Chair and department head

Jan Theeuwes

Chair and department head

Phone: +31 (0) 20 598 8790
Room: 1E-11


In 2012 I received an ERC advanced grant `What you get is what you see: How Reward Determines Perception’. In this project I investigated the effects of reward on attentional selection. In 2019, I received a second ERC advanced grant titled “What to expect when you are not expecting it: How implicit regularities drive attentional selection”. In this project I will investigate how we learn to extract statistical regularities from the environment and how this affects attentional selection. Extracting statistical regularities from the environment is one of the most fundamental abilities of any living organism. This type of learning is largely unconscious, unintentional, and implicit that runs "in the background", both seeking and giving structure to the world around us, making it coherent, predictable and quickly manageable. During the coming years I will examine on how, when and what is learned, how learning affects attentional selection, and how flexible learning is in a changing environment.


After obtaining a BSc in Mechanical Engineering (1981), I studied Psychology at Tilburg University receiving a BSc and MSc in Experimental Psychology (1987) with the highest honour (cum laude). In 1992 I received a PhD from the Vrije Universiteit (advisor A.F. Sanders) with the highest honor. I worked from 1988 until 1999 at the TNO Human Factors Institute in Soesterberg conducting applied research for governments, car companies (BMW, Caterpillar Volvo) and the EU. In 1999 I was appointed full professor at the VU. I have published more than 250 peer-reviewed papers. In 2010 I was elected into the Royal Dutch Academy of Science (KNAW). In 2001 I was awarded the first Bertelson Award in recognition of outstanding psychological research from the European Society for Cognitive Psychology. I was the president of ESCOP from 2016 to 2018. I am one of the principal advisors of the Dutch Department of Transportation (Rijkswaterstaat) regarding road design and signing. Last year, with two former PhD students I started a new company named Attention Architects, which focuses on eye tracking in applied settings

Research interests

My main interest is to acquire fundamental knowledge on a wide array of subjects including perception, attention, memory and emotion using a wide range of methods, including behavioral (RT measurement), eye tracking, functional MRI, psychophysiological recordings (e.g., ERP), patient work and modeling. I published papers on attentional and oculomotor capture, working memory, multimodal integration, remapping, face perception, visual search, emotion, unconscious processing, the attentional blink, reward processing as well as several applied papers involving road design and headlamp glare. In 2012 I published a book Designing Safe Road Systems (


Curriculum Vitae
Google Scholar

Recent publications

P Watson, D Pearson, J Theeuwes, SB Most & ME Le Pelley (2020) Delayed disengagement of attention from distractors signalling reward. Cognition 195, 104125
Y Gao & J Theeuwes (2019) Learning to suppress a distractor is not affected by working memory load. Psychonomic Bulletin & Review, 1-91
E Van der Burg, J Cass & J Theeuwes (2019) Changes (but not differences) in motion direction fail to capture attention. Vision research 165, 54-63
B Wang, J Theeuwes & CNL Olivers (2019) Momentary, Offset-Triggered Dual-Task Interference in Visual Working Memory. Journal of Cognition 2 (1)
P Watson, D Pearson, M Chow, J Theeuwes, RW Wiers, SB Most & ... (2019) Capture and Control: Working Memory Modulates Attentional Capture by Reward-Related Stimuli. Psychological science 30 (8), 1174-11851
B Wang, J van Driel, E Ort & J Theeuwes (2019) Anticipatory distractor suppression elicited by statistical regularities in visual search. Journal of cognitive neuroscience, 1-144
V Di Caro, J Theeuwes & C Della Libera (2019) Suppression history of distractor location biases attentional and oculomotor control. Visual Cognition, 1-16
PJ Boon, J Theeuwes & AV Belopolsky (2019) Updating spatial working memory in a dynamic visual environment. Cortex1
JC Van Slooten, S Jahfari, T Knapen & J Theeuwes (2019) How pupil responses track value-based decision-making during and after reinforcement learning (vol 14, e1006632, 2018).. PLOS COMPUTATIONAL BIOLOGY 15 (5)
B Wang, I Samara & J Theeuwes (2019) Statistical regularities bias overt attention. Attention, Perception, & Psychophysics, 1-91
M Failing, T Feldmann-Wustefeld, B Wang, O Christian & J Theeuwes (2019) Statistical regularities induce spatial as well as feature-specific suppression. Journal of experimental psychology: human perception and performance5
M Failing, B Wang & J Theeuwes (2019) Spatial suppression due to statistical regularities is driven by distractor suppression not by target activation. Attention, Perception, & Psychophysics, 1-106
D van Moorselaar, J Theeuwes & CNL Olivers (2019) Memory-based attentional biases survive spatial suppression driven by selection history. Visual Cognition, 1-8
J Heeman, S Van der Stigchel, DP Munoz & J Theeuwes (2019) Discriminating between anticipatory and visually triggered saccades: Measuring minimal visual saccadic response time using luminance. Journal of neurophysiology 121 (6), 2101-2111
J Theeuwes (2019) Goal-Driven, Stimulus-Driven and History-Driven selection. Current opinion in psychology9
J Theeuwes (2019) Goal-Driven, Stimulus-Driven and History-Driven selection. Current Opinion in Psychology9
J Munneke, JJ Fahrenfort, D Sutterer, J Theeuwes & E Awh (2019) Multivariate analysis of EEG activity indexes contingent and non-contingent attentional capture. bioRxiv, 734004
S Jahfari, J Theeuwes & T Knapen (2019) Learning in visual regions as support for the bias in future value-driven choice. bioRxiv, 5233401
DM van Es, J Theeuwes & T Knapen (2018) Spatial sampling in human visual cortex is modulated by both spatial and feature-based attention. eLife 7, e369285
JC Van Slooten, S Jahfari, T Knapen & J Theeuwes (2018) How pupil responses track value-based decision-making during and after reinforcement learning. PLoS computational biology 14 (11), e10066328

View full list of publications on Google Scholar