Dynamic pain connectome functional connectivity and oscillations reflect multiple sclerosis pain

Abnormal dynamic functional networks during pain-free periods: Resting-state co-activation pattern analysis in primary dysmenorrhea: Abnormal dynamic functional networks in primary dysmenorrhea

Chronic pain alters the configuration of brain functional networks. Primary dysmenorrhea (PDM) is a form of chronic visceral pain, which has been identified spatial alterations in brain functional networks using static functional connectivity analysis methods. However, the dynamics alterations of brain functional networks during pain-free periovulation phase remain unclear. Using the co-activation pattern (CAP) method, we investigated the dynamic network characteristics of brain functional networks and their relationship with pain-related emotions in a sample of 59 women with PDM and 57 demographically matched healthy controls (HCs) during the pain-free periovulation phase. We observed that patients with PDM showed significant alterations in brain dynamics compared to HCs in the slow-4 (0.027-0.073 Hz) frequency band during the pain-free periovulation phase. Additionally, the fraction of time for CAP state 2 was positively correlated with the Pain Catastrophizing Scale-helplessness score, while the persistence time for CAP state 1 was positively correlated with the McGill Pain Questionnaire score. Our results provide new insights, suggesting that the atypical brain functional network dynamics may serve as a potential biological marker of patients with PDM during the pain-free periovulation phase.

Sex-Specific White Matter Abnormalities Across the Dynamic Pain Connectome in Neuropathic Pain: A Fixel-Based Analysis Study

A fundamental issue in neuroscience is a lack of understanding regarding the relationship between brain function and the white matter architecture that supports it. Individuals with chronic neuropathic pain (NP) exhibit functional abnormalities throughout brain networks collectively termed the "dynamic pain connectome" (DPC), including the default mode network (DMN), salience network, and ascending nociceptive and descending pain modulation systems. These functional abnormalities are often observed in a sex-dependent fashion. However, the enigmatic white matter structural features underpinning these functional networks and the relationship between structure and function/dysfunction in NP remain poorly understood. Here we used fixel-based analysis of diffusion weighted imaging data in 80 individuals (40 with NP [21 female, 19 male] and 40 sex- and age-matched healthy controls [HCs]) to evaluate white matter microstructure (fiber density [FD]), macrostructure (fiber bundle cross section) and combined microstructure and macrostructure (fiber density and cross section) within anatomical connections that support the DPC. We additionally examined whether there are sex-specific abnormalities in NP white matter structure. We performed fixel-wise and connection-specific mean analyses and found three main ways in which individuals with NP differed from HCs: (1) people with NP exhibited abnormally low FD and FDC within the corona radiata consistent with the ascending nociceptive pathway between the sensory thalamus and primary somatosensory cortex (S1). Furthermore, the entire sensory thalamus-S1 pathway exhibited abnormally low FD and FDC in people with NP, and this effect was driven by the females with NP; (2) females, but not males, with NP had abnormally low FD within the cingulum consistent with the right medial prefrontal cortex-posterior cingulate cortex DMN pathway; and (3) individuals with NP had higher connection-specific mean FDC than HCs in the anterior insula-temporoparietal junction and sensory thalamus-posterior insula pathways. However, sex-specific analyses did not corroborate these connection-specific findings in either females or males with NP. Our findings suggest that females with NP exhibit microstructural and macrostructural white matter abnormalities within the DPC networks including the ascending nociceptive system and DMN. We propose that aberrant white matter structure contributes to or is driven by functional abnormalities associated with NP. Our sex-specific findings highlight the utility and importance of using sex-disaggregated analyses to identify white matter abnormalities in clinical conditions such as chronic pain.

Abnormal thalamocortical network dynamics in patients with migraine and its relationship with electroacupuncture treatment response

Acupuncture is an effective and safe alternative treatment to prevent and treat migraine, but its central analgesic mechanism remains poorly understood. It is believed that the dysfunction of the thalamocortical connectivity network is an important contributor to migraine pathophysiology. This study aimed to investigate the abnormal thalamocortical network dynamics in patients with migraine without aura (MWoA) before and after an 8-week electroacupuncture treatment. A total of 143 patients with MWoA and 100 healthy controls (HC) were included, and resting-state functional magnetic resonance imaging (fMRI) data were acquired. Dynamic functional network connectivity (dFNC) was calculated for each subject. The modulation effect of electroacupuncture on clinical outcomes of migraine, dFNC, and their association were investigated. In our results, dFNC matrices were classified into two clusters (brain states). As compared with the HC, patients with MWoA had a higher proportion of brain states with a strong thalamocortical between-network connection, implying an abnormal balance of the network organization across dFNC brain states. Correlation analysis showed that this abnormality was associated with summarized clinical measurements of migraine. A total of 60 patients were willing to receive an 8-week electroacupuncture treatment, and 24 responders had 50% changes in headache frequency. In electroacupuncture responders, electroacupuncture could change the abnormal thalamocortical connectivities towards a pattern more similar to that of HC. Our findings suggested that electroacupuncture could relieve the symptoms of migraine and has the potential capacity to regulate the abnormal function of the thalamocortical circuits.

Graph Metrics Reveal Brain Network Topological Property in Neuropathic Pain Patients: A Systematic Review

Neuropathic pain (NP) is a common and persistent disease that leads to immense suffering and serious social burden. Incomplete understanding of the underlying neural basis makes it difficult to achieve significant breakthroughs in the treatment of NP. We aimed to review the functional and structural brain topological properties in patients with NP and consider how graph measures reveal potential mechanisms and are applied to clinical practice. Related studies were searched in PubMed and Web of Science databases. Topological property changes in patients with NP, including small-worldness, functional separation, integration, and centrality metrics, were reviewed. The findings suggest that NP was characterized by retained but declined small-worldness, indicating an insidious imbalance between network integration and segregation. The global-level measures revealed decreased global and local efficiency in the NP, implying decreased information transfer efficiency for both long- and short-range connections. Altered nodal centrality measures involve various brain regions, mostly those associated with pain, cognition, and emotion. Graph theory is a powerful tool for identifying topological properties of patients with NP. These specific brain changes in patients with NP are very helpful in revealing the potential mechanisms of NP, developing new treatment strategies, and evaluating the efficacy and prognosis of NP.

Brain Network Dynamics in Women With Primary Dysmenorrhea During the Pain-Free Periovulation Phase

The human brain is a dynamic system that shows frequency-specific features. Neuroimaging studies have shown that both healthy individuals and those with chronic pain disorders experience pain influenced by various processes that fluctuate over time. Primary dysmenorrhea (PDM) is a chronic visceral pain that disrupts the coordinated activity of brain's functional network. However, it remains unclear whether the dynamic interactions across the whole-brain network over time and their associations with neurobehavioral symptoms are dependent on the frequency bands in patients with PDM during the pain-free periovulation phase. In this study, we used an energy landscape analysis to examine the interactions over time across the large-scale network in a sample of 59 patients with PDM and 57 healthy controls (HCs) at different frequency bands. Compared with HCs, patients with PDM exhibit aberrant brain dynamics, with more significant differences in the slow-4 frequency band. Patients with PDM show more indirect neural transition counts due to an unstable intermediate state, whereas neurotypical brain activity frequently transitions between 2 major states. This data-driven approach further revealed that the brains of individuals with PDM have more abnormal brain dynamics than HCs. Our results suggested that unstable brain dynamics were associated with the strength of brain functional segregation and the Pain Catastrophizing Scale score. Our findings provide preliminary evidence that atypical dynamics in the functional network may serve as a potential key feature and biological marker of patients with PDM during the pain-free phase. PERSPECTIVE: We applied energy landscape analysis on brain-imaging data to identify relatively stable and dominant brain activity patterns for patients with PDM. More atypical brain dynamics were found in the slow-4 band and were related to the strength of functional segregation, providing new insights into the dysfunction brain dynamics.

A distinct neuronal ensemble of prelimbic cortex mediates spontaneous pain in rats with peripheral inflammation

The absence of a comprehensive understanding of the neural basis of spontaneous pain limits the development of therapeutic strategies targeting this primary complaint of patients with chronic pain. Here we report a distinct neuronal ensemble within the prelimbic cortex which processes signals related to spontaneous pain in rats with chronic inflammatory pain. This neuronal ensemble specifically encodes spontaneous pain-related behaviors, independently of other locomotive and evoked behaviors. Activation of this neuronal ensemble elicits marked spontaneous pain-like behaviors and enhances nociceptive responses, whereas prolonged silencing of its activities alleviates spontaneous pain and promotes overall recovery from inflammatory pain. Notably, afferents from the primary somatosensory cortex and infralimbic cortex bidirectionally modulate the activities of the spontaneous pain-responsive prelimbic cortex neuronal ensemble and pain behaviors. These findings reveal the cortical basis of spontaneous pain at the neuronal level, highlighting a distinct neuronal ensemble within the prelimbic cortex and its associated pain-regulatory brain networks.

