Sources of auditory brainstem responses revisited: contribution by magnetoencephalography

EEG/MEG source imaging of deep brain activity within the maximum entropy on the mean framework: Simulations and validation in epilepsy

Electro/Magneto-EncephaloGraphy (EEG/MEG) source imaging (EMSI) of epileptic activity from deep generators is often challenging due to the higher sensitivity of EEG/MEG to superficial regions and to the spatial configuration of subcortical structures. We previously demonstrated the ability of the coherent Maximum Entropy on the Mean (cMEM) method to accurately localize the superficial cortical generators and their spatial extent. Here, we propose a depth-weighted adaptation of cMEM to localize deep generators more accurately. These methods were evaluated using realistic MEG/high-density EEG (HD-EEG) simulations of epileptic activity and actual MEG/HD-EEG recordings from patients with focal epilepsy. We incorporated depth-weighting within the MEM framework to compensate for its preference for superficial generators. We also included a mesh of both hippocampi, as an additional deep structure in the source model. We generated 5400 realistic simulations of interictal epileptic discharges for MEG and HD-EEG involving a wide range of spatial extents and signal-to-noise ratio (SNR) levels, before investigating EMSI on clinical HD-EEG in 16 patients and MEG in 14 patients. Clinical interictal epileptic discharges were marked by visual inspection. We applied three EMSI methods: cMEM, depth-weighted cMEM and depth-weighted minimum norm estimate (MNE). The ground truth was defined as the true simulated generator or as a drawn region based on clinical information available for patients. For deep sources, depth-weighted cMEM improved the localization when compared to cMEM and depth-weighted MNE, whereas depth-weighted cMEM did not deteriorate localization accuracy for superficial regions. For patients' data, we observed improvement in localization for deep sources, especially for the patients with mesial temporal epilepsy, for which cMEM failed to reconstruct the initial generator in the hippocampus. Depth weighting was more crucial for MEG (gradiometers) than for HD-EEG. Similar findings were found when considering depth weighting for the wavelet extension of MEM. In conclusion, depth-weighted cMEM improved the localization of deep sources without or with minimal deterioration of the localization of the superficial sources. This was demonstrated using extensive simulations with MEG and HD-EEG and clinical MEG and HD-EEG for epilepsy patients.

Reduced thalamic activity in ADHD under ABR forward masking conditions

Attention-deficit hyperactivity disorder (ADHD) is a common chronic neurodevelopmental disorder characterized by symptoms of inattention, overactivity, and/or impulsiveness. The prevalence of ADHD varies in different settings and there have been voices raised to call for more objective measures in order to avoid over- and underdiagnosing of ADHD. Auditory Brainstem Response (ABR) is a method where click shaped sounds evoke potentials that are recorder from electrodes on the skull of a patient. The aim of this study was to explore possible alterations in the ABR of 29 patients with ADHD compared to 39 healthy controls. We used a forward masked sound. We found differences in ABR that correspond to the thalamic area. The thalamus seems to play an active role in regulation of activity level in ADHD. More research is needed to draw any further conclusions on using ABR as an objective measurement to detect ADHD.

Auditory brainstem response to paired clicks as a candidate marker of cochlear synaptopathy in humans

OBJECTIVE

This study aimed to evaluate whether auditory brainstem response (ABR) using a paired-click stimulation paradigm could serve as a tool for detecting cochlear synaptopathy (CS).

METHODS

The ABRs to single-clicks and paired-clicks with various inter-click intervals (ICIs) and scores for word intelligibility in degraded listening conditions were obtained from 57 adults with normal hearing. The wave I peak amplitude and root mean square values for the post-wave I response within a range delayed from the wave I peak (referred to as the RMSpost-w1) were calculated for the single- and second-click responses.

RESULTS

The wave I peak amplitudes did not correlate with age except for the second-click responses at an ICI of 7 ms, and the word intelligibility scores. However, we found that the RMSpost-w1 values for the second-click responses significantly decreased with increasing age. Moreover, the RMSpost-w1 values for the second-click responses at an ICI of 5 ms correlated significantly with the scores for word intelligibility in degraded listening conditions.

CONCLUSIONS

The magnitude of the post-wave I response for the second-click response could serve as a tool for detecting CS in humans.

SIGNIFICANCE

Our findings shed new light on the analytical methods of ABR for quantifying CS.

Newborn Hearing Screening Results for Infants With Prenatal Opioid Exposure in Southern Appalachia

PURPOSE

Infants prenatally exposed to opioids exhibit withdrawal symptomology that introduce physiological noise and can impact newborn hearing screening results. This study compared the referral rate and physiological noise interpreted by number of trials rejected due to artifact on initial newborn hearing screenings of infants with prenatal opioid exposure (POE) and infants with no opioid exposure (NOE). Furthermore, within the POE group, it examined the relationship of referral rates with severity of withdrawal symptomology, and with maternal and infant risk factors.

METHOD

This study used a retrospective cohort design of electronic medical records from six delivery hospitals in South-Central Appalachia. Newborn hearing screenings were conducted using automated auditory brainstem response (ABR) for 334 infants with POE and 226 infants with NOE. Severity of withdrawal symptomology was measured using the Modified Finnegan Neonatal Abstinence Scoring Tool, which includes observation of behaviors that introduce physiological noise.

RESULTS

There was no significant difference in newborn hearing screening referral rate between infants with POE and infants with NOE. Referral rate was not affected by maternal or infant risk factors. Infants with POE had statistically significant higher artifact (defined as rejected ABR sweeps) than infants with NOE. There was a strong positive correlation between Finnegan scores and artifact but not referral rates. Sensitivity and specificity analysis indicated artifact decreased substantially after Day 4 of life.

CONCLUSIONS

Referral rates of infants with POE were similar to those of infants with NOE. Nevertheless, the withdrawal symptomology of infants with POE introduces physiological noise reflected as artifact on ABR, which can affect efficiency of newborn hearing screenings.

Hidden hearing loss: Fifteen years at a glance

Hearing loss affects approximately 18% of the population worldwide. Hearing difficulties in noisy environments without accompanying audiometric threshold shifts likely affect an even larger percentage of the global population. One of the potential causes of hidden hearing loss is cochlear synaptopathy, the loss of synapses between inner hair cells (IHC) and auditory nerve fibers (ANF). These synapses are the most vulnerable structures in the cochlea to noise exposure or aging. The loss of synapses causes auditory deafferentation, i.e., the loss of auditory afferent information, whose downstream effect is the loss of information that is sent to higher-order auditory processing stages. Understanding the physiological and perceptual effects of this early auditory deafferentation might inform interventions to prevent later, more severe hearing loss. In the past decade, a large body of work has been devoted to better understand hidden hearing loss, including the causes of hidden hearing loss, their corresponding impact on the auditory pathway, and the use of auditory physiological measures for clinical diagnosis of auditory deafferentation. This review synthesizes the findings from studies in humans and animals to answer some of the key questions in the field, and it points to gaps in knowledge that warrant more investigation. Specifically, recent studies suggest that some electrophysiological measures have the potential to function as indicators of hidden hearing loss in humans, but more research is needed for these measures to be included as part of a clinical test battery.

