Characterizing directional dynamics of semantic prediction based on inter-regional temporal generalization.

The event-related potential/field component N400(m) has been widely used as a neural index for semantic prediction. It has long been hypothesized that feedback information from inferior frontal areas plays a critical role in generating the N400. However, due to limitations in causal connectivity estimation, direct testing of this hypothesis has remained difficult. Here, magnetoencephalography (MEG) data was obtained during a classic N400 paradigm where the semantic predictability of a fixed target noun was manipulated in simple German sentences. To estimate causality, we implemented a novel approach based on machine learning and temporal generalization to estimate the effect of inferior frontal gyrus (IFG) on temporal areas. In this method, a support vector machine (SVM) classifier is trained on each time point of the neural activity in IFG to classify less predicted (LP) and highly predicted (HP) nouns and then tested on all time points of superior/middle temporal sub-regions activity (and vice versa, to establish spatio-temporal evidence for or against causality). The decoding accuracy was significantly above chance level when the classifier was trained on IFG activity and tested on future activity in superior and middle temporal gyrus (STG/MTG). The results present new evidence for a model predictive speech comprehension where predictive IFG activity is fed back to shape subsequent activity in STG/MTG, implying a feedback mechanism in N400 generation. In combination with the also observed strong feedforward effect from left STG/MTG to IFG, our findings provide evidence of dynamic feedback and feedforward influences between IFG and temporal areas during N400 generation.

Both stronger and weaker cerebro-cerebellar functional connectivity patterns during processing of spoken sentences in autism spectrum disorder.

Cerebellar differences have long been documented in autism spectrum disorder (ASD), yet the extent to which such differences might impact language processing in ASD remains unknown. To investigate this, we recorded brain activity with magnetoencephalography (MEG) while ASD and age-matched typically developing (TD) children passively processed spoken meaningful English and meaningless Jabberwocky sentences. Using a novel source localization approach that allows higher resolution MEG source localization of cerebellar activity, we found that, unlike TD children, ASD children showed no difference between evoked responses to meaningful versus meaningless sentences in right cerebellar lobule VI. ASD children also had atypically weak functional connectivity in the meaningful versus meaningless speech condition between right cerebellar lobule VI and several left-hemisphere sensorimotor and language regions in later time windows. In contrast, ASD children had atypically strong functional connectivity for in the meaningful versus meaningless speech condition between right cerebellar lobule VI and primary auditory cortical areas in an earlier time window. The atypical functional connectivity patterns in ASD correlated with ASD severity and the ability to inhibit involuntary attention. These findings align with a model where cerebro-cerebellar speech processing mechanisms in ASD are impacted by aberrant stimulus-driven attention, which could result from atypical temporal information and predictions of auditory sensory events by right cerebellar lobule VI.

Comparing auditory and visual aspects of multisensory working memory using bimodally matched feature patterns.

Working memory (WM) reflects the transient maintenance of information in the absence of external input, which can be attained via multiple senses separately or simultaneously. Pertaining to WM, the prevailing literature suggests the dominance of vision over other sensory systems. However, this imbalance may be stemming from challenges in finding comparable stimuli across modalities. Here, we addressed this problem by using a balanced multisensory retro-cue WM design, which employed combinations of auditory (ripple sounds) and visuospatial (Gabor patches) patterns, adjusted relative to each participant's discrimination ability. In three separate experiments, the participant was asked to determine whether the (retro-cued) auditory and/or visual items maintained in WM matched or mismatched the subsequent probe stimulus. In Experiment 1, all stimuli were audiovisual, and the probes were either fully mismatching, only partially mismatching, or fully matching the memorized item. Experiment 2 was otherwise same as Experiment 1, but the probes were unimodal. In Experiment 3, the participant was cued to maintain only the auditory or visual aspect of an audiovisual item pair. In two of the three experiments, the participant matching performance was significantly more accurate for the auditory than visual attributes of probes. When the perceptual and task demands are bimodally equated, auditory attributes can be matched to multisensory items in WM at least as accurately as, if not more precisely than, their visual counterparts.

