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Affective Modulation of Morphosyntactic Processing: An EEG Study of Mood Effects on Subject-Verb Agreement Violations
Poster Session D, Thursday, October 1, 4:30 - 6:30 pm, Wangari Maathai
This poster is part of the Sandbox Series.
Ekaterina Kopaeva1, Eva Klingvall1, Fredrik Heinat1; 1Lund University
Affective states have been shown to influence attention, cognitive control, and working memory, yet their contribution to the neurobiology of syntactic processing remains incompletely understood. Event-related potential (ERP) studies of morphosyntactic agreement violations consistently report a left anterior negativity (LAN) and a centroparietal positivity (P600), but previous investigations of mood effects on these components have yielded mixed findings. Prior work suggesting reduced or absent P600 responses under negative mood induction has been limited by methodological variability, including differences in sentence complexity, variable subject-verb distances, and the absence of a neutral comparison condition. In this ongoing study, we tightly control for these factors, allowing affective influences on the temporal dynamics of LAN and P600 responses to be isolated more precisely than in previous research. Native English speakers complete a rapid serial visual presentation sentence-reading task while EEG is recorded from 64 scalp electrodes. Sentences contain either correct subject-verb agreement or agreement violations under positive, negative, and neutral induced mood conditions. Mood induction is implemented in blocks using standardised affective stimuli and validated with self-report measures. The design controls the linear distance between agreement trigger and target, minimising confounds associated with memory load and syntactic complexity. ERP analyses focus on LAN (250-500 ms) and P600 (500-900 ms) responses, including temporally fine-grained analyses to evaluate potential mood-related shifts in component onset and scalp distribution. Linear mixed-effects models assess interactions between mood and grammaticality on ERP amplitudes. We expect to find robust LAN and P600 effects in neutral mood. Positive mood is predicted to enhance or prolong the P600 response, whereas negative mood is expected to attenuate or delay it. Within predictive accounts of affect (Barrett, 2017; Clark et al., 2018; Kiverstein et al., 2020; Kube et al., 2020; Seth, 2013), such effects may reflect mood-dependent changes in the precision-weighting of prediction errors during online information processing. Positive affective states may promote a broader range of inputs being treated as reliable and model-congruent, increasing sensitivity to agreement violations and engagement in model updating processes indexed by the P600. Negative affective states, by contrast, may narrow the scope of precision-weighted input, which biases processing toward volatility-consistent information and reduces the extent to which syntactic anomalies trigger reanalysis or updating. Mood-related modulation of LAN, if observed, would suggest that affective states influence early predictive morphosyntactic computations rather than only later model revision processes. Alternatively, mood effects restricted to the P600 would support accounts in which affect primarily modulates later stages of prediction-error updating and syntactic reanalysis. By integrating controlled mood induction with a well-established agreement violation paradigm and high-density EEG, this study aims to clarify how affective states interact with the neural architecture of language comprehension. Relying on predictive models of affect, it advances current neurolinguistic models by positioning mood not as a peripheral background factor, but as a systematic modulator of the neural dynamics underlying language processing.
Topic Areas: Syntax and Combinatorial Semantics, Control, Selection, and Executive Processes