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1.
Sci Rep ; 11(1): 19025, 2021 09 24.
Artigo em Inglês | MEDLINE | ID: mdl-34561483

RESUMO

The success of epilepsy surgery in patients with refractory epilepsy depends upon correct identification of the epileptogenic zone (EZ) and an optimal choice of the resection area. In this study we developed individualized computational models based upon structural brain networks to explore the impact of different virtual resections on the propagation of seizures. The propagation of seizures was modelled as an epidemic process [susceptible-infected-recovered (SIR) model] on individual structural networks derived from presurgical diffusion tensor imaging in 19 patients. The candidate connections for the virtual resection were all connections from the clinically hypothesized EZ, from which the seizures were modelled to start, to other brain areas. As a computationally feasible surrogate for the SIR model, we also removed the connections that maximally reduced the eigenvector centrality (EC) (large values indicate network hubs) of the hypothesized EZ, with a large reduction meaning a large effect. The optimal combination of connections to be removed for a maximal effect were found using simulated annealing. For comparison, the same number of connections were removed randomly, or based on measures that quantify the importance of a node or connection within the network. We found that 90% of the effect (defined as reduction of EC of the hypothesized EZ) could already be obtained by removing substantially less than 90% of the connections. Thus, a smaller, optimized, virtual resection achieved almost the same effect as the actual surgery yet at a considerably smaller cost, sparing on average 27.49% (standard deviation: 4.65%) of the connections. Furthermore, the maximally effective connections linked the hypothesized EZ to hubs. Finally, the optimized resection was equally or more effective than removal based on structural network characteristics both regarding reducing the EC of the hypothesized EZ and seizure spreading. The approach of using reduced EC as a surrogate for simulating seizure propagation can suggest more restrictive resection strategies, whilst obtaining an almost optimal effect on reducing seizure propagation, by taking into account the unique topology of individual structural brain networks of patients.

2.
Cereb Cortex ; 2021 Sep 25.
Artigo em Inglês | MEDLINE | ID: mdl-34564728

RESUMO

Temporal lobe epilepsy (TLE) patients are at risk of memory deficits, which have been linked to functional network disturbances, particularly of integration of the default mode network (DMN). However, the cellular substrates of functional network integration are unknown. We leverage a unique cross-scale dataset of drug-resistant TLE patients (n = 31), who underwent pseudo resting-state functional magnetic resonance imaging (fMRI), resting-state magnetoencephalography (MEG) and/or neuropsychological testing before neurosurgery. fMRI and MEG underwent atlas-based connectivity analyses. Functional network centrality of the lateral middle temporal gyrus, part of the DMN, was used as a measure of local network integration. Subsequently, non-pathological cortical tissue from this region was used for single cell morphological and electrophysiological patch-clamp analysis, assessing integration in terms of total dendritic length and action potential rise speed. As could be hypothesized, greater network centrality related to better memory performance. Moreover, greater network centrality correlated with more integrative properties at the cellular level across patients. We conclude that individual differences in cognitively relevant functional network integration of a DMN region are mirrored by differences in cellular integrative properties of this region in TLE patients. These findings connect previously separate scales of investigation, increasing translational insight into focal pathology and large-scale network disturbances in TLE.

3.
Neurosci Biobehav Rev ; 130: 81-90, 2021 11.
Artigo em Inglês | MEDLINE | ID: mdl-34324918

RESUMO

In recent years, there has been an increase in applications of network science in many different fields. In clinical neuroscience and psychopathology, the developments and applications of network science have occurred mostly simultaneously, but without much collaboration between the two fields. The promise of integrating these network applications lies in a united framework to tackle one of the fundamental questions of our time: how to understand the link between brain and behavior. In the current overview, we bridge this gap by introducing conventions in both fields, highlighting similarities, and creating a common language that enables the exploitation of synergies. We provide research examples in autism research, as it accurately represents research lines in both network neuroscience and psychological networks. We integrate brain and behavior not only semantically, but also practically, by showcasing three methodological avenues that allow to combine networks of brain and behavioral data. As such, the current paper offers a stepping stone to further develop multi-modal networks and to integrate brain and behavior.


