Muriel Lobier

The visual attention span deficit in dyslexia is visual and not verbal

The visual attention (VA) span deficit hypothesis of dyslexia posits that letter string deficits are a consequence of impaired visual processing. Alternatively, some have interpreted this deficit as resulting from a visual-to-phonology code mapping impairment. This study aims to disambiguate between the two interpretations by investigating performance in a non-verbal character string visual categorization task with verbal and non-verbal stimuli. Results show that VA span ability predicts performance for the non-verbal visual processing task in normal reading children. Furthermore, VA span impaired dyslexic children are also impaired for the categorization task independently of stimuli type. This supports the hypothesis that the underlying impairment responsible for the VA span deficit is visual, not verbal.

Phase transfer entropy: a novel phase-based measure for directed connectivity in networks coupled by oscillatory interactions.

We introduce here phase transfer entropy (Phase TE) as a measure of directed connectivity among neuronal oscillations. Phase TE quantifies the transfer entropy between phase time-series extracted from neuronal signals by filtering for instance. To validate the measure, we used coupled Neuronal Mass Models to both evaluate the characteristics of Phase TE and compare its performance with that of a real-valued TE implementation. We showed that Phase TE detects the strength and direction of connectivity even in the presence of such amounts of noise and linear mixing that typically characterize MEG and EEG recordings. Phase TE performed well across a wide range of analysis lags and sample sizes. Comparisons between Phase TE and real-valued TE estimates showed that Phase TE is more robust to nuisance parameters and considerably more efficient computationally. In addition, Phase TE accurately untangled bidirectional frequency band specific interaction patterns that confounded real-valued TE. Finally, we found that surrogate data can be used to construct appropriate null-hypothesis distributions and to estimate statistical significance of Phase TE. These results hence suggest that Phase TE is well suited for the estimation of directed phase-based connectivity in large-scale investigations of the human functional connectome.

Impaired Letter-String Processing in Developmental Dyslexia: What Visual-to-Phonology Code Mapping Disorder?.

Poor parallel letter-string processing in developmental dyslexia was taken as evidence of poor visual attention (VA) span, that is, a limitation of visual attentional resources that affects multi-character processing. However, the use of letter stimuli in oral report tasks was challenged on its capacity to highlight a VA span disorder. In particular, report of poor letter/digit-string processing but preserved symbol-string processing was viewed as evidence of poor visual-to-phonology code mapping, in line with the phonological theory of developmental dyslexia. We assessed here the visual-to-phonological-code mapping disorder hypothesis. In Experiment 1, letter-string, digit-string and colour-string processing was assessed to disentangle a phonological versus visual familiarity account of the letter/digit versus symbol dissociation. Against a visual-to-phonological-code mapping disorder but in support of a familiarity account, results showed poor letter/digit-string processing but preserved colour-string processing in dyslexic children. In Experiment 2, two tasks of letter-string report were used, one of which was performed simultaneously to a high-taxing phonological task. Results show that dyslexic children are similarly impaired in letter-string report whether a concurrent phonological task is simultaneously performed or not. Taken together, these results provide strong evidence against a phonological account of poor letter-string processing in developmental dyslexia.

Pre-orthographic character string processing and parietal cortex: A role for visual attention in reading?

The visual front-end of reading is most often associated with orthographic processing. The left ventral occipito-temporal cortex seems to be preferentially tuned for letter string and word processing. In contrast, little is known of the mechanisms responsible for pre-orthographic processing: the processing of character strings regardless of character type. While the superior parietal lobule has been shown to be involved in multiple letter processing, further data is necessary to extend these results to non-letter characters. The purpose of this study is to identify the neural correlates of pre-orthographic character string processing independently of character type. Fourteen skilled adult readers carried out multiple and single element visual categorization tasks with alphanumeric (AN) and non-alphanumeric (nAN) characters under fMRI. The role of parietal cortex in multiple element processing was further probed with a priori defined anatomical regions of interest (ROIs). Participants activated posterior parietal cortex more strongly for multiple than single element processing. ROI analyses showed that bilateral SPL/BA7 was more strongly activated for multiple than single element processing, regardless of character type. In contrast, no multiple element specific activity was found in inferior parietal lobules. These results suggests that parietal mechanisms are involved in pre-orthographic character string processing. We argue that in general, attentional mechanisms are involved in visual word recognition, as an early step of word visual analysis.

