The normative values of pain thresholds in healthy Taiwanese.

OBJECTIVE: Quantitative sensory testing is widely used in clinical and research settings to assess the sensory functions of healthy subjects and patients. It is of importance to establish normative values in a healthy population to provide reference for studies involving patients. Given the absence of normative values for pain thresholds in Taiwan, the aim of this study was to report the normative values for future reference in the Taiwanese population and compare the differences between male and female participants. METHODS: Healthy adults without any chronic or acute pain condition were recruited. The pain thresholds were assessed over the cephalic (supraorbital area and masseter muscle) and extracephalic (medio-volar forearm and thenar eminence) areas. The heat, cold, mechanical punctate, and pressure pain thresholds were measured with a standardized protocol. Comparisons between male and female participants were performed. RESULTS: One hundred and thirty healthy participants (55 males: 30.4 ± 7.4 years; 75 females: 30.5 ± 8.1 years) finished the assessments. Male participants were less sensitive to mechanical stimuli, including pressure over masseter muscle (male vs. female: 178.5 ± 56.7 vs. 156.6 ± 58.4 kPa, p = .034) and punctate over medio-volar forearm (male vs. female: 116.4 ± 45.2 vs. 98.7 ± 65.4 g, p = .011), compared to female participants. However, female participants were less sensitive to cold stimuli, indicated by lower cold pain thresholds over the supraorbital area (male vs. female: 18.6 ± 8.4 vs. 13.6 ± 9.3°C, p = .004), compared to male participants. No significant differences were found between sexes in other pain threshold parameters. CONCLUSIONS: We provided the normative values of healthy male and female adults in Taiwan. This information is crucial for comparison in future pain-related studies to identify potential hypoalgesia or hyperalgesia of tested subjects.

Decoding pain through facial expressions: a study of patients with migraine.

BACKGROUND: The present study used the Facial Action Coding System (FACS) to analyse changes in facial activities in individuals with migraine during resting conditions to determine the potential of facial expressions to convey information about pain during headache episodes. METHODS: Facial activity was recorded in calm and resting conditions by using a camera for both healthy controls (HC) and patients with episodic migraine (EM) and chronic migraine (CM). The FACS was employed to analyse the collected facial images, and intensity scores for each of the 20 action units (AUs) representing expressions were generated. The groups and headache pain conditions were then examined for each AU. RESULTS: The study involved 304 participants, that is, 46 HCs, 174 patients with EM, and 84 patients with CM. Elevated headache pain levels were associated with increased lid tightener activity and reduced mouth stretch. In the CM group, moderate to severe headache attacks exhibited decreased activation in the mouth stretch, alongside increased activation in the lid tightener, nose wrinkle, and cheek raiser, compared to mild headache attacks (all corrected p < 0.05). Notably, lid tightener activation was positively correlated with the Numeric Rating Scale (NRS) level of headache (p = 0.012). Moreover, the lip corner depressor was identified to be indicative of emotional depression severity (p < 0.001). CONCLUSION: Facial expressions, particularly lid tightener actions, served as inherent indicators of headache intensity in individuals with migraine, even during resting conditions. This indicates that the proposed approach holds promise for providing a subjective evaluation of headaches, offering the benefits of real-time assessment and convenience for patients with migraine.

Characteristic oscillatory brain networks for predicting patients with chronic migraine.

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.

Abnormal heart rate variability and its application in predicting treatment efficacy in patients with chronic migraine: An exploratory study.