No Differences in Auditory Steady-State Responses in Children with Autism Spectrum Disorder and Typically Developing Children.

Auditory steady-state response (ASSR) has been studied as a potential biomarker for abnormal auditory sensory processing in autism spectrum disorder (ASD), with mixed results. Motivated by prior somatosensory findings of group differences in inter-trial coherence (ITC) between ASD and typically developing (TD) individuals at twice the steady-state stimulation frequency, we examined ASSR at 25 and 50 as well as 43 and 86 Hz in response to 25-Hz and 43-Hz auditory stimuli, respectively, using magnetoencephalography. Data were recorded from 22 ASD and 31 TD children, ages 6-17 years. ITC measures showed prominent ASSRs at the stimulation and double frequencies, without significant group differences. These results do not support ASSR as a robust ASD biomarker of abnormal auditory processing in ASD. Furthermore, the previously observed atypical double-frequency somatosensory response in ASD did not generalize to the auditory modality. Thus, the hypothesis about modality-independent abnormal local connectivity in ASD was not supported.

Spectrotemporal content of human auditory working memory represented in functional connectivity patterns.

Recent research suggests that working memory (WM), the mental sketchpad underlying thinking and communication, is maintained by multiple regions throughout the brain. Whether parts of a stable WM representation could be distributed across these brain regions is, however, an open question. We addressed this question by examining the content-specificity of connectivity-pattern matrices between subparts of cortical regions-of-interest (ROI). These connectivity patterns were calculated from functional MRI obtained during a ripple-sound auditory WM task. Statistical significance was assessed by comparing the decoding results to a null distribution derived from a permutation test considering all comparable two- to four-ROI connectivity patterns. Maintained WM items could be decoded from connectivity patterns across ROIs in frontal, parietal, and superior temporal cortices. All functional connectivity patterns that were specific to maintained sound content extended from early auditory to frontoparietal cortices. Our results demonstrate that WM maintenance is supported by content-specific patterns of functional connectivity across different levels of cortical hierarchy.

Atypical cortical processing of bottom-up speech binding cues in children with autism spectrum disorders.

Individuals with autism spectrum disorder (ASD) commonly display speech processing abnormalities. Binding of acoustic features of speech distributed across different frequencies into coherent speech objects is fundamental in speech perception. Here, we tested the hypothesis that the cortical processing of bottom-up acoustic cues for speech binding may be anomalous in ASD. We recorded magnetoencephalography while ASD children (ages 7-17) and typically developing peers heard sentences of sine-wave speech (SWS) and modulated SWS (MSS) where binding cues were restored through increased temporal coherence of the acoustic components and the introduction of harmonicity. The ASD group showed increased long-range feedforward functional connectivity from left auditory to parietal cortex with concurrent decreased local functional connectivity within the parietal region during MSS relative to SWS. As the parietal region has been implicated in auditory object binding, our findings support our hypothesis of atypical bottom-up speech binding in ASD. Furthermore, the long-range functional connectivity correlated with behaviorally measured auditory processing abnormalities, confirming the relevance of these atypical cortical signatures to the ASD phenotype. Lastly, the group difference in the local functional connectivity was driven by the youngest participants, suggesting that impaired speech binding in ASD might be ameliorated upon entering adolescence.

Cortical depth profiles of auditory and visual 7 T functional MRI responses in human superior temporal areas.

