Changes In Brain Networks Research Articles

Age‐related Modularity Changes of the Structural Brain Network: The Framingham Study

AbstractBackgroundWhile studies have consistently shown that brain network efficiency decreases with age, data on age‐related reconfiguration of network modules are scarce. We assessed structural brain networks from healthy adults of the Framingham Study to explore age‐related modularity differences.MethodStructural brain networks of 2,903 healthy adults (mean age 55, SD 0.96, range 25‐95, 53% female) were obtained from DTI probabilistic tractography. Connectivity matrices were constructed from 72 cortical and subcortical regions. First, we calculated efficiency to check the validity of our data. Second, we constructed a multilayer network with each layer representing one age decile and calculated modularity for each layer using a robust implementation of the Louvain community‐detection algorithm (Blondel et al., 2008). Third, we compared modular structures between each layer and a reference group (youngest) using the variation of information (VI), an index measure of distance between two modular patterns (e.g. modularity at different ages). Finally, we calculated the participation coefficient, a measure of modular node integration, and the node flexibility, a measure of module allegiance change and assessed their relationships with age.ResultEfficiency decreased with age (b = ‐0.34, SE 0.02, p<0.001), being stable until approximately 50 and declining linearly thereafter (see Figure 1, panel a). Modularity showed a u‐shaped trajectory with most integration at the fifth decile of age (see Figure1, panel b). VI index revealed that modular reconfiguration was greatest between the youngest and the oldest age decile (0.43). Participation coefficient was highest at the fifth decile (see Figure2, panel c) and in frontal nodes (see Figure2, panel a), where it also exhibited high variability. Frontal variability followed a complex pattern (Figure2, panel b). Conversely, central and temporal‐occipital nodes showed less participation and variability (see Figure2, panels a and b), and the lowest flexibility (see Figure3).ConclusionBrain network modules reconfigure with aging. This reconfiguration is non‐uniform. While midline‐near modules, including the cingulate and parieto‐occipital cortices, show relative stability, frontal modules seemed to reconfigure considerably, as seen by increased average flexibility (change in modular allegiance) and less integration with advancing age, as seen by declining participation coefficients.

Effects of individual metabolic brain network changes co-affected by T2DM and aging on the probabilities of T2DM: protective and risk factors.

Neuroimaging markers for risk and protective factors related to type 2 diabetes mellitus are critical for clinical prevention and intervention. In this work, the individual metabolic brain networks were constructed with Jensen-Shannon divergence for 4 groups (elderly type 2 diabetes mellitus and healthy controls, and middle-aged type 2 diabetes mellitus and healthy controls). Regional network properties were used to identify hub regions. Rich-club, feeder, and local connections were subsequently obtained, intergroup differences in connections and correlations between them and age (or fasting plasma glucose) were analyzed. Multinomial logistic regression was performed to explore effects of network changes on the probability of type 2 diabetes mellitus. The elderly had increased rich-club and feeder connections, and decreased local connection than the middle-aged among type 2 diabetes mellitus; type 2 diabetes mellitus had decreased rich-club and feeder connections than healthy controls. Protective factors including glucose metabolism in triangle part of inferior frontal gyrus, metabolic connectivity between triangle of the inferior frontal gyrus and anterior cingulate cortex, degree centrality of putamen, and risk factors including metabolic connectivities between triangle of the inferior frontal gyrus and Heschl's gyri were identified for the probability of type 2 diabetes mellitus. Metabolic interactions among critical brain regions increased in type 2 diabetes mellitus with aging. Individual metabolic network changes co-affected by type 2 diabetes mellitus and aging were identified as protective and risk factors for the likelihood of type 2 diabetes mellitus, providing guiding evidence for clinical interventions.

Static and dynamic functional connectivity combined with the triple network model in amnestic mild cognitive impairment and Alzheimer's disease.

Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) are characterized by abnormal functional connectivity (FC) of default-mode network (DMN), salience network (SN), and central executive network (CEN). Static FC (sFC) and dynamic FC (dFC) combined with triple network model can better study the dynamic and static changes of brain networks, and improve its potential diagnostic value in the diagnosis of AD spectrum disorders. Differences in sFC values and dFC variability patterns among the three brain networks of the three groups (53 AD patients, 40 aMCI patients, and 40 NCs) were computed by ANOVA using Gaussian Random Field theory (GRF) correction. The correlation between FC values (sFC values and dFC variability) in the three networks and cognitive scores (MMSE and MoCA) in AD and aMCI groups was analyzed separately. Within the DMN network, there were significant differences of sFC values in right/left medial superior frontal gyrus and dFC variability in left opercular part inferior frontal gyrus and right dorsolateral superior frontal gyrus among the three groups. Within the CEN network, there were significant differences of sFC values in left superior parietal gyrus. Within the SN network, there were significant differences of dFC variability in right Cerebelum_7b and left opercular part inferior frontal gyrus. In addition, there was a significant negative correlation between FC values (sFC values of CEN and dFC variability of SN) and MMSE and MoCA scores. It suggests that sFC, dFC combined with triple network model can be considered as potential biomarkers for AD and aMCI.

Inside the mindful moment: The effects of brief mindfulness practice on large-scale network organization and intimate partner aggression.

Mindfulness can produce neuroplastic changes that support adaptive cognitive and emotional functioning. Recently interest in single-exercise mindfulness instruction has grown considerably because of the advent of mobile health technology. Accordingly, the current study sought to extend neural models of mindfulness by investigating transient states of mindfulness during single-dose exposure to focused attention meditation. Specifically, we examined the ability of a brief mindfulness induction to attenuate intimate partner aggression via adaptive changes to intrinsic functional brain networks. We employed a dual-regression approach to examine a large-scale functional network organization in 50 intimate partner dyads (total n = 100) while they received either mindfulness (n = 50) or relaxation (n = 50) instruction. Mindfulness instruction reduced coherence within the Default Mode Network and increased functional connectivity within the Frontoparietal Control and Salience Networks. Additionally, mindfulness decoupled primary visual and attention-linked networks. Yet, this induction was unable to elicit changes in subsequent intimate partner aggression, and such aggression was broadly unassociated with any of our network indices. These findings suggest that minimal doses of focused attention-based mindfulness can promote transient changes in large-scale brain networks that have uncertain implications for aggressive behavior.

A shift of brain network hub after spinal cord injury.

Spinal cord injury (SCI) causes severe sequelae and significant social loss, depending on the extent of the damage. Most previous studies have focused on the pathology of the spinal cord to develop treatments for SCI. However, it is now known that the brain, which is not directly damaged, also undergoes morphological changes after spinal cord injury, which could affect natural recovery and treatment. In recent years, magnetic resonance imaging (MRI) has been developed to analyze functional changes in the brain. Resting-state functional MRI (rsfMRI), which captures brain activity at rest, can calculate functional connections between brain areas and identify central hubs by network analysis. We aim to investigate functional connectivity in the brain using rsfMRI after SCI and to determine how brain-network main hubs change over time. We evaluated rsfMRI in 10 mice of the contusional SCI model and calculated connectivity using graph theory. We evaluated "centrality," a representative parameter of network analysis. The subtype of centrality was degree centrality, which indicates the hub function of a single area. The five times of rsfMRI were performed in each individual mouse: before injury and at 1, 3, 7, and 14 weeks post-injury. Before the injury, the degree centralities of the primary and secondary motor cortex were high, suggesting that these motor cortices served as main hubs for motor function. After SCI, the hub function of the motor cortices decreased by 14 weeks. In contrast, hub function in the external capsule and the putamen comparatively increased with time after injury, suggesting that the extrapyramidal/subcortical system, which runs the ventral side of the spinal cord and remains after injury in this model, becomes dominant. We demonstrated the shift of the brain network hub after SCI. The results of this study provide basic information for understanding brain network changes after SCI and would be useful for treatment selection and evaluation of its efficacy in SCI patients.

