Jelle R. Dalenberg

1.0k total citations
25 papers, 661 citations indexed

About

Jelle R. Dalenberg is a scholar working on Cognitive Neuroscience, Nutrition and Dietetics and Neurology. According to data from OpenAlex, Jelle R. Dalenberg has authored 25 papers receiving a total of 661 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cognitive Neuroscience, 8 papers in Nutrition and Dietetics and 7 papers in Neurology. Recurrent topics in Jelle R. Dalenberg's work include Biochemical Analysis and Sensing Techniques (8 papers), Neurological disorders and treatments (7 papers) and Neural and Behavioral Psychology Studies (6 papers). Jelle R. Dalenberg is often cited by papers focused on Biochemical Analysis and Sensing Techniques (8 papers), Neurological disorders and treatments (7 papers) and Neural and Behavioral Psychology Studies (6 papers). Jelle R. Dalenberg collaborates with scholars based in Netherlands, United States and Switzerland. Jelle R. Dalenberg's co-authors include Remco J. Renken, Gert J. Ter Horst, S. Gutjar, Gerry Jager, René A. de Wijk, Kees de Graaf, Cees de Graaf, Dana M. Small, Serge Luquet and Barkha P. Patel and has published in prestigious journals such as PLoS ONE, NeuroImage and Cell Metabolism.

In The Last Decade

Jelle R. Dalenberg

22 papers receiving 649 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jelle R. Dalenberg Netherlands 11 293 270 229 128 114 25 661
Lorenzo D. Stafford United Kingdom 16 112 0.4× 205 0.8× 289 1.3× 183 1.4× 168 1.5× 47 751
Ulrike Toepel Switzerland 15 105 0.4× 192 0.7× 208 0.9× 309 2.4× 360 3.2× 31 803
Krystyna Rankin United States 7 208 0.7× 430 1.6× 429 1.9× 114 0.9× 73 0.6× 9 816
Sanne Griffioen-Roose Netherlands 11 137 0.5× 209 0.8× 134 0.6× 57 0.4× 53 0.5× 16 594
Jennifer Higgins United States 7 168 0.6× 375 1.4× 371 1.6× 65 0.5× 32 0.3× 17 731
Katharine Fast United States 13 223 0.8× 501 1.9× 490 2.1× 85 0.7× 43 0.4× 17 923
René de Wijk Netherlands 10 192 0.7× 193 0.7× 150 0.7× 73 0.6× 19 0.2× 17 502
Julie Hudry Switzerland 18 122 0.4× 363 1.3× 541 2.4× 231 1.8× 241 2.1× 27 925
Laurie A. Lucchina United States 7 261 0.9× 573 2.1× 530 2.3× 101 0.8× 32 0.3× 8 826

Countries citing papers authored by Jelle R. Dalenberg

Since Specialization
Citations

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

Fields of papers citing papers by Jelle R. Dalenberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jelle R. Dalenberg. 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 Jelle R. Dalenberg. The network helps show where Jelle R. Dalenberg may publish in the future.

