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Lesion and neuroimaging studies indicate that the insula mediates motor aspects of speech production, specifically, articulatory control. Although it has direct connections to Broca's area, the canonical speech production region, the insula is also broadly connected with other speech and language centres, and may play a role in coordinating higher-order cognitive aspects of speech and language production. The extent of the insula's involvement in speech and language processing was assessed using the Activation Likelihood Estimate (ALE) method. Meta-analyses of 42 fMRI studies with healthy adults were performed, comparing insula activation during performance of language (expressive and receptive) and speech (production and perception) tasks. Both tasks activated bilateral anterior insulae. However, speech perception tasks preferentially activated the left dorsal mid-insula, whereas expressive language tasks activated left ventral mid-insula. Results suggest distinct regions of the mid-insula play different roles in speech and language processing.

The Organization for Human Brain Mapping (OHBM) has been active in advocating for the instantiation of best practices in neuroimaging data acquisition, analysis, reporting, and sharing of both data and analysis code, to deal with issues in science related to reproducibility and replicability. Here we summarize recommendations for such practices in magnetoencephalographic (MEG) and electroencephalographic (EEG) research, recently developed by the OHBM neuroimaging community known by the abbreviated name of COBIDAS MEEG. We discuss rationale for the guidelines and their general content, which encompasses many topics under active discussion in the field. We highlight future opportunities and challenges to maximizing the sharing and exploitation of MEG and EEG data, and also how this 'living' set of guidelines will evolve to continually address new developments in neurophysiological assessment methods and multimodal integration of neurophysiological data with other data types.

Objective: Vagus nerve stimulation (VNS) is a common treatment for medically intractable epilepsy, but response rates are highly variable, with no preoperative means of identifying good candidates. This study aimed to predict VNS response using structural and functional connectomic profiling. Methods: Fifty-six children, comprising discovery (n = 38) and validation (n = 18) cohorts, were recruited from 3 separate institutions. Diffusion tensor imaging was used to identify group differences in white matter microstructure, which in turn informed beamforming of resting-state magnetoencephalography recordings. The results were used to generate a support vector machine learning classifier, which was independently validated. This algorithm was compared to a second classifier generated using 31 clinical covariates. Results: Treatment responders demonstrated greater fractional anisotropy in left thalamocortical, limbic, and association fibers, as well as greater connectivity in a functional network encompassing left thalamic, insular, and temporal nodes (p < 0.05). The resulting classifier demonstrated 89.5% accuracy and area under the receiver operating characteristic (ROC) curve of 0.93 on 10-fold cross-validation. In the external validation cohort, this model demonstrated an accuracy of 83.3%, with a sensitivity of 85.7% and specificity of 75.0%. This was significantly superior to predictions using clinical covariates alone, which exhibited an area under the ROC curve of 0.57 (p < 0.008). Interpretation: This study provides the first multi-institutional, multimodal connectomic prediction algorithm for VNS, and provides new insights into its mechanism of action. Reliable identification of VNS responders is critical to mitigate surgical risks for children who may not benefit, and to ensure cost-effective allocation of health care resources. ANN NEUROL 2019;86:743-753 N early one-third of children with epilepsy are refractory to medications. 1,2 Persistent seizures are associated with mortality, disability, psychosocial isolation, and diminished quality of life. 3-6 Vagus nerve stimulation (VNS) is an effective, safe, and well-tolerated intervention for a subset of patients with treatment-resistant epilepsy. 7-10 Although the goal of VNS is not complete resolution of seizures, many children will show a significant reduction in seizure frequency, as well as a reduction in hospitalizations and psychosocial comorbidities. 11,12 View this article online at wileyonlinelibrary.com.

To characterize the developmental trajectory for expressive language representation and to test competing explanations for the relative neuroplasticity of language in childhood, we studied 28 healthy children and adolescents (aged 5-19 years) participating in a covert verb generation task in magnetoencephalography. Lateralization of neuromagnetic responses in the frontal lobe was quantified using a bootstrap statistical thresholding procedure for differential beamformer analyses. We observed a significant positive correlation between left hemisphere lateralization and age. Findings suggest that adult-typical left hemisphere lateralization emerges from an early bilateral language network, which may explain the pediatric advantage for interhemispheric plasticity of language.

Post-traumatic stress disorder (PTSD) is a serious mental health injury which can manifest after experiencing a traumatic life event. The disorder is characterized by symptoms of re-experiencing, avoidance, emotional numbing and hyper-arousal. Whilst its aetiology and resultant symptomology are better understood, relatively little is known about the underlying cortical pathophysiology, and in particular whether changes in functional connectivity may be linked to the disorder. Here, we used non-invasive neuroimaging with magnetoencephalography to examine functional connectivity in a resting-state protocol in the combat-related PTSD group (n = 23), and a military control group (n = 21). We identify atypical long-range hyperconnectivity in the high-gamma-band resting-state networks in a combat-related PTSD population compared to soldiers who underwent comparable environmental exposure but did not develop PTSD. Using graph analysis, we demonstrate that apparent network connectivity of relevant brain regions is associated with cognitive-behavioural outcomes. We also show that left hippocampal connectivity in the PTSD group correlates with scores on the well-established PTSD Checklist (PCL). These findings indicate that atypical synchronous neural interactions may underlie the psychological symptoms of PTSD, whilst also having utility as a potential biomarker to aid in the diagnosis and monitoring of the disorder.

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