Magnetoencephalography Responses Research Articles

Neural Speech Tracking Contribution of Lip Movements Predicts Behavioral Deterioration When the Speaker's Mouth Is Occluded.

Observing lip movements of a speaker facilitates speech understanding, especially in challenging listening situations. Converging evidence from neuroscientific studies shows stronger neural responses to audiovisual stimuli compared with audio-only stimuli. However, the interindividual variability of this contribution of lip movement information and its consequences on behavior are unknown. We analyzed source-localized magnetoencephalographic responses from 29 normal-hearing participants (12 females) listening to audiovisual speech, both with and without the speaker wearing a surgical face mask, and in the presence or absence of a distractor speaker. Using temporal response functions to quantify neural speech tracking, we show that neural responses to lip movements are, in general, enhanced when speech is challenging. After controlling for speech acoustics, we show that lip movements contribute to enhanced neural speech tracking, particularly when a distractor speaker is present. However, the extent of this visual contribution to neural speech tracking varied greatly among participants. Probing the behavioral relevance, we demonstrate that individuals who show a higher contribution of lip movements in terms of neural speech tracking show a stronger drop in comprehension and an increase in perceived difficulty when the mouth is occluded by a surgical face mask. In contrast, no effect was found when the mouth was not occluded. We provide novel insights on how the contribution of lip movements in terms of neural speech tracking varies among individuals and its behavioral relevance, revealing negative consequences when visual speech is absent. Our results also offer potential implications for objective assessments of audiovisual speech perception.

Cortical encoding of spatial structure and semantic content in 3D natural scenes.

Our visual system enables us to effortlessly navigate and recognize real-world visual environments. Functional magnetic resonance imaging (fMRI) studies suggest a network of scene-responsive cortical visual areas, but much less is known about the temporal order in which different scene properties are analysed by the human visual system. In this study, we selected a set of 36 full-colour natural scenes that varied in spatial structure and semantic content that our male and female human participants viewed both in 2D and 3D while we recorded magnetoencephalography (MEG) data. MEG enables tracking of cortical activity in humans at millisecond timescale. We compared the representational geometry in the MEG responses with predictions based on the scene stimuli using the representational similarity analysis framework. The representational structure first reflected the spatial structure in the scenes in time-window 90-125 ms, followed by the semantic content in time-window 140-175 ms after stimulus onset. The 3D stereoscopic viewing of the scenes affected the responses relatively late, from around 140 ms from stimulus onset. Taken together, our results indicate that the human visual system rapidly encodes a scene's spatial structure and suggest that this information is based on monocular instead of binocular depth cues.Significance statement Our visual system enables us to recognize and navigate our visual surroundings seemingly effortlessly, but what exactly happens in our brains remains poorly understood. With the help of time-resolved brain imaging (magnetoencephalography, MEG), we found that the brain first encodes the spatial structure of a scene (e.g., cluttered or navigable) before its semantic content (e.g., a car park or farm). Brain imaging studies typically use 2D pictures as stimuli. Here we asked whether binocular disparity, a depth cue which arises from our two eyes seeing the scene from slightly different angles, aids the coding of the spatial structure. Our results suggest that this 3D depth cue plays little role in the rapid, initial sensing of our spatial surroundings.

Effect of the magnitude of abrupt change in sound pressure on the magnitude and phase synchrony of 40-Hz auditory steady state response

