Ken N. Seergobin

906 total citations
25 papers, 701 citations indexed

About

Ken N. Seergobin is a scholar working on Neurology, Cognitive Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Ken N. Seergobin has authored 25 papers receiving a total of 701 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Neurology, 12 papers in Cognitive Neuroscience and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Ken N. Seergobin's work include Parkinson's Disease Mechanisms and Treatments (17 papers), Neurological disorders and treatments (11 papers) and Neural and Behavioral Psychology Studies (7 papers). Ken N. Seergobin is often cited by papers focused on Parkinson's Disease Mechanisms and Treatments (17 papers), Neurological disorders and treatments (11 papers) and Neural and Behavioral Psychology Studies (7 papers). Ken N. Seergobin collaborates with scholars based in Canada, United States and United Kingdom. Ken N. Seergobin's co-authors include Penny A. MacDonald, Leslie C. Twilley, Robert S. McCann, Derek Besner, Andrew Vo, Hooman Ganjavi, Adrian M. Owen, Alex A. MacDonald, Oury Monchi and Jean-Sébastien Provost and has published in prestigious journals such as Journal of Neuroscience, PLoS ONE and NeuroImage.

In The Last Decade

Ken N. Seergobin

25 papers receiving 666 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ken N. Seergobin Canada 14 417 266 188 101 71 25 701
Marina Papoutsi United Kingdom 14 511 1.2× 250 0.9× 150 0.8× 301 3.0× 98 1.4× 21 861
Ashley Boller United States 18 384 0.9× 325 1.2× 128 0.7× 38 0.4× 45 0.6× 23 789
Doris Eckstein Switzerland 11 555 1.3× 134 0.5× 133 0.7× 47 0.5× 162 2.3× 16 807
Anke Hammer Germany 14 332 0.8× 78 0.3× 140 0.7× 47 0.5× 107 1.5× 20 499
Yamile Bocanegra Colombia 14 383 0.9× 170 0.6× 80 0.4× 57 0.6× 91 1.3× 29 621
Iris Trinkler France 11 337 0.8× 107 0.4× 83 0.4× 131 1.3× 69 1.0× 12 546
Charlotte Jacquemot France 11 474 1.1× 58 0.2× 212 1.1× 69 0.7× 193 2.7× 23 613
Michelle Benjamin United States 10 506 1.2× 163 0.6× 103 0.5× 168 1.7× 33 0.5× 12 804
Alea Khan United States 7 319 0.8× 112 0.4× 93 0.5× 54 0.5× 78 1.1× 7 604
Katherine Field United States 10 351 0.8× 248 0.9× 319 1.7× 297 2.9× 73 1.0× 11 878

Countries citing papers authored by Ken N. Seergobin

Since Specialization
Citations

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

Fields of papers citing papers by Ken N. Seergobin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ken N. Seergobin. 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 Ken N. Seergobin. The network helps show where Ken N. Seergobin may publish in the future.