Visual processing of multiple elements in the dyslexic brain: evidence for a superior parietal dysfunction

The visual attention (VA) span deficit hypothesis of developmental dyslexia posits that impaired multiple element processing can be responsible for poor reading outcomes. In VA span impaired dyslexic children, poor performance on letter report tasks is associated with reduced parietal activations for multiple letter processing. While this hints towards a non-specific, attention-based dysfunction, it is still unclear whether reduced parietal activity generalizes to other types of stimuli. Furthermore, putative links between reduced parietal activity and reduced ventral occipito-temporal (vOT) in dyslexia have yet to be explored. Using functional magnetic resonance imaging, we measured brain activity in 12 VA span impaired dyslexic adults and 12 adult skilled readers while they carried out a categorization task on single or multiple alphanumeric or non-alphanumeric characters. While healthy readers activated parietal areas more strongly for multiple than single element processing (right-sided for alphanumeric and bilateral for non-alphanumeric), similar stronger multiple element right parietal activations were absent for dyslexic participants. Contrasts between skilled and dyslexic readers revealed significantly reduced right superior parietal lobule (SPL) activity for dyslexic readers regardless of stimuli type. Using a priori anatomically defined regions of interest, we showed that neural activity was reduced for dyslexic participants in both SPL and vOT bilaterally. Finally, we used multiple regressions to test whether SPL activity was related to vOT activity in each group. In the left hemisphere, SPL activity covaried with vOT activity for both normal and dyslexic readers. In contrast, in the right hemisphere, SPL activity covaried with vOT activity only for dyslexic readers. These results bring critical support to the VA interpretation of the VA Span deficit. In addition, they offer a new insight on how deficits in automatic vOT based word recognition could arise in developmental dyslexia.

The Role of Visual Processing Speed in Reading Speed Development

A steady increase in reading speed is the hallmark of normal reading acquisition. However, little is known of the influence of visual attention capacity on childrens reading speed. The number of distinct visual elements that can be simultaneously processed at a glance (dubbed the visual attention span), predicts single-word reading speed in both normal reading and dyslexic children. However, the exact processes that account for the relationship between the visual attention span and reading speed remain to be specified. We used the Theory of Visual Attention to estimate visual processing speed and visual short-term memory capacity from a multiple letter report task in eight and nine year old children. The visual attention span and text reading speed were also assessed. Results showed that visual processing speed and visual short term memory capacity predicted the visual attention span. Furthermore, visual processing speed predicted reading speed, but visual short term memory capacity did not. Finally, the visual attention span mediated the effect of visual processing speed on reading speed. These results suggest that visual attention capacity could constrain reading speed in elementary school children.

Visual attention deficits in developmental dyslexia cannot be ascribed solely to poor reading experience.

Visual attention deficits in developmental dyslexia cannot be ascribed solely to poor reading experience

High-alpha band synchronization across frontal, parietal and visual cortex mediates behavioral and neuronal effects of visuospatial attention

