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Lasnick, O. H. M.

Publications and source records attributed to Lasnick, O. H. M..

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Bayesian analysis of resting-state temporal low-γ power in children with phonemic decoding deficits and certain comorbidities

Dyslexia (decoding-based reading disorder, or RD) is a common learning disorder affecting a large proportion of the population. One theory of the origins of reading deficits is a language network which cannot effectively entrain to speech, with cascading effects on the development of phonological skills. Low-gamma (low-{gamma}, 30-45 Hz) neural activity is thought to correspond to tracking at phonemic rates in speech. The main goals of the current study were to investigate temporal low-{gamma} band-power during rest in a sample of children and adolescents with and without RD. We used a Bayesian statistical approach, which has become increasingly popular in the field for its ability to quantify the relative likelihood of competing hypotheses. We examined whether (1) resting-state temporal low-{gamma} power was attenuated in the left temporal region in those with RD; (2) low-{gamma} power covaried with individual performance in reading skills; (3) low-{gamma} temporal lateralization was atypical in the group with RD. Results did not support the hypothesized effects of RD status and poor phonemic decoding ability on left hemisphere low-{gamma} power or lateralization: post-hoc tests revealed that the lack of atypicality in the RD group was not due to the inclusion of those with comorbid attentional deficits. However, post-hoc tests also revealed a specific left-dominance for low-{gamma} rhythms in the RDs only when participants with attentional deficits were excluded. We also observed an inverse relationship between phonemic decoding and left-lateralization in the controls, such that those with better decoding skills were less likely to show left-lateralization, contrary to our expectations. We discuss these unexpected findings in the context of prior theoretical frameworks on temporal sampling, and suggest that our null findings in resting-state EEG may reflect the importance of real-time language processing to evoke gamma rhythms in the phonemic range during childhood and adolescence.

neuroscience↗