A periodic sound with a fixed inter-stimulus interval elicits an auditory steady-state response (ASSR). An abrupt change in a continuous sound is known to affect the brain's ongoing neural oscillatory activity, but the underlying mechanism has not been fully clarified. We investigated whether and how an abrupt change in sound intensity affects the ASSR. The control stimulus was a train of 1-ms clicks with a sound pressure level (SPL) of 70dB at 40Hz for 1000ms. In addition to the control stimulus, we applied six stimuli with changes consisting of a 500-ms train at 70dB followed by a 500-ms similar train with louder clicks of 75, 80, or 85dB or weaker clicks of 55, 60, or 65dB. We obtained the magnetoencephalographic responses from 15 healthy subjects while presenting the seven stimuli randomly. The two-dipole model obtained for the 40-Hz ASSR in the control condition was applied to all of the stimulus conditions for each subject, and then the time-frequency analysis was conducted. We observed that both the amplitude and the inter-trial phase coherence of the 40-Hz ASSR transiently decreased and returned to the steady state after the change onset, i.e., the desynchronization of 40-Hz ASSR. The degree of desynchronization depended on the magnitude of the change regardless of whether the sound intensity increased or decreased, which might be a novel neurophysiological index of cerebral response driven by a change in the sensory environment.

The Spatiotemporal Dynamics of Bottom-Up and Top-Down Processing during At-a-Glance Reading.

Like all domains of cognition, language processing is affected by top-down knowledge. Classic evidence for this is missing blatant errors in the signal. In sentence comprehension, one instance is failing to notice word order errors, such as transposed words in the middle of a sentence: "you that read wrong" (Mirault et al., 2018). Our brains seem to fix such errors, since they are incompatible with our grammatical knowledge, but how do our brains do this? Following behavioral work on inner transpositions, we flashed four-word sentences for 300 ms using rapid parallel visual presentation (Snell and Grainger, 2017). We compared magnetoencephalography responses to fully grammatical and reversed sentences (24 human participants: 21 females, 4 males). The left lateral language cortex robustly distinguished grammatical and reversed sentences starting at 213 ms. Thus, the influence of grammatical knowledge begun rapidly after visual word form recognition (Tarkiainen et al., 1999). At the earliest stage of this neural "sentence superiority effect," inner transpositions patterned between grammatical and reversed sentences, showing evidence that the brain initially "noticed" the error. However, 100 ms later, inner transpositions became indistinguishable from grammatical sentences, suggesting at this point, the brain had "fixed" the error. These results show that after a single glance at a sentence, syntax impacts our neural activity almost as quickly as higher-level object recognition is assumed to take place (Cichy et al., 2014). The earliest stage involves detailed comparisons between the bottom-up input and grammatical knowledge, while shortly afterward, top-down knowledge can override an error in the stimulus.

Population receptive field models capture the event-related magnetoencephalography response with millisecond resolution

Abstract Much of the visual system is organized into visual field maps. In humans, this organization can be studied non-invasively by estimating the receptive fields of populations of neurons (population receptive fields; pRFs) with functional magnetic resonance imaging (fMRI). However, fMRI cannot capture the temporal dynamics of visual processing that operate on a millisecond scale. Magnetoencephalography (MEG) does provide this temporal resolution but generally lacks the required spatial resolution. Here, we introduce a forward modeling approach that combines fMRI and MEG, enabling us to estimate pRFs with millisecond resolution. Using fMRI, we estimated the participant’s pRFs using conventional pRF-modeling. We then combined the pRF models with a forward model that transforms the cortical responses to the MEG sensors. This enabled us to predict event-related field responses measured with MEG while the participants viewed brief (100 ms) contrast-defined bar and circle shapes. We computed the goodness of fit between the predicted and measured MEG responses across time using cross-validated variance explained. We found that the fMRI-estimated pRFs explained up to 91% of the variance in individual MEG sensor’s responses. The variance explained varied over time and peaked between 75 ms to 250 ms after stimulus onset. Perturbing the pRF positions decreased the explained variance, suggesting that the pRFs were driving the MEG responses. In conclusion, pRF models can predict event-related MEG responses, enabling routine investigation of the spatiotemporal dynamics of human pRFs with millisecond resolution.

