Abnormal gamma phase-amplitude coupling in the parahippocampal cortex is associated with network hyperexcitability in Alzheimer's disease.

While animal models of Alzheimer's disease (AD) have shown altered gamma oscillations (∼40 Hz) in local neural circuits, the low signal-to-noise ratio of gamma in the resting human brain precludes its quantification via conventional spectral estimates. Phase-amplitude coupling (PAC) indicating the dynamic integration between the gamma amplitude and the phase of low-frequency (4-12 Hz) oscillations is a useful alternative to capture local gamma activity. In addition, PAC is also an index of neuronal excitability as the phase of low-frequency oscillations that modulate gamma amplitude, effectively regulates the excitability of local neuronal firing. In this study, we sought to examine the local neuronal activity and excitability using gamma PAC, within brain regions vulnerable to early AD pathophysiology-entorhinal cortex and parahippocampus, in a clinical population of patients with AD and age-matched controls. Our clinical cohorts consisted of a well-characterized cohort of AD patients (n = 50; age, 60 ± 8 years) with positive AD biomarkers, and age-matched, cognitively unimpaired controls (n = 35; age, 63 ± 5.8 years). We identified the presence or the absence of epileptiform activity in AD patients (AD patients with epileptiform activity, AD-EPI+, n = 20; AD patients without epileptiform activity, AD-EPI-, n = 30) using long-term electroencephalography (LTM-EEG) and 1-hour long magnetoencephalography (MEG) with simultaneous EEG. Using the source reconstructed MEG data, we computed gamma PAC as the coupling between amplitude of the gamma frequency (30-40 Hz) with phase of the theta (4-8 Hz) and alpha (8-12 Hz) frequency oscillations, within entorhinal and parahippocampal cortices. We found that patients with AD have reduced gamma PAC in the left parahippocampal cortex, compared to age-matched controls. Furthermore, AD-EPI+ patients showed greater reductions in gamma PAC than AD-EPI- in bilateral parahippocampal cortices. In contrast, entorhinal cortices did not show gamma PAC abnormalities in patients with AD. Our findings demonstrate the spatial patterns of altered gamma oscillations indicating possible region-specific manifestations of network hyperexcitability within medial temporal lobe regions vulnerable to AD pathophysiology. Greater deficits in AD-EPI+ suggests that reduced gamma PAC is a sensitive index of network hyperexcitability in AD patients. Collectively, the current results emphasize the importance of investigating the role of neural circuit hyperexcitability in early AD pathophysiology and explore its potential as a modifiable contributor to AD pathobiology.

Global MEG Resting State Functional Connectivity in Children with Autism and Sensory Processing Dysfunction.

Sensory processing dysfunction not only affects most individuals with autism spectrum disorder (ASD), but at least 5% of children without ASD also experience dysfunctional sensory processing. Our understanding of the relationship between sensory dysfunction and resting state brain activity is still emerging. This study compared long-range resting state functional connectivity of neural oscillatory behavior in children aged 8-12 years with autism spectrum disorder (ASD; N=18), those with sensory processing dysfunction (SPD; N=18) who do not meet ASD criteria, and typically developing control participants (TDC; N=24) using magnetoencephalography (MEG). Functional connectivity analyses were performed in the alpha and beta frequency bands, which are known to be implicated in sensory information processing. Group differences in functional connectivity and associations between sensory abilities and functional connectivity were examined. Distinct patterns of functional connectivity differences between ASD and SPD groups were found only in the beta band, but not in the alpha band. In both alpha and beta bands, ASD and SPD cohorts differed from the TDC cohort. Somatosensory cortical beta-band functional connectivity was associated with tactile processing abilities, while higher-order auditory cortical alpha-band functional connectivity was associated with auditory processing abilities. These findings demonstrate distinct long-range neural synchrony alterations in SPD and ASD that are associated with sensory processing abilities. Neural synchrony measures could serve as potential sensitive biomarkers for ASD and SPD.

Cortical Synchrony and Information Flow during Transition from Wakefulness to Light Non-Rapid Eye Movement Sleep.