Co-authorship network of co-authors of Jelle R. Dalenberg

This figure shows the co-authorship network connecting the top 25 collaborators of Jelle R. Dalenberg. A scholar is included among the top collaborators of Jelle R. Dalenberg 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 Jelle R. Dalenberg. Jelle R. Dalenberg 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.
Jong, Bauke M. de, et al.. (2025). Multivariate Pattern Analysis of fMRI Reveals Striato‐Cortical Network Changes in Myoclonus‐Dystonia. European Journal of Neurology. 32(4). e70085–e70085.
2.
Stouwe, A.M. Madelein van der, et al.. (2025). Explainable machine learning for movement disorders - Classification of tremor and myoclonus. Computers in Biology and Medicine. 192(Pt B). 110180–110180. 1 indexed citations
3.
Dalenberg, Jelle R., et al.. (2025). Changes in glucose metabolism in essential tremor: within and beyond the cerebello-thalamo-cortical circuit. Brain Communications. 7(3). fcaf227–fcaf227.
4.
Veen, Sterre van der, et al.. (2024). Substantiating the Short Burst Duration in Cortical Myoclonus. Movement Disorders. 39(12). 2275–2280.
5.
Dalenberg, Jelle R., et al.. (2024). Digital Health Technology Use Across Socioeconomic Groups Prior to and During the COVID-19 Pandemic: Panel Study. JMIR Public Health and Surveillance. 10. e55384–e55384. 5 indexed citations
6.
Dalenberg, Jelle R., et al.. (2024). Next move in movement disorders: neuroimaging protocols for hyperkinetic movement disorders. Frontiers in Human Neuroscience. 18. 1406786–1406786. 3 indexed citations
7.
Horn, Harm J. van der, et al.. (2022). Altered brain connectivity in hyperkinetic movement disorders: A review of resting-state fMRI. NeuroImage Clinical. 37. 103302–103302. 10 indexed citations
8.
Horn, Harm J. van der, Sanne K. Meles, Victor M. Vergara, et al.. (2022). A resting-state fMRI pattern of spinocerebellar ataxia type 3 and comparison with 18F-FDG PET. NeuroImage Clinical. 34. 103023–103023. 5 indexed citations
9.
Stouwe, A.M. Madelein van der, et al.. (2021). Next move in movement disorders (NEMO): developing a computer-aided classification tool for hyperkinetic movement disorders. BMJ Open. 11(10). e055068–e055068. 9 indexed citations
10.
Stouwe, A.M. Madelein van der, Bauke M. de Jong, Jeannette Gelauff, et al.. (2020). The chronnectome as a model for Charcot’s ‘dynamic lesion’ in functional movement disorders. NeuroImage Clinical. 28. 102381–102381. 9 indexed citations
11.
Farruggia, Michael C., et al.. (2020). No evidence for an association between obesity and milkshake liking. International Journal of Obesity. 44(8). 1668–1677. 8 indexed citations
12.
Dalenberg, Jelle R., et al.. (2018). Valence processing differs across stimulus modalities. NeuroImage. 183. 734–744. 9 indexed citations
13.
Dalenberg, Jelle R., et al.. (2017). Flavor pleasantness processing in the ventral emotion network. PLoS ONE. 12(2). e0170310–e0170310. 16 indexed citations
14.
Saliasi, Emi, Linda Geerligs, Jelle R. Dalenberg, Monicque M. Lorist, & Natasha M. Maurits. (2015). Differences in cognitive aging: typology based on a community structure detection approach. Frontiers in Aging Neuroscience. 7. 35–35. 3 indexed citations
15.
Dalenberg, Jelle R., et al.. (2015). Functional specialization of the male insula during taste perception. NeuroImage. 119. 210–220. 47 indexed citations
16.
Dalenberg, Jelle R., Remco J. Renken, Paul A.M. Smeets, et al.. (2014). To like or not to like: Neural substrates of subjective flavor preferences. Behavioural Brain Research. 269. 128–137. 27 indexed citations
17.
Dalenberg, Jelle R., S. Gutjar, Gert J. Ter Horst, et al.. (2014). Evoked Emotions Predict Food Choice. PLoS ONE. 9(12). e115388–e115388. 139 indexed citations
18.
Dalenberg, Jelle R., Luca Nanetti, Remco J. Renken, René A. de Wijk, & Gert J. Ter Horst. (2014). Dealing with Consumer Differences in Liking during Repeated Exposure to Food; Typical Dynamics in Rating Behavior. PLoS ONE. 9(3). e93350–e93350. 26 indexed citations
19.
Rijn, Hedderik van, Jelle R. Dalenberg, Jelmer P. Borst, & Simone Sprenger. (2012). Pupil Dilation Co-Varies with Memory Strength of Individual Traces in a Delayed Response Paired-Associate Task. PLoS ONE. 7(12). e51134–e51134. 45 indexed citations
20.
Dalenberg, Jelle R. & Hedderik van Rijn. (2011). Does retrieval require effort? Effects of memory strength on pupil dilation.. Cognitive Science. 33(33). 1 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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