Assuntos
Encéfalo , Neurociências , Humanos
4.
Breast Cancer Res Treat ; 189(3): 787-796, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-34259949

RESUMO

PURPOSE: This longitudinal study aimed to disentangle the impact of chemotherapy on fatigue and hypothetically associated functional brain network alterations. METHODS: In total, 34 breast cancer patients treated with chemotherapy (BCC +), 32 patients not treated with chemotherapy (BCC -), and 35 non-cancer controls (NC) were included. Fatigue was assessed using the EORTC QLQ-C30 fatigue subscale at two time points: baseline (T1) and six months after completion of chemotherapy or matched intervals (T2). Participants also underwent resting-state functional magnetic resonance imaging (rsfMRI). An atlas spanning 90 cortical and subcortical brain regions was used to extract time series, after which Pearson correlation coefficients were calculated to construct a brain network per participant per timepoint. Network measures of local segregation and global integration were compared between groups and timepoints and correlated with fatigue. RESULTS: As expected, fatigue increased over time in the BCC + group (p = 0.025) leading to higher fatigue compared to NC at T2 (p = 0.023). Meanwhile, fatigue decreased from T1 to T2 in the BCC - group (p = 0.013). The BCC + group had significantly lower local efficiency than NC at T2 (p = 0.033), while a negative correlation was seen between fatigue and local efficiency across timepoints and all participants (T1 rho = - 0.274, p = 0.006; T2 rho = - 0.207, p = 0.039). CONCLUSION: Although greater fatigue and lower local functional network segregation co-occur in breast cancer patients after chemotherapy, the relationship between the two generalized across participant subgroups, suggesting that local efficiency is a general neural correlate of fatigue.


Assuntos
Neoplasias da Mama , Encéfalo/diagnóstico por imagem , Neoplasias da Mama/tratamento farmacológico , Fadiga/induzido quimicamente , Fadiga/epidemiologia , Feminino , Humanos , Estudos Longitudinais , Imageamento por Ressonância Magnética
5.
Brain Connect ; 2021 Jun 17.
Artigo em Inglês | MEDLINE | ID: mdl-33947274

RESUMO

Introduction: Glioma patients show increased global brain network clustering related to poorer cognition and epilepsy. However, it is unclear whether this increase is spatially widespread, localized in the (peri)tumor region only, or decreases with distance from the tumor. Materials and Methods: Weighted global and local brain network clustering was determined in 71 glioma patients and 53 controls by using magnetoencephalography. Tumor clustering was determined by averaging local clustering of regions overlapping with the tumor, and vice versa for non-tumor regions. Euclidean distance was determined from the tumor centroid to the centroids of other regions. Results: Patients showed higher global clustering compared with controls. Clustering of tumor and non-tumor regions did not differ, and local clustering was not associated with distance from the tumor. Post hoc analyses revealed that in the patient group, tumors were located more often in regions with higher clustering in controls, but it seemed that tumors of patients with high global clustering were located more often in regions with lower clustering in controls. Conclusions: Glioma patients show non-local network disturbances. Tumors of patients with high global clustering may have a preferred localization, namely regions with lower clustering in controls, suggesting that tumor localization relates to the extent of network disruption. Impact statement This work uses the innovative framework of network neuroscience to investigate functional connectivity patterns associated with brain tumors. Glioma (primary brain tumor) patients experience cognitive deficits and epileptic seizures, which have been related to brain network alterations. This study shows that glioma patients have a spatially widespread increase in global network clustering, which cannot be attributed to local effects of the tumor. Moreover, tumors occur more often in brain regions with higher network clustering in controls. This study emphasizes the global character of network alterations in glioma patients and suggests that preferred tumor locations are characterized by particular network profiles.