Sleep is a highly stereotyped phenomenon, requiring robust spatiotemporal coordination of neural activity. Understanding how the brain coordinates neural activity with sleep onset can provide insights into the physiological functions subserved by sleep and the pathologic phenomena associated with sleep onset. We quantified whole-brain network changes in synchrony and information flow during the transition from wakefulness to light non-rapid eye movement (NREM) sleep, using MEG imaging in a convenient sample of 14 healthy human participants (11 female; mean 63.4 years [SD 11.8 years]). We furthermore performed computational modeling to infer excitatory and inhibitory properties of local neural activity. The transition from wakefulness to light NREM was identified to be encoded in spatially and temporally specific patterns of long-range synchrony. Within the delta band, there was a global increase in connectivity from wakefulness to light NREM, which was highest in frontoparietal regions. Within the theta band, there was an increase in connectivity in fronto-parieto-occipital regions and a decrease in temporal regions from wakefulness to Stage 1 sleep. Patterns of information flow revealed that mesial frontal regions receive hierarchically organized inputs from broad cortical regions upon sleep onset, including direct inflow from occipital regions and indirect inflow via parieto-temporal regions within the delta frequency band. Finally, biophysical neural mass modeling demonstrated changes in the anterior-to-posterior distribution of cortical excitation-to-inhibition with increased excitation-to-inhibition model parameters in anterior regions in light NREM compared with wakefulness. Together, these findings uncover whole-brain corticocortical structure and the orchestration of local and long-range, frequency-specific cortical interactions in the sleep-wake transition.SIGNIFICANCE STATEMENT Our work uncovers spatiotemporal cortical structure of neural synchrony and information flow upon the transition from wakefulness to light non-rapid eye movement sleep. Mesial frontal regions were identified to receive hierarchically organized inputs from broad cortical regions, including both direct inputs from occipital regions and indirect inputs via the parieto-temporal regions within the delta frequency range. Biophysical neural mass modeling revealed a spatially heterogeneous, anterior-posterior distribution of cortical excitation-to-inhibition. Our findings shed light on the orchestration of local and long-range cortical neural structure that is fundamental to sleep onset, and support an emerging view of cortically driven regulation of sleep homeostasis.

Phase Alignment of Low-Frequency Neural Activity to the Amplitude Envelope of Speech Reflects Evoked Responses to Acoustic Edges, Not Oscillatory Entrainment.

The amplitude envelope of speech is crucial for accurate comprehension. Considered a key stage in speech processing, the phase of neural activity in the theta-delta bands (1-10 Hz) tracks the phase of the speech amplitude envelope during listening. However, the mechanisms underlying this envelope representation have been heavily debated. A dominant model posits that envelope tracking reflects entrainment of endogenous low-frequency oscillations to the speech envelope. Alternatively, envelope tracking reflects a series of evoked responses to acoustic landmarks within the envelope. It has proven challenging to distinguish these two mechanisms. To address this, we recorded MEG while participants (n = 12, 6 female) listened to natural speech, and compared the neural phase patterns to the predictions of two computational models: an oscillatory entrainment model and a model of evoked responses to peaks in the rate of envelope change. Critically, we also presented speech at slowed rates, where the spectro-temporal predictions of the two models diverge. Our analyses revealed transient theta phase-locking in regular speech, as predicted by both models. However, for slow speech, we found transient theta and delta phase-locking, a pattern that was fully compatible with the evoked response model but could not be explained by the oscillatory entrainment model. Furthermore, encoding of acoustic edge magnitudes was invariant to contextual speech rate, demonstrating speech rate normalization of acoustic edge representations. Together, our results suggest that neural phase-locking to the speech envelope is more likely to reflect discrete representation of transient information rather than oscillatory entrainment.SIGNIFICANCE STATEMENT This study probes a highly debated topic in speech perception: the neural mechanisms underlying the cortical representation of the temporal envelope of speech. It is well established that the slow intensity profile of the speech signal, its envelope, elicits a robust brain response that "tracks" these envelope fluctuations. The oscillatory entrainment model posits that envelope tracking reflects phase alignment of endogenous neural oscillations. Here the authors provide evidence for a distinct mechanism. They show that neural speech envelope tracking arises from transient evoked neural responses to rapid increases in the speech envelope. Explicit computational modeling provides direct and compelling evidence that evoked responses are the primary mechanism underlying cortical speech envelope representations, with no evidence for oscillatory entrainment.

Glioblastoma remodelling of human neural circuits decreases survival.