Invasive neurophysiological studies in nonhuman primates have shown different laminar activation profiles to auditory vs. visual stimuli in auditory cortices and adjacent polymodal areas. Means to examine the underlying feedforward vs. feedback type influences noninvasively have been limited in humans. Here, using 1-mm isotropic resolution 3D echo-planar imaging at 7 T, we studied the intracortical depth profiles of functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) signals to brief auditory (noise bursts) and visual (checkerboard) stimuli. BOLD percent-signal-changes were estimated at 11 equally spaced intracortical depths, within regions-of-interest encompassing auditory (Heschl's gyrus, Heschl's sulcus, planum temporale, and posterior superior temporal gyrus) and polymodal (middle and posterior superior temporal sulcus) areas. Effects of differing BOLD signal strengths for auditory and visual stimuli were controlled via normalization and statistical modeling. The BOLD depth profile shapes, modeled with quadratic regression, were significantly different for auditory vs. visual stimuli in auditory cortices, but not in polymodal areas. The different depth profiles could reflect sensory-specific feedforward versus cross-sensory feedback influences, previously shown in laminar recordings in nonhuman primates. The results suggest that intracortical BOLD profiles can help distinguish between feedforward and feedback type influences in the human brain. Further experimental studies are still needed to clarify how underlying signal strength influences BOLD depth profiles under different stimulus conditions.

Wearable-Based Stair Climb Power Estimation and Activity Classification.

Stair climb power (SCP) is a clinical measure of leg muscular function assessed in-clinic via the Stair Climb Power Test (SCPT). This method is subject to human error and cannot provide continuous remote monitoring. Continuous monitoring using wearable sensors may provide a more comprehensive assessment of lower-limb muscular function. In this work, we propose an algorithm to classify stair climbing periods and estimate SCP from a lower-back worn accelerometer, which strongly agrees with the clinical standard (r = 0.92, p < 0.001; ICC = 0.90, [0.82, 0.94]). Data were collected in-lab from healthy adults (n = 65) performing the four-step SCPT and a walking assessment while instrumented (accelerometer + gyroscope), which allowed us to investigate tradeoffs between sensor modalities. Using two classifiers, we were able to identify periods of stair ascent with >89% accuracy [sensitivity = >0.89, specificity = >0.90] using two ensemble machine learning algorithms, trained on accelerometer signal features. Minimal changes in model performances were observed using the gyroscope alone (±0−6% accuracy) versus the accelerometer model. While we observed a slight increase in accuracy when combining gyroscope and accelerometer (about +3−6% accuracy), this is tolerable to preserve battery life in the at-home environment. This work is impactful as it shows potential for an accelerometer-based at-home assessment of SCP.

Functional Significance of Human Resting-State Networks Hubs Identified Using MEG During the Transition From Childhood to Adulthood.

Cortical hubs identified within resting-state networks (RSNs), areas of the cortex that have a higher-than-average number of connections, are known to be critical to typical cognitive functioning and are often implicated in disorders leading to abnormal cognitive functioning. Functionally defined cortical hubs are also known to change with age in the developing, maturing brain, mostly based on studies carried out using fMRI. We have recently used magnetoencephalography (MEG) to study the maturation trajectories of RSNs and their hubs from age 7 to 29 in 131 healthy participants with high temporal resolution. We found that maturation trajectories diverge as a function of the underlying cortical rhythm. Specifically, we found the beta band (13-30 Hz)-mediated RSNs became more locally efficient with maturation, i.e., more organized into clusters and connected with nearby regions, while gamma (31-80 Hz)-mediated RSNs became more globally efficient with maturation, i.e., prioritizing faster signal transmission between distant cortical regions. We also found that different sets of hubs were associated with each of these networks. To better understand the functional significance of this divergence, we wanted to examine the cortical functions associated with the identified hubs that grew or shrunk with maturation within each of these networks. To that end, we analyzed the results of the prior study using Neurosynth, a platform for large-scale, automated synthesis of fMRI data that links brain coordinates with their probabilistically associated terms. By mapping the Neurosynth terms associated with each of these hubs, we found that maturing hubs identified in the gamma band RSNs were more likely to be associated with bottom-up processes while maturing hubs identified in the beta band RSNs were more likely to be associated with top-down functions. The results were consistent with the idea that beta band-mediated networks preferentially support the maturation of top-down processing, while the gamma band-mediated networks preferentially support the maturation of bottom-up processing.

