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Language Rule Learning and White Matter Connectivity in Huntington's Disease
Poster Session B, Wednesday, September 30, 4:30 - 6:30 pm, Wangari Maathai
This poster is part of the Sandbox Series.
F. Javed1, A. Razumnov1, R. Knight2, E. Càmara2, J. Sierpowska2,3, R. de Diego-Balaguer2,3; 1University of Groningen, Netherlands, 2Cognition and Brain Plasticity Unit [Bellvitge Biomedical Research Institute – IDIBELL], 3Institute of Neurosciences, University of Barcelona, Spain
Emerging evidence suggests that Huntington’s disease (HD) disrupts large-scale neural systems supporting language, attention, and cognitive control long before severe motor decline. In addition to movement-related symptoms, many individuals with HD experience difficulties with language and other cognitive abilities even in the early stages of the disease. These difficulties are thought to arise from cortico-striatal and fronto-parietal disconnection rather than damage to a single isolated area. One useful way to investigate these mechanisms is through language rule learning, particularly the processing of non-adjacent dependencies (NADs), in which relationships must be identified between linguistic elements separated by intervening material (A–X–C structures). Such dependencies are fundamental to natural language and require the detection of regularities and maintenance of linguistic information during ongoing input. The present study investigates language rule learning in HD using an artificial language paradigm consisting of a learning phase, an online word-monitoring task, and an offline grammaticality judgment task. During the online task, participants respond to rule-consistent and non-rule phrases while reaction times provide an index of facilitation during continuous processing. In the offline phase, participants judge whether phrases conform to the learned language structure, requiring controlled evaluation and maintenance of learned dependencies. Behavioral data have already been collected from healthy controls, premanifest HD gene carriers, and early-stage manifest HD participants. Preliminary observations suggest relatively preserved facilitation during online processing alongside reduced offline discrimination performance in HD. This pattern raises the possibility that processing during continuous input may remain comparatively preserved, whereas tasks requiring greater attentional control and working memory resources may be more vulnerable to disease-related network disruption. To investigate the neural basis of these differences, ongoing work focuses on diffusion MRI tractography of white matter pathways associated with attentional control, working memory, and language processing. Current analyses involve extraction of the Superior Longitudinal Fasciculus (SLF I, II, and III), all segments of the arcuate fasciculus, and exploratory fronto-striatal pathways using the XTRACT pipeline within FSL. SLF I and SLF II are of particular interest because of their involvement in fronto-parietal attentional control systems, whereas the arcuate fasciculus may contribute to phonological working memory and maintenance of linguistic information during rule evaluation. Fractional anisotropy, mean diffusivity, radial diffusivity, and tract volume measures are currently being extracted and will be related to behavioral performance. We hypothesize that reduced integrity in fronto-parietal attention pathways and language-related working memory pathways will be associated more strongly with offline dependency evaluation than with facilitation during online processing. As tract extraction and quantitative analyses are ongoing, this project is presented as work in progress within the Sandbox Series. Ultimately, this study aims to better understand how brain connectivity supports language rule learning in people with Huntington’s disease.
Topic Areas: Control, Selection, and Executive Processes,