Gliomas synaptically integrate into neural circuits1,2. Previous research has demonstrated bidirectional interactions between neurons and glioma cells, with neuronal activity driving glioma growth1-4 and gliomas increasing neuronal excitability2,5-8. Here we sought to determine how glioma-induced neuronal changes influence neural circuits underlying cognition and whether these interactions influence patient survival. Using intracranial brain recordings during lexical retrieval language tasks in awake humans together with site-specific tumour tissue biopsies and cell biology experiments, we find that gliomas remodel functional neural circuitry such that task-relevant neural responses activate tumour-infiltrated cortex well beyond the cortical regions that are normally recruited in the healthy brain. Site-directed biopsies from regions within the tumour that exhibit high functional connectivity between the tumour and the rest of the brain are enriched for a glioblastoma subpopulation that exhibits a distinct synaptogenic and neuronotrophic phenotype. Tumour cells from functionally connected regions secrete the synaptogenic factor thrombospondin-1, which contributes to the differential neuron-glioma interactions observed in functionally connected tumour regions compared with tumour regions with less functional connectivity. Pharmacological inhibition of thrombospondin-1 using the FDA-approved drug gabapentin decreases glioblastoma proliferation. The degree of functional connectivity between glioblastoma and the normal brain negatively affects both patient survival and performance in language tasks. These data demonstrate that high-grade gliomas functionally remodel neural circuits in the human brain, which both promotes tumour progression and impairs cognition.

Network connectivity predicts effectiveness of responsive neurostimulation in focal epilepsy.

Responsive neurostimulation is a promising treatment for drug-resistant focal epilepsy; however, clinical outcomes are highly variable across individuals. The therapeutic mechanism of responsive neurostimulation likely involves modulatory effects on brain networks; however, with no known biomarkers that predict clinical response, patient selection remains empiric. This study aimed to determine whether functional brain connectivity measured non-invasively prior to device implantation predicts clinical response to responsive neurostimulation therapy. Resting-state magnetoencephalography was obtained in 31 participants with subsequent responsive neurostimulation device implantation between 15 August 2014 and 1 October 2020. Functional connectivity was computed across multiple spatial scales (global, hemispheric, and lobar) using pre-implantation magnetoencephalography and normalized to maps of healthy controls. Normalized functional connectivity was investigated as a predictor of clinical response, defined as percent change in self-reported seizure frequency in the most recent year of clinic visits relative to pre-responsive neurostimulation baseline. Area under the receiver operating characteristic curve quantified the performance of functional connectivity in predicting responders (≥50% reduction in seizure frequency) and non-responders (<50%). Leave-one-out cross-validation was furthermore performed to characterize model performance. The relationship between seizure frequency reduction and frequency-specific functional connectivity was further assessed as a continuous measure. Across participants, stimulation was enabled for a median duration of 52.2 (interquartile range, 27.0-62.3) months. Demographics, seizure characteristics, and responsive neurostimulation lead configurations were matched across 22 responders and 9 non-responders. Global functional connectivity in the alpha and beta bands were lower in non-responders as compared with responders (alpha, pfdr < 0.001; beta, pfdr < 0.001). The classification of responsive neurostimulation outcome was improved by combining feature inputs; the best model incorporated four features (i.e. mean and dispersion of alpha and beta bands) and yielded an area under the receiver operating characteristic curve of 0.970 (0.919-1.00). The leave-one-out cross-validation analysis of this four-feature model yielded a sensitivity of 86.3%, specificity of 77.8%, positive predictive value of 90.5%, and negative predictive value of 70%. Global functional connectivity in alpha band correlated with seizure frequency reduction (alpha, P = 0.010). Global functional connectivity predicted responder status more strongly, as compared with hemispheric predictors. Lobar functional connectivity was not a predictor. These findings suggest that non-invasive functional connectivity may be a candidate personalized biomarker that has the potential to predict responsive neurostimulation effectiveness and to identify patients most likely to benefit from responsive neurostimulation therapy. Follow-up large-cohort, prospective studies are required to validate this biomarker. These findings furthermore support an emerging view that the therapeutic mechanism of responsive neurostimulation involves network-level effects in the brain.

Clinical Validation of the Champagne Algorithm for Evoked Response Source Localization in Magnetoencephalography.

