The ability to discriminate speech sounds is crucial for higher language functions in humans. However, it remains unclear whether physiological aging affects the functional integrity of pre-attentive phonological discrimination. The neuromagnetic cortical responses during automatic change detection of speech sounds (/ba/versus/da/) were recorded in 24 young and 21 aged male adults. We used minimum norm estimate of source reconstruction to characterize the spatiotemporal dynamics of magnetic mismatch responses (MMNm). Distributed activations to phonetic changes were identified in the temporal, frontal and parietal regions. Compared to younger participants, elderly volunteers exhibited a significant reduction of cortical responses to phonetic-MMNm, except for the left orbitofrontal cortex and anterior inferior temporal gyrus. However, among the identified regions of interest, we did not observe significant between-group differences in the hemispheric asymmetry of phonetic-MMNm. Conclusively, our results suggest an altered phonetic processing at the perceptual level during physiological aging.

Sensory gating, a habituation-related but more basic protective mechanism against brain sensory overload, is altered in patients with migraine and linked to headache severity. This study investigated whether somatosensory (SI) gating responses determined 3-months treatment outcomes in patients with episodic migraine (EM) and chronic migraine (CM). A 306-channel magnetoencephalography (MEG) with paired-pulse stimulation paradigm was used to record their neuromagnetic responses. To calculate the peak amplitude and latency and compute the gating ratios (second vs. first amplitude), the first and second responses to the paired stimuli from the primary somatosensory cortex were obtained. All patients were assigned to subgroups labeled good or poor according to their headache frequency at baseline compared with at the third month of treatment. The gating ratio in the CM group (n = 37) was significantly different between those identified as good and poor (p = 0.009). In the EM group (n = 30), the latency in the second response differed by treatment outcomes (p = 0.007). In the receiver operating characteristic analysis, the areas under the curve for the CM and EM groups were 0.737 and 0.761, respectively. Somatosensory gating responses were associated with treatment outcomes in patients with migraine; future studies with large patient samples are warranted.

Paired-pulse stimulation has been used previously to evaluate cortical excitability and sensory gating. To help elucidate the neural network involved in paired-pulse suppression of somatosensory cortical processing, magnetoencephalographic (MEG) responses to paired-pulse electrical stimulation of the left median nerve of the wrists of 13 healthy males were recorded using an intra-pair interstimulus interval (ISI) of 500ms and an inter-pair ISI of 8s. Minimum norm estimates showed the presence of cortical activation in the bilateral primary somatosensory cortex, the post-central sulcus and the supplementary motor areas. Compared with the responses to the first stimulation, the responses to the second stimulation were attenuated in these areas with gating ratios (the amplitude ratios of the second response to the first response) of 0.54-0.69. By spectral power dynamic analysis, beta frequency oscillations were found to be associated with an early-latency (30-36ms) gating process in the contralateral primary somatosensory cortex and post-central sulcus, whereas theta and alpha oscillations were correlated with paired-pulse suppression of activations at 98-136ms in the ipsilateral primary somatosensory cortex, the bilateral post-central sulcus and the supplementary motor areas. In summary, it can be concluded that differential oscillatory activities are involved in the pair-pulse suppression in various somatosensory regions in response to repetitive external stimulations.

Parkinson's disease (PD) is a neurodegenerative disorder characterised by motor abnormalities. Many non-demented patients with PD have cognitive impairment especially in executive functions. Using magnetoencephalographic (MEG) recording combined with event-related desynchronisation/synchronisation (ERD/ERS) analysis, we investigated cortical executive functions during a Go/NoGo task in PD patients and matched healthy subjects. PD patients had a longer reaction time in the Go condition and had a higher error ratio in both Go and NoGo conditions. The MEG analysis showed that the PD patients had a significant reduction in beta ERD during the NoGo condition and in beta ERS during both Go and NoGo conditions compared with the healthy subjects (all p < 0.05). Moreover, in the Go condition, the onsets of beta ERD and ERS were delayed in PD patients. Notably, NoGo ERS was negatively correlated with the Unified Parkinson's Disease Rating Scale (UPDRS) score in PD patients. The present study demonstrated abnormalities in motor programming, response inhibition, and frontal inhibitory modulation in PD. Further extensive investigations are necessary to confirm the longitudinal treatment responses in PD.

