Resting functional connectivity in patients with brain tumors in eloquent areas

Global MEG Resting State Functional Connectivity in Children with Autism and Sensory Processing Dysfunction

Sensory processing dysfunction not only affects most individuals with autism spectrum disorder (ASD), but at least 5% of children without ASD also experience dysfunctional sensory processing. Our understanding of the relationship between sensory dysfunction and resting state brain activity is still emerging. This study compared long-range resting state functional connectivity of neural oscillatory behavior in children aged 8-12 years with autism spectrum disorder (ASD; N=18), those with sensory processing dysfunction (SPD; N=18) who do not meet ASD criteria, and typically developing control participants (TDC; N=24) using magnetoencephalography (MEG). Functional connectivity analyses were performed in the alpha and beta frequency bands, which are known to be implicated in sensory information processing. Group differences in functional connectivity and associations between sensory abilities and functional connectivity were examined. Distinct patterns of functional connectivity differences between ASD and SPD groups were found only in the beta band, but not in the alpha band. In both alpha and beta bands, ASD and SPD cohorts differed from the TDC cohort. Somatosensory cortical beta-band functional connectivity was associated with tactile processing abilities, while higher-order auditory cortical alpha-band functional connectivity was associated with auditory processing abilities. These findings demonstrate distinct long-range neural synchrony alterations in SPD and ASD that are associated with sensory processing abilities. Neural synchrony measures could serve as potential sensitive biomarkers for ASD and SPD.

Preoperative assessment of eloquence in neurosurgery: a systematic review

BACKGROUND AND OBJECTIVES

Tumor location and eloquence are two crucial preoperative factors when deciding on the optimal treatment choice in glioma management. Consensus is currently lacking regarding the preoperative assessment and definition of eloquent areas. This systematic review aims to evaluate the existing definitions and assessment methods of eloquent areas that are used in current clinical practice.

METHODS

A computer-aided search of Embase, Medline (OvidSP), and Google Scholar was performed to identify relevant studies. This review includes articles describing preoperative definitions of eloquence in the study's Methods section. These definitions were compared and categorized by anatomical structure. Additionally, various techniques to preoperatively assess tumor eloquence were extracted, along with their benefits, drawbacks and ease of use.

RESULTS

This review covers 98 articles including 12,714 participants. Evaluation of these studies indicated considerable variability in defining eloquence. Categorization of these definitions yielded a list of 32 brain regions that were considered eloquent. The most commonly used methods to preoperatively determine tumor eloquence were anatomical classification systems and structural MRI, followed by DTI-FT, functional MRI and nTMS.

CONCLUSIONS

There were major differences in the definitions and assessment methods of eloquence, and none of them proved to be satisfactory to express eloquence as an objective, quantifiable, preoperative factor to use in glioma decision making. Therefore, we propose the development of a novel, objective, reliable, preoperative classification system to assess eloquence. This should in the future aid neurosurgeons in their preoperative decision making to facilitate personalized treatment paradigms and to improve surgical outcomes.

Multiscale network neuroscience in neuro-oncology: How tumors, brain networks, and behavior connect across scales

Network neuroscience refers to the investigation of brain networks across different spatial and temporal scales, and has become a leading framework to understand the biology and functioning of the brain. In neuro-oncology, the study of brain networks has revealed many insights into the structure and function of cells, circuits, and the entire brain, and their association with both functional status (e.g., cognition) and survival. This review connects network findings from different scales of investigation, with the combined aim of informing neuro-oncological healthcare professionals on this exciting new field and also delineating the promising avenues for future translational and clinical research that may allow for application of network methods in neuro-oncological care.

Large-scale brain networks and intra-axial tumor surgery: a narrative review of functional mapping techniques, critical needs, and scientific opportunities

In recent years, a paradigm shift in neuroscience has been occurring from "localizationism," or the idea that the brain is organized into separately functioning modules, toward "connectomics," or the idea that interconnected nodes form networks as the underlying substrates of behavior and thought. Accordingly, our understanding of mechanisms of neurological function, dysfunction, and recovery has evolved to include connections, disconnections, and reconnections. Brain tumors provide a unique opportunity to probe large-scale neural networks with focal and sometimes reversible lesions, allowing neuroscientists the unique opportunity to directly test newly formed hypotheses about underlying brain structural-functional relationships and network properties. Moreover, if a more complete model of neurological dysfunction is to be defined as a "disconnectome," potential avenues for recovery might be mapped through a "reconnectome." Such insight may open the door to novel therapeutic approaches where previous attempts have failed. In this review, we briefly delve into the most clinically relevant neural networks and brain mapping techniques, and we examine how they are being applied to modern neurosurgical brain tumor practices. We then explore how brain tumors might teach us more about mechanisms of global brain dysfunction and recovery through pre- and postoperative longitudinal connectomic and behavioral analyses.

Comparison of direct cortical stimulation and transcranial magnetic stimulation in brain tumor surgery: systematic review and meta analyses

INTRODUCTION

Brain malignancy and, at the same time central nervous system malignancy are two of the most difficult problems in the oncology field of practice. Brain tumors located near or within eloquent areas may represent another challenge toward neurosurgeon treatment. As such, electrical stimulation, either directly or through other methods, may prove necessary as proper mapping of the eloquent area thus may create a proper resection guide. Minimal resection will hopefully preserve patient neurological function and ensure patient quality of life.

METHODS

This research is a systematic review and meta-analysis that aim to compare outcomes, primarily adverse event analysis, between direct cortical stimulation and transcortical magnetic stimulation.

RESULTS

Fourteen studies were identified between 2010 and the 2023 interval. While this number is sufficient, most studies were not randomized and were not accompanied by blinding. Meta-analysis was then applied as a hypothesis test, which showed that TMS were not inferior compared to DCS in terms of motoric and lingual outcome which were marked subjectively by diamond location and objectively through a p-value above 0.05.

CONCLUSION

TMS is a noninvasive imaging method for the evaluation of eloquent brain areas that is not inferior compared to the invasive gold-standard imaging method (DCS). However its role as adjuvant to DCS and alternative only when awake surgery is not available must be emphasized.

Screening of Brain Tumors Using Functional Connectivity Patterns of Steady-State Visually Evoked Potentials

Abstract Objective: The irregular growth and proliferation of cells in the brain and skull is named brain tumor, which is a special serious type of tumor due to its location. Nowadays, brain tumor is diagnosed by using imaging techniques such as computed tomography, positron emission tomography, single photon emission computed tomography, infrared imaging, magnetic resonance imaging (MRI), and functional MRI. However, these methods are not affordable to be used as screening tests. In contrast, electroencephalography has the ability of measuring biological signals, and it is a cost-effective and non-dangerous tool, being feasible to be used for screening purposes. The aim of this research was to evaluate the possibility of brain tumor detection, using functional connectivity features extracted from steady-state visually evoked potentials of eight brain tumor patients and four healthy control participants. Methods: For this purpose, after preprocessing, phase lag index was calculated as a functional connectivity measure. Afterward, four of the channels were chosen as the selected nodes, based on the highest number of strong connectivity (top 5%) as well as the most significant ones. The selected nodes were O1, O2, P3, and P4. As a final step, node strength was calculated for these selected nodes, which was used to classify the samples in the two groups, using Naïve Bayes, discriminant analysis (DA), k-nearest neighbors, support vector machines, and logistic regression methods. Results: The highest accuracy of 89.6% was obtained by using a DA classifier. This result shows that, in fact, brain tumor has the ability of changing brain functional connectivity. Conclusion: As the physiological alterations may occur sooner than the anatomical ones in tumor onset, detection of these alterations may be a useful measure for early diagnosis of this disease. This is still a primary study, but with the possibility of leading to further research, which can lead to the development of a method for the screening and early detection of brain tumor. Impact statement Imaging modalities are often used to diagnose brain tumors. However, these approaches are cost prohibitive for screening tests. Electroencephalography, a method that measures biological signals from the brain, on the other hand, is cost-effective, non-dangerous, and non-invasive, making it an ideal screening tool. The goal of this study is to analyze whether functional connectivity patterns taken from Steady-State Visually Evoked Potentials may be used to detect brain tumors at early stages. Since physiological changes occur before anatomical ones in tumor development, monitoring these alterations could be a useful tool to screen high-risk individuals, and also to an early diagnosis of the disease.