AIM: This study aimed to investigate the extent of autonomic nervous system dysfunction in patients with chronic migraine using heart rate variability analysis. In addition, we explored the potential association between heart rate variability and treatment outcomes in patients receiving preventive treatment. METHODS: In this cross-sectional and prospective study, we compared heart rate variability profiles in 81 preventive-naïve chronic migraine patients and 58 healthy controls. In addition, treatment responses of patients, who received a 12-week treatment with flunarizine, were assessed in relation to baseline heart rate variability. RESULTS: We observed that chronic migraine patients had a reduced heart rate variability, signifying autonomic dysfunction in comparison to healthy controls. Furthermore, patients presenting normal heart rate variability, characterized by a standard deviation exceeding 30 milliseconds in normal-to-normal RR intervals, experienced a superior response to flunarizine treatment. This improvement was exemplified by a significantly larger reduction in monthly headache days for patients with higher heart rate variability compared to those with lower heart rate variability: -9.7 (5.9) vs. -6.2 (6.0) days (p = .026). CONCLUSIONS: Autonomic dysfunction occurs in chronic migraine as evaluated by heart rate variability. A preserved function is associated with a better treatment outcome to flunarizine.Trial registration: Neurologic Signatures of Chronic Pain Disorders, NCT02747940. Registered 22 April 2016, https://clinicaltrials.gov/ct2/show/NCT02747940.

Electrophysiological findings in migraine may reflect abnormal synaptic plasticity mechanisms: A narrative review.

BACKGROUND: The cyclical brain disorder of sensory processing accompanying migraine phases lacks an explanatory unified theory. METHODS: We searched Pubmed for non-invasive neurophysiological studies on migraine and related conditions using transcranial magnetic stimulation, electroencephalography, visual and somatosensory evoked potentials. We summarized the literature, reviewed methods, and proposed a unified theory for the pathophysiology of electrophysiological abnormalities underlying migraine recurrence. RESULTS: All electrophysiological modalities have determined specific changes in brain dynamics across the different phases of the migraine cycle. Transcranial magnetic stimulation studies show unbalanced recruitment of inhibitory and excitatory circuits, more consistently in aura, which ultimately results in a substantially distorted response to neuromodulation protocols. Electroencephalography investigations highlight a steady pattern of reduced alpha and increased slow rhythms, largely located in posterior brain regions, which tends to normalize closer to the attacks. Finally, non-painful evoked potentials suggest dysfunctions in habituation mechanisms of sensory cortices that revert during ictal phases. CONCLUSION: Electrophysiology shows dynamic and recurrent functional alterations within the brainstem-thalamus-cortex loop varies continuously and recurrently in migraineurs. Given the central role of these structures in the selection, elaboration, and learning of sensory information, these functional alterations suggest chronic, probably genetically determined dysfunctions of the synaptic short- and long-term learning mechanisms.

Identification of patients with chronic migraine by using sensory-evoked oscillations from the electroencephalogram classifier.

BACKGROUND: To examine whether the modulating evoked cortical oscillations could be brain signatures among patients with chronic migraine, we investigated cortical modulation using an electroencephalogram with machine learning techniques. METHODS: We directly record evoked electroencephalogram activity during nonpainful, painful, and repetitive painful electrical stimulation tasks. Cortical modulation for experimental pain and habituation processing was analyzed and used to differentiate patients with chronic migraine from healthy controls using a validated machine-learning model. RESULTS: This study included 80 participants: 40 healthy controls and 40 patients with chronic migraine. Evoked somatosensory oscillations were dominant in the alpha band. Longer latency (nonpainful and repetitive painful) and augmented power (nonpainful and repetitive painful) were present among patients with chronic migraine. However, for painful tasks, alpha increases were observed among healthy controls. The oscillatory activity ratios between repetitive painful and painful tasks represented the frequency modulation and power habituation among healthy controls, respectively, but not among patients with chronic migraine. The classification models with oscillatory features exhibited high performance in differentiating patients with chronic migraine from healthy controls. CONCLUSION: Altered oscillatory characteristics of sensory processing and cortical modulation reflected the neuropathology of patients with chronic migraine. These characteristics can be reliably used to identify patients with chronic migraine using a machine-learning approach.

Resting-state magnetoencephalographic oscillatory connectivity to identify patients with chronic migraine using machine learning.

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.

