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Mandke, K.

Publications and source records attributed to Mandke, K..

4 recordsLinked to original sources

Musicians' brains at rest: Multilayer network analysis of MEG data

The ability to proficiently play a musical instrument requires a fine-grained synchronisation between several sensorimotor and cognitive brain regions. Previous studies have demonstrated that the brain undergoes functional changes with musical training, identifiable also in resting-state data. These studies analysed fMRI or electrophysiological frequency-specific brain networks in isolation. While the analysis of such "mono-layer" networks has proven useful, it fails to capture the complexities of multiple interacting networks. To this end, we applied a multilayer network framework for analysing publicly available data (Open MEG Archive) obtained with magnetoencephalography (MEG). We investigated resting-state differences between participants with musical training (n=31) and those without (n=31). While single-layer analysis did not demonstrate any group differences, multilayer analysis revealed that musicians show a modular organisation that spans visuomotor and frontotemporal areas, known to be involved in musical performance execution, which is significantly different from non-musicians. Differences between the two groups are primarily observed in the theta (6.5-8Hz), alpha1 (8.5-10Hz) and beta1 (12.5-16Hz) frequency bands. We demonstrate that the multilayer method provides additional information that single-layer analysis cannot. Overall, the multilayer network method provides a unique opportunity to explore the pan-spectral nature of oscillatory networks, with studies of brain plasticity as a potential future application.

neuroscience↗

Atypical beta-band effects in children with dyslexia in response to rhythmic audio-visual speech

Children with dyslexia are known to show impairments in perceiving speech rhythm, which impact their phonological development. Neural rhythmic speech studies have reported atypical delta phase in children with dyslexia, but beta band effects have not yet been studied. It is known that delta phase modulates the amplitude of the beta band response during rhythmic tasks via delta-beta phase-amplitude coupling (PAC). Accordingly, the atypical delta band effects reported for children with dyslexia may imply related atypical beta band effects. Here we analyse EEG data collected during a rhythmic speech paradigm from 51 children (21 typically-developing; 30 with dyslexia) who attended to a talking head repeating "ba" at 2Hz. Phase entrainment in the beta band, angular velocity in the beta band, power responses in the beta band and delta-beta PAC were assessed for each child and each group. Phase entrainment in the beta band was only significant for children without dyslexia. Children with dyslexia did not exhibit any phase consistency, and beta-band angular velocity was significantly faster compared to control children. Power in the beta band was significantly greater in the children with dyslexia. Delta-beta PAC was significant in both groups. The data are interpreted with respect to temporal sampling theory.

neuroscience↗

Atypical cortical encoding of speech identifies children with Dyslexia versus Developmental Language Disorder

Slow cortical oscillations play a crucial role in processing the speech envelope, which is perceived atypically by children with Developmental Language Disorder (DLD) and developmental dyslexia. Here we use electroencephalography (EEG) and natural speech listening paradigms to identify neural processing patterns that characterize dyslexic versus DLD children. Using a story listening paradigm, we show that atypical power dynamics and phase-amplitude coupling between delta and theta oscillations characterize dyslexic and DLD children groups, respectively. We further identify EEG common spatial patterns (CSP) during speech listening across delta, theta and beta oscillations describing dyslexic versus DLD children. A linear classifier using four deltaband CSP variables predicted dyslexia status (0.77 AUC). Crucially, these spatial patterns also identified children with dyslexia in a rhythmic syllable task EEG, suggesting a core developmental deficit in neural processing of speech rhythm. These findings suggest that there are distinct atypical neurocognitive mechanisms underlying dyslexia and DLD.

neuroscience↗

Decoding of Speech Information using EEG in Children with Dyslexia: Less Accurate Low-Frequency Representations of Speech, Not "Noisy" Representations

The amplitude envelope of speech carries crucial low-frequency acoustic information that assists linguistic decoding. The sensory-neural Temporal Sampling (TS) theory of developmental dyslexia proposes atypical encoding of speech envelope information <10 Hz, leading to atypical phonological representations. Here a backward linear TRF model and story listening were employed to estimate the speech information encoded in the electroencephalogram in the canonical delta, theta and alpha bands by 9-year-old children with and without dyslexia. TRF decoding accuracy provided an estimate of how faithfully the childrens brains encoded low-frequency envelope information. Between-group analyses showed that the children with dyslexia exhibited impaired reconstruction of speech information in the delta band. However, when the quality of speech encoding for each child was estimated using child-by-child decoding models, then the dyslexic children did not differ from controls. This suggests that children with dyslexia encode neither "noisy" nor "normal" representations of the speech signal, but different representations.

neuroscience↗