Cortical signatures of auditory object binding in children with autism spectrum disorder are anomalous in concordance with behavior and diagnosis.

Organizing sensory information into coherent perceptual objects is fundamental to everyday perception and communication. In the visual domain, indirect evidence from cortical responses suggests that children with autism spectrum disorder (ASD) have anomalous figure-ground segregation. While auditory processing abnormalities are common in ASD, especially in environments with multiple sound sources, to date, the question of scene segregation in ASD has not been directly investigated in audition. Using magnetoencephalography, we measured cortical responses to unattended (passively experienced) auditory stimuli while parametrically manipulating the degree of temporal coherence that facilitates auditory figure-ground segregation. Results from 21 children with ASD (aged 7-17 years) and 26 age- and IQ-matched typically developing children provide evidence that children with ASD show anomalous growth of cortical neural responses with increasing temporal coherence of the auditory figure. The documented neurophysiological abnormalities did not depend on age, and were reflected both in the response evoked by changes in temporal coherence of the auditory scene and in the associated induced gamma rhythms. Furthermore, the individual neural measures were predictive of diagnosis (83% accuracy) and also correlated with behavioral measures of ASD severity and auditory processing abnormalities. These findings offer new insight into the neural mechanisms underlying auditory perceptual deficits and sensory overload in ASD, and suggest that temporal-coherence-based auditory scene analysis and suprathreshold processing of coherent auditory objects may be atypical in ASD.

Safety, pharmacokinetics and quantitative EEG modulation of TAK-071, a novel muscarinic M1 receptor positive allosteric modulator, in healthy subjects.

AIMS: TAK-071 is a muscarinic M1 receptor positive allosteric modulator designed to have low cooperativity with acetylcholine. This was a first-in-human study to evaluate the safety, pharmacokinetics, and pharmacodynamics of TAK-071. METHODS: TAK-071 was administered as single and multiple doses in a randomized, double-blind, placebo-controlled, parallel-group design in healthy volunteers alone and in combination with donepezil. Laboratory, electrocardiogram (ECG) and electroencephalogram (EEG) evaluations were performed. Cerebrospinal fluid and blood samples were taken to evaluate the pharmacokinetics (PK), relative bioavailability and food effect. RESULTS: TAK-071 was safe and well tolerated, and no deaths or serious adverse events occurred. TAK-071 demonstrated a long mean (% coefficient of variation) half-life of 46.3 (25.2%) to 60.5 (51.5%) hours and excellent brain penetration following oral dosing. Coadministration with donepezil had no impact on the PK of either drug. There was no food effect on systemic exposure. Quantitative EEG analysis revealed that TAK-071 40-80 mg increased power in the 7-9 Hz range in the posterior electrode group with eyes open and 120-160 mg doses increased power in the 16-18 Hz range and reduced power in the 2-4 Hz range in central-posterior areas with eyes open and eyes closed. Functional connectivity was significantly reduced after TAK-071 at high doses and was enhanced with coadministration of donepezil under the eyes-closed condition. CONCLUSIONS: PK and safety profiles of TAK-071 were favorable, including those exceeding expected pharmacologically active doses based on preclinical data. When administered without donepezil TAK-071 was largely free of cholinergic adverse effects. Further clinical evaluation of TAK-071 is warranted.

Synchronization patterns reveal neuronal coding of working memory content.