Resting-state occipital alpha power is associated with treatment outcome in patients with chronic migraine.

ABSTRACT: Preventive treatment is crucial for patients with chronic migraine (CM). This study explored the association between resting-state cortical oscillations and 3-month treatment outcome in patients with CM. Treatment-naïve patients with CM were recruited with their demographic data, psychosocial data, and headache profiles as well as the healthy controls (HCs). Resting-state cortical activities were recorded using an electroencephalogram and analysed using source-based and electrode-based spectral power method. The regions of interest were the bilateral primary somatosensory (S1) and visual (V1) cortices. After 3-month treatment with flunarizine, patients with CM were categorized into responders and nonresponders. Demographic, clinical, and electroencephalogram data from 72 patients with CM and 50 HCs were analysed. Elevated anxiety, depression, and stress were observed in patients with CM. Theta power in bilateral S1 and alpha and gamma powers in the right S1 increased in patients with CM. Nonresponders (n = 34) exhibited larger alpha powers in bilateral V1 than those in responders (n = 38). Alpha powers also exhibited significant correlations with changes of monthly headache days. Notably, in responders and nonresponders, occipital alpha powers did not differ at baseline and in the third month. In conclusion, patients with CM who were not responsive to preventive treatment were associated with augmented resting-state occipital alpha activity. Moreover, changes in migraine attack frequency were associated with baseline occipital alpha power. However, the prognostic feature of visual alpha oscillation seems to be inherent because it is not altered by flunarizine treatment. These findings may be useful for developing personalised migraine treatment plans.

Resting State Electrophysiological Cortical Activity: A Brain Signature Candidate for Patients with Migraine.

PURPOSE OF REVIEW: Studies on event-related evoked potentials have indicated that altered cortical processing of sensory stimuli is associated with migraine. However, the results depend on the experimental method and patients. Electrophysiology of resting state cortical activity has revealed compelling results regarding the pathophysiology of migraine. This review summarized the available information related to patients with episodic and chronic migraine to determine whether certain features can be used as signatures for migraine. RECENT FINDINGS: A recent study examined differences in resting state functional connectivity among the pain-related regions and revealed that beta connectivity was attenuated in migraine and that altered connectivity in the anterior cingulate cortex was linked to migraine chronification. These findings suggested that chronification leads to neuroplasticity in the pain areas of higher-level processing rather than in areas involved in basic sensory discrimination (i.e., primary and secondary somatosensory areas). Another study discovered that the betweenness centrality of delta band in right precuneus was significantly lower in those with longer history of migraine. Electroencephalogram may also predict the treatment outcomes in patients with chronic migraine that those with lower pre-treatment occipital alpha power tend to show greater reduction in headache frequency. Studies on resting state activity have yielded convincing findings regarding aberrant oscillatory power and functional connectivity in relation to migraine, thus contributing to identifying brain signatures for migraine. The role of such assessment in precision medicine should be further investigated.

Dynamic brainstem and somatosensory cortical excitability during migraine cycles.

BACKGROUND: Migraine has complex pathophysiological characteristics and episodic attacks. To decipher the cyclic neurophysiological features of migraine attacks, in this study, we compared neuronal excitability in the brainstem and primary somatosensory (S1) region between migraine phases for 30 consecutive days in two patients with episodic migraine. METHODS: Both patients underwent EEG recording of event-related potentials with the somatosensory and paired-pulse paradigms for 30 consecutive days. The migraine cycle was divided into the following phases: 24-48 h before headache onset (Pre2), within 24 h before headache onset (Pre1), during the migraine attack (Ictal), within 24 h after headache offset (Post1), and the interval of ˃48 h between the last and next headache phase (Interictal). The normalised current intensity in the brainstem and S1 and gating ratio in the S1 were recorded and examined. RESULTS: Six migraine cycles (three for each patient) were analysed. In both patients, the somatosensory excitability in the brainstem (peaking at 12-14 ms after stimulation) and S1 (peaking at 18-19 ms after stimulation) peaked in the Pre1 phase. The S1 inhibitory capability was higher in the Ictal phase than in the Pre1 phase. CONCLUSION: This study demonstrates that migraine is a cyclic excitatory disorder and that the neural substrates involved include the somatosensory system, starting in the brainstem and spanning subsequently to the S1 before the migraine occurs. Further investigations with larger sample sizes are warranted.