Changes of brain network in patients with insomnia following radiotherapy for cervical cancer and their correlation with IT-TMS treatment efficacy: a graph-theory analysis

To analyze the changes of brain small-world and node function network properties in patients with insomnia following radiotherapy for cervical cancer based on graph theory analysis and explore the correlation between functional networks and the clinical efficacy of individual-target transcranial magnetic stimulation (IT-TMS) for treatment of insomnia. The resting state functional magnetic resonance imaging (rs-fMRI) data were collected from 30 patients with insomnia following radiotherapy for cervical cancer and 30 matched healthy individuals. All the patients received accelerated intelligent neuromodulation TMS therapy. Using graph theory analysis and GRETNA software, the functional connectivity matrices were constructed and the attribute features were extracted. The scores on the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), Self-Rating Anxiety Scale (SAS), and Self-Rating Depression Scale (SDS) of the participants were collected before and after IT-TMS, and the correlation between improvement in insomnia and the functional network was investigated. The two groups matched for age, gender, and education level (P>0.05) showed significant differences in PSQI, ISI, SAS and SDS scores (P<0.05). Both groups showed attributes of the small-world network. Compared with the healthy individuals, the patients showed significantly decreased σ, EI, Cp and Lp (P<0.05) and increased Eg (P<0.05) at baseline, which, along with insomnia symptoms, were all improved after IT-TMS treatment. The patients showed reduced functional connections of the node network at follow-up compared with the baseline, and the low functional connectivity between the right insula and left superior frontal gyrus was correlated with the improvement of ISI scores. The patients with insomnia following radiotherapy for cervical cancer have impaired information integration ability of the brain network, IT-TMS can significantly improve insomnia symptoms by reducing the hyperconnectivity between the default mode network and the salience network.

Resting-state electroencephalographic characteristics related to mild cognitive impairments.

Alzheimer's disease (AD) causes a rapid deterioration in cognitive and physical functions, including problem-solving, memory, language, and daily activities. Mild cognitive impairment (MCI) is considered a risk factor for AD, and early diagnosis and treatment of MCI may help slow the progression of AD. Electroencephalography (EEG) analysis has become an increasingly popular tool for developing biomarkers for MCI and AD diagnosis. Compared with healthy elderly, patients with AD showed very clear differences in EEG patterns, but it is inconclusive for MCI. This study aimed to investigate the resting-state EEG features of individuals with MCI (n = 12) and cognitively healthy controls (HC) (n = 13) with their eyes closed. EEG data were analyzed using spectral power, complexity, functional connectivity, and graph analysis. The results revealed no significant difference in EEG spectral power between the HC and MCI groups. However, we observed significant changes in brain complexity and networks in individuals with MCI compared with HC. Patients with MCI exhibited lower complexity in the middle temporal lobe, lower global efficiency in theta and alpha bands, higher local efficiency in the beta band, lower nodal efficiency in the frontal theta band, and less small-world network topology compared to the HC group. These observed differences may be related to underlying neuropathological alterations associated with MCI progression. The findings highlight the potential of network analysis as a promising tool for the diagnosis of MCI.

Noninvasive Brain Imaging and Stimulation in Post-Stroke Motor Rehabilitation: A Review

This paper provides a comprehensive review of current state of non-invasive brain imaging and brain stimulation in motor rehabilitation after stroke. The functional organization of the brain is determined by brain network connections. Brain imaging enables us to map the network organization of the brain, so as to assess the motor function in stroke state. The non-invasive functional imaging techniques include Electroencephalography (EEG) and magnetoencephalography (MEG) with better temporal resolution, and functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) with better spatial resolution. Based on single-mode or multi-mode imaging methods, the changes of brain networks caused by stroke and during motor recovery progress can be observed. Brain stimulation is an effective way to reorganize brain networks. Transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) are the most widely studied non-invasive neuromodulation techniques. Combined with imaging, brain stimulation can alter brain networks in controlled ways and making neuromodulation a closed loop. This review also outlines the methods of facilitate motor rehabilitation: 1) multi-mode imaging for motor assessment; 2) brain stimulation combined with rehabilitation training; 3) close-loop motor rehabilitation; 4) influencing factors motor rehabilitation.

Functional disruptions of the brain network in low back pain: a graph-theoretical study.