Naming impairments evoked by focal cortical electrical stimulation in the ventral temporal cortex correlate with increased functional connectivity

BACKGROUND

High-frequency cortical electrical stimulations (HF-CES) are the gold standard for presurgical functional mapping. In the dominant ventral temporal cortex (VTC) HF-CES can elicit transient naming impairment (eloquent sites), defining a basal temporal language area (BTLA).

OBJECTIVE

Whether naming impairments induced by HF-CES within the VTC are related to a specific pattern of connectivity of the BTLA within the temporal lobe remains unknown. We addressed this issue by comparing the connectivity of eloquent and non-eloquent sites from the VTC using cortico-cortical evoked potentials (CCEP).

METHODS

Low frequency cortical electrical stimulations (LF-CES) were used to evoke CCEP in nine individual brains explored with Stereo-Electroencephalography. We compared the connectivity of eloquent versus non eloquent sites within the VTC using Pearson's correlation matrix.

RESULTS

Overall, within the VTC, eloquent sites were associated with increased functional connectivity compared to non-eloquent sites. Among the VTC structures, this pattern holds true for the inferior temporal gyrus and the parahippocampal gyrus while the fusiform gyrus specifically showed a high connectivity in both non eloquent and eloquent sites.

CONCLUSIONS

Our findings suggest that the cognitive effects of focal HF-CES are related to the functional connectivity properties of the stimulated sites, and therefore to the disturbance of a wide cortical network. They further suggest that functional specialization of a cortical region emerges from its specific pattern of functional connectivity. Cortical electrical stimulation functional mapping protocols including LF coupled to HF-CES could provide valuable data characterizing both local and distant functional architecture.

Tumor Connectomics: Mapping the Intra-Tumoral Complex Interaction Network Using Machine Learning

The high-level relationships that form complex networks within tumors and between surrounding tissue is challenging and not fully understood. To better understand these tumoral networks, we developed a tumor connectomics framework (TCF) based on graph theory with machine learning to model the complex interactions within and around the tumor microenvironment that are detectable on imaging. The TCF characterization model was tested with independent datasets of breast, brain, and prostate lesions with corresponding validation datasets in breast and brain cancer. The TCF network connections were modeled using graph metrics of centrality, average path length (APL), and clustering from multiparametric MRI with IsoSVM. The Matthews Correlation Coefficient (MCC), Area Under the Curve-ROC, and Precision-Recall (AUC-ROC and AUC-PR) were used for statistical analysis. The TCF classified the breast and brain tumor cohorts with an IsoSVM AUC-PR and MCC of 0.86, 0.63 and 0.85, 0.65, respectively. The TCF benign breast lesions had a significantly higher clustering coefficient and degree centrality than malignant TCFs. Grade 2 brain tumors demonstrated higher connectivity compared to Grade 4 tumors with increased degree centrality and clustering coefficients. Gleason 7 prostate lesions had increased betweenness centrality and APL compared to Gleason 6 lesions with AUC-PR and MCC ranging from 0.90 to 0.99 and 0.73 to 0.87, respectively. These TCF findings were similar in the validation breast and brain datasets. In conclusion, we present a new method for tumor characterization and visualization that results in a better understanding of the global and regional connections within the lesion and surrounding tissue.

Advanced Imaging Techniques for Newly Diagnosed and Recurrent Gliomas

Management of gliomas following initial diagnosis requires thoughtful presurgical planning followed by regular imaging to monitor treatment response and survey for new tumor growth. Traditional MR imaging modalities such as T1 post-contrast and T2-weighted sequences have long been a staple of tumor diagnosis, surgical planning, and post-treatment surveillance. While these sequences remain integral in the management of gliomas, advances in imaging techniques have allowed for a more detailed characterization of tumor characteristics. Advanced MR sequences such as perfusion, diffusion, and susceptibility weighted imaging, as well as PET scans have emerged as valuable tools to inform clinical decision making and provide a non-invasive way to help distinguish between tumor recurrence and pseudoprogression. Furthermore, these advances in imaging have extended to the operating room and assist in making surgical resections safer. Nevertheless, surgery, chemotherapy, and radiation treatment continue to make the interpretation of MR changes difficult for glioma patients. As analytics and machine learning techniques improve, radiomics offers the potential to be more quantitative and personalized in the interpretation of imaging data for gliomas. In this review, we describe the role of these newer imaging modalities during the different stages of management for patients with gliomas, focusing on the pre-operative, post-operative, and surveillance periods. Finally, we discuss radiomics as a means of promoting personalized patient care in the future.

Resting-state functional MRI language network connectivity differences in patients with brain tumors: exploration of the cerebellum and contralesional hemisphere

Brain tumors can have far-reaching impacts on functional networks. Language processing is typically lateralized to the left hemisphere, but also involves the right hemisphere and cerebellum. This resting-state functional MRI study investigated the proximal and distal effects of left-hemispheric brain tumors on language network connectivity in the ipsilesional and contralesional hemispheres. Separate language resting-state networks were generated from seeding in ipsilesional (left) and contralesional (right) Broca's Area for 29 patients with left-hemispheric brain tumors and 13 controls. Inclusion criteria for all subjects included language left-dominance based on task-based functional MRI. Functional connectivity was analyzed in each network to the respective Wernicke's Area and contralateral cerebellum. Patients were assessed for language deficits prior to scanning. Compared to controls, patients exhibited decreased connectivity in the ipsilesional and contralesional hemispheres between the Broca's Area and Wernicke's Area homologs (mean connectivity for patients/controls: left 0.51/0.59, p < 0.002; right 0.52/0.59, p < 0.0002). No differences in mean connectivity to the contralateral cerebellum were observed between groups (p > 0.09). Crossed cerebro-cerebellar connectivity was correlated in controls (rho = 0.59, p < 0.05), patients without language deficits (rho = 0.74, p < 0.0002), and patients with high-grade gliomas (rho = 0.78, p < 0.0002), but not in patients with language deficits or low-grade gliomas (p > 0.l). These findings demonstrate that brain tumors impact the language network in the contralesional hemisphere and cerebellum, which may reflect neurological deficits and lesion-induced cortical reorganization.

Clinical applications of magnetic resonance imaging based functional and structural connectivity

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.