Improving source estimation of retinotopic MEG responses by combining data from multiple subjects

Abstract Magnetoencephalography (MEG) is a functional brain imaging modality, which measures the weak magnetic field arising from neuronal activity. The source amplitudes and locations are estimated from the sensor data by solving an ill-posed inverse problem. Commonly used solutions for these problems operate on data from individual subjects. Combining the measurements of multiple subjects has been suggested to increase the spatial resolution of MEG by leveraging the intersubject differences for increased information. In this article, we compare 3 multisubject analysis methods on a retinotopic mapping dataset recorded from 20 subjects. The compared methods are eLORETA with source-space averaging, minimum Wasserstein estimates (MWE), and MWE with source-space averaging. The results were quantified by the geodesic distances between early (60–100 ms) MEG peak activations and fMRI-based retinotopic target points in the primary visual cortex (V1). By increasing the subject count from 1 to 10, the median distances decreased by 6.6–9.4 mm (33–46%) compared with the single-subject median distances of around 20 mm. The observed peak activation locations with multisubject analysis also comply better with the established retinotopic maps of the primary visual cortex. Our results suggest that higher spatial accuracy can be achieved by pooling data from multiple subjects. The strength of MWE lies in individualized and sparse source estimates, but in our data, averaging eLORETA estimates across individuals in source space outperformed MWE in spatial accuracy.

Neuronal Modeling of Cross-Sensory Visual Evoked Magnetoencephalography Responses in the Auditory Cortex.

Previous studies have demonstrated that auditory cortex activity can be influenced by cross-sensory visual inputs. Intracortical laminar recordings in nonhuman primates have suggested a feedforward (FF) type profile for auditory evoked but feedback (FB) type for visual evoked activity in the auditory cortex. To test whether cross-sensory visual evoked activity in the auditory cortex is associated with FB inputs also in humans, we analyzed magnetoencephalography (MEG) responses from eight human subjects (six females) evoked by simple auditory or visual stimuli. In the estimated MEG source waveforms for auditory cortex regions of interest, auditory evoked response showed peaks at 37 and 90 ms and visual evoked response at 125 ms. The inputs to the auditory cortex were modeled through FF- and FB-type connections targeting different cortical layers using the Human Neocortical Neurosolver (HNN), which links cellular- and circuit-level mechanisms to MEG signals. HNN modeling suggested that the experimentally observed auditory response could be explained by an FF input followed by an FB input, whereas the cross-sensory visual response could be adequately explained by just an FB input. Thus, the combined MEG and HNN results support the hypothesis that cross-sensory visual input in the auditory cortex is of FB type. The results also illustrate how the dynamic patterns of the estimated MEG source activity can provide information about the characteristics of the input into a cortical area in terms of the hierarchical organization among areas.

The Early Subcortical Response at the Fundamental Frequency of Speech Is Temporally Separated from Later Cortical Contributions.

Most parts of speech are voiced, exhibiting a degree of periodicity with a fundamental frequency and many higher harmonics. Some neural populations respond to this temporal fine structure, in particular at the fundamental frequency. This frequency-following response to speech consists of both subcortical and cortical contributions and can be measured through EEG as well as through magnetoencephalography (MEG), although both differ in the aspects of neural activity that they capture: EEG is sensitive to both radial and tangential sources as well as to deep sources, whereas MEG is more restrained to the measurement of tangential and superficial neural activity. EEG responses to continuous speech have shown an early subcortical contribution, at a latency of around 9 msec, in agreement with MEG measurements in response to short speech tokens, whereas MEG responses to continuous speech have not yet revealed such an early component. Here, we analyze MEG responses to long segments of continuous speech. We find an early subcortical response at latencies of 4-11 msec, followed by later right-lateralized cortical activities at delays of 20-58 msec as well as potential subcortical activities. Our results show that the early subcortical component of the FFR to continuous speech can be measured from MEG in populations of participants and that its latency agrees with that measured with EEG. They furthermore show that the early subcortical component is temporally well separated from later cortical contributions, enabling an independent assessment of both components toward further aspects of speech processing.

