Publications
PEER-REVIEWED ARTICLES
2024
Zhou, H., van der Ham, S., de Boer, B., Bogaerts, L., & Raviv, L. (in press). Modality and Stimulus Effects on Distributional Statistical Learning: Sound vs. Sight, Time vs. Space. Jounral of Memory and Language. Preprint: 10.31234/osf.io/h9dce
Boeve, S., Zhou, H. & Bogaerts, L. (in press). A meta-analysis of 97 studies reveals that statistical learning and language ability are only weakly correlated. Topics in Cognitive Psychology. Preprint: 10.31234/osf.io/s8mwv
How much evidence is there for the link between statistical learning and language? We conducted a meta-analysis of studies on the relationship between individual's statistical learning and linguistic skills. Results revealed a small but significant overall correlation.
2023
Ivanov, Y., Theeuwes, J. & Bogaerts, L. (2023). Reliability of individual differences in distractor suppression driven by statistical learning. Behavior Research Methods. https://doi.org/10.3758/s13428-023-02157-7
Bogaerts, L., Siegelman, N., & Frost, R. (2023). Statistical learning. In Oxford Research Encyclopedia of Psychology. https://doi.org/10.1093/acrefore/9780190236557.013.907
de Waard, J., van Moorselaar, D., Bogaerts, L., & Theeuwes, J. (2023). Statistical learning of distractor locations is dependent on task context. Scientific reports, 13(1), 11234. https://doi.org/10.1038/s41598-023-38261-z
Li, A., Bogaerts, L., Theeuwes, J. (2023). No evidence for spatial suppression due to across-trial distractor learning in visual search. Attention, Perception, and Psychophysics. https://doi.org/10.3758/s13414-023-02667-8
Li, A., Bogaerts, L., Theeuwes, J. (2022). Statistical learning of across-trial regularities during serial search. Journal of Experimental Psychology: Human Perception and Performance. 48(3), 262–274. DOI: 10.1037/xhp0000987
de Waard, J., Bogaerts, L., van Moorselaar, D., & Theeuwes, J. (2022). Surprisingly inflexible: statistically learned suppression of distractors generalizes across contexts. Attention, Perception, and Psychophysics, 84(2), 459–473. DOI: 10.3758/s13414-021-02387-x
2021
Bogaerts, L., Siegelman, N., Christiansen, M. & Frost, R. (2021). Is there such a thing as a "good statistical learner"? Trends in Cognitive Science. DOI: 10.1016/j.tics.2021.10.012
2022
Theeuwes, J., Bogaerts, L., van Moorselaar, D. (2022). What to expect where and when: how statistical learning drives visual selection. Trends in cognitive sciences. DOI: 10.1016/j.tics.2022.06.001
Elazar, A., Alhama, R., Bogaerts, L., et al. (2022). When the “Tabula” is Anything but “Rasa:” What Determines Performance in the Auditory Statistical Learning Task? Cognitive Science, 46(2). DOI: 10.1111/cogs.13102
Bogaerts, L., van Moorselaar, D., Theeuwes, J. (2022). Does it help to expect distraction? Attentional capture is attenuated by high distractor frequency but not by trial-to-trial predictability. Journal of Experimental Psychology: Human Perception and Performance, 48(3), 246–261. DOI: 10.1037/xhp0000986
In this work on attentional capture by color distractors we found that distractors appearing in predictable sequences do not capture your attention less. We also propose a new experimental approach to control for inter-trial priming.
Bogaerts, L., Siegelman, N., & Frost, R. (2021). Statistical learning and language impairments: Towards more precise theoretical accounts. Perspectives on Psychological science, 16(2), 319-337. DOI: 10.1177/1745691620953082
2020
Bogaerts, L., Richter, C., & Landau, A.N., & Frost, R. (2020). Beta-band activity is a signature of statistical learning. Journal of Neuroscience, 40(39), 7523-7530. DOI: 10.1523/JNEUROSCI.0771-20.2020
In recent years, the importance of rythmic brain activity in cognitive processes has become increasingly evident. In this work we demonstrate that a learning brain sends out more beta waves during transitions between regular statistical patterns.
Rey, A., Bogaerts, L., Franco, A., & Favre, B. (2020). Speech onset latencies as a window of regularity extraction within noise. Quarterly Journal of Experimental Psychology. DOI: 10.1080/17470218.2017.1307432
Bogaerts, L., Frost, R., & Christiansen, M. (2020). Integrating statistical learning into cognitive science. Journal of Memory and Language, 115, 1-5. DOI: 10.1016/j.jml.2020.104167
2019
Siegelman, N., Bogaerts, L., & Frost, R. (2019). What Determines Visual Statistical Learning Performance? Insights from Information Theory. Cognitive Science, 34(12). DOI: 10.1111/cogs.12803
Pavlidou, E., & Bogaerts, L. (2019). Implicit statistical learning across modalities and its relationship with reading in childhood. Frontiers in Psychology. DOI: 10.3389/fpsyg.2019.01834
Siegelman, N., Bogaerts, L., Armstrong, B., & Frost, R. (2019). What exactly is learned in visual statistical learning? Insights from Bayesian modelling. Cognition. DOI: 10.1016/j.cognition.2019.06.014.
Is there a general statistical learning capacity that can sort individuals from ‘bad’ to ‘good’ learners? This opinion paper outlines the suppositions underlying the idea of a general capacity and evaluates the evidence supporting it. It proposes an alternative approach that considers the variability of statistical environments.