Automated eloquent cortex localization in brain tumor patients using multi-task graph neural networks

Localizing the eloquent cortex is a crucial part of presurgical planning. While invasive mapping is the gold standard, there is increasing interest in using noninvasive fMRI to shorten and improve the process. However, many surgical patients cannot adequately perform task-based fMRI protocols. Resting-state fMRI has emerged as an alternative modality, but automated eloquent cortex localization remains an open challenge. In this paper, we develop a novel deep learning architecture to simultaneously identify language and primary motor cortex from rs-fMRI connectivity. Our approach uses the representational power of convolutional neural networks alongside the generalization power of multi-task learning to find a shared representation between the eloquent subnetworks. We validate our method on data from the publicly available Human Connectome Project and on a brain tumor dataset acquired at the Johns Hopkins Hospital. We compare our method against feature-based machine learning approaches and a fully-connected deep learning model that does not account for the shared network organization of the data. Our model achieves significantly better performance than competing baselines. We also assess the generalizability and robustness of our method. Our results clearly demonstrate the advantages of our graph convolution architecture combined with multi-task learning and highlight the promise of using rs-fMRI as a presurgical mapping tool.

fMRI Retinotopic Mapping in Patients with Brain Tumors and Space-Occupying Brain Lesions in the Area of the Occipital Lobe

Simple Summary

Functional magnetic resonance imaging (fMRI) in patients with brain tumors enables the visualization of eloquent cortical areas and can be used for planning surgical interventions and assessing the risk of postoperative functional deficits. While preoperative fMRI paradigms used to determine the localization of speech-critical or motor areas dominate the literature, there are hardly any studies that investigate the retinotopic organization of the visual field in patients with occipital lesions or tumors. The aim of this study was to evaluate the effect of a brain tumor or space-occupying brain lesions on the retinotopic organization of the occipital cortex, the activation of and the functional connectivity between cortical areas involved in visual processing. We found a high degree of similarity in the activation profiles of patients and healthy controls, indicating that the retinotopic organization of the visual cortex can reliably be described by fMRI retinotopic mapping as part of the preoperative examination of patients with tumors and space-occupying brain lesions.

Abstract

Functional magnetic resonance imaging (fMRI) is a valuable tool in the clinical routine of neurosurgery when planning surgical interventions and assessing the risk of postoperative functional deficits. Here, we examined how the presence of a brain tumor or lesion in the area of the occipital lobe affects the results of fMRI retinotopic mapping. fMRI data were evaluated on a retrospectively selected sample of 12 patients with occipital brain tumors, 7 patients with brain lesions and 19 control subjects. Analyses of the cortical activation, percent signal change, cluster size of the activated voxels and functional connectivity were carried out using Statistical Parametric Mapping (SPM12) and the CONN and Marsbar toolboxes. We found similar but reduced patterns of cortical activation and functional connectivity between the two patient groups compared to a healthy control group. Here, we found that retinotopic organization was well-preserved in the patients and was comparable to that of the age-matched controls. The results also showed that, compared to the tumor patients, the lesion patients showed higher percent signal changes but lower values in the cluster sizes of the activated voxels in the calcarine fissure region. Our results suggest that the lesion patients exhibited results that were more similar to those of the control subjects in terms of the BOLD signal, whereas the extent of the activation was comparable to that of the tumor patients.

Predicting the Extent of Resection in Low-Grade Glioma by Using Intratumoral Tractography to Detect Eloquent Fascicles Within the Tumor

BACKGROUND

An early maximal safe surgical resection is the current treatment paradigm for low-grade glioma (LGG). Nevertheless, there are no reliable methods to accurately predict the axonal intratumoral eloquent areas and, consequently, to predict the extent of resection.

OBJECTIVE

To describe the functional predictive value of eloquent white matter tracts within the tumor by using a pre- and postoperative intratumoral diffusion tensor imaging (DTI) tractography protocol in patients with LGG.

METHODS

A preoperative intratumoral DTI-based tractography protocol, using the tumor segmented volume as the only seed region, was used to assess the tracts within the tumor boundaries in 22 consecutive patients with LGG. The reconstructed tracts were correlated with intraoperative electrical stimulation (IES)-based language and motor subcortical mapping findings and the extent of resection was assessed by tumor volumetrics.

RESULTS

Identification of intratumoral language and motor tracts significantly predicted eloquent areas within the tumor during the IES mapping: the positive predictive value for the pyramidal tract, the inferior fronto-occipital fasciculus, the arcuate fasciculus and the inferior longitudinal fasciculus positive was 100%, 100%, 33%, and 80%, respectively, whereas negative predictive value was 100% for all of them. The reconstruction of at least one of these tracts within the tumor was significantly associated with a lower extent of resection (67%) as opposed to the extent of resection in the cases with a negative intratumoral tractography (100%) (P < .0001).

CONCLUSION

Intratumoral DTI-based tractography is a simple and reliable method, useful in assessing glioma resectability based on the analysis of intratumoral eloquent areas associated with motor and language tracts within the tumor.

The utilisation of resting-state fMRI as a pre-operative mapping tool in patients with brain tumours in comparison to task-based fMRI and intraoperative mapping: A systematic review

PURPOSE

Resting-state functional Magnetic Resonance Imaging (rs-fMRI) is suggested to be a viable option for pre-operative mapping for patients with brain tumours. However, it remains an open issue whether the tool is useful in the clinical setting compared to task-based fMRI (T-fMRI) and intraoperative mapping. Thus, a systematic review was conducted to investigate the usefulness of this technique.

METHODS

A systematic literature search of rs-fMRI methods applied as a pre-operative mapping tool was conducted using the PubMed/MEDLINE and Cochrane Library electronic databases following PRISMA guidelines.

RESULTS

Results demonstrated that 50% (six out of twelve) of the studies comparing rs-fMRI and T-fMRI showed good concordance for both language and sensorimotor networks. In comparison to intraoperative mapping, 86% (six out of seven) studies found a good agreement to rs-fMRI. Finally, 87% (twenty out of twenty-three) studies agreed that rs-fMRI is a suitable and useful pre-operative mapping tool.

CONCLUSIONS

rs-fMRI is a promising technique for pre-operative mapping in assessing the functional brain areas. However, the agreement between rs-fMRI with other techniques, including T-fMRI and intraoperative maps, is not yet optimal. Studies to ascertain and improve the sophistication in pre-processing of rs-fMRI imaging data are needed.

A Review of Passive Brain Mapping Techniques in Neurological Surgery

Brain mapping is a quintessential part of neurosurgical practice. Accordingly, much of our understanding of the brain's functional organization, and in particular the motor homunculus, is largely attributable to the clinical investigations of past neurosurgeons. Traditionally mapping was invasive and involved the application of electrical current to the exposed brain to observe focal disruption of function or to elicit overt actions. More recently, a wide variety of techniques have been developed that do not require electrical stimulation and often do not require any explicit participation by the subject. Collectively we refer to these as passive mapping modalities. Here we review the spectrum of passive mapping used by neurosurgeons for mapping and surgical planning that ranges from invasive intracranial recordings to noninvasive imaging as well as regimented task-based protocols to completely task-free paradigms that can be performed intraoperatively while under anesthesia.

Changes in Intranetwork Functional Connectivity of Resting State Networks Between Sessions Under Anesthesia in Neurosurgical Patients

BACKGROUND

In this study, we evaluated the changes in resting-state networks (RSNs) under anesthesia in neurosurgical patients.

METHODS

RSNs were analyzed in 12 patients with pituitary adenoma presented by chiasma compression operated via standard transsphenoidal approach under propofol anesthesia before and after tumor resection. All the patients had suprasellar tumor extension with compression of the optic chiasma. We investigated second-level effects by contrasting dummy-encoded covariates representing the effects of the sessions (first vs. second) on RSNs. We corrected for multiple comparisons using a false discovery rate of 0.05 (2-sided).