Magnetoencephalography (MEG) is a robust method for non-invasive functional brain mapping of sensory cortices due to its exceptional spatial and temporal resolution. The clinical standard for MEG source localization of functional landmarks from sensory evoked responses is the equivalent current dipole (ECD) localization algorithm, known to be sensitive to initialization, noise, and manual choice of the number of dipoles. Recently many automated and robust algorithms have been developed, including the Champagne algorithm, an empirical Bayesian algorithm, with powerful abilities for MEG source reconstruction and time course estimation (Wipf et al. 2010; Owen et al. 2012). Here, we evaluate automated Champagne performance in a clinical population of tumor patients where there was minimal failure in localizing sensory evoked responses using the clinical standard, ECD localization algorithm. MEG data of auditory evoked potentials and somatosensory evoked potentials from 21 brain tumor patients were analyzed using Champagne, and these results were compared with equivalent current dipole (ECD) fit. Across both somatosensory and auditory evoked field localization, we found there was a strong agreement between Champagne and ECD localizations in all cases. Given resolution of 8mm voxel size, peak source localizations from Champagne were below 10mm of ECD peak source localization. The Champagne algorithm provides a robust and automated alternative to manual ECD fits for clinical localization of sensory evoked potentials and can contribute to improved clinical MEG data processing workflows.

Magnetoencephalography Imaging Reveals Abnormal Information Flow in Temporal Lobe Epilepsy.

Background/Introduction: Widespread network disruption has been hypothesized to be an important predictor of outcomes in patients with refractory temporal lobe epilepsy (TLE). Most studies examining functional network disruption in epilepsy have largely focused on the symmetric bidirectional metrics of the strength of network connections. However, a more complete description of network dysfunction impacts in epilepsy requires an investigation of the potentially more sensitive directional metrics of information flow. Methods: This study describes a whole-brain magnetoencephalography-imaging approach to examine resting-state directional information flow networks, quantified by phase-transfer entropy (PTE), in patients with TLE compared with healthy controls (HCs). Associations between PTE and clinical characteristics of epilepsy syndrome are also investigated. Results: Deficits of information flow were specific to alpha-band frequencies. In alpha band, while HCs exhibit a clear posterior-to-anterior directionality of information flow, in patients with TLE, this pattern of regional information outflow and inflow was significantly altered in the frontal and occipital regions. The changes in information flow within the alpha band in selected brain regions were correlated with interictal spike frequency and duration of epilepsy. Conclusions: Impaired information flow is an important dimension of network dysfunction associated with the pathophysiological mechanisms of TLE.

Neuronal synchrony abnormalities associated with subclinical epileptiform activity in early-onset Alzheimer's disease.

Since the first demonstrations of network hyperexcitability in scientific models of Alzheimer's disease, a growing body of clinical studies have identified subclinical epileptiform activity and associated cognitive decline in patients with Alzheimer's disease. An obvious problem presented in these studies is lack of sensitive measures to detect and quantify network hyperexcitability in human subjects. In this study we examined whether altered neuronal synchrony can be a surrogate marker to quantify network hyperexcitability in patients with Alzheimer's disease. Using magnetoencephalography (MEG) at rest, we studied 30 Alzheimer's disease patients without subclinical epileptiform activity, 20 Alzheimer's disease patients with subclinical epileptiform activity and 35 age-matched controls. Presence of subclinical epileptiform activity was assessed in patients with Alzheimer's disease by long-term video-EEG and a 1-h resting MEG with simultaneous EEG. Using the resting-state source-space reconstructed MEG signal, in patients and controls we computed the global imaginary coherence in alpha (8-12 Hz) and delta-theta (2-8 Hz) oscillatory frequencies. We found that Alzheimer's disease patients with subclinical epileptiform activity have greater reductions in alpha imaginary coherence and greater enhancements in delta-theta imaginary coherence than Alzheimer's disease patients without subclinical epileptiform activity, and that these changes can distinguish between Alzheimer's disease patients with subclinical epileptiform activity and Alzheimer's disease patients without subclinical epileptiform activity with high accuracy. Finally, a principal component regression analysis showed that the variance of frequency-specific neuronal synchrony predicts longitudinal changes in Mini-Mental State Examination in patients and controls. Our results demonstrate that quantitative neurophysiological measures are sensitive biomarkers of network hyperexcitability and can be used to improve diagnosis and to select appropriate patients for the right therapy in the next-generation clinical trials. The current results provide an integrative framework for investigating network hyperexcitability and network dysfunction together with cognitive and clinical correlates in patients with Alzheimer's disease.