Neuronal oscillations are suggested to play an important role in auditory working memory (WM), but their contribution to content-specific representations has remained unclear. Here, we measure magnetoencephalography during a retro-cueing task with parametric ripple-sound stimuli, which are spectrotemporally similar to speech but resist non-auditory memory strategies. Using machine learning analyses, with rigorous between-subject cross-validation and non-parametric permutation testing, we show that memorized sound content is strongly represented in phase-synchronization patterns between subregions of auditory and frontoparietal cortices. These phase-synchronization patterns predict the memorized sound content steadily across the studied maintenance period. In addition to connectivity-based representations, there are indices of more local, "activity silent" representations in auditory cortices, where the decoding accuracy of WM content significantly increases after task-irrelevant "impulse stimuli." Our results demonstrate that synchronization patterns across auditory sensory and association areas orchestrate neuronal coding of auditory WM content. This connectivity-based coding scheme could also extend beyond the auditory domain.

Altered maturation and atypical cortical processing of spoken sentences in autism spectrum disorder.

Autism spectrum disorder (ASD) is associated with widespread receptive language impairments, yet the neural mechanisms underlying these deficits are poorly understood. Neuroimaging has shown that processing of socially-relevant sounds, including speech and non-speech, is atypical in ASD. However, it is unclear how the presence of lexical-semantic meaning affects speech processing in ASD. Here, we recorded magnetoencephalography data from individuals with ASD (N = 22, ages 7-17, 4 females) and typically developing (TD) peers (N = 30, ages 7-17, 5 females) during unattended listening to meaningful auditory speech sentences and meaningless jabberwocky sentences. After adjusting for age, ASD individuals showed stronger responses to meaningless jabberwocky sentences than to meaningful speech sentences in the same left temporal and parietal language regions where TD individuals exhibited stronger responses to meaningful speech. Maturational trajectories of meaningful speech responses were atypical in temporal, but not parietal, regions in ASD. Temporal responses were associated with ASD severity, while parietal responses were associated with aberrant involuntary attentional shifting in ASD. Our findings suggest a receptive speech processing dysfunction in ASD, wherein unattended meaningful speech elicits abnormal engagement of the language system, while unattended meaningless speech, filtered out in TD individuals, engages the language system through involuntary attention capture.

Auditory cues facilitate object movement processing in human extrastriate visual cortex during simulated self-motion: A pilot study.

Visual segregation of moving objects is a considerable computational challenge when the observer moves through space. Recent psychophysical studies suggest that directionally congruent, moving auditory cues can substantially improve parsing object motion in such settings, but the exact brain mechanisms and visual processing stages that mediate these effects are still incompletely known. Here, we utilized multivariate pattern analyses (MVPA) of MRI-informed magnetoencephalography (MEG) source estimates to examine how crossmodal auditory cues facilitate motion detection during the observer's self-motion. During MEG recordings, participants identified a target object that moved either forward or backward within a visual scene that included nine identically textured objects simulating forward observer translation. Auditory motion cues 1) improved the behavioral accuracy of target localization, 2) significantly modulated the MEG source activity in the areas V2 and human middle temporal complex (hMT+), and 3) increased the accuracy at which the target movement direction could be decoded from hMT+ activity using MVPA. The increase of decoding accuracy by auditory cues in hMT+ was significant also when superior temporal activations in or near auditory cortices were regressed out from the hMT+ source activity to control for source estimation biases caused by point spread. Taken together, these results suggest that parsing object motion from self-motion-induced optic flow in the human extrastriate visual cortex can be facilitated by crossmodal influences from auditory system.

Children with autism spectrum disorder show altered functional connectivity and abnormal maturation trajectories in response to inverted faces.