Time-varying phase synchronization of resting-state functional magnetic resonance imaging reveals a shift toward self-referential processes during sustained pain

ABSTRACT

Growing evidence has suggested that time-varying functional connectivity between different brain regions might underlie the dynamic experience of pain. This study used a novel, data-driven framework to characterize the dynamic interactions of large-scale brain networks during sustained pain by estimating recurrent patterns of phase-synchronization. Resting-state functional magnetic resonance imaging signals were collected from 50 healthy participants before (once) and after (twice) the onset of sustained pain that was induced by topical application of capsaicin cream. We first decoded the instantaneous phase of neural activity and then applied leading eigenvector dynamic analysis on the time-varying phase-synchronization. We identified 3 recurrent brain states that show distinctive phase-synchronization. The presence of state 1, characterized by phase-synchronization between the default mode network and auditory, visual, and sensorimotor networks, together with transitions towards this brain state, increased during sustained pain. These changes can account for the perceived pain intensity and reported unpleasantness induced by capsaicin application. In contrast, state 3, characterized by phase-synchronization between the cognitive control network and sensory networks, decreased after the onset of sustained pain. These results are indicative of a shift toward internally directed self-referential processes (state 1) and away from externally directed cognitive control processes (state 3) during sustained pain.

High-definition tDCS over primary motor cortex modulates brain signal variability and functional connectivity in episodic migraine

OBJECTIVE

This study investigated how high-definition transcranial direct current stimulation (HD-tDCS) over the primary motor cortex (M1) affects brain signal variability and functional connectivity in the trigeminal pain pathway, and their association with changes in migraine attacks.

METHODS

Twenty-five episodic migraine patients were randomized for ten daily sessions of active or sham M1 HD-tDCS. Resting-state blood-oxygenation-level-dependent (BOLD) signal variability and seed-based functional connectivity were assessed pre- and post-treatment. A mediation analysis was performed to test whether BOLD signal variability mediates the relationship between treatment group and moderate-to-severe headache days.

RESULTS

The active M1 HD-tDCS group showed reduced BOLD variability in the spinal trigeminal nucleus (SpV) and thalamus, but increased variability in the rostral anterior cingulate cortex (rACC) compared to the sham group. Connectivity decreased between medial pulvinar-temporal pole, medial dorsal-precuneus, and the ventral posterior medial nucleus-SpV, but increased between the rACC-amygdala, and the periaqueductal gray-parahippocampal gyrus. Changes in medial pulvinar variability mediated the reduction in moderate-to-severe headache days at one-month post-treatment.

CONCLUSIONS

M1 HD-tDCS alters BOLD signal variability and connectivity in the trigeminal somatosensory and modulatory pain system, potentially alleviating migraine headache attacks.

SIGNIFICANCE

M1 HD-tDCS realigns brain signal variability and connectivity in migraineurs closer to healthy control levels.

The enhanced connectivity between the frontoparietal, somatomotor network and thalamus as the most significant network changes of chronic low back pain

The prolonged duration of chronic low back pain (cLBP) inevitably leads to changes in the cognitive, attentional, sensory and emotional processing brain regions. Currently, it remains unclear how these alterations are manifested in the interplay between brain functional and structural networks. This study aimed to predict the Oswestry Disability Index (ODI) in cLBP patients using multimodal brain magnetic resonance imaging (MRI) data and identified the most significant features within the multimodal networks to aid in distinguishing patients from healthy controls (HCs). We constructed dynamic functional connectivity (dFC) and structural connectivity (SC) networks for all participants (n = 112) and employed the Connectome-based Predictive Modeling (CPM) approach to predict ODI scores, utilizing various feature selection thresholds to identify the most significant network change features in dFC and SC outcomes. Subsequently, we utilized these significant features for optimal classifier selection and the integration of multimodal features. The results revealed enhanced connectivity among the frontoparietal network (FPN), somatomotor network (SMN) and thalamus in cLBP patients compared to HCs. The thalamus transmits pain-related sensations and emotions to the cortical areas through the dorsolateral prefrontal cortex (dlPFC) and primary somatosensory cortex (SI), leading to alterations in whole-brain network functionality and structure. Regarding the model selection for the classifier, we found that Support Vector Machine (SVM) best fit these significant network features. The combined model based on dFC and SC features significantly improved classification performance between cLBP patients and HCs (AUC=0.9772). Finally, the results from an external validation set support our hypotheses and provide insights into the potential applicability of the model in real-world scenarios. Our discovery of enhanced connectivity between the thalamus and both the dlPFC (FPN) and SI (SMN) provides a valuable supplement to prior research on cLBP.

Focused Ultrasound Central Lateral Thalamotomy for the Treatment of Refractory Neuropathic Pain: Phase I Trial

BACKGROUND AND OBJECTIVES

Magnetic resonance-guided focused ultrasound (MRgFUS) central lateral thalamotomy (CLT) has not yet been validated for treating refractory neuropathic pain (NP). Our aim was to assess the safety and potential efficacy of MRgFUS CLT for refractory NP.

METHODS

In this prospective, nonrandomized, single-arm, investigator-initiated phase I trial, patients with NP for more than 6 months related to phantom limb pain, spinal cord injury, or radiculopathy/radicular injury and who had undergone at least one previous failed intervention were eligible. The main outcomes were safety profile and pain as assessed using the brief pain inventory, the pain disability index, and the numeric rating scale. Medication use and the functional connectivity of the default mode network (DMN) were also assessed.

RESULTS

Ten patients were enrolled, with nine achieving successful ablation. There were no serious adverse events and 12 mild/moderate severity events. The mean age was 50.9 years (SD: 12.7), and the mean symptom duration was 12.3 years (SD: 9.7). Among eight patients with a 1-year follow-up, the brief pain inventory decreased from 7.6 (SD: 1.1) to 3.8 (SD: 2.8), with a mean percent decrease of 46.3 (SD: 40.6) (paired t -test, P = .017). The mean pain disability index decreased from 43.0 (SD: 7.5) to 25.8 (SD: 16.8), with a mean percent decrease of 39.3 (SD: 41.6) ( P = .034). Numeric rating scale scores decreased from a mean of 7.2 (SD: 1.8) to 4.0 (SD: 2.8), with a mean percent decrease of 42.8 (SD: 37.8) ( P = .024). Patients with predominantly intermittent pain or with allodynia responded better than patients with continuous pain or without allodynia, respectively. Some patients decreased medication use. Resting-state functional connectivity changes were noted, from disruption of the DMN at baseline to reactivation of connectivity between DMN nodes at 3 months.

CONCLUSION

MRgFUS CLT is feasible and safe for refractory NP and has potential utility in reducing symptoms as measured by validated pain scales.

Altered trends of local brain function in classical trigeminal neuralgia patients after a single trigger pain

OBJECTIVE

To investigate the altered trends of regional homogeneity (ReHo) based on time and frequency, and clarify the time-frequency characteristics of ReHo in 48 classical trigeminal neuralgia (CTN) patients after a single pain stimulate.

METHODS

All patients underwent three times resting-state functional MRI (before stimulation (baseline), after stimulation within 5 s (triggering-5 s), and in the 30th min of stimulation (triggering-30 min)). The spontaneous brain activity was investigated by static ReHo (sReHo) in five different frequency bands and dynamic ReHo (dReHo) methods.

RESULTS

In the five frequency bands, the number of brain regions which the sReHo value changed in classical frequency band were most, followed by slow 4 frequency band. The left superior occipital gyrus was only found in slow 2 frequency band and the left superior parietal gyrus was only found in slow 3 frequency band. The dReHo values were changed in midbrain, left thalamus, right putamen, and anterior cingulate cortex, which were all different from the brain regions that the sReHo value altered. There were four altered trends of the sReHo and dReHo, which dominated by decreased at triggering-5 s and increased at triggering-30 min.

CONCLUSIONS

The duration of brain function changed was more than 30 min after a single pain stimulate, although the pain of CTN was transient. The localized functional homogeneity has time-frequency characteristic in CTN patients after a single pain stimulate, and the changed brain regions of the sReHo in five frequency bands and dReHo complemented to each other. Which provided a certain theoretical basis for exploring the pathophysiology of CTN.

Brain stimulation targets for chronic pain: Insights from meta-analysis, functional connectivity and literature review

Noninvasive brain stimulation (NIBS) techniques have demonstrated their potential for chronic pain management, yet their efficacy exhibits variability across studies. Refining stimulation targets and exploring additional targets offer a possible solution to this challenge. This study aimed to identify potential brain surface targets for NIBS in treating chronic pain disorders by integrating literature review, neuroimaging meta-analysis, and functional connectivity analysis on 90 chronic low back pain patients. Our results showed that the primary motor cortex (M1) (C3/C4, 10-20 EEG system) and prefrontal cortex (F3/F4/Fz) were the most used brain stimulation targets for chronic pain treatment according to the literature review. The bilateral precentral gyrus (M1), supplementary motor area, Rolandic operculum, and temporoparietal junction, were all identified as common potential NIBS targets through both a meta-analysis sourced from Neurosynth and functional connectivity analysis. This study presents a comprehensive summary of the current literature and refines the existing NIBS targets through a combination of imaging meta-analysis and functional connectivity analysis for chronic pain conditions. The derived coordinates (with integration of the international electroencephalography (EEG) 10/20 electrode placement system) within the above brain regions may further facilitate the localization of these targets for NIBS application. Our findings may have the potential to expand NIBS target selection beyond current clinical trials and improve chronic pain treatment.