Pilot study of focused ultrasound for drug-resistant epilepsy.

OBJECTIVE: The neuromodulatory effects of focused ultrasound (FUS) have been demonstrated in animal epilepsy models; however, the safety and efficacy of FUS in humans with epilepsy have not been well established. Patients with drug-resistant epilepsy (DRE) undergoing stereo-electroencephalography (SEEG) provide an opportunity to investigate the neuromodulatory effects of FUS in humans. METHODS: Patients with DRE undergoing SEEG for localization of the seizure onset zone (SOZ) were prospectively enrolled. FUS was delivered to the SOZ using a neuronavigation-guided FUS system (ceiling spatial-peak temporal-average intensity level = 2.8 W/cm2 , duty cycle = 30%, modulating duration = 10 min). Simultaneous SEEG recordings were obtained during sonication and for 3 days after treatment. Seizures, interictal epileptiform discharges, and adverse events after FUS were monitored. RESULTS: Six patients met the eligibility criteria and completed FUS treatment. A decrease in seizure frequency was observed in two patients within the 3-day follow-up; however, one patient presented an increase in the frequency of subclinical seizures. Posttreatment magnetic resonance imaging revealed neither lesion nor brain edema. Significant changes in spectral power of SEEG were noted at the targeted electrodes during FUS treatment. One patient reported subjective scalp heating during FUS, and one patient developed transient naming and memory impairment that resolved within 3 weeks after FUS. SIGNIFICANCE: FUS can be safely delivered to the SOZ of patients with DRE, resulting in significant changes in spectral power of SEEG. A larger sample cohort and pursuing optimal sonication parameters will be required to elucidate the neuromodulatory effects of FUS when used for seizure control.

Migraine chronification is associated with beta-band connectivity within the pain-related cortical regions: a magnetoencephalographic study.

ABSTRACT: Pain disorders are associated with aberrant oscillations in the pain-related cortical regions; however, few studies have investigated the relationship between the functional cortical network and migraine chronification through direct neural signals. Magnetoencephalography was used to record the resting-state brain activity of healthy controls as well as patients with episodic migraine (EM) and chronic migraine (CM). The source-based oscillatory dynamics of the pain-related cortical regions, which comprises 10 node regions (the bilateral primary [SI] and secondary somatosensory cortices, insula, medial frontal cortex, and anterior cingulate cortex [ACC]), were calculated to determine the intrinsic connectivity and node strength at 1 to 40 Hz. The total node strength within the pain-related cortical regions was smaller in the beta band in patients with migraine (70 EM and 80 CM) than in controls (n = 65). In the beta band, the node strength and functional connectivity values of patients with CM and patients with EM differed from those of controls in specific cortical areas, notably the left SI (EM < control) and bilateral ACC (CM < control); moreover, the node strength was lower in patients with CM than in those with EM. In all patients with migraine, negative correlations were observed between headache frequency and node strength in the bilateral ACC. In conclusion, migraine is characterized by reduced beta oscillatory connectivity within the pain-related cortical regions. Reduced beta connectivity in the ACC is linked to migraine chronification. Longitudinal studies should verify whether this oscillation change is a brain signature and a potential neuromodulation target for migraine.

Somatosensory Gating Responses Are Associated with Prognosis in Patients with Migraine.

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.

Salivary cortisol is associated with cognitive changes in patients with fibromyalgia.

