Search Abstracts | Symposia | Slide Sessions | Poster Sessions
Developmental trajectories of audio-visual and tactile-visual learning: a longitudinal fMRI study in children
Poster Session B, Wednesday, September 30, 4:30 - 6:30 pm, Wangari Maathai
This poster is part of the Sandbox Series.
Alice Gilmet1, Carmen Providoli1,2, Sarah V. Di Pietro1, Nina Raduner1,3, Iliana I. Karipidis1, Theresa Dischner1, Maya Schneebeli1, Nora M. Raschle4, Michael von Rhein2, Christian C. Ruff5, Silvia Brem1; 1University Hospital of Psychiatry, University of Zurich, 2University Children's Hospital Zurich, University of Zurich, 3University of Calgary, 4Jacobs Center for Productive Youth Development, University of Zurich, 5University of Zurich
Multisensory learning and integration are crucial for children’s cognitive development, in particular for language acquisition [1,2]. However, the neural mechanisms underlying their maturation in childhood remain poorly understood. To date, most research has examined the development of multisensory learning in childhood by comparing different age groups in cross-sectional designs, which capture only single time points and fail to account for individual developmental trajectories. Moreover, studies mostly focus on audio-visual integration, often neglecting other modalities, including tactile stimuli [3]. In addition to behavioural and neuroimaging methods, computational modelling, for example, reinforcement-learning drift-diffusion models (RL-DDMs), can be used to break down performance into more specific cognitive processes, such as evidence accumulation and feedback-based learning [4]. This ongoing study, therefore, aims to longitudinally track the development of neural processes underlying multisensory learning in children using functional magnetic resonance imaging (fMRI) combined with computational modelling analyses. We investigate within-participant changes in blood-oxygen-level-dependent (BOLD) activation and performance in a multisensory learning task, where children learn audio-visual and tactile-visual associations through feedback [4]. While the baseline measurement is complete (mean age = 7.39 ± 1.34 years), 102 children aged between 7 and 12 years are currently undergoing an fMRI follow-up measurement including the same multisensory learning task, after an approximate 2.5-year interval. On a behavioural level, we hypothesise that children at follow-up will show higher accuracy and faster reaction times than at baseline during the associative learning task, in line with the cross-sectional age effects found by Raduner et al. (2025) [4,5]. Using an RL-DDM, we expect these improvements to be reflected mainly in an increased drift rate, suggesting more efficient processing of multisensory information. On a neural level, we expect within-participant changes to be associated with greater BOLD activation in higher-order multisensory regions during audio-visual learning, in particular in the superior temporal sulcus and cortex, which have been repeatedly linked to audio-visual integration [3,6]. We also expect a greater response of the anterior insula to negative feedback at follow-up [4]. Because tactile-visual development has been less studied so far, our hypotheses for the development of tactile-visual learning are more exploratory, with expected increased activity in parietal and somatosensory regions [7]. The findings of this study will help disentangle age-group differences in multisensory learning from individual learning trajectories. The longitudinal design, with a 2.5-year interval between measurements, combined with a large sample size (N=102), provides the statistical power needed to detect within-participant changes that cross-sectional studies cannot capture. Multisensory learning and integration are fundamental for language development, in particular for linking written symbols, sounds, and meaning. A better understanding of the mechanisms underlying multisensory learning would therefore also contribute to a better understanding of language acquisition and development. [1] Gori (2015). Multisensory Research, 28. [2] Seidl et al. (2024), Developmental Science, 27. [3] Gao et al. (2023), Cerebral Cortex, 33.[4] Raduner et al. (2025), Developmental Cognitive Neuroscience, 76. [5] Alhamdan et al. (2023), Brain Sciences, 13. [6] Murray et al. (2016), Trends in Neuroscience, 39. [7] Tobyne et al. (2025), The Journal of Neuroscience, 45.
Topic Areas: Multisensory or Sensorimotor Integration, Computational Approaches