Interim guidelines for the assessment and treatment of pain in children with multiple sclerosis

Introduction

Pain in multiple sclerosis (MS) is common, but literature on pain in children with MS remains scarce. Pain has physical, psychological, and social implications in MS, and both comprehensive assessment and interdisciplinary management approaches are needed. We sought to develop an interdisciplinary interim guideline for the assessment and management of pain in children with MS.

Methods and materials

We convened a modified Delphi panel composed of 13 experts in pediatric and adult MS neurology, physiotherapy, pain, patient lived-experience, advanced practice nursing, psychology, physiatry, and MS research. A survey was sent to panelists for anonymous completion. The panel discussed survey themes extracted by the panel chair. The process was repeated twice.

Results

Thirteen assessment and treatment recommendations were produced regarding pain in children with MS.

Discussion

Future studies will assess implementation of these pain assessment and treatment guidelines in the clinical setting.

Functional Magnetic Resonance Imaging Signal Variability Is Associated With Neuromodulation in Fibromyalgia

OBJECTIVES

Although primary motor cortex (M1) transcranial direct current stimulation (tDCS) has an analgesic effect in fibromyalgia (FM), its neural mechanism remains elusive. We investigated whether M1-tDCS modulates a regional temporal variability of blood-oxygenation-level-dependent (BOLD) signals, an indicator of the brain's flexibility and efficiency and if this change is associated with pain improvement.

MATERIALS AND METHODS

In a within-subjects cross-over design, 12 female FM patients underwent sham and active tDCS on five consecutive days, respectively. Each session was performed with an anode placed on the left M1 and a cathode on the contralateral supraorbital region. The subjects also participated in resting-state functional magnetic resonance imaging (fMRI) at baseline and after sham and active tDCS. We compared the BOLD signal variability (SDBOLD), defined as the standard deviation of the BOLD time-series, between the tDCS conditions. Baseline SDBOLD was compared to 15 healthy female controls.

RESULTS

At baseline, FM patients showed reduced SDBOLD in the ventromedial prefrontal cortex (vmPFC), lateral PFC, and anterior insula and increased SDBOLD in the posterior insula compared to healthy controls. After active tDCS, compared to sham, we found an increased SDBOLD in the left rostral anterior cingulate cortex (rACC), lateral PFC, and thalamus. After sham tDCS, compared to baseline, we found a decreased SDBOLD in the dorsomedial PFC and posterior cingulate cortex/precuneus. Interestingly, after active tDCS compared to sham, pain reduction was correlated with an increased SDBOLD in the rACC/vmPFC but with a decreased SDBOLD in the posterior insula.

CONCLUSION

Our findings suggest that M1-tDCS might revert temporal variability of fMRI signals in the rACC/vmPFC and posterior insula linked to FM pain. Changes in neural variability would be part of the mechanisms underlying repetitive M1-tDCS analgesia in FM.

Altered functional brain network patterns in patients with migraine without aura after transcutaneous auricular vagus nerve stimulation

Transcutaneous auricular vagus nerve stimulation (taVNS) shows excellent effects on relieving clinical symptoms in migraine patients. Nevertheless, the neurological mechanisms of taVNS for migraineurs remain unclear. In recent years, voxel-wise degree centrality (DC) and functional connectivity (FC) methods were extensively utilized for exploring alterations in patterns of FC in the resting-state brain. In the present study, thirty-five migraine patients without aura and thirty-eight healthy controls (HCs) were recruited for magnetic resonance imaging scans. Firstly, this study used voxel-wise DC analysis to explore brain regions where abnormalities were present in migraine patients. Secondly, for elucidating neurological mechanisms underlying taVNS in migraine, seed-based resting-state functional connectivity analysis was employed to the taVNS treatment group. Finally, correlation analysis was performed to explore the relationship between alterations in neurological mechanisms and clinical symptoms. Our findings indicated that migraineurs have lower DC values in the inferior temporal gyrus (ITG) and paracentral lobule than in healthy controls (HCs). In addition, migraineurs have higher DC values in the cerebellar lobule VIII and the fusiform gyrus than HCs. Moreover, after taVNS treatment (post-taVNS), patients displayed increased FC between the ITG with the inferior parietal lobule (IPL), orbitofrontal gyrus, angular gyrus, and posterior cingulate gyrus than before taVNS treatment (pre-taVNS). Besides, the post-taVNS patients showed decreased FC between the cerebellar lobule VIII with the supplementary motor area and postcentral gyrus compared with the pre-taVNS patients. The changed FC of ITG-IPL was significantly related to changes in headache intensity. Our study suggested that migraine patients without aura have altered brain connectivity patterns in several hub regions involving multisensory integration, pain perception, and cognitive function. More importantly, taVNS modulated the default mode network and the vestibular cortical network related to the dysfunctions in migraineurs. This paper provides a new perspective on the potential neurological mechanisms and therapeutic targets of taVNS for treating migraine.

Decreased gray matter volume and dynamic functional alterations in medicine-free obsessive-compulsive disorder

BACKGROUND

Previous studies discovered the presence of abnormal structures and functions in the brain regions of patients with obsessive-compulsive disorder (OCD). Nevertheless, whether structural changes in brain regions are coupled with alterations in dynamic functional connectivity (dFC) at rest in medicine-free patients with OCD remains vague.

METHODS

Three-dimensional T₁-weighed magnetic resonance imaging (MRI) and resting-state functional MRI were performed on 50 medicine-free OCD and 50 healthy controls (HCs). Firstly, the differences in gray matter volume (GMV) between OCD and HCs were compared. Then, brain regions with aberrant GMV were used as seeds for dFC analysis. The relationship of altered GMV and dFC with clinical parameters in OCD was explored using partial correlation analysis. Finally, support vector machine was applied to examine whether altered multimodal imaging data might be adopted to distinguish OCD from HCs.

RESULTS

Our findings indicated that GMV in the left superior temporal gyrus (STG) and right supplementary motor area (SMA) was reduced in OCD, and the dFC between the left STG and the left cerebellum Crus I and left thalamus, and between the right SMA and right dorsolateral prefrontal cortex (DLPFC) and left precuneus was decreased at rest in OCD. The brain regions both with altered GMV and dFC values could discriminate OCD from HCs with the accuracy of 0.85, sensitivity of 0.90 and specificity of 0.80.

CONCLUSION

The decreased gray matter structure coupling with dynamic function in the left STG and right SMA at rest may be crucial in the pathophysiology of OCD.

TRIAL REGISTRATION

Study on the mechanism of brain network in obsessive-compulsive disorder with multi-model magnetic resonance imaging (registration date: 08/11/2017; registration number: ChiCTR-COC-17,013,301).

Microstates in multiple sclerosis: an electrophysiological signature of altered large-scale networks functioning?

Multiple sclerosis has a highly variable course and disabling symptoms even in absence of associated imaging data. This clinical-radiological paradox has motivated functional studies with particular attention to the resting-state networks by functional MRI. The EEG microstates analysis might offer advantages to study the spontaneous fluctuations of brain activity. This analysis investigates configurations of voltage maps that remain stable for 80-120 ms, termed microstates. The aim of our study was to investigate the temporal dynamic of microstates in patients with multiple sclerosis, without reported cognitive difficulties, and their possible correlations with clinical and neuropsychological parameters. We enrolled fifty relapsing-remitting multiple sclerosis patients and 24 healthy subjects, matched for age and sex. Demographic and clinical data were collected. All participants underwent to high-density EEG in resting-state and analyzed 15 min free artefact segments. Microstates analysis consisted in two processes: segmentation, to identify specific templates, and back-fitting, to quantify their temporal dynamic. A neuropsychological assessment was performed by the Brief International Cognitive Assessment for Multiple Sclerosis. Repeated measures two-way ANOVA was run to compare microstates parameters of patients versus controls. To evaluate association between clinical, neuropsychological and microstates data, we performed Pearsons' correlation and stepwise multiple linear regression to estimate possible predictions. The alpha value was set to 0.05. We found six templates computed across all subjects. Significant differences were found in most of the parameters (global explained variance, time coverage, occurrence) for the microstate Class A (P < 0.001), B (P < 0.001), D (P < 0.001), E (P < 0.001) and F (P < 0.001). In particular, an increase of temporal dynamic of Class A, B and E and a decrease of Class D and F were observed. A significant positive association of disease duration with the mean duration of Class A was found. Eight percent of patients with multiple sclerosis were found cognitive impaired, and the multiple linear regression analysis showed a strong prediction of Symbol Digit Modalities Test score by global explained variance of Class A. The EEG microstate analysis in patients with multiple sclerosis, without overt cognitive impairment, showed an increased temporal dynamic of the sensory-related microstates (Class A and B), a reduced presence of the cognitive-related microstates (Class D and F), and a higher activation of a microstate (Class E) associated to the default mode network. These findings might represent an electrophysiological signature of brain reorganization in multiple sclerosis. Moreover, the association between Symbol Digit Modalities Test and Class A may suggest a possible marker of overt cognitive dysfunctions.