Co-authorship network of co-authors of Ken N. Seergobin

This figure shows the co-authorship network connecting the top 25 collaborators of Ken N. Seergobin. A scholar is included among the top collaborators of Ken N. Seergobin 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 Ken N. Seergobin. Ken N. Seergobin 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.
Ganjavi, Hooman, Ken N. Seergobin, Manas Sharma, et al.. (2024). Increased mean diffusivity of the caudal motor SNc identifies patients with REM sleep behaviour disorder and Parkinson’s disease. npj Parkinson s Disease. 10(1). 128–128. 1 indexed citations
2.
Hedger, Kathryne Van, et al.. (2023). Establishing the Roles of the Dorsal and Ventral Striatum in Humor Comprehension and Appreciation with fMRI. Journal of Neuroscience. 43(49). 8536–8546. 1 indexed citations
3.
Ganjavi, Hooman, et al.. (2020). Striatum-Mediated Deficits in Stimulus-Response Learning and Decision-Making in OCD. Frontiers in Psychiatry. 11. 13–13. 4 indexed citations
4.
Vo, Andrew, Ken N. Seergobin, & Penny A. MacDonald. (2018). Independent effects of age and levodopa on reversal learning in healthy volunteers. Neurobiology of Aging. 69. 129–139. 14 indexed citations
5.
Robertson, Brian D., Alex A. MacDonald, Ken N. Seergobin, et al.. (2018). SLC6A3 Polymorphism Predisposes to Dopamine Overdose in Parkinson's Disease. Frontiers in Neurology. 9. 693–693. 12 indexed citations
6.
Seergobin, Ken N., et al.. (2018). Dopaminergic Therapy Increases Go Timeouts in the Go/No-Go Task in Patients with Parkinson’s Disease. Frontiers in Human Neuroscience. 11. 642–642. 9 indexed citations
7.
8.
Khan, Ali R., et al.. (2018). Biomarkers of Parkinson's disease: Striatal sub-regional structural morphometry and diffusion MRI. NeuroImage Clinical. 21. 101597–101597. 27 indexed citations
9.
Seergobin, Ken N., et al.. (2017). Automatic Online Motor Control Is Intact in Parkinson’s Disease With and Without Perceptual Awareness. eNeuro. 4(5). ENEURO.0215–17.2017. 5 indexed citations
10.
Owen, Adrian M., et al.. (2017). Dorsal striatum mediates deliberate decision making, not late‐stage, stimulus–response learning. Human Brain Mapping. 38(12). 6133–6156. 7 indexed citations
11.
Vo, Andrew, Ken N. Seergobin, Sarah A. Morrow, & Penny A. MacDonald. (2016). Levodopa impairs probabilistic reversal learning in healthy young adults. Psychopharmacology. 233(14). 2753–2763. 28 indexed citations
12.
Vo, Andrew, Ken N. Seergobin, & Penny A. MacDonald. (2016). Effects of levodopa on stimulus-response learning versus response selection in healthy young adults. Behavioural Brain Research. 317. 553–561. 13 indexed citations
13.
Vo, Andrew, et al.. (2016). Pramipexole Impairs Stimulus-Response Learning in Healthy Young Adults. Frontiers in Neuroscience. 10. 374–374. 19 indexed citations
14.
Robertson, Brian, et al.. (2015). Dorsal striatum mediates cognitive control, not cognitive effort per se , in decision-making: An event-related fMRI study. NeuroImage. 114. 170–184. 47 indexed citations
15.
Vo, Andrew, et al.. (2014). Striatum in stimulus–response learning via feedback and in decision making. NeuroImage. 101. 448–457. 45 indexed citations
16.
Vo, Andrew, et al.. (2014). Dopaminergic medication impairs feedback-based stimulus-response learning but not response selection in Parkinson's disease. Frontiers in Human Neuroscience. 8. 784–784. 19 indexed citations
17.
Seergobin, Ken N., et al.. (2014). Dopaminergic therapy affects learning and impulsivity in Parkinson's disease. Annals of Clinical and Translational Neurology. 1(10). 833–843. 18 indexed citations
18.
MacDonald, Alex A., Ken N. Seergobin, Adrian M. Owen, et al.. (2013). Differential Effects of Parkinson's Disease and Dopamine Replacement on Memory Encoding and Retrieval. PLoS ONE. 8(9). e74044–e74044. 36 indexed citations
19.
MacDonald, Penny A., Alex A. MacDonald, Ken N. Seergobin, et al.. (2011). The effect of dopamine therapy on ventral and dorsal striatum-mediated cognition in Parkinson’s disease: support from functional MRI. Brain. 134(5). 1447–1463. 101 indexed citations
20.
MacDonald, Penny A., Steve Joordens, & Ken N. Seergobin. (1999). Negative priming effects that are bigger than a breadbox: Attention to distractors does not eliminate negative priming, it enhances it. Memory & Cognition. 27(2). 197–207. 41 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Marina Papoutsi Breakdown of academic impact, for papers by Ashley Boller Breakdown of academic impact, for papers by Doris Eckstein Breakdown of academic impact, for papers by Anke Hammer Breakdown of academic impact, for papers by Yamile Bocanegra Breakdown of academic impact, for papers by Iris Trinkler Breakdown of academic impact, for papers by Charlotte Jacquemot Breakdown of academic impact, for papers by Michelle Benjamin Breakdown of academic impact, for papers by Alea Khan Breakdown of academic impact, for papers by Katherine Field
Rankless by CCL
2026