6.
Mult Scler ; 27(13): 2031-2039, 2021 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-33683158

RESUMO

BACKGROUND: The impact of cerebellar damage and (dys)function on cognition remains understudied in multiple sclerosis. OBJECTIVE: To assess the cognitive relevance of cerebellar structural damage and functional connectivity (FC) in relapsing-remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS). METHODS: This study included 149 patients with early RRMS, 81 late RRMS, 48 SPMS and 82 controls. Cerebellar cortical imaging included fractional anisotropy, grey matter volume and resting-state functional magnetic resonance imaging (MRI). Cerebellar FC was assessed with literature-based resting-state networks, using static connectivity (that is, conventional correlations), and dynamic connectivity (that is, fluctuations in FC strength). Measures were compared between groups and related to disability and cognition. RESULTS: Cognitive impairment (CI) and cerebellar damage were worst in SPMS. Only SPMS showed cerebellar connectivity changes, compared to early RRMS and controls. Lower static FC was seen in fronto-parietal and default-mode networks. Higher dynamic FC was seen in dorsal and ventral attention, default-mode and deep grey matter networks. Cerebellar atrophy and higher dynamic FC together explained 32% of disability and 24% of cognitive variance. Higher dynamic FC was related to working and verbal memory and to information processing speed. CONCLUSION: Cerebellar damage and cerebellar connectivity changes were most prominent in SPMS and related to worse CI.

7.
Neuroimage Clin ; 29: 102556, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33472144

RESUMO

BACKGROUND: More than 80% of multiple sclerosis (MS) patients experience symptoms of fatigue. MS-related fatigue is only partly explained by structural (lesions and atrophy) and functional (brain activation and conventional static functional connectivity) brain properties. OBJECTIVES: To investigate the relationship of dynamic functional connectivity (dFC) with fatigue in MS patients and to compare dFC with commonly used clinical and MRI parameters. METHODS: In 35 relapsing-remitting MS patients (age: 42.83 years, female/male: 20/15, disease duration: 11 years) and 19 healthy controls (HCs) (age: 41.38 years, female/male: 11/8), fatigue was measured using the CIS-20r questionnaire at baseline and at 6-month follow-up. All subjects underwent structural and resting-state functional MRI at baseline. Global static functional connectivity (sFC) and dynamic functional connectivity (dFC) were calculated. dFC was assessed using a sliding-window approach by calculating the summed difference (diff) and coefficient of variation (cv) across windows. Moreover, regional connectivity between regions previously associated with fatigue in MS was estimated (i.e. basal ganglia and regions of the Default Mode Network (DMN): medial prefrontal, posterior cingulate and precuneal cortices). Hierarchical regression analyses were performed with forward selection to identify the most important correlates of fatigue at baseline. Results were not corrected for multiple testing due to the exploratory nature of the study. RESULTS: Patients were more fatigued than HCs at baseline (p = 0.001) and follow-up (p = 0.002) and fatigue in patients was stable over time (p = 0.213). Patients had significantly higher baseline global dFC than HCs, but no difference in basal ganglia-DMN dFC. In the regression model for baseline fatigue in patients, basal ganglia-DMN dFC-cv (standardized ß = -0.353) explained 12.5% additional variance on top of EDSS (p = 0.032). Post-hoc analysis revealed higher basal ganglia-DMN dFC-cv in non-fatigued patients compared to healthy controls (p = 0.013), whereas fatigued patients and healthy controls showed similar basal ganglia-DMN dFC. CONCLUSIONS: Less dynamic connectivity between the basal ganglia and the cortex is associated with greater fatigue in MS patients, independent of disability status. Within patients, lower dynamics of these connections could relate to lower efficiency and increased fatigue. Increased dynamics in non-fatigued patients compared to healthy controls might represent a network organization that protects against fatigue or signal early network dysfunction.


Assuntos
Esclerose Múltipla , Adulto , Encéfalo/diagnóstico por imagem , Mapeamento Encefálico , Fadiga/etiologia , Feminino , Humanos , Imageamento por Ressonância Magnética , Masculino , Esclerose Múltipla/complicações , Esclerose Múltipla/diagnóstico por imagem , Vias Neurais/diagnóstico por imagem
8.
Mult Scler ; 27(11): 1727-1737, 2021 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-33295249

RESUMO

BACKGROUND: Cognitive decline remains difficult to predict as structural brain damage cannot fully explain the extensive heterogeneity found between MS patients. OBJECTIVE: To investigate whether functional brain network organization measured with magnetoencephalography (MEG) predicts cognitive decline in MS patients after 5 years and to explore its value beyond structural pathology. METHODS: Resting-state MEG recordings, structural MRI, and neuropsychological assessments were analyzed of 146 MS patients, and 100 patients had a 5-year follow-up neuropsychological assessment. Network properties of the minimum spanning tree (i.e. backbone of the functional brain network) indicating network integration and overload were related to baseline and longitudinal cognition, correcting for structural damage. RESULTS: A more integrated beta band network (i.e. smaller diameter) and a less integrated delta band network (i.e. lower leaf fraction) predicted cognitive decline after 5 years (Radj2=15%), independent of structural damage. Cross-sectional analyses showed that a less integrated network (e.g. lower tree hierarchy) related to worse cognition, independent of frequency band. CONCLUSIONS: The level of functional brain network integration was an independent predictive marker of cognitive decline, in addition to the severity of structural damage. This work thereby indicates the promise of MEG-derived network measures in predicting disease progression in MS.