The aim of this study was to investigate alterations in the topological organization of whole-brain functional networks in patients with chronic low back pain (CLBP) and characterize the relationship of these alterations with pain characteristics. Thirty-three CLBP patients and 34 matched healthy controls (HCs) underwent fMRI scans. A graph-theoretical approach was applied to identify brain network changes in patients suffering from chronic low back pain given its nonspecific etiology and complexity. Graph theory-based analysis was used to construct functional connectivity matrices and extract the features of small-world networks of the brain in both groups. Then, the whole-brain functional connectivity differences were characterized by network-based statistics (NBS) analysis, and the relationship between the altered brain features and clinical measures was explored. At the global level, patients with CLBP showed significantly decreased gamma, sigma, global efficiency, and local efficiency and increased lambda and shortest path length compared with HCs. At the regional level, there were deficits in nodal efficiency within the default mode network and salience network. NBS analysis demonstrated that decreased functional connectivity was present in the CLBP patients, mainly in the frontolimbic circuit and temporal regions. Furthermore, aspects of topological dysfunctions in CLBP were correlated with pain severity. This study highlighted the aberrant topological organization of functional brain networks in CLBP, which may shed light on the pathophysiology of CLBP and support the development of pain management approaches.

Resting-state functional connectivity changes in older adults with sleep disturbance and the role of amyloid burden.

Sleep and related disorders could lead to changes in various brain networks, but little is known about the role of amyloid β (Aβ) burden-a key Alzheimer's disease (AD) biomarker-in the relationship between sleep disturbance and altered resting state functional connectivity (rsFC) in older adults. This cross-sectional study examined the association between sleep disturbance, Aβ burden, and rsFC using a large-scale dataset from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sample included 489 individuals (53.6% cognitively normal, 32.5% mild cognitive impairment, and 13.9% AD) who had completed sleep measures (Neuropsychiatric Inventory), PET Aβ data, and resting-state fMRI scans at baseline. Within and between rsFC of the Salience (SN), the Default Mode (DMN) and the Frontal Parietal network (FPN) were compared between participants with sleep disturbance versus without sleep disturbance. The interaction between Aβ positivity and sleep disturbance was evaluated using the linear regressions, controlling for age, diagnosis status, gender, sedatives and hypnotics use, and hypertension. Although no significant main effect of sleep disturbance was found on rsFC, a significant interaction term emerged between sleep disturbance and Aβ burden on rsFC of SN (β = 0.11, P = 0.006). Specifically, sleep disturbance was associated with SN hyperconnectivity, only with the presence of Aβ burden. Sleep disturbance may lead to altered connectivity in the SN when Aβ is accumulated in the brain. Individuals with AD pathology may be at increased risk for sleep-related aberrant rsFC; therefore, identifying and treating sleep problems in these individuals may help prevent further disease progression.

Single-subject cortical morphological brain networks across the adult lifespan.

Age-related changes in focal cortical morphology have been well documented in previous literature; however, how interregional coordination patterns of the focal cortical morphology reorganize with advancing age is not well established. In this study, we performed a comprehensive analysis of the topological changes in single-subject morphological brain networks across the adult lifespan. Specifically, we constructed four types of single-subject morphological brain networks for 650 participants (aged from 18 to 88 years old), and characterized their topological organization using graph-based network measures. Age-related changes in the network measures were examined via linear, quadratic, and cubic models. We found profound age-related changes in global small-world attributes and efficiency, local nodal centralities, and interregional similarities of the single-subject morphological brain networks. The age-related changes were mainly embodied in cortical thickness networks, involved in frontal regions and highly connected hubs, concentrated on short-range connections, characterized by linear changes, and susceptible to connections between limbic, frontoparietal, and ventral attention networks. Intriguingly, nonlinear (i.e., quadratic or cubic) age-related changes were frequently found in the insula and limbic regions, and age-related cubic changes preferred long-range morphological connections. Finally, we demonstrated that the morphological similarity in cortical thickness between two frontal regions mediated the relationship between age and cognition measured by Cattell scores. Taken together, these findings deepen our understanding of adaptive changes of the human brain with advancing age, which may account for interindividual variations in behaviors and cognition.