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.

Auditory Brainstem Response in a Child with Mitochondrial Disorder-Leigh Syndrome

The mitochondrial disorder-Leigh syndrome is a neurodegenerative disorder often manifested with brainstem abnormalities. The case report highlights the auditory brainstem response in a child with medical findings suggestive of Leigh syndrome. The case report also emphasizes the importance of ruling out any underlying neural pathology before making a clinical impression in children with developmental delays.

Rapid and objective assessment of auditory temporal processing using dynamic amplitude-modulated stimuli

Auditory neural coding of speech-relevant temporal cues can be noninvasively probed using envelope following responses (EFRs), neural ensemble responses phase-locked to the stimulus amplitude envelope. EFRs emphasize different neural generators, such as the auditory brainstem or auditory cortex, by altering the temporal modulation rate of the stimulus. EFRs can be an important diagnostic tool to assess auditory neural coding deficits that go beyond traditional audiometric estimations. Existing approaches to measure EFRs use discrete amplitude modulated (AM) tones of varying modulation frequencies, which is time consuming and inefficient, impeding clinical translation. Here we present a faster and more efficient framework to measure EFRs across a range of AM frequencies using stimuli that dynamically vary in modulation rates, combined with spectrally specific analyses that offer optimal spectrotemporal resolution. EFRs obtained from several species (humans, Mongolian gerbils, Fischer-344 rats, and Cba/CaJ mice) showed robust, high-SNR tracking of dynamic AM trajectories (up to 800Hz in humans, and 1.4 kHz in rodents), with a fivefold decrease in recording time and thirtyfold increase in spectrotemporal resolution. EFR amplitudes between dynamic AM stimuli and traditional discrete AM tokens within the same subjects were highly correlated (94% variance explained) across species. Hence, we establish a time-efficient and spectrally specific approach to measure EFRs. These results could yield novel clinical diagnostics for precision audiology approaches by enabling rapid, objective assessment of temporal processing along the entire auditory neuraxis.

80 Hz auditory steady state responses (ASSR) elicited by silent gaps embedded within a broadband noise

Introduction

Although auditory temporal processing plays an important role in speech comprehension, it cannot be measured by pure tone audiometry. Auditory temporal resolution is often assessed by behavioral gaps-in-noise test. To evaluate whether auditory temporal resolution could be objectively assessed, we measured the auditory steady state response (ASSR) elicited by silent gaps embedded within broadband noises at 80 Hz.

Methods

We prepared six sound types as test stimuli. One was a continuous broadband noise without a silent interval as a control stimulus and the others were broadband noises with 80 Hz silent intervals of 0.4, 0.8, 1.6, 3.1, and 6.3 ms.

Results

Significant ASSRs were recorded only when the gap length was longer than the behavioral thresholds and the ASSR amplitude increased as the gap length increased.

Conclusion

Eighty Hertz gap-evoked ASSR appears to reflect the neural activity related to the auditory gap processing and may be used as an objective measure of auditory temporal resolution in humans.

The IAS-MEEG Package: A Flexible Inverse Source Reconstruction Platform for Reconstruction and Visualization of Brain Activity from M/EEG Data

We present a standalone Matlab software platform complete with visualization for the reconstruction of the neural activity in the brain from MEG or EEG data. The underlying inversion combines hierarchical Bayesian models and Krylov subspace iterative least squares solvers. The Bayesian framework of the underlying inversion algorithm allows to account for anatomical information and possible a priori belief about the focality of the reconstruction. The computational efficiency makes the software suitable for the reconstruction of lengthy time series on standard computing equipment. The algorithm requires minimal user provided input parameters, although the user can express the desired focality and accuracy of the solution. The code has been designed so as to favor the parallelization performed automatically by Matlab, according to the resources of the host computer. We demonstrate the flexibility of the platform by reconstructing activity patterns with supports of different sizes from MEG and EEG data. Moreover, we show that the software reconstructs well activity patches located either in the subcortical brain structures or on the cortex. The inverse solver and visualization modules can be used either individually or in combination. We also provide a version of the inverse solver that can be used within Brainstorm toolbox. All the software is available online by Github, including the Brainstorm plugin, with accompanying documentation and test data.

Auditory-limbic-cerebellum interactions and cognitive impairments in noise-induced hearing loss

AIMS

This study aimed to explore the neural substrate of hearing loss-related central nervous system in rats and its correlation with cognition.

METHODS

We identified the neural mechanism for these debilitating abnormalities by inducing a bilateral hearing loss animal model using intense broadband noise (122 dB of broadband noise for 2 h) and used the Morris water maze test to characterize the behavioral changes at 6 months post-noise exposure. Functional magnetic resonance imaging (fMRI) was conducted to clarify disrupted functional network using bilateral auditory cortex (ACx) as a seed. Structural diffusion tensor imaging (DTI) was applied to illustrate characteristics of fibers in ACx and hippocampus. Pearson correlation was computed behavioral tests and other features.

RESULTS

A deficit in spatial learning/memory, body weight, and negative correlation between them was observed. Functional connectivity revealed weakened coupling within the ACx and inferior colliculus, lateral lemniscus, the primary motor cortex, the olfactory tubercle, hippocampus, and the paraflocculus lobe of the cerebellum. The fiber number and mean length of ACx and different hippocampal subregions were also damaged in hearing loss rats.

CONCLUSION

A new model of auditory-limbic-cerebellum interactions accounting for noise-induced hearing loss and cognitive impairments is proposed.

Sensitivity to interaural level and time differences in individuals with autism spectrum disorder

Individuals with autism spectrum disorders (ASD) are reported to exhibit degraded performance in sound localization. This study investigated whether the sensitivity to the interaural level differences (ILDs) and interaural time differences (ITDs), major cues for horizontal sound localization, are affected in ASD. Thresholds for discriminating the ILD and ITD were measured for adults with ASD and age- and IQ-matched controls in a lateralization experiment. Results show that the ASD group exhibited higher ILD and ITD thresholds than the control group. Moreover, there was a significant diversity of ITD sensitivity in the ASD group, and it contained a larger proportion of participants with poor ITD sensitivity than the control group. The current study suggests that deficits in relatively low-level processes in the auditory pathway are implicated in degraded performance of sound localization in individuals with ASD. The results are consistent with the structural abnormalities and great variability in the morphology in the brainstem reported by neuroanatomical studies of ASD.