Functional brain reconfiguration during sustained pain

Pain is constructed through complex interactions among multiple brain systems, but it remains unclear how functional brain networks are reconfigured over time while experiencing pain. Here, we investigated the time-varying changes in the functional brain networks during 20 min capsaicin-induced sustained orofacial pain. In the early stage, the orofacial areas of the primary somatomotor cortex were separated from other areas of the somatosensory cortex and integrated with subcortical and frontoparietal regions, constituting an extended brain network of sustained pain. As pain decreased over time, the subcortical and frontoparietal regions were separated from this brain network and connected to multiple cerebellar regions. Machine-learning models based on these network features showed significant predictions of changes in pain experience across two independent datasets (n = 48 and 74). This study provides new insights into how multiple brain systems dynamically interact to construct and modulate pain experience, advancing our mechanistic understanding of sustained pain.

A Hidden Markov Model reveals magnetoencephalography spectral frequency-specific abnormalities of brain state power and phase-coupling in neuropathic pain

Neuronal populations in the brain are engaged in a temporally coordinated manner at rest. Here we show that spontaneous transitions between large-scale resting-state networks are altered in chronic neuropathic pain. We applied an approach based on the Hidden Markov Model to magnetoencephalography data to describe how the brain moves from one activity state to another. This identified 12 fast transient (~80 ms) brain states including the sensorimotor, ascending nociceptive pathway, salience, visual, and default mode networks. Compared to healthy controls, we found that people with neuropathic pain exhibited abnormal alpha power in the right ascending nociceptive pathway state, but higher power and coherence in the sensorimotor network state in the beta band, and shorter time intervals between visits of the sensorimotor network, indicating more active time in this state. Conversely, the neuropathic pain group showed lower coherence and spent less time in the frontal attentional state. Therefore, this study reveals a temporal imbalance and dysregulation of spectral frequency-specific brain microstates in patients with neuropathic pain. These findings can potentially impact the development of a mechanism-based therapeutic approach by identifying brain targets to stimulate using neuromodulation to modify abnormal activity and to restore effective neuronal synchrony between brain states.

The network collapse in multiple sclerosis: An overview of novel concepts to address disease dynamics

Multiple sclerosis is a neuroinflammatory and neurodegenerative disorder of the central nervous system that can be considered a network disorder. In MS, lesional pathology continuously disconnects structural pathways in the brain, forming a disconnection syndrome. Complex functional network changes then occur that are poorly understood but closely follow clinical status. Studying these structural and functional network changes has been and remains crucial to further decipher complex symptoms like cognitive impairment and physical disability. Recent insights especially implicate the importance of monitoring network hubs in MS, like the thalamus and default-mode network which seem especially hit hard. Such network insights in MS have led to the hypothesis that as the network continues to become disconnected and dysfunctional, exceeding a certain threshold of network efficiency loss leads to a "network collapse". After this collapse, crucial network hubs become rigid and overloaded, and at the same time a faster neurodegeneration and accelerated clinical (and cognitive) progression can be seen. As network neuroscience has evolved, the MS field can now move towards a clearer classification of the network collapse itself and specific milestone events leading up to it. Such an updated network-focused conceptual framework of MS could directly impact clinical decision making as well as the design of network-tailored rehabilitation strategies. This review therefore provides an overview of recent network concepts that have enhanced our understanding of clinical progression in MS, especially focusing on cognition, as well as new concepts that will likely move the field forward in the near future.

Exploring sex differences in alpha brain activity as a potential neuromarker associated with neuropathic pain

ABSTRACT

Alpha oscillatory activity (8-13 Hz) is the dominant rhythm in the awake brain and is known to play an important role in pain states. Previous studies have identified alpha band slowing and increased power in the dynamic pain connectome (DPC) of people with chronic neuropathic pain. However, a link between alpha-band abnormalities and sex differences in brain organization in healthy individuals and those with chronic pain is not known. Here, we used resting-state magnetoencephalography to test the hypothesis that peak alpha frequency (PAF) abnormalities are general features across chronic central and peripheral conditions causing neuropathic pain but exhibit sex-specific differences in networks of the DPC (ascending nociceptive pathway [ANP], default mode network, salience network [SN], and subgenual anterior cingulate cortex). We found that neuropathic pain (N = 25 men and 25 women) was associated with increased PAF power in the DPC compared with 50 age- and sex-matched healthy controls, whereas slower PAF in nodes of the SN (temporoparietal junction) and the ANP (posterior insula) was associated with higher trait pain intensity. In the neuropathic pain group, women exhibited lower PAF power in the subgenual anterior cingulate cortex and faster PAF in the ANP and SN than men. The within-sex analyses indicated that women had neuropathic pain-related increased PAF power in the ANP, SN, and default mode network, whereas men with neuropathic pain had increased PAF power restricted to the ANP. These findings highlight neuropathic pain-related and sex-specific abnormalities in alpha oscillations across the DPC that could underlie aberrant neuronal communication in nociceptive processing and modulation.

Disconnection from prediction: A systematic review on the role of right temporoparietal junction in aberrant predictive processing

The right temporoparietal junction (rTPJ) is a brain area that plays a critical role in a variety of cognitive functions. Although different theoretical proposals tried to explain the ubiquitous role of rTPJ, recent evidence suggests that rTPJ may be a fundamental cortical region involved in different kinds of predictions. This systematic review aims to better investigate the potential role of rTPJ under a predictive processing perspective, providing an overview of cognitive impairments in neurological patients as the consequence of structural or functional disconnections or damage of rTPJ. Results confirm the involvement of rTPJ across several tasks and neurological pathologies. RTPJ, via its connections with other brain networks, would integrate diverse information and update internal models of the world. Against traditional views, which tend to focus on distinct domains, we argue that the role of rTPJ can be parsimoniously interpreted as a key hub involved in domain-general predictions. This alternative account of rTPJ role in aberrant predictive processing opens different perspectives, stimulating new hypotheses in basic research and clinical contexts.

Lysophosphatidic acid receptor type-1 mediates brain activation in micro-Positron Emission Tomography analysis in a fibromyalgia-like mouse model

The intermittent cold stress-induced generalized pain response mimics the pathophysiological and pharmacotherapeutic features reported for fibromyalgia patients, including the presence of chronic generalized pain and female dominance. In addition, the intermittent cold stress-induced generalized pain is abolished in lysophosphatidic acid receptor type-1 knockout mice, as reported in many cases of neuropathic pain models. This study aimed to identify the brain loci involved in the intermittent cold stress generalized pain response and test their dependence on the lysophosphatidic acid receptor type-1. Positron emission tomography analyses using 2-deoxy-2-[¹⁸ F]fluoro-D-glucose in the presence of a pain stimulus showed that intermittent cold stress causes a significant increase in uptake in the ipsilateral regions, including the salience networking-related anterior cingulate cortex and insular cortex and the cognition-related hippocampus. A significant decrease was observed in the default mode network-related posterior cingulate cortex. Almost these intermittent cold stress-induced changes were abolished in lysophosphatidic acid receptor type-1 knockout mice. There results suggest that the intermittent cold stress-induced generalized pain response is mediated by the lysophosphatidic acid receptor type-1 in specific brain loci related to salience networking and cognition, which may lead to further developments in the treatment of fibromyalgia.

Task- and resting-state fMRI studies in multiple sclerosis: From regions to systems and time-varying analysis. Current status and future perspective

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Functional MRI is able to detect adaptive and maladaptive abnormalities at different MS stages.

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Increased fMRI activity is a feature of early MS, while progressive exhaustion of adaptive mechanisms is detected later on in the disease.

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Collapse of long-range connections and impaired hub integration characterize MS network reorganization.

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Time-varying connectivity analysis provides useful and complementary pieces of information to static functional connectivity.

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New perspectives might be the use of multimodal MRI and artificial intelligence.

Multiple sclerosis (MS) is a neurological disorder affecting the central nervous system and features extensive functional brain changes that are poorly understood but relate strongly to clinical impairments. Functional magnetic resonance imaging (fMRI) is a non-invasive, powerful technique able to map activity of brain regions and to assess how such regions interact for an efficient brain network. FMRI has been widely applied to study functional brain changes in MS, allowing to investigate functional plasticity consequent to disease-related structural injury. The first studies in MS using active fMRI tasks mainly aimed to study such plastic changes by identifying abnormal activity in salient brain regions (or systems) involved by the task. In later studies the focus shifted towards resting state (RS) functional connectivity (FC) studies, which aimed to map large-scale functional networks of the brain and to establish how MS pathology impairs functional integration, eventually leading to the hypothesized network collapse as patients clinically progress. This review provides a summary of the main findings from studies using task-based and RS fMRI and illustrates how functional brain alterations relate to clinical disability and cognitive deficits in this condition. We also give an overview of longitudinal studies that used task-based and RS fMRI to monitor disease evolution and effects of motor and cognitive rehabilitation. In addition, we discuss the results of studies using newer technologies involving time-varying FC to investigate abnormal dynamism and flexibility of network configurations in MS. Finally, we show some preliminary results from two recent topics (i.e., multimodal MRI analysis and artificial intelligence) that are receiving increasing attention. Together, these functional studies could provide new (conceptual) insights into disease stage-specific mechanisms underlying progression in MS, with recommendations for future research.