Clinical Validation of the Champagne Algorithm for Epilepsy Spike Localization.

Magnetoencephalography (MEG) is increasingly used for presurgical planning in people with medically refractory focal epilepsy. Localization of interictal epileptiform activity, a surrogate for the seizure onset zone whose removal may prevent seizures, is challenging and depends on the use of multiple complementary techniques. Accurate and reliable localization of epileptiform activity from spontaneous MEG data has been an elusive goal. One approach toward this goal is to use a novel Bayesian inference algorithm-the Champagne algorithm with noise learning-which has shown tremendous success in source reconstruction, especially for focal brain sources. In this study, we localized sources of manually identified MEG spikes using the Champagne algorithm in a cohort of 16 patients with medically refractory epilepsy collected in two consecutive series. To evaluate the reliability of this approach, we compared the performance to equivalent current dipole (ECD) modeling, a conventional source localization technique that is commonly used in clinical practice. Results suggest that Champagne may be a robust, automated, alternative to manual parametric dipole fitting methods for localization of interictal MEG spikes, in addition to its previously described clinical and research applications.

Interhemispheric Auditory Cortical Synchronization in Asymmetric Hearing Loss.

OBJECTIVES: Auditory cortical activation of the two hemispheres to monaurally presented tonal stimuli has been shown to be asynchronous in normal hearing (NH) but synchronous in the extreme case of adult-onset asymmetric hearing loss (AHL) with single-sided deafness. We addressed the wide knowledge gap between these two anchoring states of interhemispheric temporal organization. The objectives of this study were as follows: (1) to map the trajectory of interhemispheric temporal reorganization from asynchrony to synchrony using magnitude of interaural threshold difference as the independent variable in a cross-sectional study and (2) to evaluate reversibility of interhemispheric synchrony in association with hearing in noise performance by amplifying the aidable poorer ear in a repeated measures, longitudinal study. DESIGN: The cross-sectional and longitudinal cohorts were comprised of 49 subjects (AHL; N = 21; 11 male, 10 female; mean age = 48 years) and NH (N = 28; 16 male, 12 female; mean age = 45 years). The maximum interaural threshold difference of the two cohorts spanned from 0 to 65 dB. Magnetoencephalography analyses focused on latency of the M100 peak response from auditory cortex in both hemispheres between 50 msec and 150 msec following monaural tonal stimulation at the frequency (0.5, 1, 2, 3, or 4 kHz) corresponding to the maximum and minimum interaural threshold difference for better and poorer ears separately. The longitudinal AHL cohort was drawn from three subjects in the cross-sectional AHL cohort (all male; ages 49 to 60 years; varied AHL etiologies; no amplification for at least 2 years). All longitudinal study subjects were treated by monaural amplification of the poorer ear and underwent repeated measures examination of the M100 response latency and quick speech in noise hearing in noise performance at baseline, and postamplification months 3, 6, and 12. RESULTS: The M100 response peak latency values in the ipsilateral hemisphere lagged those in the contralateral hemisphere for all stimulation conditions. The mean (SD) interhemispheric latency difference values (ipsilateral less contralateral) to better ear stimulation for three categories of maximum interaural threshold difference were as follows: NH (≤ 10 dB)-8.6 (3.0) msec; AHL (15 to 40 dB)-3.0 (1.2) msec; AHL (≥ 45 dB)-1.4 (1.3) msec. In turn, the magnitude of difference values were used to define interhemispheric temporal organization states of asynchrony, mixed asynchrony and synchrony, and synchrony, respectively. Amplification of the poorer ear in longitudinal subjects drove interhemispheric organization change from baseline synchrony to postamplification asynchrony and hearing in noise performance improvement in those with baseline impairment over a 12-month period. CONCLUSIONS: Interhemispheric temporal organization in AHL was anchored between states of asynchrony in NH and synchrony in single-sided deafness. For asymmetry magnitudes between 15 and 40 dB, the intermediate mixed state of asynchrony and synchrony was continuous and reversible. Amplification of the poorer ear in AHL improved hearing in noise performance and restored normal temporal organization of auditory cortices in the two hemispheres. The return to normal interhemispheric asynchrony from baseline synchrony and improvement in hearing following monoaural amplification of the poorer ear evolved progressively over a 12-month period.

NUTMEG: Open Source Software for M/EEG Source Reconstruction.