Clinical and investigational tools for monitoring noise-induced hyperacusis

Hyperacusis is a recognized perceptual consequence of acoustic overexposure that can lead to debilitating psychosocial effects. Despite the profound impact of hyperacusis on quality of life, clinicians and researchers lack objective biomarkers and standardized protocols for its assessment. Outcomes of conventional audiologic tests are highly variable in the hyperacusis population and do not adequately capture the multifaceted nature of the condition on an individual level. This presents challenges for the differential diagnosis of hyperacusis, its clinical surveillance, and evaluation of new treatment options. Multiple behavioral and objective assays are emerging as contenders for inclusion in hyperacusis assessment protocols but most still await rigorous validation. There remains a pressing need to develop tools to quantify common nonauditory symptoms, including annoyance, fear, and pain. This review describes the current literature on clinical and investigational tools that have been used to diagnose and monitor hyperacusis, as well as those that hold promise for inclusion in future trials.

A retrospective cohort study exploring the association between different mitochondrial diseases and hearing loss

Some pathogenic variants in mtDNA and nuclear DNA, affecting mitochondrial function, are associated with hearing loss. Behavioral and electrophysiological auditory performance are obtained from 62 patients, clinically diagnosed with different mitochondrial diseases (MD) using tone/speech audiometry and Auditory Brainstem Responses (ABR). Audiological variables (hearing loss type, pure tone average (PTA), interaural asymmetry, speech perception and brainstem neural conductivity) were analyzed and related to Newcastle Mitochondrial Disease Scale for Adults (NMDAS). In 35% of MDs, a mild to severe symmetrical sensorineural hearing loss (SNHL) was found. Patients with Maternally Inherited Diabetes and Deafness (MIDD) show significantly higher PTAs compared to other MDs. For all MDs, speech recognition scores were in accordance with their individual age- and gender-corrected tone audiometry, but ABR peak latencies were prolonged in patients with MIDD, Mitochondrial Encephalopathy Lactate acidosis and Stroke-like episodes (MELAS), Chronic Progressive External Ophthalmoplegia (CPEO) and Subacute necrotizing encephalopathy (Leigh). Correlations between NMDAS and audiological variables were low.

Targeted deletion of the RNA-binding protein Caprin1 leads to progressive hearing loss and impairs recovery from noise exposure in mice

Cell cycle associated protein 1 (Caprin1) is an RNA-binding protein that can regulate the cellular post-transcriptional response to stress. It is a component of both stress granules and neuronal RNA granules and is implicated in neurodegenerative disease, synaptic plasticity and long-term memory formation. Our previous work suggested that Caprin1 also plays a role in the response of the cochlea to stress. Here, targeted inner ear-deletion of Caprin1 in mice leads to an early onset, progressive hearing loss. Auditory brainstem responses from Caprin1-deficient mice show reduced thresholds, with a significant reduction in wave-I amplitudes compared to wildtype. Whilst hair cell structure and numbers were normal, the inner hair cell-spiral ganglion neuron (IHC-SGN) synapse revealed abnormally large post-synaptic GluA2 receptor puncta, a defect consistent with the observed wave-I reduction. Unlike wildtype mice, mild-noise-induced hearing threshold shifts in Caprin1-deficient mice did not recover. Oxidative stress triggered TIA-1/HuR-positive stress granule formation in ex-vivo cochlear explants from Caprin1-deficient mice, showing that stress granules could still be induced. Taken together, these findings suggest that Caprin1 plays a key role in maintenance of auditory function, where it regulates the normal status of the IHC-SGN synapse.

Delayed Auditory Brainstem Responses (ABR) in children after sight-recovery

Studies in non-human animal models have revealed that in early development, the onset of visual input gates the critical period closure of some auditory functions. The study of rare individuals whose sight was restored after a period of congenital blindness offers the rare opportunity to assess whether early visual input is a prerequisite for the full development of auditory functions in humans as well. Here, we investigated whether a few months of delayed visual onset would affect the development of Auditory Brainstem Responses (ABRs). ABRs are widely used in the clinical practice to assess both functionality and development of the subcortical auditory pathway and, provide reliable data at the individual level. We collected Auditory Brainstem Responses from two case studies, young children (both having less than 5 years of age) who experienced a transient visual deprivation since birth due to congenital bilateral dense cataracts (BC), and who acquired sight at about two months of age. As controls, we tested 41 children (sighted controls, SC) with typical development, as well as two children who were treated (at about two months of age) for congenital monocular cataracts (MC). The SC group data served to predict, at the individual level, wave latencies of each BC and MC participant. Statistics were performed both at the single subject as well as at the group levels on latencies of main ABR waves (I, III, V and SN10). Results revealed delayed response latencies for both BC children compared with the SC group starting from the wave III. Conversely, no difference emerged between MC children and the SC group. These findings suggest that in case the onset of patterned visual input is delayed, the functional development of the subcortical auditory pathway lags behind typical developmental trajectories. Ultimately results are in favor of the presence of a crossmodal sensitive period in the human subcortical auditory system.

Sound level context modulates neural activity in the human brainstem

Optimal perception requires adaptation to sounds in the environment. Adaptation involves representing the acoustic stimulation history in neural response patterns, for example, by altering response magnitude or latency as sound-level context changes. Neurons in the auditory brainstem of rodents are sensitive to acoustic stimulation history and sound-level context (often referred to as sensitivity to stimulus statistics), but the degree to which the human brainstem exhibits such neural adaptation is unclear. In six electroencephalography experiments with over 125 participants, we demonstrate that the response latency of the human brainstem is sensitive to the history of acoustic stimulation over a few tens of milliseconds. We further show that human brainstem responses adapt to sound-level context in, at least, the last 44 ms, but that neural sensitivity to sound-level context decreases when the time window over which acoustic stimuli need to be integrated becomes wider. Our study thus provides evidence of adaptation to sound-level context in the human brainstem and of the timescale over which sound-level information affects neural responses to sound. The research delivers an important link to studies on neural adaptation in non-human animals.

Real-time threshold determination of auditory brainstem responses by cross-correlation analysis

Auditory brainstem response (ABR) serves as an objective indication of auditory perception at a given sound level and is nowadays widely used in hearing function assessment. Despite efforts for automation over decades, ABR threshold determination by machine algorithms remains unreliable and thereby one still relies on visual identification by trained personnel. Here, we described a procedure for automatic threshold determination that can be used in both animal and human ABR tests. The method terminates level averaging of ABR recordings upon detection of time-locked waveform through cross-correlation analysis. The threshold level was then indicated by a dramatic increase in the sweep numbers required to produce “qualified” level averaging. A good match was obtained between the algorithm outcome and the human readouts. Moreover, the method varies the level averaging based on the cross-correlation, thereby adapting to the signal-to-noise ratio of sweep recordings. These features empower a robust and fully automated ABR test.