Aberrant functional connectivity and temporal variability of the dynamic pain connectome in patients with low back related leg pain

Neuroimaging studies have suggested a link between the intensity of chronic low back pain intensity and structural and functional brain alterations. However, chronic pain results from the coordination and dynamics among several brain networks that comprise the dynamic pain connectome. Here, we use resting-state functional magnetic resonance imaging and measures of static (sFC) and dynamic functional connectivity (dFC) variability in the typical (0.01–0.1 Hz) and five specific (slow-6 to slow-2) frequency bands to test hypotheses regarding disruption in this variability in low back-related leg pain (LBLP) patients who experience chronic pain and numbness. Twenty-four LBLP patients and 23 healthy controls completed clinical assessments, and partial correlational analyses between altered sFC and dFC variability and clinical measures were conducted. We found a lower within-network sFC in the ascending nociceptive pathway (Asc) and a lower cross-network sFC between nodes of the salience network and the Asc in the typical frequency band. In the slow-5 frequency band, a lower within-network sFC was found in the Asc. Abnormal cross-network sFC was found between nodes of the salience network-Asc (slow-5 and slow-6) and the default mode network-Asc (slow-4 and slow-6). Furthermore, cross-network abnormalities in the typical and certain specific frequency bands were linked to clinical assessments. These findings indicate that frequency-related within- and cross-network communication among the nodes in the dynamic pain connectome is dysfunctional in LBLP patients and that selecting specific frequencies may be potentially useful for detecting LBLP-related brain activity.

Alteration in Functional Magnetic Resonance Imaging Signal Complexity Across Multiple Time Scales in Patients With Migraine Without Aura

Background

Migraine is a primary neurological disorder associated with complex brain activity. Recently, mounting evidence has suggested that migraine is underpinned by aberrant dynamic brain activity characterized by linear and non-linear changes across a variety of time scales. However, the abnormal dynamic brain activity at different time scales is still unknown in patients with migraine without aura (MWoA). This study aimed to assess the altered patterns of brain activity dynamics over different time scales and the potential pathophysiological mechanisms of alterations in patients with MWoA.

Methods

Multiscale entropy in 50 patients and 20 healthy controls (HCs) was calculated to investigate the patterns and altered brain complexity (BC) across five different time scales. Spearman rank correlation analysis between BC in regions showing significant intergroup differences and clinical scores (i.e., frequency of migraine attacks, duration, headache impact test) was conducted in patients with MWoA.

Results

The spatial distribution of BC varied across different time scales. At time scale1, BC was higher in the posterior default mode network (DMN) across participants. Compared with HCs, patients with MWoA had higher BC in the DMN and sensorimotor network. At time scale2, BC was mainly higher in the anterior DMN across participants. Patients with MWoA had higher BC in the sensorimotor network. At time scale3, BC was mainly higher in the frontoparietal network across participants. Patients with MWoA had increased BC in the parietal gyrus. At time scale4, BC is mainly higher in the sensorimotor network. Patients with MWoA had higher BC in the postcentral gyrus. At time scale5, BC was mainly higher in the DMN. Patients with MWoA had lower BC in the posterior DMN. In particular, BC values in the precuneus and paracentral lobule significantly correlated with clinical symptoms.

Conclusion

Migraine is associated with alterations in dynamic brain activity in the sensorimotor network and DMN over multiple time scales. Time-varying BC within these regions could be linked to instability in pain transmission and modulation. Our findings provide new evidence for the hypothesis of abnormal dynamic brain activity in migraine.

Coupling cognitive and brainstem dysfunction in multiple sclerosis-related chronic neuropathic limb pain

Chronic pain in multiple sclerosis is common and difficult to treat. Its mechanisms remain incompletely understood. Dysfunction of the descending pain modulatory system is known to contribute to human chronic pain conditions. However, it is not clear how alterations in executive function influence this network, despite healthy volunteer studies linking function of the descending pain modulatory system, to cognition. In adults with multiple sclerosis-associated chronic neuropathic limb pain, compared to those without pain, we hypothesized altered functional connectivity of the descending pain modulatory system, coupled to executive dysfunction. Specifically we hypothesized reduced mental flexibility, because of potential importance in stimulus reappraisal. To investigate these hypotheses, we conducted a case-control cross-sectional study of 47 adults with relapsing remitting multiple sclerosis (31 with chronic neuropathic limb pain, 16 without pain), employing clinical, neuropsychological, structural, and functional MRI measures. We measured brain lesions and atrophy affecting descending pain modulatory system structures. Both cognitive and affective dysfunctions were confirmed in the chronic neuropathic limb pain group, including reduced mental flexibility (Delis Kaplan Executive Function System card sorting tests P < 0.001). Functional connectivity of rostral anterior cingulate and ventrolateral periaqueductal gray, key structures of the descending pain modulatory system, was significantly lower in the group experiencing chronic neuropathic pain. There was no significant between-group difference in whole-brain grey matter or lesion volumes, nor lesion volume affecting white matter tracts between rostral anterior cingulate and periaqueductal gray. Brainstem-specific lesion volume was higher in the chronic neuropathic limb pain group (P = 0.0017). Differential functional connectivity remained after correction for brainstem-specific lesion volume. Gabapentinoid medications were more frequently used in the chronic pain group. We describe executive dysfunction in people with multiple sclerosis affected by chronic neuropathic pain, along with functional and structural MRI evidence compatible with dysfunction of the descending pain modulatory system. These findings extend understanding of close inter-relationships between cognition, function of the descending pain modulatory system, and chronic pain, both in multiple sclerosis and more generally in human chronic pain conditions. These findings could support application of pharmacological and cognitive interventions in chronic neuropathic pain associated with multiple sclerosis.

Performances of whole-brain dynamic and static functional connectivity fingerprinting in machine learning-based classification of major depressive disorder

BACKGROUND

Alterations in static and dynamic functional connectivity during resting state have been widely reported in major depressive disorder (MDD). The objective of this study was to compare the performances of whole-brain dynamic and static functional connectivity combined with machine learning approach in differentiating MDD patients from healthy controls at the individual subject level. Given the dynamic nature of brain activity, we hypothesized that dynamic connectivity would outperform static connectivity in the classification.

METHODS

Seventy-one MDD patients and seventy-one well-matched healthy controls underwent resting-state functional magnetic resonance imaging scans. Whole-brain dynamic and static functional connectivity patterns were calculated and utilized as classification features. Linear kernel support vector machine was employed to design the classifier and a leave-one-out cross-validation strategy was used to assess classifier performance.

RESULTS

Experimental results of dynamic functional connectivity-based classification showed that MDD patients could be discriminated from healthy controls with an excellent accuracy of 100% irrespective of whether or not global signal regression (GSR) was performed (permutation test with P < 0.0002). Brain regions with the most discriminating dynamic connectivity were mainly and reliably located within the default mode network, cerebellum, and subcortical network. In contrast, the static functional connectivity-based classifiers exhibited unstable classification performances, i.e., a low accuracy of 38.0% without GSR (P = 0.9926) while a high accuracy of 96.5% with GSR (P < 0.0002); moreover, there was a considerable variability in the distribution of brain regions with static connectivity most informative for classification.

CONCLUSION

These findings suggest the superiority of dynamic functional connectivity in machine learning-based classification of depression, which may be helpful for a better understanding of the neural basis of MDD as well as for the development of effective computer-aided diagnosis tools in clinical settings.

Altered brain activity in end-stage knee osteoarthritis revealed by resting-state functional magnetic resonance imaging

INTRODUCTION

Knee osteoarthritis (KOA) is characterized by a degenerative change of knee cartilage and secondary bone hyperplasia, resulting in pain, stiffness, and abnormal walking gait. Long-term chronic pain causes considerable cortical plasticity alternations in patients. However, the brain structural and functional alterations associated with the pathological changes in knee joints of end-stage KOA patients remain unclear. This study aimed to analyze the structural and functional connectivity alterations in end-stage KOA to comprehensively understand the main brain-associated mechanisms underlying its development and progression.

METHODS

In this study, 37 patients with KOA and 37 demographically matched healthy controls (HCs) were enrolled. Alternations in gray matter (GM) volume in patients with KOA were determined using voxel-based morphometry. The region with the largest GM volume alteration was selected as the region of interest to calculate the voxel-wise resting-state functional connectivity (rs-FC) in the two groups. Pearson's correlation coefficient was used to analyze the correlation between clinical measures and GM volume alternations in patients with KOA.

RESULTS

Compared with HCs, patients with KOAs exhibited significantly decreased GM volumes in the left middle temporal gyrus (left-MTG) and the left inferior temporal gyrus. Results of the voxel-wise rs-FC analysis revealed that compared with HCs, patients with KOA had decreased left-MTG rs-FC to the right dorsolateral superior frontal gyrus, left middle frontal gyrus, and left medial superior frontal gyrus. GM volume in the left-MTG was negatively correlated with the Western Ontario and McMaster Universities Arthritis Index in patients with KOA (r = -0.393, p = .016).