Although aging-related alterations in the auditory sensory memory and involuntary change discrimination have been widely studied, it remains controversial whether the mismatch negativity (MMN) or its magnetic counterpart (MMNm) is modulated by physiological aging. This study aimed to examine the effects of aging on mismatch activity to pitch deviants by using a whole-head magnetoencephalography (MEG) together with distributed source modeling analysis. The neuromagnetic responses to oddball paradigms consisting of standards (1000 Hz, p=0.85) and deviants (1100 Hz, p=0.15) were recorded in healthy young (n=20) and aged (n=18) male adults. We used minimum norm estimate of source reconstruction to characterize the spatiotemporal neural dynamics of MMNm responses. Distributed activations to MMNm were identified in the bilateral fronto-temporo-parietal areas. Compared to younger participants, the elderly exhibited a significant reduction of cortical activation in bilateral superior temporal guri, superior temporal sulci, inferior fontal gyri, orbitofrontal cortices and right inferior parietal lobules. In conclusion, our results suggest an aging-related decline in auditory sensory memory and automatic change detection as indexed by MMNm.

Fibromyalgia (FM) is a disabling chronic pain syndrome with unknown pathophysiology. Functional magnetic resonance imaging studies on FM have suggested altered brain connectivity between the insula and the default mode network (DMN). However, this connectivity change has not been characterized through direct neural signals for exploring the embedded spectrotemporal features and the pertinent clinical relevance.

Pain sensitivity may determine the risk, severity, prognosis, and efficacy of treatment of clinical pain. Magnetic resonance imaging studies have linked thermal pain sensitivity to changes in brain structure. However, the neural correlates of mechanical pain sensitivity remain to be clarified through investigation of direct neural activities on the resting-state cortical oscillation and synchrony.

Discriminating between those with and without subjective cognitive decline (SCD) in cross-sectional investigations using neuropsychological tests is challenging. The available magnetoencephalographic (MEG) studies have demonstrated altered alpha-band spectral power and functional connectivity in those with SCD. However, whether the functional connectivity in other frequencies and brain networks, particularly the default mode network (DMN), exhibits abnormalities in SCD remains poorly understood. We recruited 26 healthy controls (HC) without SCD and 27 individuals with SCD to perform resting-state MEG recordings. The power of each frequency band and functional connectivity within the DMN were compared between these two groups. Posterior cingulate cortex (PCC)-based connectivity was also used to test its diagnostic accuracy as a predictor of SCD. There were no significant between-group differences of spectral power in the regional nodes. However, compared with HC, those with SCD demonstrated increased delta-band and gamma-band functional connectivity within the DMN. Moreover, node strength in the PCC exhibited a good discrimination ability at both delta and gamma frequencies. Our data suggest that the node strength of delta and gamma frequencies in the PCC may be a good neurophysiological marker in the discrimination of individuals with SCD from those without SCD.

To determine specific resting-state network patterns underlying alterations in chronic migraine, we employed oscillatory connectivity and machine learning techniques to distinguish patients with chronic migraine from healthy controls and patients with other pain disorders. This cross-sectional study included 350 participants (70 healthy controls, 100 patients with chronic migraine, 40 patients with chronic migraine with comorbid fibromyalgia, 35 patients with fibromyalgia, 30 patients with chronic tension-type headache, and 75 patients with episodic migraine). We collected resting-state magnetoencephalographic data for analysis. Source-based oscillatory connectivity within each network, including the pain-related network, default mode network, sensorimotor network, visual network, and insula to default mode network, was examined to determine intrinsic connectivity across a frequency range of 1-40 Hz. Features were extracted to establish and validate classification models constructed using machine learning algorithms. The findings indicated that oscillatory connectivity revealed brain network abnormalities in patients with chronic migraine compared with healthy controls, and that oscillatory connectivity exhibited distinct patterns between various pain disorders. After the incorporation of network features, the best classification model demonstrated excellent performance in distinguishing patients with chronic migraine from healthy controls, achieving high accuracy on both training and testing datasets (accuracy > 92.6% and area under the curve > 0.93). Moreover, in validation tests, classification models exhibited high accuracy in discriminating patients with chronic migraine from all other groups of patients (accuracy > 75.7% and area under the curve > 0.8). In conclusion, oscillatory synchrony within the pain-related network and default mode network corresponded to altered neurophysiological processes in patients with chronic migraine. Thus, these networks can serve as pivotal signatures in the model for identifying patients with chronic migraine, providing reliable and generalisable results. This approach may facilitate the objective and individualised diagnosis of migraine.