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Automatic threshold determination of auditory brainstem response (ABR)

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Detection of “clear” responses from iteratively averaged level representation

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Wide application in both animal and human ABR tests

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Stop on-going level averaging based on detection outcome

Reinterpreting the human ABR binaural interaction component: isolating attention from stimulus effects

Subtracting the sum of left and right monaural auditory brainstem responses (ABRs) from the corresponding binaural ABR isolates the binaural interaction component (ABR-BIC). In a previous investigation (Ikeda, 2015), during auditory yet not visual tasks, tone-pips elicited a significant difference in amplitude between summed monaural and binaural ABRs. With click stimulation, this amplitude difference was task-independent. This self-critical reanalysis's purpose was to establish that a difference waveform (i.e., ABR-BIC DN1) reflected an auditory selective attention effect that was isolable from stimulus factors. Regardless of whether stimuli were tone-pips or clicks, effect sizes of the DN1 peak amplitudes relative to zero improved during auditory tasks over visual tasks. Auditory selective attention effects on the monaural and binaural ABR wave-V amplitudes were tone-pip specific. Those wave-V effects thus could not explain the stimulus-universal effect of auditory selective attention on DN1 detectability, which was thus entirely binaural. In a manner isolated from auditory selective attention, multiple mediation analyses indicated that the higher right monaural wave-V amplitudes mediated individual differences in how clicks, relative to tone-pips, augmented DN1 amplitudes. There are implications of these findings for advancing ABR-BIC measurement.

Extended Signal-Space Separation Method for Improved Interference Suppression in MEG

Objective:

Magnetoencephalography (MEG) signals typically reflect a mixture of neuromagnetic fields, subject-related artifacts, external interference and sensor noise. Even inside a magnetically shielded room, external interference can be significantly stronger than brain signals. Methods such as signal-space projection (SSP) and signal-space separation (SSS) have been developed to suppress this residual interference, but their performance might not be sufficient in cases of strong interference or when the sources of interference change over time.

Methods:

Here we suggest a new method, extended signal-space separation (eSSS), which combines a physical model of the magnetic fields (as in SSS) with a statistical description of the interference (as in SSP). We demonstrate the performance of this method via simulations and experimental MEG data.

Results:

The eSSS method clearly outperforms SSS and SSP in interference suppression regardless of the extent of a priori information available on the interference sources. We also show that the method does not cause location or amplitude bias in dipole modeling.

Conclusion:

Our eSSS method provides better data quality than SSP or SSS and can be readily combined with other SSS-based methods, such as spatiotemporal SSS or head movement compensation. Thus, eSSS extends and complements the interference suppression techniques currently available for MEG.

Significance:

Due to its ability to suppress external interference to the level of sensor noise, eSSS can facilitate single-trial data analysis, exemplified in automated analysis of epileptic data. Such an enhanced suppression is especially important in environments with large interference fields.

Auditory brainstem responses in adults with autism spectrum disorder

OBJECTIVE

To investigate possible differences in the auditory peripheral and brainstem functions between adults with autism spectrum disorder (ASD) and neurotypical (NT) adults.

METHODS

Click-evoked auditory brainstem responses (ABRs) were obtained from 17 high-functioning ASD adults (aged 21-38 years) and 20 NT adults (aged 22-36 years). A relatively large number of stimulus presentations (6000) were adopted, and ABRs by horizontal and vertical electrode montages were evaluated, in order to allow precise evaluations of early ABR components.

RESULTS

Waves I, II, III, and V were identified in the vertical electrode montage, and wave I and the summating potential (SP) in electrocochleograms were identified in the horizontal electrode montage. There were no significant group differences in the wave I, II, III, and V latencies or the interpeak latencies (IPLs) in the vertical electrode montage. In the horizontal montage, the ASD adults exhibited significantly shortened SP latencies compared with the NT adults, whereas there was no significant group difference in the wave I latency.

CONCLUSION

The ASD adults may have the abnormalities of processing more in the peripheral auditory system than in the brainstem.

SIGNIFICANCE

The current study suggests that the peripheral abnormality is associated with ASD.

A review of magnetoencephalography use in pediatric epilepsy: an update on best practice

Introduction: Magnetoencephalography (MEG) is a noninvasive technique that is used for presurgical evaluation of children with drug-resistant epilepsy (DRE).Areas covered: The contributions of MEG for localizing the epileptogenic zone are discussed, in particular in extra-temporal lobe epilepsy and focal cortical dysplasia, which are common in children, as well as in difficult to localize epilepsy such as operculo-insular epilepsy. Further, the authors review current evidence on MEG for mapping eloquent cortex, its performance, application in clinical practice, and potential challenges.Expert opinion: MEG could change the clinical management of children with DRE by directing placement of intracranial electrodes thereby enhancing their yield. With improved identification of a circumscribed epileptogenic zone, MEG could render more patients as suitable candidates for epilepsy surgery and increase utilization of surgery.

Adjudicating Between Local and Global Architectures of Predictive Processing in the Subcortical Auditory Pathway

Predictive processing, a leading theoretical framework for sensory processing, suggests that the brain constantly generates predictions on the sensory world and that perception emerges from the comparison between these predictions and the actual sensory input. This requires two distinct neural elements: generative units, which encode the model of the sensory world; and prediction error units, which compare these predictions against the sensory input. Although predictive processing is generally portrayed as a theory of cerebral cortex function, animal and human studies over the last decade have robustly shown the ubiquitous presence of prediction error responses in several nuclei of the auditory, somatosensory, and visual subcortical pathways. In the auditory modality, prediction error is typically elicited using so-called oddball paradigms, where sequences of repeated pure tones with the same pitch are at unpredictable intervals substituted by a tone of deviant frequency. Repeated sounds become predictable promptly and elicit decreasing prediction error; deviant tones break these predictions and elicit large prediction errors. The simplicity of the rules inducing predictability make oddball paradigms agnostic about the origin of the predictions. Here, we introduce two possible models of the organizational topology of the predictive processing auditory network: (1) the global view, that assumes that predictions on the sensory input are generated at high-order levels of the cerebral cortex and transmitted in a cascade of generative models to the subcortical sensory pathways; and (2) the local view, that assumes that independent local models, computed using local information, are used to perform predictions at each processing stage. In the global view information encoding is optimized globally but biases sensory representations along the entire brain according to the subjective views of the observer. The local view results in a diminished coding efficiency, but guarantees in return a robust encoding of the features of sensory input at each processing stage. Although most experimental results to-date are ambiguous in this respect, recent evidence favors the global model.

A comprehensive study on electroencephalography and magnetoencephalography sensitivity to cortical and subcortical sources

Signal-to-noise ratio (SNR) maps are a good way to visualize electroencephalography (EEG) and magnetoencephalography (MEG) sensitivity. SNR maps extend the knowledge about the modulation of EEG and MEG signals by source locations and orientations and can therefore help to better understand and interpret measured signals as well as source reconstruction results thereof. Our work has two main objectives. First, we investigated the accuracy and reliability of EEG and MEG finite element method (FEM)-based sensitivity maps for three different head models, namely an isotropic three and four-compartment and an anisotropic six-compartment head model. As a result, we found that ignoring the cerebrospinal fluid leads to an overestimation of EEG SNR values. Second, we examined and compared EEG and MEG SNR mappings for both cortical and subcortical sources and their modulation by source location and orientation. Our results for cortical sources show that EEG sensitivity is higher for radial and deep sources and MEG for tangential ones, which are the majority of sources. As to the subcortical sources, we found that deep sources with sufficient tangential source orientation are recordable by the MEG. Our work, which represents the first comprehensive study where cortical and subcortical sources are considered in highly detailed FEM-based EEG and MEG SNR mappings, sheds a new light on the sensitivity of EEG and MEG and might influence the decision of brain researchers or clinicians in their choice of the best modality for their experiment or diagnostics, respectively.