Speech comprehension across time, space, frequency, and age: MEG-MVPA classification of intertrial phase coherence

Language is a key part of human cognition, essential for our well-being at all stages of our lives. Whereas many neurocognitive abilities decline with age, for language the picture is much less clear, and how exactly speech comprehension changes with ageing is still unknown. To investigate this, we employed magnetoencephalography (MEG) and recorded neuromagnetic brain responses to auditory linguistic stimuli in healthy participants of younger and older age using a passive task-free paradigm and a range of different linguistic stimulus contrasts, which enabled us to assess neural processing of spoken language at multiple levels (lexical, semantic, morphosyntactic). Using machine learning-based classification algorithms to scrutinise intertrial phase coherence of MEG responses in cortical source space, we found that patterns of oscillatory neural activity diverged between younger and older participants across several frequency bands (alpha, beta, gamma) for all tested linguistic information types. The results suggest multiple age-related changes in the brain's neurolinguistic circuits, which may be due to both healthy ageing in general and compensatory processes in particular.

Maturation of cortical responses to sound in the first year of life

Infants show sophisticated sound discrimination from the time they are born but the neural mechanisms that support infant auditory perception are not well understood. A central question is the discrepancy between the early onset of auditory skills and the protracted and extended maturation of the auditory cortex. To investigate the cortical processing of sound, we have been employing magnetoencephalography (MEG) with recent advancements in movement compensation to obtain functional neural measures of sound processing in awake infants. MEG responses from an Elekta Neuromag 306-channel system were recorded longitudinally at 3 (n = 27), 6 (n = 19), and 11 (n = 14) months to an ecologically salient bi-syllabic word and an amplitude-modulated complex tone pair in typically hearing infants. The neural generators of the MEG signals were determined using an equivalent current dipole (ECD) model. Our preliminary analyses have focused on two measures: cortical responses to acoustic change and the development of hemispheric lateralization to speech. Our preliminary analyses show that high quality MEG data with good signal-to-noise ratios can be obtained by 3 months and dipole modeling of MEG signals in combination with advanced movement compensation offers a temporally precise method of investigating the maturation of auditory cortical networks in infants.

Temporal hierarchy of cortical responses reflects core-belt-parabelt organization of auditory cortex in musicians.

Human auditory cortex (AC) organization resembles the core-belt-parabelt organization in nonhuman primates. Previous studies assessed mostly spatial characteristics; however, temporal aspects were little considered so far. We employed co-registration of functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) in musicians with and without absolute pitch (AP) to achieve spatial and temporal segregation of human auditory responses. First, individual fMRI activations induced by complex harmonic tones were consistently identified in four distinct regions-of-interest within AC, namely in medial Heschl's gyrus (HG), lateral HG, anterior superior temporal gyrus (STG), and planum temporale (PT). Second, we analyzed the temporal dynamics of individual MEG responses at the location of corresponding fMRI activations. In the AP group, the auditory evoked P2 onset occurred ~25ms earlier in the right as compared with the left PT and ~15ms earlier in the right as compared with the left anterior STG. This effect was consistent at the individual level and correlated with AP proficiency. Based on the combined application of MEG and fMRI measurements, we were able for the first time to demonstrate a characteristic temporal hierarchy ("chronotopy") of human auditory regions in relation to specific auditory abilities, reflecting the prediction for serial processing from nonhuman studies.