RESULTS

Connectivity between the right and left precentral gyri (motor network) decreased significantly from the first to the second session (P = 0.0002), as did the connectivity between the postcentral gyri (P = 0.009). The same was valid for connectivity between the visual cortices (P = 0.0002). The salience network showed a significant decrease in the connectivity of the anterior part of the cingulate gyrus and insular cortex (P = 0.0001). The default mode network showed a decrease in the connectivity between the posterior part of the cingulate gyrus, parietal, and frontal cortices (P = 0.0002). There was no significant correlation between the reduction in connectivity and dose or duration of anesthesia.

CONCLUSIONS

Different RSNs could be identified under anesthesia and used for intraoperative brain mapping and remapping during tumor resection. However, RSNs showed a significant decrease in connectivity with the continuation of anesthesia.

The Fluctuations of Blood Oxygen Level-Dependent Signals as a Method of Brain Tumor Characterization: A Preliminary Report

OBJECTIVE

In this study we present the nature and characteristic of the fluctuation of blood oxygen level-dependent (BOLD) signals measured from brain tumors.

METHODS

Supratentorial astrocytomas, which were neither operated nor previously managed with chemotherapy or radiotherapy, were segmented, and the time series of the BOLD signal fluctuations were extracted. The mean (across patients) power spectra were plotted for the different World Health Organization tumor grades. One-way analysis of variance (ANOVA) was performed to identify significant differences between the power spectra of different tumor grades. Results were considered significant at P < 0.05.

RESULTS

A total of 58 patients were included in the study. This group of patients included 1 patient with grade I glioma; 15 with grade II; 12 with grade III; and 30 with grade IV. The power spectra of the tumor time series were individually inspected, and all tumors exhibited high peaks at the lower frequency signals, but these were more pronounced in high-grade tumors. ANOVA showed a significant difference in power spectra between groups (P = 0.000). Post hoc analysis with Bonferroni correction showed a significant difference between grade II and grade III (P = 0.012) and grade IV (P = 0.000). There was no significant power spectra difference between grade III and IV tumors (P = 1).

CONCLUSIONS

The power spectra of BOLD signals from tumor tissue showed fluctuations in the low-frequency signals and were significantly correlated with tumor grade. These signals could have a misleading effect when analyzing resting state functional magnetic resonance imaging and could be also viewed as a potential method of tumor characterization.

Global resting-state functional connectivity of neural oscillations in tinnitus with and without hearing loss

This study examined global resting-state functional connectivity of neural oscillations in individuals with chronic tinnitus and normal and impaired hearing. We tested the hypothesis that distinct neural oscillatory networks are engaged in tinnitus with and without hearing loss. In both tinnitus groups, with and without hearing loss, we identified multiple frequency band-dependent regions of increased and decreased global functional connectivity. We also found that the auditory domain of tinnitus severity, assayed by the Tinnitus Functional Index, was associated with global functional connectivity in both auditory and nonauditory regions. These findings provide candidate biomarkers to target and monitor treatments for tinnitus with and without hearing loss.

The impact of high functional connectivity network hub resection on language task performance in adult low- and high-grade glioma

OBJECTIVE

Gliomas are intrinsic brain tumors with the hallmark of diffuse white matter infiltration, resulting in short- and long-range network dysfunction. Preoperative magnetoencephalography (MEG) can assist in maximizing the extent of resection while minimizing morbidity. While MEG has been validated in motor mapping, its role in speech mapping remains less well studied. The authors assessed how the resection of intraoperative electrical stimulation (IES)-negative, high functional connectivity (HFC) network sites, as identified by MEG, impacts language performance.

METHODS

Resting-state, whole-brain MEG recordings were obtained from 26 patients who underwent perioperative language evaluation and glioma resection that was guided by awake language and IES mapping. The functional connectivity of an individual voxel was determined by the imaginary coherence between the index voxel and the rest of the brain, referenced to its contralesional pair. The percentage of resected HFC voxels was correlated with postoperative language outcomes in tasks of increasing complexity: text reading, 4-syllable repetition, picture naming, syntax (SYN), and auditory stimulus naming (AN).

RESULTS

Overall, 70% of patients (14/20) in whom any HFC tissue was resected developed an early postoperative language deficit (mean 2.3 days, range 1-8 days), compared to 33% of patients (2/6) in whom no HFC tissue was resected (p = 0.16). When bifurcated by the amount of HFC tissue that was resected, 100% of patients (3/3) with an HFC resection > 25% displayed deficits in AN, compared to 30% of patients (6/20) with an HFC resection < 25% (p = 0.04). Furthermore, there was a linear correlation between the severity of AN and SYN decline with percentage of HFC sites resected (p = 0.02 and p = 0.04, respectively). By 2.2 months postoperatively (range 1-6 months), the correlation between HFC resection and both AN and SYN decline had resolved (p = 0.94 and p = 1.00, respectively) in all patients (9/9) except two who experienced early postoperative tumor progression or stroke involving inferior frontooccipital fasciculus.

CONCLUSIONS

Imaginary coherence measures of functional connectivity using MEG are able to identify HFC network sites within and around low- and high-grade gliomas. Removal of IES-negative HFC sites results in early transient postoperative decline in AN and SYN, which resolved by 3 months in all patients without stroke or early tumor progression. Measures of functional connectivity may therefore be a useful means of counseling patients about postoperative risk and assist with preoperative surgical planning.

Altered Rich-Club Organization and Regional Topology Are Associated With Cognitive Decline in Patients With Frontal and Temporal Gliomas

Objectives

Gliomas are widely considered to be related to the altered topological organization of functional networks before operations. Tumors are usually thought to cause multimodal cognitive impairments. The structure is thought to form the basics of function, and the aim of this study was to reveal the rich-club organization and topological patterns of white matter (WM) structural networks associated with cognitive impairments in patients with frontal and temporal gliomas.

Methods

Graph theory approaches were utilized to reveal the global and regional topological organization and rich-club organization of WM structural networks of 14 controls (CN), 13 frontal tumors (FTumor), and 18 temporal tumors (TTumor). Linear regression was used to assess the relationship between cognitive performances and altered topological parameters.

Results

When compared with CN, both FTumor and TTumor showed no alterations in small-world properties and global network efficiency, but instead showed altered local network efficiency. Second, FTumor and TTumor patients showed similar deficits in the nodal shortest path in the left rolandic operculum and degree centrality (DC) of the right dorsolateral and medial superior frontal gyrus (SFGmed). Third, compared to FTumor patients, TTumor patients showed a significantly higher DC in the right dorsolateral and SFGmed, a higher level of betweenness in the right SFGmed, and higher nodal efficiency in the left middle frontal gyrus and right SFGmed. Finally, rich-club organization was disrupted, with increased structural connectivity among rich-club nodes and reduced structural connectivity among peripheral nodes in FTumor and TTumor patients. Altered local efficiency in TTumor correlated with memory function, while altered local efficiency in FTumor correlated with the information processing speed.

Conclusion

Both FTumor and TTumor presented an intact global topology and altered regional topology related to cognitive impairment and may also share the convergent and divergent regional topological organization of WM structural networks. This suggested that a compensatory mechanism plays a key role in global topology formation in both FTumor and TTumor patients, and as such, development of a structural connectome for patients with brain tumors would be an invaluable medical resource and allow clinicians to make comprehensive preoperative planning.

