👤 Valérie Chanoine

Electroencephalography (EEG) and magnetoencephalography (MEG), two of the most widely used tools for studying human brain dynamics, are thought to have varying spatial resolutions. Here, we simultaneously recorded EEG and MEG data from 14 participants to directly compare their sensitivities - at both the sensor and source levels - to the auditory Mismatch Negativity (MMN in EEG and MMNm in MEG) elicited by pitch deviants. At the sensor level, we observed that negative components emerged in early (100-190 ms) and late (260-420 ms) latency windows. These responses displayed a fronto-central distribution in EEG and a centro-parietal distribution in MEG. MEG also yielded larger effect sizes than EEG, likely reflecting differences in signal-to-noise ratio between MEG and EEG. At the source level, our findings support the involvement of a fronto-temporal auditory MMN network. Both EEG and MEG identified generators in the superior temporal gyrus, Heschl's gyrus, interior frontal gyrus, and insular regions. Notably, EEG source localization revealed additional generators in the left superior temporal sulcus not detected by MEG, whereas MEG identified late components generators in the right hemisphere that were not observed with EEG. Taken together, these results suggest that EEG and MEG may provide complementary perspectives on auditory processing. However, given the inherent complexity of comparing data acquired with different methodologies and the limited sample size, our conclusions should be regarded as preliminary. Show less

Reading relies on the ability to map written symbols with speech sounds. A specific part of the left ventral occipitotemporal cortex, known as the Visual Word Form Area (VWFA), plays a crucial role in this process. Through the automatization of the mapping ability, this area progressively becomes specialized in written word recognition. Yet, despite its key role in reading, the area also responds to speech. This observation raises questions about the actual nature of neural representations encoded in the VWFA and, therefore, the underlying mechanism of the cross-modal responses. Here, we addressed this issue by applying fine-grained analyses of within- and cross-modal repetition suppression effects (RSEs) and Multi-Voxel Pattern Analyses in fMRI and sEEG experiments. Convergent evidence across analysis methods and protocols showed significant RSEs and successful decoding in both within-modal visual and auditory conditions, suggesting that populations of neurons within the VWFA distinctively encode written and spoken language. This functional organization of neural populations enables the area to respond to both written and spoken inputs. The finding opens further discussions on how the human brain may be prepared and adapted for an acquisition of a complex ability such as reading. Show less

Prediction has become a key concept for understanding language comprehension, language production, and more recently reading. Recent studies suggest that predictive mechanisms in reading may be related to domain-general statistical learning (SL) abilities that support the extraction of regularities from sequential input. Both mechanisms have been discussed in relation to developmental dyslexia. Some suggest that SL is impaired in dyslexia with negative effects on the ability to make linguistic predictions. Others suggest that dyslexic readers rely to a greater extent on semantic and syntactic predictions to compensate for lower-level deficits. Here, we followed these two research questions in a single study. We therefore assessed the effects of semantic and syntactic prediction in reading and SL abilities in a population of university students with dyslexia and a group of typical readers using fMRI. The SL task was a serial reaction time (SRT) task that was performed inside and outside the scanner. The predictive reading task was performed in the scanner and used predictive versus nonpredictive semantic and syntactic contexts. Our results revealed distinct neural networks underlying semantic and syntactic predictions in reading, group differences in predictive processing in the left precentral gyrus and right anterior insula, and an association between predictive reading and SL, particularly in dyslexic readers. These findings contribute to our understanding of the interplay between SL, predictive processing, and compensation in dyslexia, providing new insights into the neural mechanisms that support reading. Show less

The "MEG-GLOUPS" dataset offers a curated collection of raw magnetoencephalography recordings from seventeen French participants engaged in a pseudoword learning task as well as resting-state activity before and after the task. A dataset called Gloups with the same participants and a similar learning task adapted to functional magnetic resonance imaging is already available. In the learning task, participants were instructed to pronounce monosyllabic pseudowords, which were presented both visually and auditorily. These pseudowords were either phonotactically legal or illegal in the participants' native language, French. We organized the dataset according to the Brain Imaging Data Structure (BIDS), pre-processed the data and performed a minimal analysis of Event-Related Fields (ERFs), to ensure data quality and integrity of the dataset. This data collection includes comprehensive descriptions of the theoretical background, methods, data recordings, and technical validation. Show less

It has been argued that university students with dyslexia compensate for their reading deficits by a neural re-organization of the typical reading network, where the lexical representations of words are (re-)structured according to semantic rather than orthographic information. To investigate the re-organization of neural word representations more directly, we used multivariate representational similarity analyses (RSA) to find out which brain regions of the reading network respond to orthographic and semantic similarity between 544 pairs of words and whether there were any differences between typical and dyslexic readers. In accordance with the re-organization hypothesis, we predicted greater similarity (i.e., correlation of neural dissimilarity matrices) in adult dyslexic than in typical readers in regions associated with semantic processing and weaker similarity in regions associated with orthographic processing. Our results did not confirm these predictions. First, we found sensitivity to semantic similarity in all three subparts of the fusiform gyrus (FG1, FG2, and FG3) bilaterally. Adults with dyslexia showed less (rather than more) sensitivity to semantic similarity in the posterior subpart of fusiform gyrus (FG1) in the left hemisphere. Second, in typical readers, sensitivity to orthographic information was not only found in the left fusiform gyrus (FG1, FG2, and FG3) but also in left inferior frontal gyrus (IFG). Adults with dyslexia, in contrast, did not show sensitivity to orthographic information in left IFG. However, they showed increased sensitivity to orthographic information in the right hemisphere FG1. Together, the results show abnormal orthographic processing in left IFG and right FG1 and reduced semantic information in left FG1. While we found evidence for compensatory re-organization in adult dyslexia, the present results do not support the hypothesis according to which adults with dyslexia rely more heavily on semantic information. Instead, they revealed atypical hemispheric organization of the reading network that is not restricted to the typical left language hemisphere. Show less

Congenital hypogonadotropic hypogonadism (CHH) and its anosmia-associated form (Kallmann syndrome [KS]) are genetically heterogeneous. Among the >15 genes implicated in these conditions, mutations in FGF8 and FGFR1 account for ~12% of cases; notably, KAL1 and HS6ST1 are also involved in FGFR1 signaling and can be mutated in CHH. We therefore hypothesized that mutations in genes encoding a broader range of modulators of the FGFR1 pathway might contribute to the genetics of CHH as causal or modifier mutations. Thus, we aimed to (1) investigate whether CHH individuals harbor mutations in members of the so-called "FGF8 synexpression" group and (2) validate the ability of a bioinformatics algorithm on the basis of protein-protein interactome data (interactome-based affiliation scoring [IBAS]) to identify high-quality candidate genes. On the basis of sequence homology, expression, and structural and functional data, seven genes were selected and sequenced in 386 unrelated CHH individuals and 155 controls. Except for FGF18 and SPRY2, all other genes were found to be mutated in CHH individuals: FGF17 (n = 3 individuals), IL17RD (n = 8), DUSP6 (n = 5), SPRY4 (n = 14), and FLRT3 (n = 3). Independently, IBAS predicted FGF17 and IL17RD as the two top candidates in the entire proteome on the basis of a statistical test of their protein-protein interaction patterns to proteins known to be altered in CHH. Most of the FGF17 and IL17RD mutations altered protein function in vitro. IL17RD mutations were found only in KS individuals and were strongly linked to hearing loss (6/8 individuals). Mutations in genes encoding components of the FGF pathway are associated with complex modes of CHH inheritance and act primarily as contributors to an oligogenic genetic architecture underlying CHH. Show less