High gamma cortical processing of continuous speech in younger and older listeners

Neural processing along the ascending auditory pathway is often associated with a progressive reduction in characteristic processing rates. For instance, the well-known frequency-following response (FFR) of the auditory midbrain, as measured with electroencephalography (EEG), is dominated by frequencies from ∼100 Hz to several hundred Hz, phase-locking to the acoustic stimulus at those frequencies. In contrast, cortical responses, whether measured by EEG or magnetoencephalography (MEG), are typically characterized by frequencies of a few Hz to a few tens of Hz, time-locking to acoustic envelope features. In this study we investigated a crossover case, cortically generated responses time-locked to continuous speech features at FFR-like rates. Using MEG, we analyzed responses in the high gamma range of 70-200 Hz to continuous speech using neural source-localized reverse correlation and the corresponding temporal response functions (TRFs). Continuous speech stimuli were presented to 40 subjects (17 younger, 23 older adults) with clinically normal hearing and their MEG responses were analyzed in the 70-200 Hz band. Consistent with the relative insensitivity of MEG to many subcortical structures, the spatiotemporal profile of these response components indicated a cortical origin with ∼40 ms peak latency and a right hemisphere bias. TRF analysis was performed using two separate aspects of the speech stimuli: a) the 70-200 Hz carrier of the speech, and b) the 70-200 Hz temporal modulations in the spectral envelope of the speech stimulus. The response was dominantly driven by the envelope modulation, with a much weaker contribution from the carrier. Age-related differences were also analyzed to investigate a reversal previously seen along the ascending auditory pathway, whereby older listeners show weaker midbrain FFR responses than younger listeners, but, paradoxically, have stronger cortical low frequency responses. In contrast to both these earlier results, this study did not find clear age-related differences in high gamma cortical responses to continuous speech. Cortical responses at FFR-like frequencies shared some properties with midbrain responses at the same frequencies and with cortical responses at much lower frequencies.

Can EEG and MEG detect signals from the human cerebellum?

The cerebellum plays a key role in the regulation of motor learning, coordination and timing, and has been implicated in sensory and cognitive processes as well. However, our current knowledge of its electrophysiological mechanisms comes primarily from direct recordings in animals, as investigations into cerebellar function in humans have instead predominantly relied on lesion, haemodynamic and metabolic imaging studies. While the latter provide fundamental insights into the contribution of the cerebellum to various cerebellar-cortical pathways mediating behaviour, they remain limited in terms of temporal and spectral resolution. In principle, this shortcoming could be overcome by monitoring the cerebellum's electrophysiological signals. Non-invasive assessment of cerebellar electrophysiology in humans, however, is hampered by the limited spatial resolution of electroencephalography (EEG) and magnetoencephalography (MEG) in subcortical structures, i.e., deep sources. Furthermore, it has been argued that the anatomical configuration of the cerebellum leads to signal cancellation in MEG and EEG. Yet, claims that MEG and EEG are unable to detect cerebellar activity have been challenged by an increasing number of studies over the last decade. Here we address this controversy and survey reports in which electrophysiological signals were successfully recorded from the human cerebellum. We argue that the detection of cerebellum activity non-invasively with MEG and EEG is indeed possible and can be enhanced with appropriate methods, in particular using connectivity analysis in source space. We provide illustrative examples of cerebellar activity detected with MEG and EEG. Furthermore, we propose practical guidelines to optimize the detection of cerebellar activity with MEG and EEG. Finally, we discuss MEG and EEG signal contamination that may lead to localizing spurious sources in the cerebellum and suggest ways of handling such artefacts. This review is to be read as a perspective review that highlights that it is indeed possible to measure cerebellum with MEG and EEG and encourages MEG and EEG researchers to do so. Its added value beyond highlighting and encouraging is that it offers useful advice for researchers aspiring to investigate the cerebellum with MEG and EEG.

Predicting Neural Response Latency of the Human Early Visual Cortex from MRI-Based Tissue Measurements of the Optic Radiation

Although the non-invasive measurement of visually evoked responses has been extensively studied, the structural basis of variabilities in latency in healthy humans is not well understood. We investigated how tissue properties of optic radiation could predict interindividual variability in the latency of the initial visually evoked component (C1), which may originate from the primary visual cortex (V1). We collected C1 peak latency data using magnetoencephalography (MEG) and checkerboard stimuli, and multiple structural magnetic resonance imaging (MRI) data from 20 healthy subjects. While we varied the contrast and position of the stimuli, the C1 measurement was most reliable when high-contrast stimuli were presented to the lower visual field (LVF). We then attempted to predict interindividual variability in C1 peak latency in this stimulus condition with a multiple regression model using MRI parameters along the optic radiation. We found that this model could predict >20% of variance in C1 latency, when the data were averaged across the hemispheres. The model using the corticospinal tract did not predict variability in C1 latency, suggesting that there is no evidence for generalization to a non-visual tract. In conclusion, our results suggest that the variability in neural latencies in the early visual cortex in healthy subjects can be partly explained by tissue properties along the optic radiation. We discuss the challenges of predicting neural latency using current structural neuroimaging methods and other factors that may explain interindividual variance in neural latency.

Age-related hearing loss: Why we need to think about sex as a biological variable

It has long been known that age-related hearing loss (ARHL) is more common, more severe, and with an earlier onset in men compared to women. Even in the absence of confounding factors such as noise exposure, these sexdifferences in susceptibility to ARHL remain. In the last decade, insight into the pleiotrophic nature by which estrogen signaling can impact multiple signaling mechanisms to mediate downstream changes in gene expression and/or elicit rapid changes in cellular function has rapidly gathered pace, and a role for estrogen signaling in the biological pathways that confer neuroprotection is becoming undeniable. Here I review the evidence why we need to consider sex as a biological variable (SABV) when investigating the etiology of ARHL. Loss of auditory function with aging is frequency-specific and modulated by SABV. Evidence also suggests that differences in cochlear physiology between women and men are already present from birth. Understanding the molecular basis of these sex differences in ARHL will accelerate the development of precision medicine therapies for ARHL.

