The aim of this study was to develop a presurgical magnetoencephalography (MEG) protocol to localize and lateralize expressive and receptive language function as well as verbal memory in patients with epilepsy. Two simple language tasks and a different analytical procedure were developed. Ten healthy participants and 13 epileptic patients completed two language tasks during MEG recording: a verbal memory task and a verbal fluency task. As a first step, principal component analyses (PCA) were performed on source data from the group of healthy participants to identify spatiotemporal factors that were relevant to these paradigms. Averaged source data were used to localize areas activated during each task and a laterality index (LI) was computed on an individual basis for both groups, healthy participants and patients, using sensor data. PCA revealed activation in the left temporal lobe (300 ms) during the verbal memory task, and from the frontal lobe (210 ms) to the temporal lobe (500 ms) during the verbal fluency task in healthy participants. Averaged source data showed activity in the left hemisphere (250-750 ms), in Wernicke's area, for all participants. Left hemisphere dominance was demonstrated better using the verbal memory task than the verbal fluency task (F1,19=4.41, p=0.049). Cohen's kappa statistic revealed 93% agreement (k=0.67, p=0.002) between LIs obtained from MEG sensor data and fMRI, the IAT, electrical cortical stimulation or handedness with the verbal memory task for all participants. At 74%, agreement results for the verbal fluency task did not reach statistical significance. Analysis procedures yielded interesting findings with both tasks and localized language-related activation. However, based on source localization and laterality indices, the verbal memory task yielded better results in the context of the presurgical evaluation of epileptic patients. The verbal fluency task did not add any further information to the verbal memory task as regards language localization and lateralization for most patients and healthy participants that would facilitate decision making prior to surgery.

Patients with brain tumor or refractory epilepsy may be candidates for neurosurgery. Presurgical evaluation often includes language investigation to prevent or reduce the risk of postsurgical language deficits. Current techniques involve significant limitations with pediatric populations. Recently, near-infrared spectroscopy (NIRS) has been shown to be a valuable neuroimaging technique for language localization in children. However, it typically requires the child to perform a task (task-based NIRS), which may constitute a significant limitation. Resting-state functional connectivity NIRS (fcNIRS) is an approach that can be used to identify language networks at rest. This study aims to assess the utility of fcNIRS in children by comparing fcNIRS to more conventional task-based NIRS for language mapping in 33 healthy participants: 25 children (ages 3 to 16) and 8 adults. Data were acquired at rest and during a language task. Results show very good concordance between both approaches for language localization (Dice similarity $coefficient=0.81±0.13$) and hemispheric language dominance ($kappa=0.86$, $p<0.006$). The fcNIRS technique may be a valuable tool for language mapping in clinical populations, including children and patients with cognitive and behavioral impairments.

SignificanceCurrent techniques for data analysis in functional near-infrared spectroscopy (fNIRS), such as artifact correction, do not allow to integrate the information originating from both wavelengths, considering only temporal and spatial dimensions of the signal’s structure. Parallel factor analysis (PARAFAC) has previously been validated as a multidimensional decomposition technique in other neuroimaging fields.AimWe aimed to introduce and validate the use of PARAFAC for the analysis of fNIRS data, which is inherently multidimensional (time, space, and wavelength).ApproachWe used data acquired in 17 healthy adults during a verbal fluency task to compare the efficacy of PARAFAC for motion artifact correction to traditional two-dimensional decomposition techniques, i.e., target principal (tPCA) and independent component analysis (ICA). Correction performance was further evaluated under controlled conditions with simulated artifacts and hemodynamic response functions.ResultsPARAFAC achieved significantly higher improvement in data quality as compared to tPCA and ICA. Correction in several simulated signals further validated its use and promoted it as a robust method independent of the artifact’s characteristics.ConclusionsThis study describes the first implementation of PARAFAC in fNIRS and provides validation for its use to correct artifacts. PARAFAC is a promising data-driven alternative for multidimensional data analyses in fNIRS and this study paves the way for further applications.

Our ability to merge information from different senses into a unified percept is a crucial perceptual process for efficient interaction with our multisensory environment. Yet, the developmental process underlying how the brain implements multisensory integration (MSI) remains poorly known. This cross-sectional study aims to characterize the developmental patterns of audiovisual events in 131 individuals aged from 3 months to 30 years. Electroencephalography (EEG) was recorded during a passive task, including simple auditory, visual, and audiovisual stimuli. In addition to examining age-related variations in MSI responses, we investigated EventRelated Potentials (ERPs) linked with auditory and visual stimulation alone. This was done to depict the typical developmental trajectory of unisensory processing from infancy to adulthood within our sample and to contextualize the maturation effects of MSI in relation to unisensory development. Comparing the neural response to audiovisual stimuli to the sum of the unisensory responses revealed signs of MSI in the ERPs, more specifically between the P2 and N2 components (P2 effect). Furthermore, adult-like MSI responses emerge relatively late in the development, around 8 years old. The automatic integration of simple audiovisual stimuli is a long developmental process that emerges during childhood and continues to mature during adolescence with ERP latencies decreasing with age.