Candidates are highly recommended to write a proposal that fits into one of the following research lines and are recommended to contact the relevant supervisors when developing proposals. Other projects may be developed but the potential supervisors at the partner universities MUST be contacted prior to application.
When writing your research proposal, please use the structure provided in this proposal template.
The list of projects may be updated throughout the application period.
Online measurement of statistical learning in auditory word segmentation in children with Developmental Language Disorder
Supervisory team:
Dr Vânia de Aguiar (University of Groningen, vania.de.aguiar@rug.nl)
Prof Natalie Boll-Avetisyan (University of Potsdam, nboll@uni-potsdam.de)
A/Prof Dr Lisi Beyersmann (Macquarie University, lisi.beyersmann@mq.edu.au)
Learning to segment words from a continuous speech stream is a challenge that typically developing children solve early in life. One of the mechanisms through which they do this, is through tracking of statistical co-occurrences between syllables, meaning, their transitional probabilities. This form of statistical learning has also been studied in children who struggle to develop language, namely those with Developmental Language Disorder (for a review, see Lammertink et al., 2017). The literature shows inconsistent findings concerning whether statistical learning is impaired in children with DLD. It has been proposed that statistical learning can be separated into two stages: perceptual binding (during/online learning) and memory consolidation (storage) (Batterink & Paller, 2019). It was also suggested that perceptual binding, the online learning phase, may be impaired in children with DLD (Lammertink et al., 2019). However, as of yet, there is only limited evidence for this proposal, as usually, statistical learning experiments are designed for measuring learning after it happened (using post-learning, offline measures such as alternative forced choice paradigms), failing to capture learning while it happens (e.g., via online measures of this perceptual binding stage). This project aims to develop behavioral online measures of statistical word segmentation from continuous speech, study them in relation to neural measures of online learning (potentially eye tracking), and test whether children with DLD show impairment in the online learning processes. The student will be based at Groningen University combined with either Macquarie University or Potsdam University – applicants should be willing to accept either mobility option. Supervision will be, in any case, provided by all three partners, by the team listed above.
Lammertink, I., Boersma, P., Wijnen, F., & Rispens, J. (2017). Statistical Learning in Specific Language Impairment: A Meta-Analysis. Journal of speech, language, and hearing research: JSLHR, 60(12), 3474–3486. https://doi.org/10.1044/2017_JSLHR-L-16-0439
Batterink, L. J., & Paller, K. A. (2017). Online neural monitoring of statistical learning. Cortex, 90, 31-45. https://doi.org/10.1016/j.cortex.2017.02.004
Behavioral and network analyses of morphology during picture description in aphasia
Supervisory team:
A/Prof Adrià Rofes (Groningen University, a.rofes@rug.nl)
A/Prof Dr Lisi Beyersmann (Macquarie University, lisi.beyersmann@mq.edu.au)
People with aphasia after stroke can be impaired producing and comprehending word-level morphology (i.e. compounding and derivation) and/or in morpho-syntax (i.e. inflection, Badecker & Caramazza, 2017). Morphological processes have been recently studied with newer tasks, including word association and verbal fluency (Rofes et al., 2026; van der Sluijs et al., subm.). Such approaches have considered behavioral and network analyses, the latter being a promising tool to obtain further information regarding the types of morphological processes that may be affected, beyond other measures such as accuracy (van der Sluijs et al., subm.).
In this project, we propose picture description as a new approach to assess morphology in people with post-stroke aphasia. Measures that can be extracted from picture description relate to formal tasks, such as object naming and sentence completion (Rofes et al., 2018). Yet, the study of specific morphological processes tends to be overlooked during picture description. One of the reasons for this gap in the literature is that the picture tasks we currently administer are typically suited to assess lexical retrieval rather than to differentiate specific morphological processes.
The goal of the PhD candidate will be then to create a new picture description task to assess the production of specific morphological processes in people with post-stroke aphasia. The data of people with post-stroke aphasia and a sample of age-and-education matched healthy controls will be analyzed with quantitative measures of picture description (e.g., mean length of utterance, type token ratio, number of inflected words) as well as network metrics (e.g., diameter, average shortest path length). Comparisons between the two groups [on the new task, but also on other regularly used (picture description) tasks] will be drawn and discussed, given the current literature.
We welcome students with different cultural and linguistic backgrounds. However, priority may be given to speakers or Dutch and/or German, provided that we are able to recruit speakers with aphasia. Applications from researchers speaking other languages are of course more than welcome, particularly if they (or we) may be able to recruitment of people with aphasia due to stroke.
