Atypical cortical entrainment to speech in the right hemisphere underpins phonemic deficits in dyslexia
Introduction
Developmental dyslexia (hereafter dyslexia) is a learning disorder manifested in difficulties in the acquisition of reading and spelling that affects 5–10% of school-aged children and that can arise despite an adequate learning environment and otherwise normal intellectual and sensory functioning (Snowling, 2000). Children affected by dyslexia usually perform poorly in tests of phonological awareness, verbal short-term memory, and lexical-access (e.g., rapid naming), highlighting the relationship between this disorder and linguistic components involved in reading (Vellutino et al., 2004). Dyslexia can impact other spheres of a person's life, such as substantially higher rates of depression and anxiety, juvenile delinquency, school dropout, and a lower chance of future employment (Baker and Ireland, 2007; Brooks, 2014; Daniel et al., 2006; McNulty, 2003; Sabornie, 1994; Wiener and Schneider, 2002). The identification of the root causes of dyslexia could better inform the necessary conditions for environmental enrichment and improve the development of clinical tools for its early diagnosis. This, in turn could benefit the education and future employment of millions of children (Goswami, 2014).
A rich literature indicates a link between dyslexia and sensory dysfunctions in both the visual and auditory domains (Giraud and Ramus, 2013; Gori and Facoetti, 2015; McArthur and Bishop, 2001; Rosen, 2003; Schulte-Körne and Bruder, 2010; Valdois et al., 2004). However, it has been argued that such a link does not necessarily inform us about the root cause of dyslexia, which is currently under debate (Goswami, 2014). One reason is that learning to read moulds the brain by training its sensory and attentional neural networks, so sensory dysfunctions may be a result of diminished reading experience, rather than being directly linked with dyslexia (Bishop et al., 2012). This poses an additional challenge for the study of potential sensory causes of dyslexia, and highlights the importance of including a typically-developing control group matched in reading achievement to the children with dyslexia (the ‘reading-level-match’ research design, to control for the effects of reading experience on the brain). One area of relative agreement concerns the hypothesis that a proximal cause of dyslexia is a behavioural ‘phonological deficit’, encompassing all levels of phonology (prosody, syllables, rhymes, and the short categorical speech units reflected by the alphabet, phonemes) (Clark et al., 2014; Goswami, 2014, 2011; Goswami and Leong, 2013; Lehongre et al., 2013; Richlan, 2012). Further, it is generally agreed that the speech processing mechanisms that yield these phonological units are underpinned by a hierarchical system, whose critical mechanisms lie in the infrastructure provided by neuronal oscillations (Giraud and Poeppel, 2012; Leong and Goswami, 2014). It is possible that phonological deficits associated with dyslexia stem from an impairment in these fundamental mechanisms related to neuronal oscillations, such as the temporal sampling of the auditory input (temporal sampling framework, Goswami, 2011).
Stimulus-induced modulations in delta-, theta-, and gamma-bands (1–4 Hz, 4–8 Hz, and >25 Hz respectively) have been shown to reflect successful speech comprehension and processing related to different speech units (e.g., phrasal, syllabic, phonemic) (Ghitza, 2011; Poeppel, 2003). Furthermore, recent studies have demonstrated links between dyslexia and anomalies in specific neural oscillations. For example, deficits in the processing of slow temporal modulations (e.g., <8 Hz) have been related to difficulties in perceiving both syllable stress and the phonemic constituents of syllables, difficulties which would likely impair the development of well-specified phonological representations of words (Goswami, 2011; Molinaro et al., 2016; Poeppel, 2003; Power et al., 2016). In addition, another factor that has been linked with dyslexia is working memory, the temporary storage system necessary for a wide range of complex cognitive activities, including speech and language processing (Baddeley, 2003). Recent research has shown stronger cortical entrainment for high-frequency oscillations (>40 Hz) in adults with dyslexia (Lehongre et al., 2011) and it has been suggested that this is due to oversampling of speech information, causing an excessive demand on working memory, and consequent impairment of its related cortical functions (Giraud and Poeppel, 2012).