Neurodynamic Utility Toolbox for Magnetoencephalo- and Electroencephalography (NUTMEG) is an open-source MATLAB-based toolbox for the analysis and reconstruction of magnetoencephalography/electroencephalography data in source space. NUTMEG includes a variety of options for the user in data import, preprocessing, source reconstruction, and functional connectivity. A group analysis toolbox allows the user to run a variety of inferential statistics on their data in an easy-to-use GUI-driven format. Importantly, NUTMEG features an interactive five-dimensional data visualization platform. A key feature of NUTMEG is the availability of a large menu of interference cancelation and source reconstruction algorithms. Each NUTMEG operation acts as a stand-alone MATLAB function, allowing the package to be easily adaptable and scripted for the more advanced user for interoperability with other software toolboxes. Therefore, NUTMEG enables a wide range of users access to a complete "sensor-to- source-statistics" analysis pipeline.

Optimizing Magnetoencephalographic Imaging Estimation of Language Lateralization for Simpler Language Tasks.

Magnetoencephalographic imaging (MEGI) offers a non-invasive alternative for defining preoperative language lateralization in neurosurgery patients. MEGI indeed can be used for accurate estimation of language lateralization with a complex language task - auditory verb generation. However, since language function may vary considerably in patients with focal lesions, it is important to optimize MEGI for estimation of language function with other simpler language tasks. The goal of this study was to optimize MEGI laterality analyses for two such simpler language tasks that can have compliance from those with impaired language function: a non-word repetition (NWR) task and a picture naming (PN) task. Language lateralization results for these two tasks were compared to the verb-generation (VG) task. MEGI reconstruction parameters (regions and time windows) for NWR and PN were first defined in a presurgical training cohort by benchmarking these against laterality indices for VG. Optimized time windows and regions of interest (ROIs) for NWR and PN were determined by examining oscillations in the beta band (12-30 Hz) a marker of neural activity known to be concordant with the VG laterality index (LI). For NWR, additional ROIs include areas MTG/ITG and for both NWR and PN, the postcentral gyrus was included in analyses. Optimal time windows for NWR were defined as 650-850 ms (stimulus-locked) and -350 to -150 ms (response-locked) and for PN -450 to -250 ms (response-locked). To verify the optimal parameters defined in our training cohort for NWR and PN, we examined an independent validation cohort (n = 30 for NWR, n = 28 for PN) and found high concordance between VG laterality and PN laterality (82%) and between VG laterality and NWR laterality (87%). Finally, in a test cohort (n = 8) that underwent both the intracarotid amobarbital procedure (IAP) test and MEG for VG, NWR, and PN, we identified excellent concordance (100%) with IAP for VG + NWR + PN composite LI, high concordance for PN alone (87.5%), and moderate concordance for NWR alone (66.7%). These findings provide task options for non-invasive language mapping with MEGI that can be calibrated for language abilities of individual patients. Results also demonstrate that more accurate estimates can be obtained by combining laterality estimates obtained from multiple tasks. MEGI.

Motor Cortical Network Plasticity in Patients With Recurrent Brain Tumors.

Objective: The adult brain's potential for plastic reorganization is an important mechanism for the preservation and restoration of function in patients with primary glial neoplasm. Patients with recurrent brain tumors requiring multiple interventions over time present an opportunity to examine brain reorganization. Magnetoencephalography (MEG) is a noninvasive imaging modality that can be used for motor cortical network mapping which, when performed at regular intervals, offers insight into this process of reorganization. Utilizing MEG-based motor mapping, we sought to characterize the reorganization of motor cortical networks over time in a cohort of 78 patients with recurrent glioma. Methods: MEG-based motor cortical maps were obtained by measuring event-related desynchronization (ERD) in ß-band frequency during unilateral index finger flexion. Each patient presented at our Department at least on two occasions for tumor resection due to tumor recurrence, and MEG-based motor mapping was performed as part of preoperative assessment before each surgical resection. Whole-brain activation patterns from first to second MEG scan (obtained before first and second surgery) were compared. Additionally, we calculated distances of activation peaks, which represent the location of the primary motor cortex (MC), to determine the magnitude of movement in motor eloquent areas between the first and second MEG scan. We also explored which demographic, anatomic, and pathological factors influence these shifts. Results: The whole-brain activation motor maps showed a subtle movement of the primary MC from first to second timepoint, as was confirmed by the determination of motor activation peaks. The shift of ipsilesional MC was directly correlated with a frontal-parietal tumor location (p < 0.001), presence of motor deficits (p = 0.021), and with a longer period between MEG scans (p = 0.048). Also, a disengagement of wide areas in the contralesional (ipsilateral to finger movement) hemisphere at the second time point was observed. Conclusions: MEG imaging is a sensitive method for depicting the plasticity of the motor cortical network. Although the location of the primary MC undergoes only subtle changes, appreciable shifts can occur in the setting of a stronger and longer impairment of the tumor on the MC. The ipsilateral hemisphere may serve as a reservoir for functional recovery.