References:
Badecker, W., & Caramazza, A. (2017). Morphology and aphasia. In A. Spencer & A.M. Zwicky (Eds), The Handbook of Morphology (1st edn, pp. 390–405). Wiley. doi: 10.1002/9781405166348.ch20
Rofes, A., Beyersmann, E., Rossetto, A., & Castro, N. (2026). Limited evidence ofmorphology in semantic and phonological free association tasks. Language andCognition, 18, Article e15. doi: 10.1017/langcog.2026.10065
Rofes, A., Talacchi, A., Santini, B., Pinna, G., Nickels, L., Bastiaanse, R., & Miceli, G. (2018). Language in individuals with left hemisphere tumors: Is spontaneous speech analysis comparable to formal testing? Journal of Clinical and Experimental Neuropsychology, 40(7), 722-732. doi:10.1080/13803395.2018.1426734
van der Sluijs, J.-A. H., Beyersmann, E., Jonkers, R., & Rofes, A. (submitted). Morphological word families in the mental lexicon: A new verbal fluency task.
Assessing individual differences in infants’ speech perception with a toy
Supervisory team:
Prof Natalie Boll-Avetisyan (University of Potsdam, nboll@uni-potsdam.de)
A/Prof Dr Lisi Beyersmann (Macquarie University, lisi.beyersmann@mq.edu.au)
Numerous studies in language acquisition have shown that infants’ perception of phonemes and prosody, as well as their ability to segment continuous speech into words, predict later language development (for a meta-analysis, see Cristia et al., 2014). However, most experimental methods used in infant language research are designed to detect speech perception abilities at the group level and are therefore not well suited for studying individual differences. In addition, these methods typically require laboratory testing, which often results in samples biased toward infants from urban and highly educated backgrounds. In this project, we will employ a newly developed toy-based method (Boll-Avetisyan, 2022) that allows the study of infants’ speech perception directly in their homes. The project aims to further advance this mobile testing procedure and evaluate its potential to capture individual differences in early speech perception more effectively than current laboratory-based methods. Good knowledge of German is a prerequisite for this project.
Boll-Avetisyan, N. (2022). System zur Früherkennung von Sprachentwicklungsstörung und Verfahren zum Erfassen von Daten zur Präferenz eines Hörerlebnisses bei Säuglingen und Kleinkindern (10 2020 124 842). Deutsches Patent- und Markenamt. https://register.dpma.de/DPMAregister/pat/register?AKZ=1020201248423
Cristia, A., Seidl, A., Junge, C., Soderstrom, M., & Hagoort, P. (2014). Predicting individual variation in language from infant speech perception measures. Child Dev, 85(4), 1330-1345.
Early cognitive markers of infant morphology
Supervisory team:
Prof Natalie Boll-Avetisyan (University of Potsdam, nboll@uni-potsdam.de)
A/Prof Dr Lisi Beyersmann (Macquarie University, lisi.beyersmann@mq.edu.au)
This project investigates how infants process and represent morphologically complex words during spoken word recognition. Although segmentation studies show that babies can break complex words into their morphemic parts (Kim & Sundara, 2021; Liang & Sundara, 2025), much less is known about how these forms are stored and organised in the developing mental lexicon. Understanding this early morphological processing is crucial, as it provides foundational insight into how children build their vocabularies, learn grammatical structure, and ultimately develop efficient reading and language comprehension skills. This work also has broader implications for identifying early markers of language delay and informing theory-driven interventions. The project will explore these questions using infant priming paradigms using word priming paradigms (Arias-Trejo & Plunkett, 2009; Mani & Plunkett, 2011), were babies will hear pairs of morphologically related prime-target words (e.g., cat – cats), semantically related prime-target words (e.g., cat – dog) and phonologically related prime-target words (e.g. cat – hat), while their eye movements are recorded with eye-tracking. The student will have scope to shape the specific research questions, methods, and experimental designs within this broad framework.
App-based verbal treatment in aphasia
Supervisory team:
Dr Dörte de Kok (University of Groningen, d.a.de.kok@rug.nl)
Dr Vânia de Aguiar (University of Groningen, vania.de.aguiar@rug.nl)
A/Prof Dr Lisi Beyersmann (Macquarie University, lisi.beyersmann@mq.edu.au)
In a previous project, Pauline Cuperus developed an app to treat verb- and sentence production deficits in aphasia (Cuperus, 2023; https://doi.org/10.33612/diss.769923247). We invite a project that builds further on this tool studying the efficacy of the treatment. Project proposals should therefore include a (case-series) efficacy study, investigating the treatment effects by comparing various pre- and postmeasures. A second research chapter should focus on the in-app data on e.g. cue-usage, time spent per item and accuracy development across sessions in relation to the outcomes of the treatment. The project should be completed with a third research study that could take several directions. We welcome proposals using online tasks taking a closer look at language processing in order to understand what drives potential improvement during treatment. The focus could be on morphological or sentence level, lexical retrieval or argument structure. Another option would be to study lesion symptom mapping by extending the baseline tasks and analyzing structural MRI data in relation to those tasks. A third option would be to focus on the narrative speech that is collected before and after treatment and investigate this not only with traditional measures, but also with computational (i.e., NLP) measures and analyzing changes in these measures due to treatment. While the two chapters described above are essential to the project, there is room for defining this third research study more freely. We’re open to other suggestions than those stated here, as long as they fit into the overall context of the project.