Neurophysiological tracking of speech-structure learning in typical and dyslexic readers

Unraveling individual differences in learning potential: A dynamic framework for the case of reading development

Children show an enormous capacity to learn during development, but with large individual differences in the time course and trajectory of learning and the achieved skill level. Recent progress in developmental sciences has shown the contribution of a multitude of factors including genetic variation, brain plasticity, socio-cultural context and learning experiences to individual development. These factors interact in a complex manner, producing children's idiosyncratic and heterogeneous learning paths. Despite an increasing recognition of these intricate dynamics, current research on the development of culturally acquired skills such as reading still has a typical focus on snapshots of children's performance at discrete points in time. Here we argue that this 'static' approach is often insufficient and limits advancements in the prediction and mechanistic understanding of individual differences in learning capacity. We present a dynamic framework which highlights the importance of capturing short-term trajectories during learning across multiple stages and processes as a proxy for long-term development on the example of reading. This framework will help explain relevant variability in children's learning paths and outcomes and fosters new perspectives and approaches to study how children develop and learn.

Phonological deficits in dyslexia impede lexical processing of spoken words: Linking behavioural and MEG data

Phonological difficulties have been identified as a core deficit in developmental dyslexia, yet everyday speech comprehension, which relies on phonological processing, is seemingly unaffected. This raises the question as to how dyslexic readers process spoken words to achieve normal word comprehension. Here we establish a link between neural correlates of lexical and sublexical processing in auditory words and behaviourally measured phonological deficits using magnetoencephalography (MEG). Spatiotemporally resolved cortical responses to phonological and lexico-semantic information were computed with the event-related regression technique (Hauk et al., 2009) and correlated with dyslexic and non-dyslexic subjects' phonological skills. We found that phonological deficits reduced cortical responses to both phonological and lexico-semantic information (phonological neighbours and word frequency). Individuals with lower phonological skills - independent of dyslexia diagnosis - showed weaker neural responses to phonological neighbourhood information in both hemispheres 200-500 ms after word onset and reduced sensitivity to written and spoken word frequency between 200 and 650 ms. Dyslexic readers showed weaker responses to written word frequency in particular compared to the control group, pointing towards an additional effect of print exposure on auditory word processing. Source space analysis localised phonological and lexico-semantic effect peaks to the left superior temporal gyrus, a key area that has been related to core deficits in dyslexia across a range of neuroimaging studies. The results provide comprehensive evidence that phonological deficits impact both sublexical and lexical stages of spoken word processing and that these deficits cannot be fully compensated through neural re-organization of lexical-distributional information at the single word level. Theoretical and practical implications for typical readers, dyslexic readers, and readers with developmental language disorder are discussed.

Rhythmically Modulating Neural Entrainment during Exposure to Regularities Influences Statistical Learning

The ability to discover regularities in the environment, such as syllable patterns in speech, is known as statistical learning. Previous studies have shown that statistical learning is accompanied by neural entrainment, in which neural activity temporally aligns with repeating patterns over time. However, it is unclear whether these rhythmic neural dynamics play a functional role in statistical learning or whether they largely reflect the downstream consequences of learning, such as the enhanced perception of learned words in speech. To better understand this issue, we manipulated participants' neural entrainment during statistical learning using continuous rhythmic visual stimulation. Participants were exposed to a speech stream of repeating nonsense words while viewing either (1) a visual stimulus with a "congruent" rhythm that aligned with the word structure, (2) a visual stimulus with an incongruent rhythm, or (3) a static visual stimulus. Statistical learning was subsequently measured using both an explicit and implicit test. Participants in the congruent condition showed a significant increase in neural entrainment over auditory regions at the relevant word frequency, over and above effects of passive volume conduction, indicating that visual stimulation successfully altered neural entrainment within relevant neural substrates. Critically, during the subsequent implicit test, participants in the congruent condition showed an enhanced ability to predict upcoming syllables and stronger neural phase synchronization to component words, suggesting that they had gained greater sensitivity to the statistical structure of the speech stream relative to the incongruent and static groups. This learning benefit could not be attributed to strategic processes, as participants were largely unaware of the contingencies between the visual stimulation and embedded words. These results indicate that manipulating neural entrainment during exposure to regularities influences statistical learning outcomes, suggesting that neural entrainment may functionally contribute to statistical learning. Our findings encourage future studies using non-invasive brain stimulation methods to further understand the role of entrainment in statistical learning.

Is there evidence for a noisy computation deficit in developmental dyslexia?