The processing of information conveyed by faces is a critical component of social communication. While the neurophysiology of processing upright faces has been studied extensively in autism spectrum disorder (ASD), less is known about the neurophysiological abnormalities associated with processing inverted faces in ASD. We used magnetoencephalography (MEG) to study both long-range and local functional connectivity, with the latter assessed using local cross-frequency coupling, in response to inverted faces stimuli, in 7-18 years old individuals with ASD and age and IQ matched typically developing (TD) individuals. We found abnormally reduced coupling between the phase of the alpha rhythm and the amplitude of the gamma rhythm in the fusiform face area (FFA) in response to inverted faces, as well as reduced long-range functional connectivity between the FFA and the inferior frontal gyrus (IFG) in response to inverted faces in the ASD group. These group differences were absent in response to upright faces. The magnitude of functional connectivity between the FFA and the IFG was significantly correlated with the severity of ASD, and FFA-IFG long-range functional connectivity increased with age in TD group, but not in the ASD group. Our findings suggest that both local and long-range functional connectivity are abnormally reduced in children with ASD when processing inverted faces, and that the pattern of abnormalities associated with the processing of inverted faces differs from the pattern of upright faces in ASD, likely due to the presumed greater reliance on top-down regulations necessary for efficient processing of inverted faces. LAY SUMMARY: We found alterations in the neurophysiological responses to inverted faces in children with ASD, that were not reflected in the evoked responses, and were not observed in the responses to upright faces. These alterations included reduced local functional connectivity in the fusiform face area (FFA), and decreased long-range alpha-band modulated functional connectivity between the FFA and the left IFG. The magnitude of long-range functional connectivity between the FFA and the inferior frontal gyrus was correlated with the severity of ASD.

Classification of evoked responses to inverted faces reveals both spatial and temporal cortical response abnormalities in Autism spectrum disorder.

The neurophysiology of face processing has been studied extensively in the context of social impairments associated with autism spectrum disorder (ASD), but the existing studies have concentrated mainly on univariate analyses of responses to upright faces, and, less frequently, inverted faces. The small number of existing studies on neurophysiological responses to inverted face in ASD have used univariate approaches, with divergent results. Here, we used a data-driven, classification-based, multivariate machine learning decoding approach to investigate the temporal and spatial properties of the neurophysiological evoked response for upright and inverted faces, relative to the neurophysiological evoked response for houses, a neutral stimulus. 21 (2 females) ASD and 29 (4 females) TD participants ages 7 to 19 took part in this study. Group level classification accuracies were obtained for each condition, using first the temporal domain of the evoked responses, and then the spatial distribution of the evoked responses on the cortical surface, each separately. We found that classification of responses to inverted neutral faces vs. houses was less accurate in ASD compared to TD, in both the temporal and spatial domains. In contrast, there were no group differences in the classification of evoked responses to upright neutral faces relative to houses. Using the classification in the temporal domain, lower decoding accuracies in ASD were found around 120 ms and 170 ms, corresponding the known components of the evoked responses to faces. Using the classification in the spatial domain, lower decoding accuracies in ASD were found in the right superior marginal gyrus (SMG), intra-parietal sulcus (IPS) and posterior superior temporal sulcus (pSTS), but not in core face processing areas. Importantly, individual classification accuracies from both the temporal and spatial classifiers correlated with ASD severity, confirming the relevance of the results to the ASD phenotype.

Spatial fidelity of MEG/EEG source estimates: A general evaluation approach.

Low spatial resolution is often cited as the most critical limitation of magneto- and electroencephalography (MEG and EEG), but a unifying framework for quantifying the spatial fidelity of M/EEG source estimates has yet to be established; previous studies have focused on linear estimation methods under ideal scenarios without noise. Here we present an approach that quantifies the spatial fidelity of M/EEG estimates from simulated patch activations over the entire neocortex superposed on measured resting-state data. This approach grants more generalizability in the evaluation process that allows for, e.g., comparing linear and non-linear estimates in the whole brain for different signal-to-noise ratios (SNR), number of active sources and activation waveforms. Using this framework, we evaluated the MNE, dSPM, sLORETA, eLORETA, and MxNE methods and found that the spatial fidelity varies significantly with SNR, following a largely sigmoidal curve whose shape varies depending on which aspect of spatial fidelity that is being quantified and the source estimation method. We believe that these methods and results will be useful when interpreting M/EEG source estimates as well as in methods development.