Altered structural connectivity in olfactory disfunction after mild COVID-19 using probabilistic tractography

We aimed to investigate changes in olfactory bulb volume and brain network in the white matter (WM) in patients with persistent olfactory disfunction (OD) following COVID-19. A cross-sectional study evaluated 38 participants with OD after mild COVID-19 and 24 controls, including Sniffin' Sticks identification test (SS-16), MoCA, and brain magnetic resonance imaging. Network-Based Statistics (NBS) and graph theoretical analysis were used to explore the WM. The COVID-19 group had reduced olfactory bulb volume compared to controls. In NBS, COVID-19 patients showed increased structural connectivity in a subnetwork comprising parietal brain regions. Regarding global network topological properties, patients exhibited lower global and local efficiency and higher assortativity than controls. Concerning local network topological properties, patients had reduced local efficiency (left lateral orbital gyrus and pallidum), increased clustering (left lateral orbital gyrus), increased nodal strength (right anterior orbital gyrus), and reduced nodal strength (left amygdala). SS-16 test score was negatively correlated with clustering of whole-brain WM in the COVID-19 group. Thus, patients with OD after COVID-19 had relevant WM network dysfunction with increased connectivity in the parietal sensory cortex. Reduced integration and increased segregation are observed within olfactory-related brain areas might be due to compensatory plasticity mechanisms devoted to recovering olfactory function.

The effect of erenumab on brain network function in episodic migraine patients: a randomized, placebo-controlled clinical trial (RESET BRAIN)

BackgroundWe aimed to explore whether erenumab, a monoclonal antibody targeting the calcitonin gene-related peptide receptor, could exert a central effect on brain network function in migraine, and investigate the persistence of such an effect following treatment discontinuation.MethodsThis was a randomized, double-blind, placebo-controlled, multicenter trial with a crossover design performed in adult episodic migraine patients with previous treatment failure. Patients were randomized (1:1) to 12 weeks of erenumab 140 mg or placebo, followed by a 12-week crossover. Resting state (RS) functional connectivity (FC) changes of brain networks involved in migraine were investigated using a seed-based correlation approach.ResultsSixty-one patients were randomized to treatment. In each treatment sequence, 27 patients completed the visit at week 12. Forty-four enrolled patients, 22 in each treatment sequence, completed the study procedures with no major protocol violations. We observed a carry-over effect of erenumab during the placebo treatment and therefore data analysis was performed as a parallel comparison of erenumab vs placebo of the first 12 weeks of treatment. From baseline to week 12, compared to placebo, patients receiving erenumab showed RS FC changes within the cerebellar, thalamic and periaqueductal gray matter networks, significantly associated with clinical improvement. Compared to non-responders, patients achieving a 50% reduction in migraine days had distinct patterns of thalamic and visual network RS FC. Brain RS FC changes reversed when erenumab was stopped. A lower baseline RS FC of the pontine network identified patients responding to erenumab.ConclusionErenumab modulates RS FC of networks involved in migraine pathophysiology. In line with clinical response, erenumab-induced brain RS FC changes tend to reverse when treatment is stopped.

Inflammation affects dynamic functional network connectivity pattern changes via plasma NFL in cognitive impairment patients.

Plasma neurofilament light chain (NFL) is a biomarker of inflammation and neurodegenerative diseases such as Alzheimer's disease (AD). However, the underlying neural mechanisms by which NFL affects cognitive function remain unclear. In this study, we investigated the effects of inflammation on cognitive integrity in patients with cognitive impairment through the functional interaction of plasma NFL with large-scale brain networks. This study included 29 cognitively normal, 55 LowNFL patients, and 55 HighNFL patients. Group independent component analysis (ICA) was applied to the resting-state fMRI data, and 40 independent components (IC) were extracted for the whole brain. Next, the dynamic functional network connectivity (dFNC) of each subject was estimated using the sliding-window method and k-means clustering, and five dynamic functional states were identified. Finally, we applied mediation analysis to investigate the relationship between plasma NFL and dFNC indicators and cognitive scales. The present study explored the dynamics of whole-brain FNC in controls and LowNFL and HighNFL patients and highlighted the temporal properties of dFNC states in relation to psychological scales. A potential mechanism for the association between dFNC indicators and NFL levels in cognitively impaired patients. Our findings suggested the decreased ability of information processing and communication in the HighNFL group, which helps us to understand their abnormal cognitive functions clinically. Characteristic changes in the inflammation-coupled dynamic brain network may provide alternative biomarkers for the assessment of disease severity in cognitive impairment patients.

Preliminary evidence for changes in frontoparietal network connectivity in the early abstinence period in alcohol use disorder: a longitudinal resting-state functional magnetic resonance imaging study.