A backward encoding approach to recover subcortical auditory activity

Several subcortical nuclei along the auditory pathway are involved in the processing of sounds. One of the most commonly used methods of measuring the activity of these nuclei is the auditory brainstem response (ABR). Due to its low signal-to-noise ratio, ABR's have to be derived by averaging over activity generated by thousands of artificial sounds such as clicks or tone bursts. This approach cannot be easily applied to natural listening situations (e.g. speech, music), which limits auditory cognitive neuroscientific studies to investigate mostly cortical processes. We propose that by individually training backward encoding models to reconstruct evoked ABRs from high-density electrophysiological data, spatial filters can be tuned to auditory brainstem activity. Since these individualized filters can be applied (i.e. generalized) to any other data set using the same spatial coverage, this could allow for the estimation of auditory brainstem activity from any continuous sensor level data. In this study, we established a proof-of-concept by using backward encoding models generated using a click stimulation rate of 30 ​Hz to predict ABR activity recorded using EEG from an independent measurement using a stimulation rate of 9 ​Hz. We show that individually predicted and measured ABR's are highly correlated (r ​~ ​0.7). Importantly these predictions are stable even when applying the trained backward encoding model to a low number of trials, mimicking a situation with an unfavorable signal-to-noise ratio. Overall, this work lays the necessary foundation to use this approach in more interesting listening situations.

Auditory Dysfunction in Parkinson's Disease

PD is a progressive and complex neurological disorder with heterogeneous symptomatology. PD is characterized by classical motor features of parkinsonism and nonmotor symptoms and involves extensive regions of the nervous system, various neurotransmitters, and protein aggregates. Extensive evidence supports auditory dysfunction as an additional nonmotor feature of PD. Studies indicate a broad range of auditory impairments in PD, from the peripheral hearing system to the auditory brainstem and cortical areas. For instance, research demonstrates a higher occurrence of hearing loss in early-onset PD and evidence of abnormal auditory evoked potentials, event-related potentials, and habituation to novel stimuli. Electrophysiological data, such as auditory P3a, also is suggested as a sensitive measure of illness duration and severity. Improvement in auditory responses following dopaminergic therapies also indicates the presence of similar neurotransmitters (i.e., glutamate and dopamine) in the auditory system and basal ganglia. Nonetheless, hearing impairments in PD have received little attention in clinical practice so far. This review summarizes evidence of peripheral and central auditory impairments in PD and provides conclusions and directions for future empirical and clinical research. © 2020 International Parkinson and Movement Disorder Society.

Sensory evoked potentials in patients with Rett syndrome through the lens of animal studies: Systematic review

OBJECTIVE

Systematically review the abnormalities in event related potential (ERP) recorded in Rett Syndrome (RTT) patients and animals in search of translational biomarkers of deficits related to the particular neurophysiological processes of known genetic origin (MECP2 mutations).

METHODS

Pubmed, ISI Web of Knowledge and BIORXIV were searched for the relevant articles according to PRISMA standards.

RESULTS

ERP components are generally delayed across all sensory modalities both in RTT patients and its animal model, while findings on ERPs amplitude strongly depend on stimulus properties and presentation rate. Studies on RTT animal models uncovered the abnormalities in the excitatory and inhibitory transmission as critical mechanisms underlying the ERPs changes, but showed that even similar ERP alterations in auditory and visual domains have a diverse neural basis. A range of novel approaches has been developed in animal studies bringing along the meaningful neurophysiological interpretation of ERP measures in RTT patients.

CONCLUSIONS

While there is a clear evidence for sensory ERPs abnormalities in RTT, to further advance the field there is a need in a large-scale ERP studies with the functionally-relevant experimental paradigms.

SIGNIFICANCE

The review provides insights into domain-specific neural basis of the ERP abnormalities and promotes clinical application of the ERP measures as the non-invasive functional biomarkers of RTT pathophysiology.

Auditory cortical generators of the Frequency Following Response are modulated by intermodal attention

The efferent auditory system suggests that brainstem auditory regions could also be sensitive to top-down processes. In electrophysiology, the Frequency Following Response (FFR) to speech stimuli has been used extensively to study brainstem areas. Despite seemingly straight-forward in addressing the issue of attentional modulations of brainstem regions by means of the FFR, the existing results are inconsistent. Moreover, the notion that the FFR exclusively represents subcortical generators has been challenged. We aimed to gain a more differentiated perspective on how the generators of the FFR are modulated by either attending to the visual or auditory input while neural activity was recorded using magnetoencephalography (MEG). In a first step our results confirm the strong contribution of also cortical regions to the FFR. Interestingly, of all regions exhibiting a measurable FFR response, only the right primary auditory cortex was significantly affected by intermodal attention. By showing a clear cortical contribution to the attentional FFR effect, our work significantly extends previous reports that focus on surface level recordings only. It underlines the importance of making a greater effort to disentangle the different contributing sources of the FFR and serves as a clear precaution of simplistically interpreting the FFR as brainstem response.

Presurgical Functional Cortical Mapping Using Electromagnetic Source Imaging

Preoperative localization of functionally eloquent cortex (functional cortical mapping) is common clinical practice in order to avoid or reduce postoperative morbidity. This review aims at providing a general overview of magnetoencephalography (MEG) and high-density electroencephalography (hdEEG) based methods and their clinical role as compared to common alternatives for functional cortical mapping of (1) verbal language function, (2) sensorimotor cortex, (3) memory, (4) visual, and (5) auditory cortex. We highlight strengths, weaknesses and limitations of these functional cortical mapping modalities based on findings in the recent literature. We also compare their performance relative to other non-invasive functional cortical mapping methods, such as functional Magnetic Resonance Imaging (fMRI), Transcranial Magnetic Stimulation (TMS), and to invasive methods like the intracarotid Amobarbital Test (WADA-Test) or intracranial investigations.

Frequency-Following Responses to Complex Tones at Different Frequencies Reflect Different Source Configurations

The neural generators of the frequency-following response (FFR), a neural response widely used to study the human auditory system, remain unclear. There is evidence that the balance between cortical and subcortical contributions to the FFR varies with stimulus frequency. In this study, we tried to clarify whether this variation extended to subcortical nuclei at higher stimulus frequencies where cortical sources were inactive. We evoked FFRs, in 17 human listeners with normal hearing (9 female), with three complex tones with missing-fundamentals corresponding to musical tones C4 (262 Hz), E4 (330 Hz), and G4 (393 Hz) presented to left, right, or both ears. Source imaging results confirmed the dominance of subcortical activity underlying both fundamental frequency (F0) and second harmonic (H2) components of the FFR. Importantly, several FFR features (spatial complexity, scalp distributions of spectral strength and inter-trial phase coherence, and functional connectivity patterns) varied systematically with stimulus F0, suggesting an unfixed source configuration. We speculated that the variation of FFR source configuration with stimulus frequency resulted from changing relative contributions of subcortical nuclei. Supportively, topographic comparison between the FFR and the auditory brainstem response (ABR) evoked by clicks revealed that the topography of the F0 component resembled that of the click-ABR at an earlier latency when stimulus F0 was higher and that the topography of the H2 component resembled that of the click-ABR at a nearly fixed latency regardless of stimulus F0, particularly for binaurally evoked FFRs. Possible generation sites of the FFR and implications for future studies were discussed.