Fibromyalgia (FM) is a stress-related chronic pain disorder with common cognitive complaints. This study characterized cognitive dysfunction in patients with FM and explored whether these changes are linked to altered cortisol levels. Consecutive 44 patients with FM and 48 healthy controls were enrolled for the assessments of subjective and objective cognitive functions and diurnal levels of salivary cortisol (sampled at awakening, 30 min after awakening, 3 pm, and bedtime). All measurements were compared between the groups and evaluated for clinical correlation. The FM group had more subjective cognitive complaints and performed poorer in objective cognitive testing in memory (delayed recall in Chinese Version Verbal Learning Test and Taylor Complex Figure Test), language (Boston Naming Test), and executive domains (Wisconsin Card Sorting Test) after adjustments for education. The diurnal cortisol levels of patients with FM tended to be lower, especially at 30 min after awakening and bedtime. Moreover, moderate positive correlations existed between the Chinese Version Verbal Learning Test, Boston Naming Test and the morning cortisol levels within the FM group. We suggested the altered cognitive function in FM may be linked to stress maladaptation. Future studies are warranted to elucidate whether stress management improves cognitive performance in patients with FM.

Brain Excitability in Tension-Type Headache: a Separate Entity from Migraine?

PURPOSE OF REVIEW: Tension-type headache is often regarded as the "normal" headache due to its high prevalence and mild disability in contrast with migraine. Clinically, both headaches are common comorbidities to each other. To date there has been many studies linked migraine to a brain excitability disorder. This review summarized earlier studies on brain excitability of TTH and discuss if TTH is a separate clinical entity from migraine as suggested by the diagnostic criteria. RECENT FINDINGS: A recent magnetoencephalographic study from our group enrolled patients with "strict-criteria" TTH (i.e., absence of any migraine characteristics and associated symptoms) to compare the somatosensory excitability with patients with migraine and controls. This study provided evidence that TTH and migraine differ in excitability profiles and the measurement of preactivation excitability was able to discriminate TTH from migraine. Earlier studies on brain excitability of TTH yielded negative findings or a common change shared with migraine. Future studies using strict diagnostic criteria to avoid the unwanted interference from migraine comorbidity may help decipher the "true" pathophysiology of TTH, which may pave the way to a TTH-specific brain signature and treatment.

Machine learning-based prediction of heat pain sensitivity by using resting-state EEG.

INTRODUCTION: The development of quantitative, objective signatures or predictors to evaluate pain sensitivity is crucial in the clinical management of pain and in precision medicine. This study combined multimodal (neurophysiology and psychometrics) signatures to classify the training dataset and predict the testing dataset on individual heat pain sensitivity. METHODS: Healthy individuals were recruited in this study. Individual heat pain sensitivity and psychometric scores, as well as the resting-state electroencephalography (EEG) data, were obtained from each participant. Participants were divided into low-sensitivity and high-sensitivity subgroups according to their heat pain sensitivity. Psychometric data obtained from psychometric measurements and power spectral density (PSD) and functional connectivity (FC) derived from resting-state EEG analysis were subjected to feature selection with an independent t test and were then trained and predicted using machine learning models, including support vector machine (SVM) and k-nearest neighbor. RESULTS: In total, 85 participants were recruited in this study, and their data were divided into training (n = 65) and testing (n = 20) datasets. We identified the resting-state PSD and FC, which can serve as brain signatures to classify heat pain as high-sensitive or low-sensitive. Using machine learning algorithms of SVM with different kernels, we obtained an accuracy of 86.2%-93.8% in classifying the participants into thermal pain high-sensitivity and low-sensitivity groups; moreover, using the trained model of cubic SVM, an accuracy of 80% was achieved in predicting the pain sensitivity of an independent dataset of combined PSD and FC features of resting-state EEG data. CONCLUSION: Acceptable accuracy in classification and prediction by using the SVM model indicated that pain sensitivity could be achieved, leading to considerable possibilities of the use of objective evaluation of pain perception in clinical practice. However, the predictive model presented in this study requires further validation by studies with a larger dataset.