The impact of high functional connectivity network hub resection on language task performance in adult low- and high-grade glioma.

OBJECTIVE: Gliomas are intrinsic brain tumors with the hallmark of diffuse white matter infiltration, resulting in short- and long-range network dysfunction. Preoperative magnetoencephalography (MEG) can assist in maximizing the extent of resection while minimizing morbidity. While MEG has been validated in motor mapping, its role in speech mapping remains less well studied. The authors assessed how the resection of intraoperative electrical stimulation (IES)-negative, high functional connectivity (HFC) network sites, as identified by MEG, impacts language performance. METHODS: Resting-state, whole-brain MEG recordings were obtained from 26 patients who underwent perioperative language evaluation and glioma resection that was guided by awake language and IES mapping. The functional connectivity of an individual voxel was determined by the imaginary coherence between the index voxel and the rest of the brain, referenced to its contralesional pair. The percentage of resected HFC voxels was correlated with postoperative language outcomes in tasks of increasing complexity: text reading, 4-syllable repetition, picture naming, syntax (SYN), and auditory stimulus naming (AN). RESULTS: Overall, 70% of patients (14/20) in whom any HFC tissue was resected developed an early postoperative language deficit (mean 2.3 days, range 1-8 days), compared to 33% of patients (2/6) in whom no HFC tissue was resected (p = 0.16). When bifurcated by the amount of HFC tissue that was resected, 100% of patients (3/3) with an HFC resection > 25% displayed deficits in AN, compared to 30% of patients (6/20) with an HFC resection < 25% (p = 0.04). Furthermore, there was a linear correlation between the severity of AN and SYN decline with percentage of HFC sites resected (p = 0.02 and p = 0.04, respectively). By 2.2 months postoperatively (range 1-6 months), the correlation between HFC resection and both AN and SYN decline had resolved (p = 0.94 and p = 1.00, respectively) in all patients (9/9) except two who experienced early postoperative tumor progression or stroke involving inferior frontooccipital fasciculus. CONCLUSIONS: Imaginary coherence measures of functional connectivity using MEG are able to identify HFC network sites within and around low- and high-grade gliomas. Removal of IES-negative HFC sites results in early transient postoperative decline in AN and SYN, which resolved by 3 months in all patients without stroke or early tumor progression. Measures of functional connectivity may therefore be a useful means of counseling patients about postoperative risk and assist with preoperative surgical planning.

Global resting-state functional connectivity of neural oscillations in tinnitus with and without hearing loss.

This study examined global resting-state functional connectivity of neural oscillations in individuals with chronic tinnitus and normal and impaired hearing. We tested the hypothesis that distinct neural oscillatory networks are engaged in tinnitus with and without hearing loss. In both tinnitus groups, with and without hearing loss, we identified multiple frequency band-dependent regions of increased and decreased global functional connectivity. We also found that the auditory domain of tinnitus severity, assayed by the Tinnitus Functional Index, was associated with global functional connectivity in both auditory and nonauditory regions. These findings provide candidate biomarkers to target and monitor treatments for tinnitus with and without hearing loss.

Corticostriatal functional connectivity of bothersome tinnitus in single-sided deafness.