CONCLUSION

Structural remodeling and functional connectivity alterations may be one of the central brain mechanisms associated with end-stage KOA.

Dynamics of brain function in patients with chronic pain assessed by microstate analysis of resting-state electroencephalography

ABSTRACT

Chronic pain is a highly prevalent and severely disabling disease that is associated with substantial changes of brain function. Such changes have mostly been observed when analyzing static measures of resting-state brain activity. However, brain activity varies over time, and it is increasingly recognized that the temporal dynamics of brain activity provide behaviorally relevant information in different neuropsychiatric disorders. Here, we therefore investigated whether the temporal dynamics of brain function are altered in chronic pain. To this end, we applied microstate analysis to eyes-open and eyes-closed resting-state electroencephalography data of 101 patients suffering from chronic pain and 88 age- and sex-matched healthy controls. Microstate analysis describes electroencephalography activity as a sequence of a limited number of topographies termed microstates that remain stable for tens of milliseconds. Our results revealed that sequences of 5 microstates, labelled with the letters A to E, consistently described resting-state brain activity in both groups in the eyes-closed condition. Bayesian analysis of the temporal characteristics of microstates revealed that microstate D has a less predominant role in patients than in controls. As microstate D has previously been related to attentional networks and functions, these abnormalities might relate to dysfunctional attentional processes in chronic pain. Subgroup analyses replicated microstate D changes in patients with chronic back pain, while patients with chronic widespread pain did not show microstates alterations. Together, these findings add to the understanding of the pathophysiology of chronic pain and point to changes of brain dynamics specific to certain types of chronic pain.

Pain, quality of life, and religiosity in people with multiple sclerosis

PURPOSE

To investigate in multiple sclerosis (MS) patients, the relationship between pain and religiosity and to determine whether distinct dimensions of religiosity were associated with quality of life.

METHODS

MS patients during clinical follow-up filled out the visual analogue scale for pain (VAS), the Mc Gill questionnaire (McGQ), the 36-Item Short Form Health Survey (SF-36), and the religious attitude scale (RAS), and expanded disability status scale (EDSS) was assessed.

RESULTS

Ninety-two MS patients were enrolled, only two declined. There was a negative correlation between religious practice and faith and some domains of the SF-36 and a positive correlation between sensory, affective, and evaluative aspects of pain (at McGQ) and religious practices, and between evaluative aspects of pain (at McGQ) and faith. EDSS was significantly higher in practitioner believers compared to not practitioners.

CONCLUSIONS

More disabled MS patients, with worse quality of life, also due to physical pain, find a source of comfort in faith and religious practices. Pain is not relieved by prayer; therefore, we may guess that in MS the poor beneficial effect of religiosity and practice on pain perception may be linked to a structural/functional damage of neural circuits involved in reducing pain during prayer.

Sex differences in brain modular organization in chronic pain

ABSTRACT

Men and women can exhibit different pain sensitivities, and many chronic pain conditions are more prevalent in one sex. Although there is evidence of sex differences in the brain, it is not known whether there are sex differences in the organization of large-scale functional brain networks in chronic pain. Here, we used graph theory with modular analysis and machine-learning of resting-state-functional magnetic resonance imaging data from 220 participants: 155 healthy controls and 65 individuals with chronic low back pain due to ankylosing spondylitis, a form of arthritis. We found an extensive overlap in the graph partitions with the major brain intrinsic systems (ie, default mode, central, visual, and sensorimotor modules), but also sex-specific network topological characteristics in healthy people and those with chronic pain. People with chronic pain exhibited higher cross-network connectivity, and sex-specific nodal graph properties changes (ie, hub disruption), some of which were associated with the severity of the chronic pain condition. Females exhibited atypically higher functional segregation in the mid cingulate cortex and subgenual anterior cingulate cortex and lower connectivity in the network with the default mode and frontoparietal modules, whereas males exhibited stronger connectivity with the sensorimotor module. Classification models on nodal graph metrics could classify an individual's sex and whether they have chronic pain with high accuracies (77%-92%). These findings highlight the organizational abnormalities of resting-state-brain networks in people with chronic pain and provide a framework to consider sex-specific pain therapeutics.

Abnormal subgenual anterior cingulate circuitry is unique to women but not men with chronic pain

The subgenual anterior cingulate cortex (sgACC) plays an important role in pain modulation. We previously demonstrated sex differences in sgACC functional connectivity (FC) in healthy individuals. Given that many chronic pain conditions show sex differences in prevalence, here we tested the hypothesis that people with chronic pain exhibit a sex-specific pattern of abnormal sgACC FC. We acquired resting-state functional magnetic resonance imaging data from 156 (82 W: 74 M) healthy participants and 38 (19 W: 19 M) people with chronic low back pain resulting from ankylosing spondylitis, a condition that predominantly affects men. We confirmed that there are sex differences in sgACC FC in our large cohort of healthy adults; women had greater sgACC FC with the precuneus, a key node of the default mode network, and men had greater sgACC FC with the posterior insula and the operculum. Next, we identified an interaction effect between sex and pain status (healthy/chronic pain) for sgACC FC. Within the chronic pain group, women had greater sgACC FC than men to the default mode and sensorimotor networks. Compared to healthy women, women with chronic pain also had greater sgACC FC to the precuneus and lower FC to the hippocampus and frontal regions. No differences in sgACC FC were seen in men with vs without chronic pain. Our findings indicate that abnormal sgACC circuitry is unique to women but not men with ankylosing spondylitis-related chronic pain. These sex differences may impact the benefit of therapeutics that target the sgACC for chronic pain.

Dynamic Functional Connectivity in the Main Clinical Phenotypes of Multiple Sclerosis

Introduction: Dynamic functional connectivity (dFC) allows capturing recurring patterns (states) of interaction among functional networks. In this study, we investigated resting state (RS) dFC abnormalities across the different clinical phenotypes of multiple sclerosis (MS) and assessed their correlation with motor and cognitive performances. Methods: RS functional magnetic resonance imaging (fMRI) and 3D T1-weighted MRI data were acquired from 128 MS patients (69 relapsing-remitting [RR] MS, 34 secondary progressive [SP] MS, and 25 primary progressive [PP] MS) and 40 healthy controls (HC). RS fMRI data underwent independent component analysis and sliding-window correlations, to identify recurring dFC states and between-group dFC differences in the main networks. Results: dFC identified three recurring connectivity states: State 1 (frequency of appearance during fMRI acquisition = 57%, low dFC strength), State 2 (frequency = 19%, middle-high dFC strength), and State 3 (frequency = 24%, high sensorimotor and visual dFC strength). Compared to HC, MS (as a whole), RRMS, and PPMS patients exhibited lower State1/State 3 dFC (p = 0.0001, corrected) between sensorimotor, cerebellar, and cognitive networks, and some dFC increments (p = 0.001-0.05, uncorrected) in sensorimotor, visual, default-mode, and frontal/attention networks in States 2 and 3. Similar results were observed in SPMS versus RRMS patients. In MS, dFC decrease in sensorimotor, default-mode, and frontal/attention networks was correlated with worse motor and cognitive performances. Conclusions: MS patients exhibited overall lower dFC, and marginally higher dFC in sensorimotor/cognitive networks in the less-frequent middle/high-connected States. dFC abnormalities became more severe in progressive MS and correlated with motor and cognitive impairment, suggesting the presence of maladaptive mechanisms concomitant with accumulation of damage.

Temporal instability of salience network activity in migraine with aura

This study aims to investigate whether intranetwork dynamic functional connectivity and causal interactions of the salience network is altered in the interictal term of migraine. Thirty-two healthy controls, 37 migraineurs without aura, and 20 migraineurs with aura were recruited. Participants underwent a T1-weighted scan and resting-state fMRI protocol inside a 1.5T MR scanner. We obtained average spatial maps of resting-state networks using group independent component analysis, which yielded subject-specific time series through a dual regression approach. Salience network regions of interest (bilateral insulae and prefrontal cortices, dorsal anterior cingulate cortex) were obtained from the group average map through cluster-based thresholding. To describe intranetwork connectivity, average and dynamic conditional correlation was calculated. Causal interactions between the default-mode, dorsal attention, and salience network were characterised by spectral Granger's causality. Time-averaged correlation was lower between the right insula and prefrontal cortex in migraine without aura vs with aura and healthy controls (P < 0.038, P < 0.037). Variance of dynamic conditional correlation was higher in migraine with aura vs healthy controls and migraine with aura vs without aura between the right insula and dorsal anterior cingulate cortex (P < 0.011, P < 0.026), and in migraine with aura vs healthy controls between the dorsal anterior cingulate and left prefrontal cortex (P < 0.021). Causality was weaker in the <0.05 Hz frequency range between the salience and dorsal attention networks in migraine with aura (P < 0.032). Overall, migraineurs with aura exhibit more fluctuating connections in the salience network, which also affect network interactions, and could be connected to altered cortical excitability and increased sensory gain.