These and other studies with both adults and children using both speech and non-speech stimuli have demonstrated differences in both amplitude and hemispheric bias between individuals with dyslexia and control groups (Abrams et al., 2009; Cutini et al., 2016; Goswami, 2011; Heim et al., 2003; Peter et al., 2016; Vanvooren et al., 2014). However, the root causes of such processing biases remain unclear. One reason for this lack of clarity is that most studies did not control for differences in reading skills via a reading-level-match control group and, therefore, did not provide the conditions necessary to assess possible causality regarding dyslexia (Goswami, 2014). A second reason for this lack of clarity is that, although dyslexia has been shown to affect phonological skills regardless of age, different phonological skills may be affected in different age-groups, which would likely be reflected in the neural responses to speech (Miller-Shaul, 2005). A third reason is that neurophysiological studies have usually been conducted using non-naturalistic stimuli such as isolated syllables (Power et al., 2013), modulated noise (Lehongre et al., 2011), and noise-vocoded speech (Power et al., 2016).
While a tailored experimental design is sufficient to overcome the first two limitations, the use of more naturalistic stimuli in neurophysiological studies is less straightforward. Indeed, the ability to derive objective neural measures of phonological processing using natural speech could be key to clarifying the cortical underpinnings of dyslexia and, in particular, of the corresponding phonological deficit. The complexity of natural speech and associated cortical responses poses a challenge that has only been tackled quite recently. Specifically, recent research has demonstrated that cortical oscillations track the low-frequency rhythms of incoming speech stimuli. In a growing body of literature this entrainment phenomenon is being investigated by focusing on the mapping between the temporal envelope of speech and neurophysiological recordings such as electroencephalography (EEG; Aiken and Picton, 2008; Ding et al., 2017), magnetoencephalography (MEG; Ahissar et al., 2001), and electrocorticography (ECoG; Pasley et al., 2012). To date, low-frequency cortical oscillatory mechanisms have been thought primarily to aid syllable parsing and the identification of stressed syllables. However, recent research from Di Liberto and colleagues has demonstrated that low-frequency EEG signals track also phoneme categories. This provides us for the first time with a methodology to isolate quantitative measures of children's phoneme-level processing using natural continuous speech (Crosse et al., 2016; Di Liberto et al., 2015).
Here we used this novel methodology to objectively measure whether impaired cortical tracking of the temporal envelope of speech directly affects the representation of phoneme-level units in dyslexia. We investigated this in dyslexic and non-dyslexic school-aged children using EEG, controlling for the effects of age and reading level. In addition, correlational analyses were conducted between the neural measures at individual scalp electrodes and the results of a standard battery of behavioural tests of language skills, memory capacity, and attention used in dyslexia diagnosis.
Section snippets
Material and methods
Seventy children (26 female) aged between 6 and 12 years (mean = 8.6 years, SD = 1.5), who were monolingual speakers of Australian English, participated in the experiment. The ethics committee for Human Research at Western Sydney University (Approval Number H9660) approved all the experimental methods used in the study. Informed consent was obtained from the parents of all the participants. Children also gave verbal assent for the study.
Results
70 children (6–12 years of age) undertook a standard battery of behavioural tests of phonological and language skills, memory capacity, IQ, and attention. These behavioural tests identified 25 participants with the typical symptoms of dyslexia (DX group). In a separate session, 129-channel EEG was recorded as participants listened to an audio-story for 9 min, while watching the corresponding cartoon. Scalp electrical signals were analysed to test the hypothesis that dyslexia is linked to an
Discussion
This study investigated the cortical underpinnings of developmental dyslexia, a developmental disorder of learning whose root causes remain debated, but with a reasonable consensus around impairments in phonological processing (Snowling, 2000). Recently, it has been suggested that phonological impairments in individuals with dyslexia may relate to atypical function of the cortical oscillatory mechanisms of temporal sampling and phase-locking at <10 Hz that underpin continuous speech
Conflicts of interest
None declared.
Funding sources
This study was supported by an Irish Research Council Government of Ireland Postgraduate Scholarship (GOIPG/2013/1249) awarded to the first and sixth authors and an Australian Research Council Discovery Project grant (DP110105123) awarded to the fourth and fifth authors.
Author contributions
The study was conceived by V.P., M.K., D.B., and G.D.L.; V.P. programmed the tasks; V.P. and M.K. collected the data; G.D.L. analysed the data; M.K. and V.P. analysed the behavioural data; G.D.L. wrote the first draft of the manuscript; V.P., M.K., D.B., U.G. and E.C.L. edited the manuscript.
Acknowledgements
This study was supported by an Irish Research Council Government of Ireland Postgraduate Scholarship to the first author (GOIPG, 2013–2017), and an Australian Research Council Discovery Project grant (DP110105123) to the fourth and fifth authors. The authors would like to thank all the children and their families who invested so many long hours during the testing sessions for this study. The authors also thank Maria Christou-Ergos, Scott O'Loughlin, Samra Alispahic and Elizabeth Byron for their
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