Altered binaural hearing in pre-ataxic and ataxic mutation carriers of spinocerebellar ataxia type 3

Brainstem degeneration is a prominent feature of spinocerebellar ataxia type 3 (SCA3), involving structures that execute binaural synchronization with microsecond precision. As a consequence, auditory processing may deteriorate during the course of disease. We tested whether the binaural “Huggins pitch” effect is suitable to study the temporal precision of brainstem functioning in SCA3 mutation carriers. We expected that they would have difficulties perceiving Huggins pitch at high frequencies, and that they would show attenuated neuromagnetic responses to Huggins pitch. The upper limit of Huggins pitch perception was psychoacoustically determined in 18 pre-ataxic and ataxic SCA3 mutation carriers and in 18 age-matched healthy controls. Moreover, the cortical N100 response following Huggins pitch onset was acquired by means of magnetoencephalography (MEG). MEG recordings were analyzed using dipole source modeling and comprised a monaural pitch condition and a no-pitch condition with simple binaural correlation changes. Compared with age-matched controls, ataxic but not pre-ataxic SCA3 mutation carriers had significantly lower frequency limits up to which Huggins pitch could be heard. Listeners with lower frequency limits also showed diminished MEG responses to Huggins pitch, but not in the two control conditions. Huggins pitch is a promising tool to assess brainstem functioning in ataxic SCA3 patients. Future studies should refine the psychophysiological setup to capture possible performance decrements also in pre-ataxic mutation carriers. Longitudinal observations will be needed to prove the potential of the assessment of Huggins pitch as a biomarker to track brainstem functioning during the disease course in SCA3.

Direct Estimation of Linear Filters for EEG Source-Localization in a Competing-Talker Scenario

Direct Estimation of Linear Filters for EEG Source-Localization in a Competing-Talker Scenario

Late dominance of the right hemisphere during narrative comprehension

PET and fMRI studies suggest that auditory narrative comprehension is supported by a bilateral multilobar cortical network. The superior temporal resolution of magnetoencephalography (MEG) makes it an attractive tool to investigate the dynamics of how different neuroanatomic substrates engage during narrative comprehension. Using beta-band power changes as a marker of cortical engagement, we studied MEG responses during an auditory story comprehension task in 31 healthy adults. The protocol consisted of two runs, each interleaving 7 blocks of the story comprehension task with 15 blocks of an auditorily presented math task as a control for phonological processing, working memory, and attention processes. Sources at the cortical surface were estimated with a frequency-resolved beamformer. Beta-band power was estimated in the frequency range of 16-24 Hz over 1-sec epochs starting from 400 msec after stimulus onset until the end of a story or math problem presentation. These power estimates were compared to 1-second epochs of data before the stimulus block onset. The task-related cortical engagement was inferred from beta-band power decrements. Group-level source activations were statistically compared using non-parametric permutation testing. A story-math contrast of beta-band power changes showed greater bilateral cortical engagement within the fusiform gyrus, inferior and middle temporal gyri, parahippocampal gyrus, and left inferior frontal gyrus (IFG) during story comprehension. A math-story contrast of beta power decrements showed greater bilateral but left-lateralized engagement of the middle frontal gyrus and superior parietal lobule. The evolution of cortical engagement during five temporal windows across the presentation of stories showed significant involvement during the first interval of the narrative of bilateral opercular and insular regions as well as the ventral and lateral temporal cortex, extending more posteriorly on the left and medially on the right. Over time, there continued to be sustained right anterior ventral temporal engagement, with increasing involvement of the right anterior parahippocampal gyrus, STG, MTG, posterior superior temporal sulcus, inferior parietal lobule, frontal operculum, and insula, while left hemisphere engagement decreased. Our findings are consistent with prior imaging studies of narrative comprehension, but in addition, they demonstrate increasing right-lateralized engagement over the course of narratives, suggesting an important role for these right-hemispheric regions in semantic integration as well as social and pragmatic inference processing.