Spatiotemporal dynamics of postoperative functional plasticity in patients with brain tumors in language areas

Postoperative functional neuroimaging provides a unique opportunity to investigate the neural mechanisms that facilitate language network reorganization. Previous studies in patients with low grade gliomas (LGGs) in language areas suggest that postoperative recovery is likely due to functional neuroplasticity in peritumoral and contra-tumoral healthy regions, but have attributed varying degrees of importance to specific regions. In this study, we used Magnetoencephalography (MEG) to investigate functional connectivity changes in peritumoral and contra-tumoral regions after brain tumor resection. MEG recordings of cortical activity during resting-state were obtained from 12 patients with LGGs in left-hemisphere language brain areas. MEG data were recorded before (Pre session), and 3 (Post_1 session) and 6 (Post_2 session) months after awake craniotomy. For each MEG session, we measured the functional connectivity of the peritumoral and contra-tumoral regions to the rest of the brain across the 1-100 Hz frequency band. We found that functional connectivity in the Post_1 and Post_2 sessions was higher than in the Pre session only in peritumoral regions and within the alpha frequency band. Functional connectivity in peritumoral regions did not differ between the Post_1 and Post_2 sessions. Alpha connectivity enhancement in peritumoral regions was observed in all patients regardless of the LGG location. Together, these results suggest that postoperative language functional reorganization occurs in peritumoral regions regardless of the location of the tumor and mostly develops within 3 months after surgery.

Beyond eloquence and onto centrality: a new paradigm in planning supratentorial neurosurgery

PURPOSE

Minimizing post-operational neurological deficits as a result of brain surgery has been one of the most pertinent endeavours of neurosurgical research. Studies have utilised fMRIs, EEGs and MEGs in order to delineate and establish eloquent areas, however, these methods have not been utilized by the wider neurosurgical community due to a lack of clinical endpoints. We sought to ascertain if there is a correlation between graph theory metrics and the neurosurgical notion of eloquent brain regions. We also wanted to establish which graph theory based nodal centrality measure performs the best in predicting eloquent areas.

METHODS

We obtained diffusion neuroimaging data from the Human Connectome Project (HCP) and applied a parcellation scheme to it. This enabled us to construct a weighted adjacency matrix which we then analysed. Our analysis looked at the correlation between PageRank centrality and eloquent areas. We then compared PageRank centrality to eigenvector centrality and degree centrality to see what the best measure of empirical neurosurgical eloquence was.

RESULTS

Areas that are considered neurosurgically eloquent tended to be predicted by high PageRank centrality. By using summary scores for the three nodal centrality measures we found that PageRank centrality best correlated to empirical neurosurgical eloquence.

CONCLUSION

The notion of eloquent areas is important to neurosurgery and graph theory provides a mathematical framework to predict these areas. PageRank centrality is able to consistently find areas that we consider eloquent. It is able to do so better than eigenvector and degree central measures.

Cross-modal plasticity in adult single-sided deafness revealed by alpha band resting-state functional connectivity

Single-sided deafness (SSD) or profound unilateral hearing loss is the condition where the transfer of acoustic information to the brain is restricted to one ear. SSD impairment is most evident under adverse acoustic environments with overlapping interference, which burdens cognitive resources. It is known that bilateral deafness induces cross-modal brain plasticity within visual cortical areas. Here we investigate whether similar cross-modal plasticity is observed in adult-onset SSD. In SSD patients (n ​= ​29) and matched controls (n ​= ​29) we estimated voxel level resting-state power and functional connectivity in the alpha band (8-12 ​Hz) from magnetoencephalography (MEG) data. We examined both global functional connectivity (mean functional connectivity of each voxel with the rest of the brain), and seeded functional connectivity of primary auditory cortices (A1), primary visual cortices (V1) and posterior cingulate cortex (PCC) of the default mode network (DMN). Power reduction was observed in left auditory cortex. Global functional connectivity showed reduction in frontal cortices and enhancement in visual cortex. Seeded functional connectivity of auditory cortices showed reduction in temporal, frontal and occipital regions, and enhancement in parietal cortex. Interestingly, seeded functional connectivity of visual cortices showed enhancement in visual cortices, inferior parietal lobe, post-central gyrus, and the precuneus, and reduction in auditory cortex. Seeded functional connectivity of PCC showed reduction in frontal cortical regions that are part of the DMN, attention, and working memory networks. Adult-onset SSD exhibited widespread cross-modal brain plasticity involving alterations in auditory, visual, attention, working memory and default mode networks.

Critical Language Areas Show Increased Functional Connectivity in Human Cortex

Electrocortical stimulation (ECS) mapping is routinely used to identify critical language sites before resective neurosurgery. The precise locations of these sites are highly variable across patients, occurring in the frontal, temporal, and parietal lobes-it is this variability that necessitates individual patient mapping. But why these particular anatomical sites are so privileged in each patient is unknown. We hypothesized that critical language sites have greater functional connectivity with nearby cortex than sites without critical functions, since they serve as central nodes within the language network. Functional connectivity across language, motor, and cleared sites was measured in 15 patients undergoing electrocortiographic (ECoG) mapping for epilepsy surgery. Critical language sites had significantly higher connectivity than sites without critical functions (P = 0.001), and this also held for motor sites (P = 0.022). These data support the hypothesis that critical language sites are highly connected within the local cortical network, perhaps explaining why their disruption with ECS leads to transient disturbances in language function. It is our hope that improved understanding of the mechanisms of ECS will permit improved surgical planning and perhaps contribute to the understanding of normal language physiology.

Intraoperative Identification and Preservation of Verbal Memory in Diffuse Gliomas: A Matched-Pair Cohort Study

BACKGROUND

Recent glioma surgery series with intraoperative electrical stimulation (IES) language mapping have demonstrated high rates of postoperative memory impairment, raising a question regarding the efficacy of this approach to preserve memory.

OBJECTIVE

To evaluate if intraoperative identification and preservation of verbal memory sites with IES mapping in diffuse gliomas in eloquent areas consistently protect patients from long-term postoperative decline in short-term memory.

METHODS

A cohort of 16 subjects with diffuse low-grade or anaplastic gliomas that were operated with IES and intraoperative evaluation of language and verbal memory (cohort A) was matched by tumor side, pathology, and radiotherapy with a cohort of 16 subjects that were operated with IES and evaluation of language (cohort B). Detailed neuropsychological assessment was performed before and 6 mo after surgery.

RESULTS

Intraoperative memory mapping was a strong predictor of verbal memory prognosis. In cohort A, 4 patients (26.7%) had a decline of at least one of the 4 short-term memory tests evaluated. In cohort B, 11 patients (73.3%) had a decline of at least one of the 4 tests. This difference was statistically significant in multivariate analysis (P = .022; odds ratio = 9.88; 95% confidence interval = 1.39-70.42).

CONCLUSION

Verbal memory areas identified intraoperatively with the current paradigm are critically involved in verbal memory, as memory impairment can be significantly reduced by adapting the resection to avoid those memory areas. Incorporation of verbal memory evaluation in stimulation mapping protocols might assist in reducing postoperative sequelae and preserving the patient's quality of life.