Distinct Regional Oscillatory Connectivity Patterns During Auditory Target and Novelty Processing.

Auditory attention allows us to focus on relevant target sounds in the acoustic environment while maintaining the capability to orient to unpredictable (novel) sound changes. An open question is whether orienting to expected vs. unexpected auditory events are governed by anatomically distinct attention pathways, respectively, or by differing communication patterns within a common system. To address this question, we applied a recently developed PeSCAR analysis method to evaluate spectrotemporal functional connectivity patterns across subregions of broader cortical regions of interest (ROIs) to analyze magnetoencephalography data obtained during a cued auditory attention task. Subjects were instructed to detect a predictable harmonic target sound embedded among standard tones in one ear and to ignore the standard tones and occasional unpredictable novel sounds presented in the opposite ear. Phase coherence of estimated source activity was calculated between subregions of superior temporal, frontal, inferior parietal, and superior parietal cortex ROIs. Functional connectivity was stronger in response to target than novel stimuli between left superior temporal and left parietal ROIs and between left frontal and right parietal ROIs, with the largest effects observed in the beta band (15-35 Hz). In contrast, functional connectivity was stronger in response to novel than target stimuli in inter-hemispheric connections between left and right frontal ROIs, observed in early time windows in the alpha band (8-12 Hz). Our findings suggest that auditory processing of expected target vs. unexpected novel sounds involves different spatially, temporally, and spectrally distributed oscillatory connectivity patterns across temporal, parietal, and frontal areas.

Permutation Statistics for Connectivity Analysis between Regions of Interest in EEG and MEG Data.

Connectivity estimates based on electroencephalography (EEG) and magnetoencephalography (MEG) are unique in their ability to provide neurophysiologically meaningful spectral and temporal information non-invasively. This multi-dimensional aspect of the MEG/EEG based connectivity increases the challenges of the analysis and interpretation of the data. Many MEG/EEG studies address this complexity by using a hypothesis-driven approach, which focuses on particular regions of interest (ROI). However, if an effect is distributed unevenly over a large ROI and variable across subjects, it may not be detectable using conventional methods. Here, we propose a novel approach, which enhances the statistical power for weak and spatially discontinuous effects. This results in the ability to identify statistically significant connectivity patterns with spectral, temporal, and spatial specificity while correcting for multiple comparisons using nonparametric permutation methods. We call this new approach the Permutation Statistics for Connectivity Analysis between ROI (PeSCAR). We demonstrate the processing steps with simulated and real human data. The open-source Matlab code implementing PeSCAR are provided online.

Oscillatory dynamics of cortical functional connections in semantic prediction.

An event related potential, known as the N400, has been particularly useful in investigating language processing as it serves as a neural index for semantic prediction. There are numerous studies on the functional segregation of N400 neural sources; however, the oscillatory dynamics of functional connections among the relevant sources has remained elusive. In this study we acquired magnetoencephalography data during a classic N400 paradigm, where the semantic predictability of a fixed target noun was manipulated in simple German sentences. We conducted inter-regional functional connectivity (FC) and time-frequency analysis on known regions of the semantic network, encompassing bilateral temporal, and prefrontal cortices. Increased FC was found in less predicted (LP) nouns compared with highly predicted (HP) nouns in three connections: (a) right inferior frontal gyrus (IFG) and right middle temporal gyrus (MTG) from 0 to 300 ms mainly within the alpha band, (b) left lateral orbitofrontal (LOF) and right IFG around 400 ms within the beta band, and (c) left superior temporal gyrus (STG) and left LOF from 300 to 700 ms in the beta and low gamma bands. Furthermore, gamma spectral power (31-70 Hz) was stronger in HP nouns than in LP nouns in left anterior temporal cortices in earlier time windows (0-200 ms). Our findings support recent theories in language comprehension, suggesting fronto-temporal top-down connections are mainly mediated through beta oscillations while gamma band frequencies are involved in matching between prediction and input.