To identify and validate the neural signatures of resting-state oscillatory connectivity for chronic migraine (CM), we used machine learning techniques to classify patients with CM from healthy controls (HC) and patients with other pain disorders. The cross-sectional study obtained resting-state magnetoencephalographic data from 240 participants (70 HC, 100 CM, 35 episodic migraine [EM], and 35 fibromyalgia [FM]). Source-based oscillatory connectivity of relevant cortical regions was calculated to determine intrinsic connectivity at 1-40 Hz. A classification model that employed a support vector machine was developed using the magnetoencephalographic data to assess the reliability and generalizability of CM identification. In the findings, the discriminative features that differentiate CM from HC were principally observed from the functional interactions between salience, sensorimotor, and part of the default mode networks. The classification model with these features exhibited excellent performance in distinguishing patients with CM from HC (accuracy ≥ 86.8%, area under the curve (AUC) ≥ 0.9) and from those with EM (accuracy: 94.5%, AUC: 0.96). The model also achieved high performance (accuracy: 89.1%, AUC: 0.91) in classifying CM from other pain disorders (FM in this study). These resting-state magnetoencephalographic electrophysiological features yield oscillatory connectivity to identify patients with CM from those with a different type of migraine and pain disorder, with adequate reliability and generalizability.

Paroxysmal kinesigenic dyskinesia (PKD) is conventionally regarded as a movement disorder (MD) and characterized by episodic hyperkinesia by sudden movements. However, patients of PKD often have sensory aura and respond excellently to antiepileptic agents. PRRT2 mutations, the most common genetic etiology of PKD, could cause epilepsy syndromes as well. Standing in the twilight zone between MDs and epilepsy, the pathogenesis of PKD is unclear. Gamma oscillations arise from the inhibitory interneurons which are crucial in the thalamocortical circuits. The role of synchronized gamma oscillations in sensory gating is an important mechanism of automatic cortical inhibition. The patterns of gamma oscillations have been used to characterize neurophysiological features of many neurological diseases, including epilepsy and MDs. This study was aimed to investigate the features of gamma synchronizations in PKD. In the paired-pulse electrical-stimulation task, we recorded the magnetoencephalographic data with distributed source modeling and time-frequency analysis in 19 patients of newly-diagnosed PKD without receiving pharmacotherapy and 18 healthy controls. In combination with the magnetic resonance imaging, the source of gamma oscillations was localized in the primary somatosensory cortex. Somatosensory evoked fields of PKD patients had a reduced peak frequency (p < 0.001 for the first and the second response) and a prolonged peak latency (the first response p = 0.02, the second response p = 0.002), indicating the synchronization of gamma oscillation is significantly attenuated. The power ratio between two responses was much higher in the PKD group (p = 0.013), indicating the incompetence of activity suppression. Aberrant gamma synchronizations revealed the defective sensory gating of the somatosensory area contributes the pathogenesis of PKD. Our findings documented disinhibited cortical function is a pathomechanism common to PKD and epilepsy, thus rationalized the clinical overlaps of these two diseases and the therapeutic effect of antiepileptic agents for PKD. There is a greater reduction of the peak gamma frequency in PRRT2-related PKD than the non-PRRT PKD group (p = 0.028 for the first response, p = 0.004 for the second response). Loss-of-function PRRT2 mutations could lead to synaptic dysfunction. The disinhibiton change on neurophysiology reflected the impacts of PRRT2 mutations on human neurophysiology.