The noisy computation hypothesis of developmental dyslexia (DD) is particularly appealing because it can explain deficits across a variety of domains, such as temporal, auditory, phonological, visual and attentional processes. A key prediction is that noisy computations lead to more variable and less stable word representations. A way to test this hypothesis is through repetition of words, that is, when there is noise in the system, the neural signature of repeated stimuli should be more variable. The hypothesis was tested in an functional magnetic resonance imaging experiment with dyslexic and typical readers by repeating words twelve times. Variability measures were computed both at the behavioral and neural levels. At the behavioral level, we compared the standard deviation of reaction time distributions of repeated words. At the neural level, in addition to standard univariate analyses and measures of intra-item variability, we also used multivariate pattern analyses (representational similarity and classification) to find out whether there was evidence for noisier representations in dyslexic readers compared to typical readers. Results showed that there were no significant differences between the two groups in any of the analyses despite robust results within each group (i.e., high representational similarity between repeated words, good classification of words vs. non-words). In summary, there was no evidence in favor of the idea that dyslexic readers would have noisier neural representations than typical readers.

Repeated series learning revisited with a novel prediction on the reduced effect of item frequency in dyslexia

Developmental dyslexia, a difficulty with acquiring fluent reading, has also been characterized by reduced short-term memory (STM) capacity, which is often operationalized with span tasks. The low performance of individuals with dyslexia (IDDs) in such tasks is commonly attributed to poor phonological memory. However, we suggest an alternative explanation based on the observation that many times the items that are used in spans tasks are high-frequency items (e.g., digit words). We suggest that IDDs do not enjoy the benefit of item frequency to the same extent as controls, and thus their performance in span tasks is especially hampered. On the contrary, learning of repeated sequences was shown to be largely independent of item frequency, and therefore this type of learning may be unimpaired in dyslexia. To test both predictions, we used the Hebb-learning paradigm. We found that IDDs’ performance is especially poor compared to controls’ when high-frequency items are used, and that their repeated series learning does not differ from that of controls. Taken together with existing literature, our findings suggest that impaired learning of repeated series is not a core characteristic of dyslexia, and that the reports on reduced STM in dyslexia may to a large extent be explained by reduced benefit of item frequency.

Altered brain network topology during speech tracking in developmental dyslexia

Developmental dyslexia is often accompanied by altered phonological processing of speech. Underlying neural changes have typically been characterized in terms of stimulus- and/or task-related responses within individual brain regions or their functional connectivity. Less is known about potential changes in the more global functional organization of brain networks. Here we recorded electroencephalography (EEG) in typical and dyslexic readers while they listened to (a) a random sequence of syllables and (b) a series of tri-syllabic real words. The network topology of the phase synchronization of evoked cortical oscillations was investigated in four frequency bands (delta, theta, alpha and beta) using minimum spanning tree graphs. We found that, compared to syllable tracking, word tracking triggered a shift toward a more integrated network topology in the theta band in both groups. Importantly, this change was significantly stronger in the dyslexic readers, who also showed increased reliance on a right frontal cluster of electrodes for word tracking. The current findings point towards an altered effect of word-level processing on the functional brain network organization that may be associated with less efficient phonological and reading skills in dyslexia.

Simple statistical regularities presented during sleep are detected but not retained

In recent years, there has been growing interest and excitement over the newly discovered cognitive capacities of the sleeping brain, including its ability to form novel associations. These recent discoveries raise the possibility that other more sophisticated forms of learning may also be possible during sleep. In the current study, we tested whether sleeping humans are capable of statistical learning - the process of becoming sensitive to repeating, hidden patterns in environmental input, such as embedded words in a continuous stream of speech. Participants' EEG was recorded while they were presented with one of two artificial languages, composed of either trisyllabic or disyllabic nonsense words, during slow-wave sleep. We used an EEG measure of neural entrainment to assess whether participants became sensitive to the repeating regularities during sleep-exposure to the language. We further probed for long-term memory representations by assessing participants' performance on implicit and explicit tests of statistical learning during subsequent wake. In the disyllabic-but not trisyllabic-language condition, participants' neural entrainment to words increased over time, reflecting a gradual gain in sensitivity to the embedded regularities. However, no significant behavioural effects of sleep-exposure were observed after the nap, for either language. Overall, our results indicate that the sleeping brain can detect simple, repeating pairs of syllables, but not more complex triplet regularities. However, the online detection of these regularities does not appear to produce any durable long-term memory traces that persist into wake - at least none that were revealed by our current measures and sample size. Although some perceptual aspects of statistical learning are preserved during sleep, the lack of memory benefits during wake indicates that exposure to a novel language during sleep may have limited practical value.

How Learning to Read Changes the Listening Brain

Reading acquisition reorganizes existing brain networks for speech and visual processing to form novel audio-visual language representations. This requires substantial cortical plasticity that is reflected in changes in brain activation and functional as well as structural connectivity between brain areas. The extent to which a child's brain can accommodate these changes may underlie the high variability in reading outcome in both typical and dyslexic readers. In this review, we focus on reading-induced functional changes of the dorsal speech network in particular and discuss how its reciprocal interactions with the ventral reading network contributes to reading outcome. We discuss how the dynamic and intertwined development of both reading networks may be best captured by approaching reading from a skill learning perspective, using audio-visual learning paradigms and longitudinal designs to follow neuro-behavioral changes while children's reading skills unfold.