How expectations of pain elicited by consciously and unconsciously perceived cues unfold over time

Expectation can shape the perception of pain within a fraction of time, but little is known about how perceived expectation unfolds over time and modulates pain perception. Here, we combine magnetoencephalography (MEG) and machine learning approaches to track the neural dynamics of expectations of pain in healthy participants with both sexes. We found that the expectation of pain, as conditioned by facial cues, can be decoded from MEG as early as 150 ms and up to 1100 ms after cue onset, but decoding expectation elicited by unconsciously perceived cues requires more time and decays faster compared to consciously perceived ones. Also, results from temporal generalization suggest that neural dynamics of decoding cue-based expectation were predominately sustained during cue presentation but transient after cue presentation. Finally, although decoding expectation elicited by consciously perceived cues were based on a series of time-restricted brain regions during cue presentation, decoding relied on the medial prefrontal cortex and anterior cingulate cortex after cue presentation for both consciously and unconsciously perceived cues. These findings reveal the conscious and unconscious processing of expectation during pain anticipation and may shed light on enhancing clinical care by demonstrating the impact of expectation cues.

Central neuropathic pain in multiple sclerosis is associated with impaired innocuous thermal pathways and neuronal hyperexcitability

OBJECTIVE

About a third of patients with multiple sclerosis (MS) suffer from chronic and excruciating central neuropathic pain (CNP). The mechanism underlying CNP in MS is not clear, since previous studies are scarce and their results are inconsistent. Our aim was to determine whether CNP in MS is associated with impairment of the spinothalamic-thalamocortical pathways (STTCs) and/or increased excitability of the pain system.

DESIGN

Cross sectional study.

SETTING

General hospital.

SUBJECTS

47 MS patients with CNP, 42 MS patients without CNP, and 32 healthy controls.

METHODS

Sensory testing included the measurement of temperature, pain, and touch thresholds and the thermal grill illusion (TGI) for evaluating STTCs function, and hyperpathia and allodynia as indicators of hyperexcitability. CNP was characterized using interviews and questionnaires.

RESULTS

The CNP group had higher cold and warm thresholds (p < 0.01), as well as higher TGI perception thresholds (p < 0.05), especially in painful body regions compared to controls, whereas touch and pain thresholds values were normal. The CNP group also had a significantly greater prevalence of hyperpathia and allodynia. Regression analysis revealed that whereas presence of CNP was associated with a higher cold threshold, CNP intensity, and the number of painful body regions were associated with allodynia and hyperpathia, respectively.

CONCLUSIONS

CNP in MS is characterized by a specific impairment of STTC function; the innocuous thermal pathways, and by pain hyperexcitability. Whereas CNP presence is associated with STTC impairment, its severity and extent are associated with pain hyperexcitability. Interventions that reduce excitability level may therefore mitigate CNP severity.

Current Understanding of the Involvement of the Insular Cortex in Neuropathic Pain: A Narrative Review

Neuropathic pain is difficult to cure and is often accompanied by emotional and psychological changes. Exploring the mechanisms underlying neuropathic pain will help to identify a better treatment for this condition. The insular cortex is an important information integration center. Numerous imaging studies have documented increased activity of the insular cortex in the presence of neuropathic pain; however, the specific role of this region remains controversial. Early studies suggested that the insular lobe is mainly involved in the processing of the emotional motivation dimension of pain. However, increasing evidence suggests that the role of the insular cortex is more complex and may even be related to the neural plasticity, cognitive evaluation, and psychosocial aspects of neuropathic pain. These effects contribute not only to the development of neuropathic pain, but also to its comorbidity with neuropsychiatric diseases. In this review, we summarize the changes that occur in the insular cortex in the presence of neuropathic pain and analgesia, as well as the molecular mechanisms that may underlie these conditions. We also discuss potential sex-based differences in these processes. Further exploration of the involvement of the insular lobe will contribute to the development of new pharmacotherapy and psychotherapy treatments for neuropathic pain.

Dynamic functional connectome predicts individual working memory performance across diagnostic categories

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We created transdiagnostic predictive working memory models using connectome-based predictive modeling (CPM).

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Dynamic functional connectivity-based CPM models successfully predicted working memory.

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Static functional connectivity-based CPM models fell short in prediction.

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Frontoparietal, somato-motor, default mode and visual networks contributed most to prediction.

Working memory impairment is a common feature of psychiatric disorders. Although its neural mechanisms have been extensively examined in healthy subjects or individuals with a certain clinical condition, studies investigating neural predictors of working memory in a transdiagnostic sample are scarce. The objective of this study was to create a transdiagnostic predictive working memory model from whole-brain functional connectivity using connectome-based predictive modeling (CPM), a recently developed machine learning approach. Resting-state functional MRI data from 242 subjects across 4 diagnostic categories (healthy controls and individuals with schizophrenia, bipolar disorder, and attention deficit/hyperactivity) were used to construct dynamic and static functional connectomes. Spatial working memory was assessed by the spatial capacity task. CPM was conducted to predict individual working memory from dynamic and static functional connectivity patterns. Results showed that dynamic connectivity-based CPM models successfully predicted overall working memory capacity and accuracy as well as mean reaction time, yet their static counterparts fell short in the prediction. At the neural level, we found that dynamic connectivity of the frontoparietal and somato-motor networks were negatively correlated with working memory capacity and accuracy, and those of the default mode and visual networks were positively associated with mean reaction time. Moreover, different feature selection thresholds, parcellation strategies and model validation methods as well as diagnostic categories did not significantly influence the prediction results. Our findings not only are coherent with prior reports that dynamic functional connectivity encodes more behavioral information than static connectivity, but also help advance the translation of cognitive “connectome fingerprinting” into real-world application.

Aberrant Brain Signal Variability and COMT Genotype in Chronic TMD Patients

The analysis of brain signal variability is a promising approach to understand pathological brain function related to chronic pain. This study investigates whether blood-oxygen-level-dependent signal variability (BOLD_SV) in specific frequency bands is altered in temporomandibular disorder (TMD) and correlated to its clinical features. Twelve patients with chronic myofascial TMD and 24 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. The BOLD_SV was measured as the standard deviation of the BOLD time series at each voxel and compared between groups. We also examined the potential relationship between the BOLD_SV and the catechol-O-methyltransferase (COMT) Val¹⁵⁸Met polymorphism. We assessed sensory-discriminative pain in the craniofacial region, pain sensitivity to sustained masseteric pain challenge, and TMD pain frequency for clinical correlation. Patients displayed reduced BOLD_SV in the dorsolateral prefrontal cortex (dlPFC) as compared with HC in all frequency bands. In the slow-3 band, patients also showed reduced BOLD_SV in the medial dorsal thalamus, primary motor cortex (M1), and primary somatosensory cortex (S1) and heightened BOLD_SV in the temporal pole. Notably, we found a significant correlation between lower BOLD_SV (slow-3) in the orofacial M1/S1 regions and higher clinical pain (intensity/area) and higher sensitivity of the masseter muscle pain. Moreover, lower BOLD_SV (slow-3) in the dlPFC and ventrolateral PFC was associated with a higher TMD pain frequency. Participants who had the COMT ¹⁵⁸Met substitution exhibited lower BOLD_SV in the dlPFC and higher BOLD_SV in the temporal pole as compared with participants without the COMT ¹⁵⁸Met substitution. An increasing number of Met alleles was associated with lower dlPFC and greater temporal pole BOLD_SV in both HC and TMD groups. Together, we demonstrated that chronic TMD patients exhibit aberrant BOLD_SV in the top-down pain modulatory and sensorimotor circuits associated with their pain frequency and severity. COMT Val¹⁵⁸Met polymorphism might affect clinical symptoms in association with regional brain signal variability, specifically involved in cognitive and emotional regulation of pain.

Mind the gap: from neurons to networks to outcomes in multiple sclerosis

MRI studies have provided valuable insights into the structure and function of neural networks, particularly in health and in classical neurodegenerative conditions such as Alzheimer disease. However, such work is also highly relevant in other diseases of the CNS, including multiple sclerosis (MS). In this Review, we consider the effects of MS pathology on brain networks, as assessed using MRI, and how these changes to brain networks translate into clinical impairments. We also discuss how this knowledge can inform the targeting of MS treatments and the potential future directions for research in this area. Studying MS is challenging as its pathology involves neurodegenerative and focal inflammatory elements, both of which could disrupt neural networks. The disruption of white matter tracts in MS is reflected in changes in network efficiency, an increasingly random grey matter network topology, relative cortical disconnection, and both increases and decreases in connectivity centred around hubs such as the thalamus and the default mode network. The results of initial longitudinal studies suggest that these changes evolve rather than simply increase over time and are linked with clinical features. Studies have also identified a potential role for treatments that functionally modify neural networks as opposed to altering their structure.

Differential alteration of fMRI signal variability in the ascending trigeminal somatosensory and pain modulatory pathways in migraine

BACKGROUND

The moment-to-moment variability of resting-state brain activity has been suggested to play an active role in chronic pain. Here, we investigated the regional blood-oxygen-level-dependent signal variability (BOLDSV) and inter-regional dynamic functional connectivity (dFC) in the interictal phase of migraine and its relationship with the attack severity.