9.
Brain Sci ; 10(12)2020 Nov 27.
Artigo em Inglês | MEDLINE | ID: mdl-33260895

RESUMO

It has long been understood that a multitude of biological systems, from genetics, to brain networks, to psychological factors, all play a role in personality. Understanding how these systems interact with each other to form both relatively stable patterns of behaviour, cognition and emotion, but also vast individual differences and psychiatric disorders, however, requires new methodological insight. This article explores a way in which to integrate multiple levels of personality simultaneously, with particular focus on its neural and psychological constituents. It does so first by reviewing the current methodology of studies used to relate the two levels, where psychological traits, often defined with a latent variable model are used as higher-level concepts to identify the neural correlates of personality (NCPs). This is known as a top-down approach, which though useful in revealing correlations, is not able to include the fine-grained interactions that occur at both levels. As an alternative, we discuss the use of a novel complex system approach known as a multilayer network, a technique that has recently proved successful in revealing veracious interactions between networks at more than one level. The benefits of the multilayer approach to the study of personality neuroscience follow from its well-founded theoretical basis in network science. Its predictive and descriptive power may surpass that of statistical top-down and latent variable models alone, potentially allowing the discernment of more complete descriptions of individual differences, and psychiatric and neurological changes that accompany disease. Though in its infancy, and subject to a number of methodological unknowns, we argue that the multilayer network approach may contribute to an understanding of personality as a complex system comprised of interrelated psychological and neural features.

10.
Neurology ; 95(5): e532-e544, 2020 08 04.
Artigo em Inglês | MEDLINE | ID: mdl-32661099

RESUMO

OBJECTIVE: To investigate the association between ß-amyloid (Aß) load and postmortem structural network topology in decedents without dementia. METHODS: Fourteen decedents (mean age at death 72.6 ± 7.2 years) without known clinical diagnosis of neurodegenerative disease and meeting pathology criteria only for no or low Alzheimer disease (AD) pathologic change were selected from the Normal Aging Brain Collection Amsterdam database. In situ brain MRI included 3D T1-weighted images for anatomical registration and diffusion tensor imaging for probabilistic tractography with subsequent structural network construction. Network topologic measures of centrality (degree), integration (global efficiency), and segregation (clustering and local efficiency) were calculated. Tissue sections from 12 cortical regions were sampled and immunostained for Aß and hyperphosphorylated tau (p-tau), and histopathologic burden was determined. Linear mixed effect models were used to assess the relationship between Aß and p-tau load and network topologic measures. RESULTS: Aß was present in 79% of cases and predominantly consisted of diffuse plaques; p-tau was sparsely present. Linear mixed effect models showed independent negative associations between Aß load and global efficiency (ß = -0.83 × 10-3, p = 0.014), degree (ß = -0.47, p = 0.034), and clustering (ß = -0.55 × 10-2, p = 0.043). A positive association was present between Aß load and local efficiency (ß = 3.16 × 10-3, p = 0.035). Regionally, these results were significant in the posterior cingulate cortex (PCC) for degree (ß = -2.22, p < 0.001) and local efficiency (ß = 1.01 × 10-2, p = 0.014) and precuneus for clustering (ß = -0.91 × 10-2, p = 0.017). There was no relationship between p-tau and network topology. CONCLUSION: This study in deceased adults with AD-related pathologic change provides evidence for a relationship among early Aß accumulation, predominantly of the diffuse type, and structural network topology, specifically of the PCC and precuneus.