Cognitive functioning in glioma patients is related to functional connectivity measures of the non-tumoural hemisphere

Previous studies have shown that cognitive functioning in patients with brain tumour is associated with the functional network characteristics of specific resting‐state networks or with whole‐brain network characteristics. These studies, however, did not acknowledge the functional contribution of areas in the contralesional, non‐tumoural hemisphere, even though these healthy remote areas likely play a critical role in compensating for the loss of function in damaged tissue. In the current study, we examined whether there is an association between cognitive performance and functional network features of the contralesional hemisphere of patients with glioma. We found that local efficiency of the contralesional hemisphere was associated with performance on the reaction time domain, whereas contralesional assortativity was associated with complex attention and cognitive flexibility scores. Our results suggest that a less segregated organization of the contralesional hemisphere is associated with better reaction time scores, whereas a better spread of information over the contralesional hemisphere through mutually interconnected contralesional hubs is associated with better cognitive flexibility and better complex attention scores. These findings urge researchers to recognize the functional contribution of remote, undamaged regions and to focus more on the graph metrics of the contralesional hemisphere in the search for predictors of cognitive functioning in patients with brain tumour.

Presurgical localization and spatial shift of resting state networks in patients with brain metastases

Brain metastases are the most prevalent cerebral tumors. Resting state networks (RSNs) are involved in multiple perceptual and cognitive functions. Therefore, precisely localizing multiple RSNs may be extremely valuable before surgical resection of metastases, to minimize neurocognitive impairments. Here we aimed to investigate the reliability of independent component analysis (ICA) for localizing multiple RSNs from resting-state functional MRI (rs-fMRI) data in individual patients, and further evaluate lesion-related spatial shifts of the RSNs. Twelve patients with brain metastases and 14 healthy controls were recruited. Using an improved automatic component identification method, we successfully identified seven common RSNs, including: the default mode network (DMN), executive control network (ECN), dorsal attention network (DAN), language network (LN), sensorimotor network (SMN), auditory network (AN) and visual network (VN), in both individual patients and controls. Moreover, the RSNs in the patients showed a visible spatial shift compared to those in the controls, and the spatial shift of some regions was related to the tumor location, which may reflect a complicated functional mechanism - functional disruptions and reorganizations - caused by metastases. Besides, higher cognitive networks (DMN, ECN, DAN and LN) showed significantly larger spatial shifts than perceptual networks (SMN, AN and VN), supporting a functional dichotomy between the two network groups even in pathologic alterations associated with metastases. Overall, our findings provide evidence that ICA is a promising approach for presurgical localization of multiple RSNs from rs-fMRI data in individual patients. More attention should be paid to the spatial shifts of the RSNs before surgical resection.

EEG coherence in theta, alpha, and beta bands in frontal regions and executive functions

Executive functions are higdevel cognitive processes that make possible the formation of flexible and adaptive goal-directed behaviors and the frontal lobes regulate these functions. The purpose of this study was to investigate the relationship between frontal EEG coherence in theta, alpha, and beta bands and executive functions in adults. A sample of 168 students (M_age = 25.44 years, SD = 4.52) were included in this study. EEG records were recorded at the psychology laboratory of Mohaghegh Ardabili University (Iran), then intrahemispheric and interhemispheric coherence of frontal regions were analyzed using the NeuroGuide software. The participants were asked to fill in the Adult Executive Skills Questionnaire. Correlational results showed that there is a positive relationship between executive functions and EEG coherence in theta, alpha, and beta bands in frontal regions of the left hemisphere, EEG coherence of alpha and beta bands in frontal regions of the right hemisphere and EEG coherence of alpha band between frontal regions of the two hemispheres. The results of the regression analysis also revealed that coherence of alpha, beta, and theta bands between left and right frontal regions and coherence of beta and theta bands in the left frontal regions predict executive functions. These results indicate that the common activity of frontal cortex, especially the left hemisphere, is associated with executive functions and cognitive control.

Presurgical Functional Cortical Mapping Using Electromagnetic Source Imaging

Preoperative localization of functionally eloquent cortex (functional cortical mapping) is common clinical practice in order to avoid or reduce postoperative morbidity. This review aims at providing a general overview of magnetoencephalography (MEG) and high-density electroencephalography (hdEEG) based methods and their clinical role as compared to common alternatives for functional cortical mapping of (1) verbal language function, (2) sensorimotor cortex, (3) memory, (4) visual, and (5) auditory cortex. We highlight strengths, weaknesses and limitations of these functional cortical mapping modalities based on findings in the recent literature. We also compare their performance relative to other non-invasive functional cortical mapping methods, such as functional Magnetic Resonance Imaging (fMRI), Transcranial Magnetic Stimulation (TMS), and to invasive methods like the intracarotid Amobarbital Test (WADA-Test) or intracranial investigations.

Brain networks and their relevance for stroke rehabilitation

Stroke has long been regarded as focal disease with circumscribed damage leading to neurological deficits. However, advances in methods for assessing the human brain and in statistics have enabled new tools for the examination of the consequences of stroke on brain structure and function. Thereby, it has become evident that stroke has impact on the entire brain and its network properties and can therefore be considered as a network disease. The present review first gives an overview of current methodological opportunities and pitfalls for assessing stroke-induced changes and reorganization in the human brain. We then summarize principles of plasticity after stroke that have emerged from the assessment of networks. Thereby, it is shown that neurological deficits do not only arise from focal tissue damage but also from local and remote changes in white-matter tracts and in neural interactions among wide-spread networks. Similarly, plasticity and clinical improvements are associated with specific compensatory structural and functional patterns of neural network interactions. Innovative treatment approaches have started to target such network patterns to enhance recovery. Network assessments to predict treatment response and to individualize rehabilitation is a promising way to enhance specific treatment effects and overall outcome after stroke.

Combining resting state functional MRI with intraoperative cortical stimulation to map the mentalizing network

OBJECTIVE

To infer the face-based mentalizing network from resting-state functional MRI (rsfMRI) using a seed-based correlation analysis with regions of interest identified during intraoperative cortical electrostimulation.

METHODS

We retrospectively included 23 patients in whom cortical electrostimulation induced transient face-based mentalizing impairment during 'awake' craniotomy for resection of a right-sided diffuse low-grade glioma. Positive stimulation sites were recorded and transferred to the patients' preoperative normalized MRI, and then used as seeds for subsequent seed-to-voxel functional connectivity analyses. The analyses, conducted with an uncorrected voxel-level p-value of 0.001 and a false-discovery-rate cluster-level p-value of 0.05, allowed identification of the cortical structures, functionally coupled with the mentalizing-related sites.

RESULTS

Two clusters of responsive stimulations were identified intraoperatively - one in the right dorsolateral prefrontal cortex (dlPFC, n = 13) and the other in the right inferior frontal gyrus (IFG, n = 10). A whole group level analysis revealed that stimulation sites correlated mainly with voxels located in the pars triangularis of the IFG, the dorsolateral and dorsomedial prefrontal cortices, the temporo-parietal junction, the posterior superior temporal sulcus, and the posterior inferior temporal/fusiform gyrus. Other analyses, taking into consideration the location of the responsive sites (IFG versus dlPFC cluster), highlighted only minor differences between both groups.

CONCLUSIONS

The present study successfully demonstrated the involvement of a large-scale neural network in the face-based mentalizing that strongly matches networks, classically identified using task-based fMRI paradigms. We thus validated the combination of rsfMRI and stimulation mapping as a powerful approach to identify functional networks in brain-damaged patients.