Individual pain sensitivity is associated with resting-state cortical activities in healthy individuals but not in patients with migraine: a magnetoencephalography study.

BACKGROUND: 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. METHODS: We recorded the resting-state magnetoencephalographic (MEG) activities of 27 healthy individuals and 30 patients with episodic migraine (EM) and analyzed the source-based oscillatory powers and functional connectivity at 2 to 59 Hz in pain-related cortical regions, which are the bilateral anterior cingulate cortex (ACC), medial orbitofrontal (MOF) cortex, lateral orbitofrontal (LOF) cortex, insula cortex, primary somatosensory cortex (SI), primary motor cortex (MI), and posterior cingulate cortex (PCC). The mechanical punctate pain threshold (MPPT) was obtained at the supraorbital area (the first branch of the trigeminal nerve dermatome, V1) and the forearm (the first thoracic nerve dermatome, T1) and further correlated with MEG measures. RESULTS: The MPPT is inversely correlated with the resting-state relative powers of gamma oscillation in healthy individuals (all corrected P < 0.05). Specifically, inverse correlation was noted between the MPPT at V1 and gamma powers in the bilateral insula (r = - 0.592 [left] and - 0.529 [right]), PCC (r = - 0.619 and - 0.541) and MI (r = - 0.497 and - 0.549) and between the MPPT at T1 and powers in the left PCC (r = - 0.561) and bilateral MI (r = - 0.509 and - 0.520). Furthermore, resting-state functional connectivity at the delta to beta bands, especially between frontal (MOF, ACC, LOF, and MI), parietal (PCC), and sensorimotor (bilateral SI and MI) regions, showed a positive correlation with the MPPT at V1 and T1 (all corrected P < 0.05). By contrast, in patients with EM, the MPPT was not associated with resting-state cortical activities. CONCLUSIONS: Pain sensitivity in healthy individuals is associated with the resting-state gamma oscillation and functional connectivity in pain-related cortical regions. Further studies must be conducted in a large population to confirm whether resting-state cortical activities can be an objective measurement of pain sensitivity in individuals without clinical pain.

Neuromagnetic Amygdala Response to Pain-Related Fear as a Brain Signature of Fibromyalgia.

INTRODUCTION: Fibromyalgia (FM) is a chronic pain condition characterized by impaired emotional regulation. This study explored the brain response to pain-related fear as a potential brain signature of FM. METHODS: We used a conditioned fear task and magnetoencephalography to record pain-related fear responses in patients with FM. Two blocks of 30 fear responses were collected to compute the response strength in the first block and the strength difference between the first and second blocks (fear habituation). These measurements were investigated for their clinical relevance and compared with measurements obtained from healthy controls and patients with chronic migraine (CM), a different chronic pain condition often comorbid with FM. RESULTS: Pain-related fear clearly activated the bilateral amygdala and anterior insula in patients with FM (n = 52), patients with CM (n = 50), and the controls (n = 30); the response strength in the first block was consistent across groups. However, fear habituation in the right amygdala decreased in the FM group (vs. CM and control groups, both p ≤ 0.001, no difference between CM and control groups). At the 3-month follow-up, the patients with FM reporting < 30% improvement in pain severity (n = 15) after pregabalin treatment exhibited lower fear habituation in the left amygdala at baseline (vs. ≥ 30% improvement, n = 22, p = 0.019). Receiver operating characteristic analysis confirmed that amygdala fear habituation is a suitable predictor of diagnosis and treatment outcomes of FM (area under the curve > 0.7). CONCLUSIONS: Amygdala activation to pain-related fear is maladaptive and linked to treatment outcomes in patients with FM. Because the aberrant amygdala response was not observed in the CM group, this response is a potential brain signature of FM. TRIAL REGISTRATION: ClinicalTrials.gov Identifier, NCT02747940.