What do people learn when we expose them to visual patterns?
Interestingly, it looks like not everyone learns the same thing(s).
Using Bayesian modeling, we show that some individuals learn transitions whereas other learn the entire pattern units.
For the study of individual differences we need reliable measures. Somewhat counterintuitively, tasks that produce robust group findings at the group level are not always good tools to use at the level of the individual.
Smalle, E.H.M., Szmalec, A., Bogaerts, L., Page, M.P.A., Narang, V., Misra, D., Lohagun, N., Khan O., Singh, Mishra, R.K. & Huettig, F. (2019). Stronger verbal short-term serial recall abilities in literate compared to illiterate people. Cognition. DOI: 10.1016/j.cognition.2019.01.012.
2018
Rey, A., Minier, L., Malassis, R., Bogaerts, L. & Fagot, J. (2018). Regularity extraction across species: associative learning mechanisms shared by human and non-human primates. Topics in Cognitive Science. DOI: 10.1111/tops.12343.
Bogaerts, L., Siegelman, N., Benporat, T., & Frost, R. (2018). Is the Hebb repetition task a reliable measure of individual differences in sequence learning? Quarterly Journal of Experimental Psychology, 71(4), 892-905. DOI: 10.1080/17470218.2017.1307432.
Siegelman, N., Bogaerts, L., Elazar, A., Arciuli, J., & Frost, R. (2018). Statistical entrenchment: prior knowledge impacts statistical learning performance. Cognition, 177, 198-213. DOI: 10.1016/j.cognition.2018.04.011.
Hung, Y.H., Frost, S.J., Molfese, P., Malins, J.G., Landi, N.W., Mencl, E., Rueckl, J.G., Bogaerts, L. & Pugh, K.R. (2018). Common neural basis of motor sequence learning and word recognition and its relation with individual differences in reading skill. Scientific Studies of Reading. DOI: 10.1080/10888438.2018.1451533.
2017
Siegelman, N., Bogaerts, L., Kronenfeld, O. & Frost, R. (2017). Re-defining "learning" in statistical learning: what does an online measure reveal about the assimilation of visual regularities? Cognitive Science. DOI: 10.1111/cogs.12556.
2016
Bogaerts, L., Siegelman, N., Frost, R. (2016). Splitting the variance of statistical learning performance: A parametric investigation of exposure duration and transitional probabilities. Psychonomic Bulletin & Review, 23(4), 1250-1256. DOI: 10.3758/s13423-015-0996-z.
Bogaerts, L., Szmalec, A., De Maeyer, M., Page, M. P. A., Duyck, W. (2016). The involvement of long-term serial-order memory in reading development: A longitudinal study. Journal of Experimental Child Psychology,145, 139-156. DOI: 10.1016/j.jecp.2015.12.008
This study followed children from kindergarden to second grade and aimed to predict their reading skills.
The findings highlight the role of serial-order memory in reading ability, even at the onset of reading instruction.
Siegelman, N., Bogaerts, L., Christiansen, M., & Frost, R. (2016). Towards a theory of individual differences in statistical learning. Philosophical Transactions of the Royal Society – Biology, 372, 20160059. DOI: 10.1098/rstb.2016.0059.
Siegelman, N., Bogaerts, L., Frost, R. (2016). Measuring individual differences in statistical learning: Current pitfalls and possible solutions. Behavior Research Methods, 49(2), 418-432. DOI: 10.3758/s13428-016-0719-z.
2015
Bogaerts, L., Szmalec, A., Hachmann, W. M., Page, M. P. A., Duyck, W. (2015). Linking memory and language: Evidence for a serial-order learning impairment in dyslexia. Research in Developmental Disabilities, 43-44,106-22. DOI: 10.1016/j.ridd.2015.06.012.
Smalle, E., Bogaerts, L., Simonis, M., Duyck, W., Page, M.P.A., Edwards, M. & Szmalec, A. (2015). Can chunk size differences explain developmental changes in lexical learning? Frontiers in Psychology, 6, 1925. DOI: 10.3389/fpsyg.2015.01925
2014
Hachmann, W.M., Bogaerts, L., Szmalec, A., Woumans, E. Duyck, W., Job, R. (2014). Short-term memory for order but not for item information is impaired in developmental dyslexia. Annals of Dyslexia, 64(2), 121-136. DOI: 10.1007/s11881-013-0089-5.
Bogaerts, L., Szmalec, A., Hachmann, W.M., Page, M.P.A., Woumans, E., & Duyck, W. (2014). Increased susceptibility to proactive interference in adults with dyslexia? Memory, 23(2), 268-277. DOI: 10.1080/09658211.2014.882957.
2013
Verreyt, N., Bogaerts, L., Cop, U., Bernolet, S., De Letter, M., Hemelsoet, D., Santens, P., & Duyck, W. (2013). Syntactic priming in bilingual patients with parallel and differential aphasia. Aphasiology, 27(7), 867-887. DOI: 10.1080/02687038.2013.791918
PROCEEDING PAPERS & OTHER PUBLICATIONS
Linzen, T., Siegelman, N. & Bogaerts L. (2017). Prediction and uncertainty in an artificial language. Proceedings of the 39th Annual Conference of the Cognitive Science Society. [link]
Bogaerts, L., & Duyck, W. (2013). Dyslexie louter aangeleerd? Een reactie op Erik Moonen. Nederlands Van Nu, 1, 35-37. [link]