Kessels, R. P. C. | bioRxiv Science

bioRxiv2026

The Concise Language Paradigm in left and right hemisphere stroke: a longitudinal source-localized EEG study

The mechanisms underlying language recovery after stroke remain poorly understood. Most previous studies have either focused on language comprehension or production and/or relied on hemodynamic measures, with limited complementary electrophysiological evidence. Here, we combined the Concise Language Paradigm (CLaP), assessing comprehension and production, with individualized electroencephalography (EEG) source reconstruction to investigate post-stroke language function and changes in hemispheric dominance over time. In two sessions, we tested stroke-free controls, individuals with left hemisphere (LH) or right hemisphere (RH) stroke. Participants with stroke were assessed two and seven months post-stroke. EEG data were analyzed using event-related potentials and time-frequency representations, followed by source reconstruction based on state-of-the-art individual MRI-derived forward models. Laterality indices were calculated to assess changes in hemispheric dominance between sessions. Behaviorally, the LH group showed low performance at two months followed by overall improvement, whereas the RH group mainly improved in functional communication. EEG activity was significantly modulated by task condition across comprehension and production contrasts. Source-level results in controls were consistent with established language-related networks, serving as regions of interest for the stroke analyses. In the stroke groups, hemispheric dominance differed between LH and RH stroke participants, with LH participants showing systematic shifts from left- to right-hemisphere dominance between sessions, if not already right-hemisphere dominant at two months. Our study provides evidence on comprehension and production performance after stroke using a single paradigm. These findings demonstrate dynamic changes in hemispheric dominance during post-stroke recovery, ultimately highlighting the value of individualized EEG source reconstruction to investigate post-stroke plasticity.

neuroscience↗

bioRxiv2024

Does early-stage Alzheimer's disease affect the dynamics of motor adaptation?

Alzheimers disease (AD) is characterized by an initial decline in declarative memory, while non-declarative memory processing remains relatively intact. Error-based motor adaptation is traditionally seen as a form of non-declarative memory, but recent findings suggest that it involves both fast, declarative and slow, non-declarative adaptive processes. If the declarative memory system shares resources with the fast process in motor adaptation, it can be hypothesized that the fast, but not the slow, process is disturbed in AD patients. To test this, we studied 20 early-stage AD patients and 21 age-matched controls of both sexes using a reach adaptation paradigm that relies on spontaneous recovery after sequential exposure to opposing force fields. Adaptation was measured using error clamps and expressed as an adaptation index (AI). Although patients with AD showed slightly lower adaptation to the force field than the controls, both groups demonstrated effects of spontaneous recovery. The time course of the AI was fitted by a hierarchical Bayesian two-state model in which each dynamic state is characterized by a retention and learning rate. Compared to controls, the retention rate of the fast process was the only parameter that was significantly different (lower) in the AD patients, confirming that the memory of the declarative, fast process is disturbed by AD. The slow adaptive process was virtually unaffected. Since the slow process learns only weakly from error, our results provide neurocomputational evidence for the clinical practice of errorless learning of everyday tasks in people with dementia.

neuroscience↗