Subjective tinnitus is an auditory phantom perceptual disorder without an objective biomarker. Bothersome tinnitus in single-sided deafness (SSD) is particularly challenging to treat because the deaf ear can no longer be stimulated by acoustic means. We contrasted an SSD cohort with bothersome tinnitus (TIN; N = 15) against an SSD cohort with no or non-bothersome tinnitus (NO TIN; N = 15) using resting-state functional magnetic resonance imaging (fMRI). All study participants had normal hearing in one ear and severe or profound hearing loss in the other. We evaluated corticostriatal functional connectivity differences by placing seeds in the caudate nucleus and Heschl's Gyrus (HG) of both hemispheres. The TIN cohort showed increased functional connectivity between the left caudate and left HG, and left and right HG and the left caudate. Within the TIN cohort, functional connectivity between the right caudate and cuneus was correlated with the Tinnitus Functional Index (TFI) relaxation subscale. And, functional connectivity between the right caudate and superior lateral occipital cortex, and the right caudate and anterior supramarginal gyrus were correlated with the TFI control subscale. These findings support a striatal gating model of tinnitus and suggest tinnitus biomarkers to monitor treatment response and to target specific brain areas for innovative neuromodulation therapies.

Sensorimotor Cortical Oscillations during Movement Preparation in 16p11.2 Deletion Carriers.

Sensorimotor deficits are prevalent in many neurodevelopmental disorders like autism, including one of its common genetic etiologies, a 600 kb reciprocal deletion/duplication at 16p11.2. We have previously shown that copy number variations of 16p11.2 impact regional brain volume, white matter integrity, and early sensory responses in auditory cortex. Here, we test the hypothesis that abnormal cortical neurophysiology is present when genes in the 16p11.2 region are haploinsufficient, and in humans that this in turn may account for behavioral deficits specific to deletion carriers. We examine sensorimotor cortical network activity in males and females with 16p11.2 deletions compared with both typically developing individuals, and those with duplications of 16p11.2, using magnetoencephalographic imaging during preparation of overt speech or hand movements in tasks designed to be easy for all participants. In deletion carriers, modulation of beta oscillations (12-30 Hz) were increased during both movement types over effector-specific regions of motor cortices compared with typically developing individuals or duplication carriers, with no task-related performance differences between cohorts, even when corrected for their own cognitive and sensorimotor deficits. Reduced left hemispheric language specialization was observed in deletion carriers but not in duplication carriers. Neural activity over sensorimotor cortices in deletion carriers was linearly related to clinical measures of speech and motor impairment. These findings link insufficient copy number repeats at 16p11.2 to excessive neural activity (e.g., increased beta oscillations) in motor cortical networks for speech and hand motor control. These results have significant implications for understanding the neural basis of autism and related neurodevelopmental disorders.SIGNIFICANCE STATEMENT The recurrent ∼600 kb deletion at 16p11.2 (BP4-BP5) is one of the most common genetic etiologies of ASD and, more generally, of neurodevelopmental disorders. Here, we use high-resolution magnetoencephalographic imaging (MEG-I) to define with millisecond precision the underlying neurophysiological signature of motor impairments for individuals with 16p11.2 deletions. We identify significant increases in beta (12-30 Hz) suppression in sensorimotor cortices related to performance during speech and hand movement tasks. These findings not only provide a neurophysiological phenotype for the clinical presentation of this genetic deletion, but also guide our understanding of how genetic variation encodes for neural oscillatory dynamics.

Beta-band activity in medial prefrontal cortex predicts source memory encoding and retrieval accuracy.

Reality monitoring is defined as the ability to distinguish internally self-generated information from externally-derived information. The medial prefrontal cortex (mPFC) is a key brain region subserving reality monitoring and has been shown to be activated specifically during the retrieval of self-generated information. However, it is unclear if mPFC is activated during the encoding of self-generated information into memory. If so, it is important to understand whether successful retrieval of self-generated information critically depends on enhanced neural activity within mPFC during initial encoding of this self-generated information. We used magnetoencephalographic imaging (MEGI) to determine the timing and location of cortical activity during a reality-monitoring task involving self generated contextual source memory encoding and retrieval. We found both during encoding and retrieval of self-generated information, when compared to externally-derived information, mPFC showed significant task induced oscillatory power modulation in the beta-band. During initial encoding of self-generated information, greater mPFC beta-band power reductions occurred within a time window of -700 ms to -500 ms prior to vocalization. This increased activity in mPFC was not observed during encoding of externally-derived information. Additionally, increased mPFC activity during encoding of self-generated information predicted subsequent retrieval accuracy of this self-generated information. Beta-band activity in mPFC was also observed during the initial retrieval of self-generated information within a time window of 300 to 500 ms following stimulus onset and correlated with accurate retrieval performance of self-generated information. Together, these results further highlight the importance of mPFC in mediating the initial generation and awareness of participants' internal thoughts.