Magnetoencephalography and the infant brain

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique that provides whole-head measures of neural activity with millisecond temporal resolution. Over the last three decades, MEG has been used for assessing brain activity, most commonly in adults. MEG has been used less often to examine neural function during early development, in large part due to the fact that infant whole-head MEG systems have only recently been developed. In this review, an overview of infant MEG studies is provided, focusing on the period from birth to three years. The advantages of MEG for measuring neural activity in infants are highlighted (See Box 1), including the ability to assess activity in brain (source) space rather than sensor space, thus allowing direct assessment of neural generator activity. Recent advances in MEG hardware and source analysis are also discussed. As the review indicates, efforts in this area demonstrate that MEG is a promising technology for studying the infant brain. As a noninvasive technology, with emerging hardware providing the necessary sensitivity, an expected deliverable is the capability for longitudinal infant MEG studies evaluating the developmental trajectory (maturation) of neural activity. It is expected that departures from neuro-typical trajectories will offer early detection and prognosis insights in infants and toddlers at-risk for neurodevelopmental disorders, thus paving the way for early targeted interventions.

Cortical Signal Suppression (CSS) for Detection of Subcortical Activity Using MEG and EEG

Magnetoencephalography (MEG) and electroencephalography (EEG) use non-invasive sensors to detect neural currents. Since the contribution of superficial neural sources to the measured M/EEG signals are orders-of-magnitude stronger than the contribution of subcortical sources, most MEG and EEG studies have focused on cortical activity. Subcortical structures, however, are centrally involved in both healthy brain function as well as in many neurological disorders such as Alzheimer's disease and Parkinson's disease. In this paper, we present a method that can separate and suppress the cortical signals while preserving the subcortical contributions to the M/EEG data. The resulting signal subspace of the data mainly originates from subcortical structures. Our method works by utilizing short-baseline planar gradiometers with short-sighted sensitivity distributions as reference sensors for cortical activity. Since the method is completely data-driven, forward and inverse modeling are not required. In this study, we use simulations and auditory steady state response experiments in a human subject to demonstrate that the method can remove the cortical signals while sparing the subcortical signals. We also test our method on MEG data recorded in an essential tremor patient with a deep brain stimulation implant and show how it can be used to reduce the DBS artifact in the MEG data by ~ 99.9% without affecting low frequency brain rhythms.

Brain Activity Mapping from MEG Data via a Hierarchical Bayesian Algorithm with Automatic Depth Weighting

A recently proposed iterated alternating sequential (IAS) MEG inverse solver algorithm, based on the coupling of a hierarchical Bayesian model with computationally efficient Krylov subspace linear solver, has been shown to perform well for both superficial and deep brain sources. However, a systematic study of its ability to correctly identify active brain regions is still missing. We propose novel statistical protocols to quantify the performance of MEG inverse solvers, focusing in particular on how their accuracy and precision at identifying active brain regions. We use these protocols for a systematic study of the performance of the IAS MEG inverse solver, comparing it with three standard inversion methods, wMNE, dSPM, and sLORETA. To avoid the bias of anecdotal tests towards a particular algorithm, the proposed protocols are Monte Carlo sampling based, generating an ensemble of activity patches in each brain region identified in a given atlas. The performance in correctly identifying the active areas is measured by how much, on average, the reconstructed activity is concentrated in the brain region of the simulated active patch. The analysis is based on Bayes factors, interpreting the estimated current activity as data for testing the hypothesis that the active brain region is correctly identified, versus the hypothesis of any erroneous attribution. The methodology allows the presence of a single or several simultaneous activity regions, without assuming that the number of active regions is known. The testing protocols suggest that the IAS solver performs well with both with cortical and subcortical activity estimation.

Linguistic effect on speech perception observed at the brainstem

Linguistic experience affects speech perception from early infancy, as previously evidenced by behavioral and brain measures. Current research focuses on whether linguistic effects on speech perception can be observed at an earlier stage in the neural processing of speech (i.e., auditory brainstem). Brainstem responses reflect rapid, automatic, and preattentive encoding of sounds. Positive experiential effects have been reported by examining the frequency-following response (FFR) component of the complex auditory brainstem response (cABR) in response to sustained high-energy periodic portions of speech sounds (vowels and lexical tones). The current study expands the existing literature by examining the cABR onset component in response to transient and low-energy portions of speech (consonants), employing simultaneous magnetoencephalography (MEG) in addition to electroencephalography (EEG), which provide complementary source information on cABR. Utilizing a cross-cultural design, we behaviorally measured perceptual responses to consonants in native Spanish- and English-speaking adults, in addition to cABR. Brain and behavioral relations were examined. Results replicated previous behavioral differences between language groups and further showed that individual consonant perception is strongly associated with EEG-cABR onset peak latency. MEG-cABR source analysis of the onset peaks complimented the EEG-cABR results by demonstrating subcortical sources for both peaks, with no group differences in peak locations. Current results demonstrate a brainstem-perception relation and show that the effects of linguistic experience on speech perception can be observed at the brainstem level.

IFCN-endorsed practical guidelines for clinical magnetoencephalography (MEG)

Magnetoencephalography (MEG) records weak magnetic fields outside the human head and thereby provides millisecond-accurate information about neuronal currents supporting human brain function. MEG and electroencephalography (EEG) are closely related complementary methods and should be interpreted together whenever possible. This manuscript covers the basic physical and physiological principles of MEG and discusses the main aspects of state-of-the-art MEG data analysis. We provide guidelines for best practices of patient preparation, stimulus presentation, MEG data collection and analysis, as well as for MEG interpretation in routine clinical examinations. In 2017, about 200 whole-scalp MEG devices were in operation worldwide, many of them located in clinical environments. Yet, the established clinical indications for MEG examinations remain few, mainly restricted to the diagnostics of epilepsy and to preoperative functional evaluation of neurosurgical patients. We are confident that the extensive ongoing basic MEG research indicates potential for the evaluation of neurological and psychiatric syndromes, developmental disorders, and the integrity of cortical brain networks after stroke. Basic and clinical research is, thus, paving way for new clinical applications to be identified by an increasing number of practitioners of MEG.

The characterization of auditory brainstem response (ABR) waveforms: A study in tree shrews (Tupaia belangeri)

To characterize the patterns of ABR waves in tree shrews, we must understand the hearing sensitivity and auditory function of healthy adult tree shrews. Fifteen tree shrews (30 ears) were stimulated with clicks and tone-pips at 11 different frequencies from 1 to 60 kHz. The ABR waves were recorded and analyzed. The ABR consisted of five to seven positive waves in the first 10 ms after a click stimulus, and the average hearing threshold of component III was 27.86 ± 3.78 dB SPL. Wave III was the largest and most clear. The ABR threshold was related to the tone-pip sitmulus by a “U” shaped curve. The sensitive frequency was approximately 8 kHz in tree shrews. The latencies systematically decreased with increasing stimulus frequencies. The ABR amplitudes of wave III increased as the sound pressure level increased. All of these results provide an empirical basis for future studies of hearing diseases in tree shrews.