ß-Oscillations Reflect Recovery of the Paretic Upper Limb in Subacute Stroke.

Background. Recovery of upper limb function post-stroke can be partly predicted by initial motor function, but the mechanisms underpinning these improvements have yet to be determined. Here, we sought to identify neural correlates of post-stroke recovery using longitudinal magnetoencephalography (MEG) assessments in subacute stroke survivors. Methods. First-ever, subcortical ischemic stroke survivors with unilateral mild to moderate hand paresis were evaluated at 3, 5, and 12 weeks after stroke using a finger-lifting task in the MEG. Cortical activity patterns in the ß-band (16-30 Hz) were compared with matched healthy controls. Results. All stroke survivors (n=22; 17 males) had improvements in action research arm test (ARAT) and Fugl-Meyer upper extremity (FM-UE) scores between 3 and 12 weeks. At 3 weeks post-stroke the peak amplitudes of the movement-related ipsilesional ß-band event-related desynchronization (ß-ERD) and synchronization (ß-ERS) in primary motor cortex (M1) were significantly lower than the healthy controls (p<0.001) and were correlated with both the FM-UE and ARAT scores (r=0.51-0.69, p<0.017). The decreased ß-ERS peak amplitudes were observed both in paretic and non-paretic hand movement particularly at 3 weeks post-stroke, suggesting a generalized disinhibition status. The peak amplitudes of ipsilesional ß-ERS at week 3 post-stroke correlated with the FM-UE score at 12 weeks (r=0.54, p=0.03) but no longer significant when controlling for the FM-UE score at 3 weeks post-stroke.Conclusions. Although early ß-band activity does not independently predict outcome at 3 months after stroke, it mirrors functional changes, giving a potential insight into the mechanisms underpinning recovery of motor function in subacute stroke.

Cingulate gyrus epilepsy: semiology, invasive EEG, and surgical approaches.

OBJECTIVE: The semiology of cingulate gyrus epilepsy is varied and may involve the paracentral area, the adjacent limbic system, and/or the orbitofrontal gyrus. Invasive electroencephalography (iEEG) recording is usually required for patients with deeply located epileptogenic foci. This paper reports on the authors' experiences in the diagnosis and surgical treatment of patients with focal epilepsy originating in the cingulate gyrus. METHODS: Eighteen patients (median age 24 years, range 5-53 years) with a mean seizure history of 23 years (range 2-32 years) were analyzed retrospectively. The results of presurgical evaluation, surgical strategy, and postoperative pathology are reported, as well as follow-up concerning functional morbidity and seizures (median follow-up 7 years, range 2-12 years). RESULTS: Patients with cingulate gyrus epilepsy presented with a variety of semiologies and scalp EEG patterns. Prior to ictal onset, 11 (61%) of the patients presented with aura. Initial ictal symptoms included limb posturing in 12 (67%), vocalization in 5, and hypermotor movement in 4. In most patients (n = 16, 89%), ictal EEG presented as widespread patterns with bilateral hemispheric origin, as well as muscle artifacts obscuring the onset of EEG during the ictal period in 11 patients. Among the 18 patients who underwent resection, the pathology revealed mild malformation of cortical development in 2, focal cortical dysplasia (FCD) Ib in 4, FCD IIa in 4, FCD IIb in 4, astrocytoma in 1, ganglioglioma in 1, and gliosis in 2. The seizure outcome after surgery was satisfactory: Engel class IA in 12 patients, IIB in 3, IIIA in 1, IIIB in 1, and IVB in 1 at the 2-year follow-up. CONCLUSIONS: In this study, the authors exploited the improved access to the cingulate epileptogenic network made possible by the use of 3D electrodes implanted using stereoelectroencephalography methodology. Under iEEG recording and intraoperative neuromonitoring, epilepsy surgery on lesions in the cingulate gyrus can result in good outcomes in terms of seizure recurrence and the incidence of postoperative permanent deficits.