METHODS

We acquired resting-state functional magnetic resonance imaging from 20 migraine patients and 26 healthy controls (HC). We calculated the standard deviation (SD) of the BOLD time-series at each voxel as a measure of the BOLD signal variability (BOLDSV) and performed a whole-brain voxel-wise group comparison. The brain regions showing significant group differences in BOLDSV were used to define the regions of interest (ROIs). The SD and mean of the dynamic conditional correlation between those ROIs were calculated to measure the variability and strength of the dFC. Furthermore, patients' experimental pain thresholds and headache pain area/intensity levels during the migraine ictal-phase were assessed for clinical correlations.

RESULTS

We found that migraineurs, compared to HCs, displayed greater BOLDSV in the ascending trigeminal spinal-thalamo-cortical pathways, including the spinal trigeminal nucleus, pulvinar/ventral posteromedial (VPM) nuclei of the thalamus, primary somatosensory cortex (S1), and posterior insula. Conversely, migraine patients exhibited lower BOLDSV in the top-down modulatory pathways, including the dorsolateral prefrontal (dlPFC) and inferior parietal (IPC) cortices compared to HCs. Importantly, abnormal interictal BOLDSV in the ascending trigeminal spinal-thalamo-cortical and frontoparietal pathways were associated with the patient's headache severity and thermal pain sensitivity during the migraine attack. Migraineurs also had significantly lower variability and greater strength of dFC within the thalamo-cortical pathway (VPM-S1) than HCs. In contrast, migraine patients showed greater variability and lower strength of dFC within the frontoparietal pathway (dlPFC-IPC).

CONCLUSIONS

Migraine is associated with alterations in temporal signal variability in the ascending trigeminal somatosensory and top-down modulatory pathways, which may explain migraine-related pain and allodynia. Contrasting patterns of time-varying connectivity within the thalamo-cortical and frontoparietal pathways could be linked to abnormal network integrity and instability for pain transmission and modulation.

A neuroimaging marker for predicting longitudinal changes in pain intensity of subacute back pain based on large-scale brain network interactions

Identification of predictive neuroimaging markers of pain intensity changes is a crucial issue to better understand macroscopic neural mechanisms of pain. Although a single connection between the medial prefrontal cortex and nucleus accumbens has been suggested as a powerful marker, how the complex interactions on a large-scale brain network can serve as the markers is underexplored. Here, we aimed to identify a set of functional connections predictive of longitudinal changes in pain intensity using large-scale brain networks. We re-analyzed previously published resting-state functional magnetic resonance imaging data of 49 subacute back pain (SBP) patients. We built a network-level model that predicts changes in pain intensity over one year by combining independent component analysis and a penalized regression framework. Connections involving top-down pain modulation, multisensory integration, and mesocorticolimbic circuits were identified as predictive markers for pain intensity changes. Pearson's correlations between actual and predicted pain scores were r = 0.33-0.72, and group classification results between SBP patients with persisting pain and recovering patients, in terms of area under the curve (AUC), were 0.89/0.75/0.75 for visits four/three/two, thus outperforming the previous work (AUC 0.83/0.73/0.67). This study identified functional connections important for longitudinal changes in pain intensity in SBP patients, providing provisional markers to predict future pain using large-scale brain networks.

Cerebellar-cerebral dynamic functional connectivity alterations in major depressive disorder

BACKGROUND

The cerebellum plays an important role in the neural mechanism of depression and its static functional connectivity (FC) with the cerebrum is disrupted in patients with major depressive disorder (MDD). However, cerebellar-cerebral dynamic FC alterations in MDD remain largely unknown.

METHODS

50 patients with MDD and 36 well-matched healthy controls underwent resting-state functional magnetic resonance imaging. Cerebellar-cerebral dynamic FC analyses were performed using the cerebellar seeds previously identified as being involved in the executive, default-mode, affective-limbic, and motor networks. Inter-group differences in the cerebellar dynamic FC and their associations with clinical and cognitive variables were examined.

RESULTS

Compared to healthy controls, patients with MDD had decreased cerebellar-cerebral dynamic FC of the cerebellar subregions connecting with the executive, default-mode and affective-limbic networks. The dynamic FC of the cerebellar subregion connecting with the affective-limbic network was related to severity of depression and anxiety symptoms in MDD patients. The dynamic FC of the cerebellar subregions connecting with the default-mode and affective-limbic networks were related to sustained attention and prospective memory in controls, while the correlations were inverse or non-significant in patients.

LIMITATIONS

The fairly modest sample size and potential medication effect may increase the instability of the results.

CONCLUSIONS

Our findings provide further evidence for the pivotal role of the cerebellum in the neuropathology of depression, pointing to potential targets of cerebellar-cerebral pathways for alternative intervention or monitoring therapeutic responses.

Neural Oscillations: Understanding a Neural Code of Pain

Neural oscillations play an important role in the integration and segregation of brain regions that are important for brain functions, including pain. Disturbances in oscillatory activity are associated with several disease states, including chronic pain. Studies of neural oscillations related to pain have identified several functional bands, especially alpha, beta, and gamma bands, implicated in nociceptive processing. In this review, we introduce several properties of neural oscillations that are important to understand the role of brain oscillations in nociceptive processing. We also discuss the role of neural oscillations in the maintenance of efficient communication in the brain. Finally, we discuss the role of neural oscillations in healthy and chronic pain nociceptive processing. These data and concepts illustrate the key role of regional and interregional neural oscillations in nociceptive processing underlying acute and chronic pains.

Individual variability and sex differences in conditioned pain modulation and the impact of resilience, and conditioning stimulus pain unpleasantness and salience

Distinct pain experiences are shaped both by personal attributes and characteristics of noxious stimuli. An Individual's capacity for endogenous pain inhibition (reflected by conditioned pain modulation [CPM]), their resilience, and the pain unpleasantness and salience of painful stimuli can impact their pain perception. Here, we aimed to determine how individual variability in CPM relates to sex and resilience as personal attributes, and pain unpleasantness and salience of the CPM conditioning stimulus (CS). We evaluated CPM in 106 healthy participants (51 female and 55 male) based on the change in test stimulus pain applied concurrently with a painful CS, both delivered by painful heat. The CS reduced test stimulus pain in only half of the participants (CPM subgroup), but did not do so for the other half (no-CPM subgroup), many who exhibited pain facilitation. A regression model explained CPM effects after accounting for sex, resilience, CS pain unpleasantness and salience. In the CPM subgroup regression model, the CPM effect was positively related to CS pain unpleasantness, while the CPM effect was not related to any variable in the no-CPM subgroup model. Correlation analyses revealed that the CPM effect was anticorrelated with resilience in males with no-CPM. The CPM effect was correlated with CS pain unpleasantness in males with CPM and in females with no-CPM. The CPM effect and CS salience were correlated in the whole group more strongly than in the subgroups. These data reveal that the complexity of contributors to CPM variability include both personal attributes and attributes of the CS.

Imaging vs quantitative sensory testing to predict chronic pain treatment outcomes

In this article, I review the concept of personalized pain management and consider how brain imaging and quantitative sensory testing can be used to derive biomarkers of chronic pain treatment outcome. I review how different modalities of brain imaging can be used to acquire information about brain structure and function and how this information can be linked to individual measures of pain.

Abnormal alpha band power in the dynamic pain connectome is a marker of chronic pain with a neuropathic component

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High theta and low gamma activity in the dynamic pain connectome is linked to chronic pain.

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High alpha-band activity is present when neuropathic pain is likely.

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Spectral frequency band strength distinguish neuropathic from non-neuropathic pain.

We previously identified alpha frequency slowing and beta attenuation in the dynamic pain connectome related to pain severity and interference in patients with multiple sclerosis-related neuropathic pain (NP). Here, we determined whether these abnormalities, are markers of aberrant temporal dynamics in non-neuropathic inflammatory pain (non-NP) or when NP is also suspected. We measured resting-state magnetoencephalography (MEG) spectral density in 45 people (17 females, 28 males) with chronic back pain due to ankylosing spondylitis (AS) and 38 age/sex matched healthy controls. We used painDETECT scores to divide the chronic pain group into those with only non-NP (NNP) and those who likely also had a component of NP in addition to their inflammatory pain. We also assessed pain severity, pain interference, and disease activity with the Brief Pain Inventory and Bath AS Disease Activity Index (BASDAI). We examined spectral power in the dynamic pain connectome, including nodes of the ascending nociceptive pathway (ANP), default mode (DMN), and salience networks (SN). Compared to the healthy controls, the AS patients exhibited increased theta power in the DMN and decreased low-gamma power in the DMN and ANP, but did not exhibit beta-band attenuation or peak-alpha slowing. The NNP patients were not different from HCs. Compared to both healthy controls and NNP, NP patients had increased alpha power in the ANP. Increased alpha power within the ANP was associated with reduced BASDAI in the NNP group, and increased pain in the mixed-NP group within the DMN, SN, and ANP. Thus, high theta and low gamma activity may be markers of chronic pain but high alpha-band activity may relate to particular features of neuropathic chronic pain.