ABSTRACT Visuospatial attention prioritizes processing of attended visual stimuli. It is characterized by lateralized alpha‐band (8–14 Hz) amplitude suppression in visual cortex and increased neuronal activity in a network of frontal and parietal areas. It has remained unknown what mechanisms coordinate neuronal processing among frontoparietal network and visual cortices and implement the attention‐related modulations of alpha‐band amplitudes and behavior. We investigated whether large‐scale network synchronization could be such a mechanism. We recorded human cortical activity with magnetoencephalography (MEG) during a visuospatial attention task. We then identified the frequencies and anatomical networks of inter‐areal phase synchronization from source localized MEG data. We found that visuospatial attention is associated with robust and sustained long‐range synchronization of cortical oscillations exclusively in the high‐alpha (10–14 Hz) frequency band. This synchronization connected frontal, parietal and visual regions and was observed concurrently with amplitude suppression of low‐alpha (6–9 Hz) band oscillations in visual cortex. Furthermore, stronger high‐alpha phase synchronization was associated with decreased reaction times to attended stimuli and larger suppression of alpha‐band amplitudes. These results thus show that high‐alpha band phase synchronization is functionally significant and could coordinate the neuronal communication underlying the implementation of visuospatial attention. HighlightsLarge‐scale high‐alpha band synchrony characterizes visuospatial attention.High‐alpha band phase synchrony connects frontal, parietal and visual cortices.Phase synchrony strength co‐varies with visual cortex low‐alpha amplitude suppression.Phase synchrony strength co‐varies with attentional modulations of reaction times.High‐alpha synchrony may support attentional top‐down coordination.

Hyperedge bundling: A practical solution to spurious interactions in MEG/EEG source connectivity analyses

&NA; Inter‐areal functional connectivity (FC), neuronal synchronization in particular, is thought to constitute a key systems‐level mechanism for coordination of neuronal processing and communication between brain regions. Evidence to support this hypothesis has been gained largely using invasive electrophysiological approaches. In humans, neuronal activity can be non‐invasively recorded only with magneto‐ and electroencephalography (MEG/EEG), which have been used to assess FC networks with high temporal resolution and whole‐scalp coverage. However, even in source‐reconstructed MEG/EEG data, signal mixing, or “source leakage”, is a significant confounder for FC analyses and network localization. Signal mixing leads to two distinct kinds of false‐positive observations: artificial interactions (AI) caused directly by mixing and spurious interactions (SI) arising indirectly from the spread of signals from true interacting sources to nearby false loci. To date, several interaction metrics have been developed to solve the AI problem, but the SI problem has remained largely intractable in MEG/EEG all‐to‐all source connectivity studies. Here, we advance a novel approach for correcting SIs in FC analyses using source‐reconstructed MEG/EEG data. Our approach is to bundle observed FC connections into hyperedges by their adjacency in signal mixing. Using realistic simulations, we show here that bundling yields hyperedges with good separability of true positives and little loss in the true positive rate. Hyperedge bundling thus significantly decreases graph noise by minimizing the false‐positive to true‐positive ratio. Finally, we demonstrate the advantage of edge bundling in the visualization of large‐scale cortical networks with real MEG data. We propose that hypergraphs yielded by bundling represent well the set of true cortical interactions that are detectable and dissociable in MEG/EEG connectivity analysis.

Measuring Large-Scale Synchronization with Human MEG and EEG: Challenges and Solutions

Specific kinds of neuronal interactions, such as phase coupling of neuronal oscillations, are likely to be essential systems-level mechanisms for coordinating neuronal communication, integration, and segregation. The functional roles of these interactions during cognitive tasks in healthy humans can be investigated with magneto- and electroencephalography (MEG/EEG), the only means for noninvasive electrophysiological recordings of human cortical activity. While advances in source modeling have opened new avenues for assessing inter-areal interactions with MEG/EEG, several factors limit the accuracy and inferential value of such analyses. In this chapter, we provide an overview of common source analysis strategies for mapping inter-areal interactions with MEG/EEG. Linear mixing between sources, as caused by volume conduction and signal mixing, is the principal confounder in connectivity analysis and always leads to false positive observations. We discuss the sensitivity of different interaction metrics to directly and indirectly caused false positives and conclude with approaches to mitigate these problems. In conclusion, MEG and EEG are becoming increasingly useful for assessing inter-areal neuronal interaction in humans.