Deep Recurrent Encoder: an end-to-end network to model magnetoencephalography at scale

Understanding how the brain responds to sensory inputs from non-invasive brain recordings like magnetoencephalography (MEG) can be particularly challenging: (i) the high-dimensional dynamics of mass neuronal activity are notoriously difficult to model, (ii) signals can greatly vary across subjects and trials and (iii) the relationship between these brain responses and the stimulus features is non-trivial. These challenges have led the community to develop a variety of preprocessing and analytical (almost exclusively linear) methods, each designed to tackle one of these issues. Instead, we propose to address these challenges through a specific end-to-end deep learning architecture, trained to predict the MEG responses of multiple subjects at once. We successfully test this approach on a large cohort of MEG recordings acquired during a one-hour reading task. Our Deep Recurrent Encoder (DRE) reliably predicts MEG responses to words with a three-fold improvement over classic linear methods. We further describe a simple variable importance analysis to investigate the MEG representations learnt by our model and recover the expected evoked responses to word length and word frequency. Last, we show that, contrary to linear encoders, our model captures modulations of the brain response in relation to baseline fluctuations in the alpha frequency band. The quantitative improvement of the present deep learning approach paves the way to a better characterization of the complex dynamics of brain activity from large MEG datasets.

Magnetoencephalography contrast adaptation reflects perceptual adaptation.

Contrast adaptation is a fundamental visual process that has been extensively investigated and used to infer the selectivity of visual cortex. We recently reported an apparent disconnect between the effects of contrast adaptation on perception and functional magnetic resonance imaging BOLD response adaptation, in which adaptation between chromatic and achromatic stimuli measured psychophysically showed greater selectivity than adaptation measured using BOLD signals. Here we used magnetoencephalography (MEG) recordings of neural responses to the same chromatic and achromatic adaptation conditions to characterize the neural effects of contrast adaptation and to determine whether BOLD adaptation or MEG better reflect the measured perceptual effects. Participants viewed achromatic, L-M isolating, or S-cone isolating radial sinusoids before adaptation and after adaptation to each of the three contrast directions. We measured adaptation-related changes in the neural response to a range of stimulus contrast amplitudes using two measures of the MEG response: the overall response amplitude, and a novel time-resolved measure of the contrast response function, derived from a classification analysis combined with multidimensional scaling. Within-stimulus adaptation effects on the contrast response functions in each case showed a pattern of contrast-gain or a combination of contrast-gain and response-gain effects. Cross-stimulus adaptation conditions showed that adaptation effects were highly stimulus selective across early, ventral, and dorsal visual cortical areas, consistent with the perceptual effects.

A MEG compatible, interactive IR game paradigm for the study of visuomotor reach-to-target movements in young children and clinical populations: The Target-Touch Motor Task

The conventional focus on discrete finger movements (i.e., index finger flexion or button-box key presses) has been an effective method to study neuromotor control using magnetoencephalography (MEG). However, this approach is challenging for young children and not possible for some people with physical disability. We have developed a novel, interactive MEG compatible reach-to-target task to investigate neuromotor function, specifically for use with young children. We used an infrared touch-screen frame to detect responses to targets presented using custom software. The game can be played using a conventional computer monitor or during MEG recordings via projector. We termed this game the Target-Touch Motor Task (TTMT). We demonstrate that the TTMT is a feasible motor task for use with young children including children with physical impairments. TTMT response-to-target trial counts are also comparable to conventional methods. Artifacts from the touch screen, while present >100Hz, did not affect MEG source analysis in the beta band (14-30Hz). MEG responses during TTMT game play reveal robust cortical activity from expected areas of motor cortex as typically observed following movements of the upper limb. The TTMT paradigm allows participation by individuals with a broad range of motor abilities on a reach-to-target' functional task rather than conventional tasks focusing on discrete finger movements. The TTMT is well suited for young children and successfully activates expected motor cortical areas. The TTMT opens-up new opportunities for the assessment of motor function across the lifespan, including for children with physical limitations.

The age-related changes in 40 Hz Auditory Steady-State Response and sustained Event-Related Fields to the same amplitude-modulated tones in typically developing children: A magnetoencephalography study.