Source Connectivity Analysis Can Assess Recovery of Acute Mild Traumatic Brain Injury Patients

In this study we investigated whether source connectivity analysis of resting-state Magnetoencephalographic (MEG) activity could separate mild traumatic brain injury (mTBI) patients from age-and sex-matched controls. For each subject, we used artifact-free data recorded on three sessions to estimate intracranial sources which were then projected onto a standardized brain atlas for common reference. The statistical and topological properties of functional brain networks, estimated using Granger causality, were analyzed using MANOVA, with group and recording session as the independent variables and number of in-going and out-going connections in each atlas region as dependent variables. Overall, mTBI subjects showed a larger number of stronger connections compared to controls. The number and topology of in-going and out-going connections were significantly different across the two groups in areas involved with spatial memory, perception of visual space, emotion formation and processing, learning, and memory. Additionally, differences between patients and controls were decreasing across the three sessions indicating patient improvement. Our results suggest that connectivity analysis may be used as a reliable biomarker of mTBI and can also help with the diagnosis and assessment of patient recovery.

How much is enough-Can resting state fMRI provide a demarcation for neurosurgical resection in glioma?

This study represents a systematic review of the insights provided by resting state functional MRI (rs-fMRI) use in the glioma population. Following PRISMA guidelines, 45 studies were included in the review and were classified in glioma-related neuronal changes (n=28) and eloquent area localization (n=17). Despite the heterogeneous nature of the studies, there is considerable evidence of diffuse functional reorganization occurring in the setting of gliomas with local and interhemispheric functional connectivity alterations involving different functional networks. The studies showed evidence of decreased long distance functional connectivity and increased global local efficiency occurring in the setting of gliomas. The tumour grade seems to correlate with distinct functional connectivity changes. Overall, there is a potential clinical utility of rs-fMRI for identifying the functional brain network disruptions occurring in the setting of gliomas. Further studies utilizing standardized analytical methods are required to elucidate the mechanism through which gliomas induce global changes in brain connectivity.

Distinct spatiotemporal patterns of neuronal functional connectivity in primary progressive aphasia variants

Primary progressive aphasia is a syndrome characterized by progressive loss of language abilities with three main phenotypic clinical presentations, including logopenic, non-fluent/agrammatic, and semantic variants. Previous imaging studies have shown unique anatomic impacts within language networks in each variant. However, direct measures of spontaneous neuronal activity and functional integrity of these impacted neural networks in primary progressive aphasia are lacking. The aim of this study was to characterize the spatial and temporal patterns of resting state neuronal synchronizations in primary progressive aphasia syndromes. We hypothesized that resting state brain oscillations will show unique deficits within language network in each variant of primary progressive aphasia. We examined 39 patients with primary progressive aphasia including logopenic variant (n = 14, age = 61 ± 9 years), non-fluent/agrammatic variant (n = 12, age = 71 ± 8 years) and semantic variant (n = 13, age = 65 ± 7 years) using magnetoencephalographic imaging, compared to a control group that was matched in age and gender to each primary progressive aphasia subgroup (n = 20, age = 65 ± 5 years). Each patient underwent a complete clinical evaluation including a comprehensive battery of language tests. We examined the whole-brain resting state functional connectivity as measured by imaginary coherence in each patient group compared to the control cohort, in three frequency oscillation bands-delta-theta (2-8 Hz); alpha (8-12 Hz); beta (12-30 Hz). Each variant showed a distinct spatiotemporal pattern of altered functional connectivity compared to age-matched controls. Specifically, we found significant hyposynchrony of alpha and beta frequency within the left posterior temporal and occipital cortices in patients with the logopenic variant, within the left inferior frontal cortex in patients with the non-fluent/agrammatic variant, and within the left temporo-parietal junction in patients with the semantic variant. Patients with logopenic variant primary progressive aphasia also showed significant hypersynchrony of delta-theta frequency within bilateral medial frontal and posterior parietal cortices. Furthermore, region of interest-based analyses comparing the spatiotemporal patterns of variant-specific regions of interest identified in comparison to age-matched controls showed significant differences between primary progressive aphasia variants themselves. We also found distinct patterns of regional spectral power changes in each primary progressive aphasia variant, compared to age-matched controls. Our results demonstrate neurophysiological signatures of network-specific neuronal dysfunction in primary progressive aphasia variants. The unique spatiotemporal patterns of neuronal synchrony signify diverse neurophysiological disruptions and pathological underpinnings of the language network in each variant.

Altered insula-default mode network connectivity in fibromyalgia: a resting-state magnetoencephalographic study

Background

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

Methods

We recorded the resting-state magnetoencephalographic activities of 28 patients with FM and 28 age- and sex-matched controls, and analyzed the source-based functional connectivity between the insula and the DMN at 1–40 Hz by using the minimum norm estimates and imaginary coherence methods. We also measured the connectivity between the DMN and the primary visual (V1) and somatosensory (S1) cortices as intrapatient negative controls. Connectivity measurement was further correlated with the clinical parameters of FM.

Results

Compared with the controls, patients with FM reported more tender points (15.2±2.0 vs. 5.9±3.7) and higher total tenderness score (TTS; 29.1±7.0 vs. 7.7±5.5; both p < 0.001); they also had decreased insula–DMN connectivity at the theta band (4–8 Hz; left, p = 0.007; right, p = 0.035), but displayed unchanged V1–DMN and S1–DMN connectivity (p > 0.05). When patients with FM and the controls were combined together, the insula-DMN theta connectivity was negatively correlated with the number of tender points (left insula, r = −0.428, p = 0.001; right insula, r = −0.4, p = 0.002) and TTS score (left insula, r = −0.429, p = 0.001; right insula, r = −0.389, p = 0.003). Furthermore, in patients with FM, the right insula–DMN connectivity at the beta band (13–25 Hz) was negatively correlated with the number of tender points (r = −0.532, p = 0.004) and TTS (r = −0.428, p = 0.023), and the bilateral insula–DMN connectivity at the delta band (1–4 Hz) was negatively correlated with FM Symptom Severity (left: r = −0.423, p = 0.025; right: r = −0.437, p = 0.020) and functional disability (Fibromyalgia Impact Questionnaire; left: r = −0.415, p = 0.028; right: r = −0.374, p = 0.050).

Conclusions

We confirmed the frequency-specific reorganization of the insula–DMN connectivity in FM. The clinical relevance of this connectivity change may warrant future studies to elucidate its causal relationship and potential as a neurological signature for FM.

Electronic supplementary material

The online version of this article (doi:10.1186/s10194-017-0799-x) contains supplementary material, which is available to authorized users.

Dynamic hub load predicts cognitive decline after resective neurosurgery

Resective neurosurgery carries the risk of postoperative cognitive deterioration. The concept of ‘hub (over)load’, caused by (over)use of the most important brain regions, has been theoretically postulated in relation to symptomatology and neurological disease course, but lacks experimental confirmation. We investigated functional hub load and postsurgical cognitive deterioration in patients undergoing lesion resection. Patients (n = 28) underwent resting-state magnetoencephalography and neuropsychological assessments preoperatively and 1-year after lesion resection. We calculated stationary hub load score (SHub) indicating to what extent brain regions linked different subsystems; high SHub indicates larger processing pressure on hub regions. Dynamic hub load score (DHub) assessed its variability over time; low values, particularly in combination with high SHub values, indicate increased load, because of consistently high usage of hub regions. Hypothetically, increased SHub and decreased DHub relate to hub overload and thus poorer/deteriorating cognition. Between time points, deteriorating verbal memory performance correlated with decreasing upper alpha DHub. Moreover, preoperatively low DHub values accurately predicted declining verbal memory performance. In summary, dynamic hub load relates to cognitive functioning in patients undergoing lesion resection: postoperative cognitive decline can be tracked and even predicted using dynamic hub load, suggesting it may be used as a prognostic marker for tailored treatment planning.