The early abstinence period is a crucial phase in alcohol use disorder (AUD) in which patients have to find a new equilibrium and may start recovery, or conversely, relapse. However, the changes in brain functions during this key period are still largely unknown. We set out to study longitudinal changes in large-scale brain networks during the early abstinence period using resting-state scans. We scanned AUD patients twice in a well-controlled inpatient setting, with the first scan taking place shortly after admission and the second scan 4 weeks (±9 days) later near the end of the treatment period. We studied 37 AUD patients (22 males) and 27 healthy controls (16 males). We focused on three networks that are affected in AUD and underly core symptom dimensions in this disorder: the frontoparietal networks (left and right FPN) and default mode network (DMN). Both the whole brain and within network connectivity of these networks were studied using dual regression. Finally, we explored correlations between these brain networks and various neuropsychological and behavioral measures. In contrast to the controls (Z = -1.081, p = 0.280), the AUD patients showed a decrease in within left FPN connectivity (Z = -2.029, p = 0.042). However, these results did not survive a strict Bonferroni correction. The decrease in left FPN connectivity during the early abstinence period in AUD may reflect an initially upregulated FPN, which recovers to a lower resting-state connectivity level during subsequent weeks of abstinence. The AUD patients showed a trend for a positive association between the change in left FPN connectivity and trait anxiety (rs = 0.303, p = 0.068), and a trend for a negative association between the change in left FPN connectivity and delay discounting (rs = -0.283, p = 0.089) (uncorrected for multiple comparisons). This suggests that the FPN might be involved in top-down control of impulsivity and anxiety, which are important risk factors for relapse. Although there were no statistically significant results (after multiple comparison correction), our preliminary findings encourage further research into the dynamic neuroadaptations during the clinically crucial early abstinence period and could inform future study designs.

Changes of Functional Brain Network in Neonates with Different Degrees of Hypoxic-Ischemic Encephalopathy.

Background: Neonatal hypoxic-ischemic encephalopathy (HIE) is the main cause of neonatal death and disability worldwide. At present, there are few researches on the application of resting-state functional magnetic resonance imaging (rs-fMRI) to explore the brain development of HIE children. This study aimed to explore the changes of brain function in neonates with different degrees of HIE using rs-fMRI. Methods: From February 2018 to May 2020, 44 patients with HIE were recruited, including 21 mild patients and 23 moderate and severe patients. The recruited patients were scanned by conventional and functional magnetic resonance image, and the method of amplitude of low-frequency fluctuation and connecting edge analysis of brain network was used. Results: Compared with the mild group, the connections between the right supplementary motor area and the right precentral gyrus, the right lingual gyrus and the right hippocampus, the left calcarine cortex and the right amygdala, and the right pallidus and the right posterior cingulate cortex in the moderate and severe groups were reduced (t values were 4.04, 4.04, 4.04, 4.07, all p < 0.001, uncorrected). Conclusion: By analyzing the functional connection changes of brain network in infants with different degrees of HIE, the findings of the current study suggested that neonates with moderate to severe HIE lag behind those with mild HIE in emotional processing, sensory movement, cognitive function, and learning and memory. Chinese Clinical Trial Registry registration number: ChiCTR1800016409.

Age differences in the neural processing of semantics, within and beyond the core semantic network

Aging is associated with functional activation changes in domain-specific regions and large-scale brain networks. This preregistered Functional magnetic resonance imaging (fMRI) study investigated these effects within the domain of semantic cognition. Participants completed 1 nonsemantic and 2 semantic tasks. We found no age differences in semantic activation in core semantic regions. However, the right inferior frontal gyrus showed difficulty-related increases in both age groups. This suggests that age-related upregulation of this area may be a compensatory response to increased processing demands. At a network level, older people showed more engagement in the default mode network and less in the executive multiple-demand network, aligning with older people’s greater knowledge reserves and executive declines. In contrast, activation was age-invariant in semantic control regions. Finally, older adults showed reduced demand-related modulation of multiple-demand network activation in the nonsemantic task but not the semantic tasks. These findings provide a new perspective on the neural basis of semantic cognition in aging, suggesting that preserved function in specialized semantic networks may help to maintain semantic cognition in later life.

