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Using gender cues to predict upcoming nouns: A comparison between younger and older adults

Gianna Urbanczik1,2,3, Leonie F. Lampe1,3, Seçkin Arslan4, Lyndsey Nickels3 & Sandra Hanne1

1Cognitive Sciences, Department of Linguistics, University of Potsdam, Potsdam, Germany, 2International Doctorate for Experimental Approaches to Language and Brain (IDEALAB), Universities of Groningen (NL), Potsdam (DE), Newcastle (UK), and Macquarie University (AU), 3School of Psychological Sciences, Macquarie University, Sydney, Australia, 4Université Côte d’Azur, CNRS, BCL, France

Keywords: possessive processing, visual world eye-tracking, prediction, gender agreement, ageing

Effects of predictive processing, that is the pre-activation of linguistic information before it is encountered, tend to decrease with age (e.g., Federmeier & Kutas, 2019; Haeuser et al., 2022; Jongman et al., 2022). However, the picture is not as clear when it comes to the use of gender marking to predict an upcoming noun. For example, Huettig and Janse (2016) investigated online processing of sentences with Dutch gender-marked definite articles in a visual world eye-tracking experiment. Contrary to other literature, they found a weak effect whereby predictive effects were stronger with age. We aimed to extend these findings to further investigate the role of age in predictive processing using gender cues. To this end, we investigated gender-marked possessive determiners in German (e.g., ihreFEM SeifeFEM ‘her soap’), following Stone et al.’s (2021) research with younger adults.

We are currently collecting data from 30 younger (18 to 40 years of age) and 30 older (60+ years of age) German-speaking adults. Using a 2x2 visual world eye-tracking design and an accompanying sentence-picture matching task we measure both on-line and off-line processing of possessive determiners.

We will analyse predictive effects based on participants’ fixations of the target picture and carry out group comparisons between younger and older adults. Specifically, we will run time-window analyses and generalised additive mixed models (GAMMs; Porretta et al., 2018) to analyse the time-course of processing within groups and interactions between groups. Results will be presented at the conference.

  • Federmeier, K. D., & Kutas, M. (2019). What's "left"? Hemispheric sensitivity to predictability and congruity during sentence reading by older adults. Neuropsychologia, 133, Article 107173.
  • Haeuser, K. I., Kray, J., & Borovsky, A. (2022). Hedging bets in linguistic prediction: Younger and older adults vary in the breadth of predictive processing. Collabra: Psychology, 8(1), Article 36945.
  • Huettig, F., & Janse, E. (2016). Individual differences in working memory and processing speed predict anticipatory spoken language processing in the visual world. Language, Cognition and Neuroscience, 31(1), 80–93.
  • Jongman, S. R., Copeland, A., Xu, Y., Payne, B. R., & Federmeier, K. D. (2022). Older adults show intraindividual variation in the use of predictive processing. Experimental Aging Research.
  • Porretta, V., Kyröläinen, A.-J., van Rij, J., & Järvikivi, J. (2018). Visual world paradigm data: From preprocessing to nonlinear time-course analysis. In I. Czarnowski, R. J. Howlett, & L. C. Jain (Eds.), Smart Innovation, Systems and Technologies: Vol. 73. Intelligent Decision Technologies 2017 (pp. 268–277). Springer International Publishing.
  • Stone, K., Veríssimo, J., Schad, D. J., Oltrogge, E., Vasishth, S., & Lago, S. (2021). The interaction of grammatically distinct agreement dependencies in predictive processing. Language, Cognition and Neuroscience, 36(9), 1159–1179.