Network Plasticity and Intraoperative Mapping for Personalized Multimodal Management of Diffuse Low-Grade Gliomas

Gliomas are the most frequent primary brain tumors and include a variety of different histological tumor types and malignancy grades. Recent achievements in terms of molecular and imaging fields have created an unprecedented opportunity to perform a comprehensive interdisciplinary assessment of the glioma pathophysiology, with direct implications in terms of the medical and surgical treatment strategies available for patients. The current paradigm shift considers glioma management in a comprehensive perspective that takes into account the intricate connectivity of the cerebral networks. This allowed significant improvement in the outcome of patients with lesions previously considered inoperable. The current review summarizes the current theoretical framework integrating the adult human brain plasticity and functional reorganization within a dynamic individualized treatment strategy for patients affected by diffuse low-grade gliomas. The concept of neuro-oncology as a brain network surgery has major implications in terms of the clinical management and ensuing outcomes, as indexed by the increased survival and quality of life of patients managed using such an approach.

Disrupted functional connectivity affects resting state based language lateralization

Pre-operative assessment of language localization and lateralization is critical to preserving brain function after lesion or epileptogenic tissue resection. Task fMRI (t-fMRI) has been extensively and reliably used to this end, but resting state fMRI (rs-fMRI) is emerging as an alternative pre-operative brain mapping method that is independent of a patient's ability to comply with a task. We sought to evaluate if language lateralization obtained from rs-fMRI can replace standard assessment using t-fMRI. In a group of 43 patients scheduled for pre-operative fMRI brain mapping and 17 healthy controls, we found that existing methods of determining rs-fMRI lateralization by considering interhemispheric and intrahemispheric functional connectivity are inadequate compared to t-fMRI when applied to the language network. We determined that this was attributable to widespread but nuanced disturbances in the functional connectivity of the language network in patients. We found changes in interhemispheric and intrahemispheric functional connectivity that were dependent on lesion location, and particularly impacted patients with lesions in the left temporal lobe. We then tested whether a simpler measure of functional connectivity to the language network has a better relation to t-fMRI based language lateralization. Remarkably, we found that functional connectivity between the language network and the frontal pole, and superior frontal gyrus, as well as the supramarginal gyrus, significantly correlated to task based language lateralization indices in both patients and healthy controls. These findings are consistent with prior work with epilepsy patients, and provide a framework for evaluating language lateralization at rest.

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Existing methods of determining rs-fMRI lateralization are inadequate for language.

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Functional connectivity to language network correlates with task lateralization.

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Lesion location affects functional connectivity.

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Lesions exhibit some interhemispheric hyperconnectivity within language network.

From Structure to Circuits: The Contribution of MEG Connectivity Studies to Functional Neurosurgery

New advances in structural neuroimaging have revealed the intricate and extensive connections within the brain, data which have informed a number of ambitious projects such as the mapping of the human connectome. Elucidation of the structural connections of the brain, at both the macro and micro levels, promises new perspectives on brain structure and function that could translate into improved outcomes in functional neurosurgery. The understanding of neuronal structural connectivity afforded by these data now offers a vista on the brain, in both healthy and diseased states, that could not be seen with traditional neuroimaging. Concurrent with these developments in structural imaging, a complementary modality called magnetoencephalography (MEG) has been garnering great attention because it too holds promise for being able to shed light on the intricacies of functional brain connectivity. MEG is based upon the elemental principle of physics that an electrical current generates a magnetic field. Hence, MEG uses highly sensitive biomagnetometers to measure extracranial magnetic fields produced by intracellular neuronal currents. Put simply then, MEG is a measure of neurophysiological activity, which captures the magnetic fields generated by synchronized intraneuronal electrical activity. As such, MEG recordings offer exquisite resolution in the time and oscillatory domain and, as well, when co-registered with magnetic resonance imaging (MRI), offer excellent resolution in the spatial domain. Recent advances in MEG computational and graph theoretical methods have led to studies of connectivity in the time-frequency domain. As such, MEG can elucidate a neurophysiological-based functional circuitry that may enhance what is seen with MRI connectivity studies. In particular, MEG may offer additional insight not possible by MRI when used to study complex eloquent function, where the precise timing and coordination of brain areas is critical. This article will review the traditional use of MEG for functional neurosurgery, describe recent advances in MEG connectivity analyses, and consider the additional benefits that could be gained with the inclusion of MEG connectivity studies. Since MEG has been most widely applied to the study of epilepsy, we will frame this article within the context of epilepsy surgery and functional neurosurgery for epilepsy.

Cortical plasticity catalyzed by prehabilitation enables extensive resection of brain tumors in eloquent areas

OBJECTIVE The extent of resection is the most important prognostic factor following brain glioma surgery. However, eloquent areas within tumors limit the extent of resection and, thus, critically affect outcomes. The authors hypothesized that presurgical suppression of the eloquent areas within a tumor by continuous cortical electrical stimulation, coupled with appropriate behavioral training ("prehabilitation"), would induce plastic reorganization and enable a more extensive resection. METHODS The authors report on 5 patients harboring gliomas involving eloquent brain areas within tumors as identified on intraoperative stimulation mapping. A grid of electrodes was placed over the residual tumor, and continuous cortical electrical stimulation was targeted to the functional areas. The stimulation intensity was adjusted daily to provoke a mild functional impairment while the function was intensively trained. RESULTS The stimulation intensity required to impair function increased progressively in all patients, and all underwent another operation a mean of 33.6 days later (range 27-37 days), when the maximal stimulation voltage in all active contacts induced no functional deficit. In all cases, a substantially more extensive resection of the tumor was possible. Intraoperative mapping and functional MRI demonstrated a plastic reorganization, and most previously demonstrated eloquent areas within the tumor were silent, while there was new functional activation of brain areas in the same region or toward the contralateral hemisphere. CONCLUSIONS Prehabilitation with continuous cortical electrical stimulation and appropriate behavioral training prior to surgery in patients with WHO Grade II and III gliomas affecting eloquent areas accelerate plastic changes. This can help maximize tumor resection and, thus, improve survival while maintaining function.

Functional connectivity changes detected with magnetoencephalography after mild traumatic brain injury

Mild traumatic brain injury (mTBI) may affect normal cognition and behavior by disrupting the functional connectivity networks that mediate efficient communication among brain regions. In this study, we analyzed brain connectivity profiles from resting state Magnetoencephalographic (MEG) recordings obtained from 31 mTBI patients and 55 normal controls. We used phase-locking value estimates to compute functional connectivity graphs to quantify frequency-specific couplings between sensors at various frequency bands. Overall, normal controls showed a dense network of strong local connections and a limited number of long-range connections that accounted for approximately 20% of all connections, whereas mTBI patients showed networks characterized by weak local connections and strong long-range connections that accounted for more than 60% of all connections. Comparison of the two distinct general patterns at different frequencies using a tensor representation for the connectivity graphs and tensor subspace analysis for optimal feature extraction showed that mTBI patients could be separated from normal controls with 100% classification accuracy in the alpha band. These encouraging findings support the hypothesis that MEG-based functional connectivity patterns may be used as biomarkers that can provide more accurate diagnoses, help guide treatment, and monitor effectiveness of intervention in mTBI.

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We analyzed resting state connectivity profiles in 31 mTBI patients and 55 controls.

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We quantified frequency-specific connectivity couplings using phase-locking values.

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Normal control networks showed dense local and sparse long-range connections.

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TBI patient networks showed sparse local and dense long-range connections.

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Tensor subspace analysis could classify subjects with 100% accuracy in the α band