Neural source dynamics of brain responses to continuous stimuli: Speech processing from acoustics to comprehension

Human experience often involves continuous sensory information that unfolds over time. This is true in particular for speech comprehension, where continuous acoustic signals are processed over seconds or even minutes. We show that brain responses to such continuous stimuli can be investigated in detail, for magnetoencephalography (MEG) data, by combining linear kernel estimation with minimum norm source localization. Previous research has shown that the requirement to average data over many trials can be overcome by modeling the brain response as a linear convolution of the stimulus and a kernel, or response function, and estimating a kernel that predicts the response from the stimulus. However, such analysis has been typically restricted to sensor space. Here we demonstrate that this analysis can also be performed in neural source space. We first computed distributed minimum norm current source estimates for continuous MEG recordings, and then computed response functions for the current estimate at each source element, using the boosting algorithm with cross-validation. Permutation tests can then assess the significance of individual predictor variables, as well as features of the corresponding spatio-temporal response functions. We demonstrate the viability of this technique by computing spatio-temporal response functions for speech stimuli, using predictor variables reflecting acoustic, lexical and semantic processing. Results indicate that processes related to comprehension of continuous speech can be differentiated anatomically as well as temporally: acoustic information engaged auditory cortex at short latencies, followed by responses over the central sulcus and inferior frontal gyrus, possibly related to somatosensory/motor cortex involvement in speech perception; lexical frequency was associated with a left-lateralized response in auditory cortex and subsequent bilateral frontal activity; and semantic composition was associated with bilateral temporal and frontal brain activity. We conclude that this technique can be used to study the neural processing of continuous stimuli in time and anatomical space with the millisecond temporal resolution of MEG. This suggests new avenues for analyzing neural processing of naturalistic stimuli, without the necessity of averaging over artificially short or truncated stimuli.

Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG

Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields generated by neuronal activity in subcortical structures can be recorded noninvasively, using magnetoencephalography (MEG) and electroencephalography (EEG). However, these subcortical signals are much weaker than those generated by cortical activity. In addition, we show here that it is difficult to resolve subcortical sources because distributed cortical activity can explain the MEG and EEG patterns generated by deep sources. We then demonstrate that if the cortical activity is spatially sparse, both cortical and subcortical sources can be resolved with M/EEG. Building on this insight, we develop a hierarchical sparse inverse solution for M/EEG. We assess the performance of this algorithm on realistic simulations and auditory evoked response data, and show that thalamic and brainstem sources can be correctly estimated in the presence of cortical activity. Our work provides alternative perspectives and tools for characterizing electrophysiological activity in subcortical structures in the human brain.

Cingulate and cerebellar beta oscillations are engaged in the acquisition of auditory-motor sequences

Singing, music performance, and speech rely on the retrieval of complex sounds, which are generated by the corresponding actions and are organized into sequences. It is crucial in these forms of behavior that the serial organization (i.e., order) of both the actions and associated sounds be monitored and learned. To investigate the neural processes involved in the monitoring of serial order during the initial learning of sensorimotor sequences, we performed magnetoencephalographic recordings while participants explicitly learned short piano sequences under the effect of occasional alterations of auditory feedback (AAF). The main result was a prominent and selective modulation of beta (13-30 Hz) oscillations in cingulate and cerebellar regions during the processing of AAF that simulated serial order errors. Furthermore, the AAF-induced modulation of beta oscillations was associated with higher error rates, reflecting compensatory changes in sequence planning. This suggests that cingulate and cerebellar beta oscillations play a role in tracking serial order during initial sensorimotor learning and in updating the mapping of the sensorimotor representations. The findings support the notion that the modulation of beta oscillations is a candidate mechanism for the integration of sequential motor and auditory information during an early stage of skill acquisition in music performance. This has potential implications for singing and speech. Hum Brain Mapp 38:5161-5179, 2017. © 2017 Wiley Periodicals, Inc.

Cortical Correlates of the Auditory Frequency-Following and Onset Responses: EEG and fMRI Evidence

The frequency-following response (FFR) is a measure of the brain's periodic sound encoding. It is of increasing importance for studying the human auditory nervous system due to numerous associations with auditory cognition and dysfunction. Although the FFR is widely interpreted as originating from brainstem nuclei, a recent study using MEG suggested that there is also a right-lateralized contribution from the auditory cortex at the fundamental frequency (Coffey et al., 2016b). Our objectives in the present work were to validate and better localize this result using a completely different neuroimaging modality and to document the relationships between the FFR, the onset response, and cortical activity. Using a combination of EEG, fMRI, and diffusion-weighted imaging, we show that activity in the right auditory cortex is related to individual differences in FFR-fundamental frequency (f₀) strength, a finding that was replicated with two independent stimulus sets, with and without acoustic energy at the fundamental frequency. We demonstrate a dissociation between this FFR-f₀-sensitive response in the right and an area in left auditory cortex that is sensitive to individual differences in the timing of initial response to sound onset. Relationships to timing and their lateralization are supported by parallels in the microstructure of the underlying white matter, implicating a mechanism involving neural conduction efficiency. These data confirm that the FFR has a cortical contribution and suggest ways in which auditory neuroscience may be advanced by connecting early sound representation to measures of higher-level sound processing and cognitive function.

SIGNIFICANCE STATEMENT

The frequency-following response (FFR) is an EEG signal that is used to explore how the auditory system encodes temporal regularities in sound and is related to differences in auditory function between individuals. It is known that brainstem nuclei contribute to the FFR, but recent findings of an additional cortical source are more controversial. Here, we use fMRI to validate and extend the prediction from MEG data of a right auditory cortex contribution to the FFR. We also demonstrate a dissociation between FFR-related cortical activity from that related to the latency of the response to sound onset, which is found in left auditory cortex. The findings provide a clearer picture of cortical processes for analysis of sound features.

Using generative models to make probabilistic statements about hippocampal engagement in MEG

Magnetoencephalography (MEG) enables non-invasive real time characterization of brain activity. However, convincing demonstrations of signal contributions from deeper sources such as the hippocampus remain controversial and are made difficult by its depth, structural complexity and proximity to neocortex. Here, we demonstrate a method for quantifying hippocampal engagement probabilistically using simulated hippocampal activity and realistic anatomical and electromagnetic source modelling. We construct two generative models, one which supports neuronal current flow on the cortical surface, and one which supports neuronal current flow on both the cortical and hippocampal surface. Using Bayesian model comparison, we then infer which of the two models provides a more likely explanation of the dataset at hand. We also carry out a set of control experiments to rule out bias, including simulating medial temporal lobe sources to assess the risk of falsely positive results, and adding different types of displacements to the hippocampal portion of the mesh to test for anatomical specificity of the results. In addition, we test the robustness of this inference by adding co-registration error and sensor level noise. We find that the model comparison framework is sensitive to hippocampal activity when co-registration error is <3 mm and the sensor-level signal-to-noise ratio (SNR) is >-20 dB. These levels of co-registration error and SNR can now be achieved empirically using recently developed subject-specific head-casts.