Correlation between Functional Magnetic Resonance and Symptomatologic Examination in Adult Patients with Myofascial Pain Syndrome of the Masticatory Muscles

Myofascial pain syndrome is the most common cause of TMD, characterised by trigger points of skeletal muscles in the masticatory region. Patients with myofascial pain suffer from orofacial pain and headaches. Parafunctional activity such as unconscious teeth clenching predisposes a higher possibility of developing myofascial pain. We report the results of a prospective study of 10 patients with a myofascial pain diagnosis related to TMD who underwent treatment with passive aligners and biofeedback exercise. All patients underwent pain assessment (visual analogic scale and muscular palpation test), measurement of masseters thickness with Dolphin Imaging Software, nuclear magnetic resonance of the temporomandibular joint, and functional nuclear magnetic resonance of the brain before and after gnathological treatment. The same patients underwent pain assessment (VAS and palpation test) for the entire duration of their treatment. This study aimed to assess if the results obtained with the therapy were repeatable using functional magnetic resonance imaging. This enabled us to correlate a subjective datum (pain) to an objective one (variation in the functional connectivity of the networks correlated to pain perception). According to the pain assessment, the treatment considerably reduced the pain in 9 out of 10 patients. Furthermore, the functional nuclear magnetic resonance of the brain showed similar modifications in the cerebral pain and default mode networks in these nine patients. The change in the masseter muscle dimensions was not correlated with the modification of pain. Statistical analysis was performed to evaluate the effects of treatment on VAS and trigger point stimulation and on the length and width of the masseter muscle. Linear regression analysis was used to assess a correlation between the modification of the masseter muscle dimension and the amendment of VAS. A paired t-test was used to evaluate statistically significant differences in the connectivity of brain areas of the DMN and the pain network. Our results suggest that the proper treatment of myofascial pain can reduce pain and consistently modify the functional activation of the cerebral pain and default mode networks. Overall, the treatment was repeatable because brain network changes were homogeneous in all patients and did not relate to the intracapsular TMJ condition but only to pain symptoms.

EEG functional connectivity after perinatal stroke.

Impaired cognitive functioning after perinatal stroke has been associated with long-term functional brain network changes. We explored brain functional connectivity using a 64-channel resting-state electroencephalogram in 12 participants, aged 5-14 years with a history of unilateral perinatal arterial ischemic or haemorrhagic stroke. A control group of 16 neurologically healthy subjects was also included-each test subject was compared with multiple control subjects, matched by sex and age. Functional connectomes from the alpha frequency band were calculated for each subject and the differences in network graph metrics between the 2 groups were analyzed. Our results suggest that the functional brain networks of children with perinatal stroke show evidence of disruption even years after the insult and that the scale of changes appears to be influenced by the lesion volume. The networks remain more segregated and show a higher synchronization at both whole-brain and intrahemispheric level. Total interhemispheric strength was higher in children with perinatal stroke compared with healthy controls.

Cognitive, behavioral, and brain functional connectivity correlates of fatigue in amyotrophic lateral sclerosis.

Fatigue is defined as a symptom of exhaustion unexplained by drug effects or psychiatric disorders and comprises two main components (i.e., central or "mental" and peripheral or "physical" components), both influencing global disability in amyotrophic lateral sclerosis (ALS). We aim at investigating the clinical correlations between "physical" and "mental" components of fatigue, measured by the Multidimensional Fatigue Inventory scale, and motor and cognitive/behavioral disability in a large sample of patients with ALS. We also investigated the correlations between these measures of fatigue and resting-state functional connectivity of brain functional magnetic resonance imaging (RS-fMRI) large-scale networks in a subset of patients. One hundred and thirty ALS patients were assessed for motor disability, cognitive and behavioral dysfunctions, fatigue, anxiety, apathy, and daytime sleepiness. Moreover, the collected clinical parameters were correlated with RS-fMRI functional connectivity changes in the large-scale brain networks of 30 ALS patients who underwent MRI. Multivariate correlation analysis revealed that "physical" fatigue was related to anxiety and respiratory dysfunction, while "mental" fatigue was related to memory impairment and apathy. Moreover, the mental fatigue score was directly related to functional connectivity in the right and left insula (within the salience network), and inversely related to functional connectivity in the left middle temporal gyrus (within the default mode network). Although the "physical" component of fatigue may be influenced by the disease itself, in ALS the "mental" component of fatigue correlates with cognitive and behavioral impairment, as well as with alterations of functional connectivity in extra-motor networks.