Recent studies have revealed that gamma-band oscillatory and transient evoked potentials may change with age during childhood. It is hypothesized that these changes can be associated with a maturation of GABAergic neurotransmission and, subsequently, the age-related changes of excitation-inhibition balance in the neural circuits. One of the reliable paradigms for investigating these effects in the auditory cortex is 40 Hz Auditory Steady-State Response (ASSR), where participants are presented with the periodic auditory stimuli. It is known that such stimuli evoke two types of responses in magnetoencephalography (MEG)-40 Hz steady-state gamma response (or 40 Hz ASSR) and auditory evoked response called sustained Event-Related Field (ERF). Although several studies have been conducted in children, focusing on the changes of 40 Hz ASSR with age, almost nothing is known about the age-related changes of the sustained ERF to the same periodic stimuli and their relationships with changes in the gamma strength. Using MEG, we investigated the association between 40 Hz steady-state gamma response and sustained ERF response to the same stimuli and also their age-related changes in the group of 30 typically developing 7-to-12-year-old children. The results revealed a tight relationship between 40 Hz ASSR and ERF, indicating that the age-related increase in strength of 40 Hz ASSR was associated with the age-related decrease of the amplitude of ERF. These effects were discussed in the light of the maturation of the GABAergic system and excitation-inhibition balance development, which may contribute to the changes in ASSR and ERF.

Reproducibility of evoked and induced MEG responses to proprioceptive stimulation of the ankle joint

Cortical processing of proprioceptive afference can be investigated by examining phase locked evoked and induced responses in cortical signals to passive movement stimuli. Reproducibility of evoked and induced responses has been studied using electroencephalography (EEG), but proprioceptive domain has received little attention. It is unclear whether evoked and induced responses to proprioceptive stimulation arising from the lower limbs are reproducible using magnetoencephalography (MEG). Nineteen healthy volunteers (18 right-foot dominant, 36.1 ± 6.6 yr, 7 females) were measured in two MEG sessions separated by 9 ± 5 days in which their right ankle was rotated intermittently using a pneumatic movement actuator (160 stimuli, 3000 ± 250 ms interstimulus interval) to elicit evoked fields and induced responses. The peak evoked field amplitude used in the final analysis was calculated from the gradiometer pair yielding the peak vector sum over vertex ( i.e. , the primary sensorimotor cortex for the lower limb). Peak induced response amplitudes were analyzed from the peak gradiometer demonstrating the most robust beta suppression and beta rebound. The between session reproducibility was estimated using intra-class correlation coefficient (ICC). Evoked field amplitudes, beta suppression and beta rebound amplitudes all demonstrated a large inter-individual variation but excellent between session reproducibility (ICC >0.81). Kinematics of the proprioceptive stimuli were stable and did not correlate with MEG response strengths. The results indicate that evoked and induced responses to proprioceptive stimuli from the lower limbs are reproducible and provide a valid tool for longitudinal experiments investigating the processing of proprioceptive afference in e.g., different clinical populations, but caution is advised when comparing individuals using these measures.

Interaction within and between cortical networks subserving multisensory learning and its reorganization due to musical expertise

Recent advancements in the field of network science allow us to quantify inter-network information exchange and model the interaction within and between task-defined states of large-scale networks. Here, we modeled the inter- and intra- network interactions related to multisensory statistical learning. To this aim, we implemented a multifeatured statistical learning paradigm and measured evoked magnetoencephalographic responses to estimate task-defined state of functional connectivity based on cortical phase interaction. Each network state represented the whole-brain network processing modality-specific (auditory, visual and audiovisual) statistical learning irregularities embedded within a multisensory stimulation stream. The way by which domain-specific expertise re-organizes the interaction between the networks was investigated by a comparison of musicians and non-musicians. Between the modality-specific network states, the estimated connectivity quantified the characteristics of a supramodal mechanism supporting the identification of statistical irregularities that are compartmentalized and applied in the identification of uni-modal irregularities embedded within multisensory stimuli. Expertise-related re-organization was expressed by an increase of intra- and a decrease of inter-network connectivity, showing increased compartmentalization.