Assuntos
Envelhecimento/patologia , Peptídeos beta-Amiloides , Encéfalo/patologia , Rede Nervosa/patologia , Idoso , Idoso de 80 Anos ou mais , Encéfalo/fisiopatologia , Imagem de Tensor de Difusão , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Rede Nervosa/fisiopatologia , Redes Neurais de Computação
11.
Brain Connect ; 10(5): 224-235, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32397732

RESUMO

Migraine is a common disorder with high social and medical impact. Patients with migraine have a much higher chance of experiencing headache attacks compared with the general population. Recent neuroimaging studies have confirmed that pathophysiology in the brain is not only limited to the moment of the attack but is also present in between attacks, the interictal phase. In this study, we hypothesized that the topology of functional brain networks is also different in the interictal state, compared with people who are not affected by migraine. We also expected that the level of network disturbances scales with the number of years people have suffered from migraine. Functional connectivity between 78 cortical brain regions was estimated for source-level magnetoencephalography data by calculating the phase lag index, in five frequency bands (delta-beta), and compared between healthy controls (n = 24) and patients who had been suffering from migraine for longer than 6 years (n = 12) or shorter than 6 years (n = 12). Moreover, the topology of the functional networks was characterized using the minimum spanning tree. The migraine groups did not differ from each other in functional connectivity. However, the network topology was different compared with healthy controls. The results were frequency specific, and higher average nodal betweenness centrality was specifically evident in higher frequency bands in patients with longer disease duration, while an opposite trend was present for lower frequencies. This study shows that patients with migraine have a different network topology in the resting state compared with healthy controls, whereby specific brain areas have altered topological roles in a frequency-specific manner. Some alterations appear specifically in patients with long-term migraine, which might show the long-term effects of the disease.


Assuntos
Ondas Encefálicas/fisiologia , Córtex Cerebral/fisiopatologia , Conectoma , Magnetoencefalografia/métodos , Rede Nervosa/fisiopatologia , Adulto , Estudos de Casos e Controles , Doença Crônica , Feminino , Humanos , Estudos Longitudinais , Masculino , Fatores de Tempo
12.
Hum Brain Mapp ; 41(11): 3161-3171, 2020 08 01.
Artigo em Inglês | MEDLINE | ID: mdl-32395892

RESUMO

Repetitive transcranial magnetic stimulation (rTMS) is used to investigate normal brain function in healthy participants and as a treatment for brain disorders. Various subject factors can influence individual response to rTMS, including brain network properties. A previous study by our group showed that "virtually lesioning" the left dorsolateral prefrontal cortex (dlPFC; important for cognitive flexibility) using 1 Hz rTMS reduced performance on a set-shifting task. We aimed to determine whether this behavioural response was related to topological features of pre-TMS resting-state and task-based functional networks. 1 Hz (inhibitory) rTMS was applied to the left dlPFC in 16 healthy participants, and to the vertex in 17 participants as a control condition. Participants performed a set-shifting task during fMRI at baseline and directly after a single rTMS session 1-2 weeks later. Functional network topology measures were calculated from resting-state and task-based fMRI scans using graph theoretical analysis. The dlPFC-stimulated group, but not the vertex group, showed reduced setshifting performance after rTMS, associated with lower task-based betweenness centrality (BC) of the dlPFC at baseline (p = .030) and a smaller reduction in task-based BC after rTMS (p = .024). Reduced repeat trial accuracy after rTMS was associated with higher baseline resting state node strength of the dlPFC (p = .017). Our results suggest that behavioural response to 1 Hz rTMS to the dlPFC is dependent on baseline functional network features. Individuals with more globally integrated stimulated regions show greater resilience to rTMS effects, while individuals with more locally well-connected regions show greater vulnerability.

