed citations

Kiral-Kornek, Isabell, Subhrajit Roy, Ewan S. Nurse, et al.. (2017). Epileptic Seizure Prediction Using Big Data and Deep Learning: Toward a Mobile System. EBioMedicine. 27. 103–111. 191 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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