Lee Jollans

924 total citations
17 papers, 417 citations indexed

About

Lee Jollans is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Psychiatry and Mental health. According to data from OpenAlex, Lee Jollans has authored 17 papers receiving a total of 417 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cognitive Neuroscience, 5 papers in Experimental and Cognitive Psychology and 4 papers in Psychiatry and Mental health. Recurrent topics in Lee Jollans's work include Functional Brain Connectivity Studies (8 papers), Neural and Behavioral Psychology Studies (5 papers) and EEG and Brain-Computer Interfaces (4 papers). Lee Jollans is often cited by papers focused on Functional Brain Connectivity Studies (8 papers), Neural and Behavioral Psychology Studies (5 papers) and EEG and Brain-Computer Interfaces (4 papers). Lee Jollans collaborates with scholars based in Ireland, United States and Canada. Lee Jollans's co-authors include Robert Whelan, Rory Boyle, Hugh Garavan, Antoine Grigis, Michael N. Smolka, Jean‐Luc Martinot, Tomáš Paus, Henrik Walter, Éric Artiges and Laura M. Rueda‐Delgado and has published in prestigious journals such as NeuroImage, Addiction and Behavioural Brain Research.

In The Last Decade

Lee Jollans

17 papers receiving 415 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lee Jollans Ireland 11 229 82 65 58 37 17 417
Tehila Eilam‐Stock United States 8 286 1.2× 89 1.1× 34 0.5× 43 0.7× 55 1.5× 12 468
Tim Hahn Germany 13 242 1.1× 101 1.2× 101 1.6× 81 1.4× 54 1.5× 35 520
Tor Ivar Hansen Norway 9 191 0.8× 119 1.5× 50 0.8× 78 1.3× 20 0.5× 19 420
Daniel A. Rinker United States 8 202 0.9× 75 0.9× 58 0.9× 109 1.9× 31 0.8× 9 376
Filippo Cieri Italy 11 304 1.3× 134 1.6× 70 1.1× 72 1.2× 62 1.7× 23 451
Dani Beck Norway 15 232 1.0× 74 0.9× 40 0.6× 221 3.8× 38 1.0× 42 602
Ádám Szabó Hungary 12 204 0.9× 153 1.9× 56 0.9× 63 1.1× 36 1.0× 28 515
Seyed Amir Hossein Batouli Iran 13 252 1.1× 91 1.1× 46 0.7× 109 1.9× 28 0.8× 59 493
Yukiko Honda Japan 12 258 1.1× 57 0.7× 52 0.8× 33 0.6× 41 1.1× 45 437
Clara Alloza United Kingdom 9 336 1.5× 110 1.3× 106 1.6× 191 3.3× 46 1.2× 9 609

Countries citing papers authored by Lee Jollans

Since Specialization
Citations

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

Fields of papers citing papers by Lee Jollans

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lee Jollans

This figure shows the co-authorship network connecting the top 25 collaborators of Lee Jollans. A scholar is included among the top collaborators of Lee Jollans 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 Lee Jollans. Lee Jollans 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.
2.
Kenney, Joanne, Laura M. Rueda‐Delgado, Lee Jollans, et al.. (2022). Neuroanatomical markers of psychotic experiences in adolescents: A machine-learning approach in a longitudinal population-based sample. NeuroImage Clinical. 34. 102983–102983. 1 indexed citations
3.
Tzovara, Athina, Valentina Borghesani, M. Mallar Chakravarty, et al.. (2021). Embracing diversity and inclusivity in an academic setting: Insights from the Organization for Human Brain Mapping. NeuroImage. 229. 117742–117742. 30 indexed citations
4.
Boyle, Rory, Lee Jollans, Laura M. Rueda‐Delgado, et al.. (2020). Brain-predicted age difference score is related to specific cognitive functions: a multi-site replication analysis. Brain Imaging and Behavior. 15(1). 327–345. 64 indexed citations
5.
Brückl, Tanja, Victor I. Spoormaker, Philipp G. Sämann, et al.. (2020). The biological classification of mental disorders (BeCOME) study: a protocol for an observational deep-phenotyping study for the identification of biological subtypes. BMC Psychiatry. 20(1). 213–213. 30 indexed citations
6.
Jollans, Lee, Rory Boyle, Éric Artiges, et al.. (2019). Quantifying performance of machine learning methods for neuroimaging data. NeuroImage. 199. 351–365. 108 indexed citations
7.
Rueda‐Delgado, Laura M., Kathy Ruddy, Hanni Kiiski, et al.. (2019). Brain event-related potentials predict individual differences in inhibitory control. International Journal of Psychophysiology. 163. 22–34. 17 indexed citations
8.
Rueda‐Delgado, Laura M., Lee Jollans, Zhipeng Cao, et al.. (2019). Inhibitory‐control event‐related potentials correlate with individual differences in alcohol use. Addiction Biology. 25(2). e12729–e12729. 8 indexed citations
9.
Jollans, Lee & Robert Whelan. (2018). Neuromarkers for Mental Disorders: Harnessing Population Neuroscience. Frontiers in Psychiatry. 9. 242–242. 36 indexed citations
10.
Jollans, Lee, et al.. (2018). Individual differences in learning from probabilistic reward and punishment predicts smoking status. Addictive Behaviors. 88. 73–76. 6 indexed citations
11.
Kiiski, Hanni, Lee Jollans, Hugh Nolan, et al.. (2018). Machine Learning EEG to Predict Cognitive Functioning and Processing Speed Over a 2-Year Period in Multiple Sclerosis Patients and Controls. Brain Topography. 31(3). 346–363. 29 indexed citations
12.
Jollans, Lee, et al.. (2018). A Combination of Impulsivity Subdomains Predict Alcohol Intoxication Frequency. Alcoholism Clinical and Experimental Research. 42(8). 1530–1540. 13 indexed citations
13.
Jollans, Lee & Robert Whelan. (2017). Predicting adolescent smoking using fMRI – a possible predisposing role for inhibitory control and reward processing in addictive behaviours. European Neuropsychopharmacology. 27. S1079–S1080. 1 indexed citations
14.
Jollans, Lee & Robert Whelan. (2016). The Clinical Added Value of Imaging: A Perspective From Outcome Prediction. Biological Psychiatry Cognitive Neuroscience and Neuroimaging. 1(5). 423–432. 29 indexed citations
15.
Jollans, Lee, Robert Whelan, Louise Venables, et al.. (2016). Computational EEG modelling of decision making under ambiguity reveals spatio-temporal dynamics of outcome evaluation. Behavioural Brain Research. 321. 28–35. 13 indexed citations
16.
Nymberg, Charlotte, et al.. (2016). The potential of neuroimaging for identifying predictors of adolescent alcohol use initiation and misuse. Addiction. 112(4). 719–726. 23 indexed citations
17.
Briggs, Zoe, et al.. (2015). Flexible emotion-based decision-making behavior varies in current and former smokers. Addictive Behaviors. 45. 269–275. 8 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 Tehila Eilam‐Stock Breakdown of academic impact, for papers by Tim Hahn Breakdown of academic impact, for papers by Tor Ivar Hansen Breakdown of academic impact, for papers by Daniel A. Rinker Breakdown of academic impact, for papers by Filippo Cieri Breakdown of academic impact, for papers by Dani Beck Breakdown of academic impact, for papers by Ádám Szabó Breakdown of academic impact, for papers by Seyed Amir Hossein Batouli Breakdown of academic impact, for papers by Yukiko Honda Breakdown of academic impact, for papers by Clara Alloza
Rankless by CCL
2026