13.
Neuroimage ; 216: 116805, 2020 08 01.
Artigo em Inglês | MEDLINE | ID: mdl-32335264

RESUMO

Functional brain networks are shaped and constrained by the underlying structural network. However, functional networks are not merely a one-to-one reflection of the structural network. Several theories have been put forward to understand the relationship between structural and functional networks. However, it remains unclear how these theories can be unified. Two existing recent theories state that 1) functional networks can be explained by all possible walks in the structural network, which we will refer to as the series expansion approach, and 2) functional networks can be explained by a weighted combination of the eigenmodes of the structural network, the so-called eigenmode approach. To elucidate the unique or common explanatory power of these approaches to estimate functional networks from the structural network, we analysed the relationship between these two existing views. Using linear algebra, we first show that the eigenmode approach can be written in terms of the series expansion approach, i.e., walks on the structural network associated with different hop counts correspond to different weightings of the eigenvectors of this network. Second, we provide explicit expressions for the coefficients for both the eigenmode and series expansion approach. These theoretical results were verified by empirical data from Diffusion Tensor Imaging (DTI) and functional Magnetic Resonance Imaging (fMRI), demonstrating a strong correlation between the mappings based on both approaches. Third, we analytically and empirically demonstrate that the fit of the eigenmode approach to measured functional data is always at least as good as the fit of the series expansion approach, and that errors in the structural data lead to large errors of the estimated coefficients for the series expansion approach. Therefore, we argue that the eigenmode approach should be preferred over the series expansion approach. Results hold for eigenmodes of the weighted adjacency matrices as well as eigenmodes of the graph Laplacian. â€‹Taken together, these results provide an important step towards unification of existing theories regarding the structure-function relationships in brain networks.


Assuntos
Mapeamento Encefálico/métodos , Encéfalo , Imagem de Tensor de Difusão/métodos , Rede Nervosa , Adulto , Encéfalo/anatomia & histologia , Encéfalo/diagnóstico por imagem , Encéfalo/fisiologia , Conjuntos de Dados como Assunto , Humanos , Modelos Estatísticos , Rede Nervosa/anatomia & histologia , Rede Nervosa/diagnóstico por imagem , Rede Nervosa/fisiologia
14.
Netw Neurosci ; 4(1): 30-69, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32043043

RESUMO

The brain is a complex, multiscale dynamical system composed of many interacting regions. Knowledge of the spatiotemporal organization of these interactions is critical for establishing a solid understanding of the brain's functional architecture and the relationship between neural dynamics and cognition in health and disease. The possibility of studying these dynamics through careful analysis of neuroimaging data has catalyzed substantial interest in methods that estimate time-resolved fluctuations in functional connectivity (often referred to as "dynamic" or time-varying functional connectivity; TVFC). At the same time, debates have emerged regarding the application of TVFC analyses to resting fMRI data, and about the statistical validity, physiological origins, and cognitive and behavioral relevance of resting TVFC. These and other unresolved issues complicate interpretation of resting TVFC findings and limit the insights that can be gained from this promising new research area. This article brings together scientists with a variety of perspectives on resting TVFC to review the current literature in light of these issues. We introduce core concepts, define key terms, summarize controversies and open questions, and present a forward-looking perspective on how resting TVFC analyses can be rigorously and productively applied to investigate a wide range of questions in cognitive and systems neuroscience.

15.
J Neurooncol ; 147(1): 49-58, 2020 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-31953611

RESUMO

INTRODUCTION: Progression-free survival (PFS) in glioma patients varies widely, even when stratifying for known predictors (i.e. age, molecular tumor subtype, presence of epilepsy, tumor grade and Karnofsky performance status). Neuronal activity has been shown to accelerate tumor growth in an animal model, suggesting that brain activity may be valuable as a PFS predictor. We investigated whether postoperative oscillatory brain activity, assessed by resting-state magnetoencephalography is of additional value when predicting PFS in glioma patients. METHODS: We included 27 patients with grade II-IV gliomas. Each patient's oscillatory brain activity was estimated by calculating broadband power (0.5-48 Hz) in 56 epochs of 3.27 s and averaged over 78 cortical regions of the Automated Anatomical Labeling atlas. Cox proportional hazard analysis was performed to test the predictive value of broadband power towards PFS, adjusting for known predictors by backward elimination. RESULTS: Higher broadband power predicted shorter PFS after adjusting for known prognostic factors (n = 27; HR 2.56 (95% confidence interval (CI) 1.15-5.70); p = 0.022). Post-hoc univariate analysis showed that higher broadband power also predicted shorter overall survival (OS; n = 38; HR 1.88 (95% CI 1.00-3.54); p = 0.038). CONCLUSIONS: Our findings suggest that postoperative broadband power is of additional value in predicting PFS beyond already known predictors.


Assuntos
Neoplasias Encefálicas/diagnóstico , Neoplasias Encefálicas/cirurgia , Ondas Encefálicas , Glioma/diagnóstico , Glioma/cirurgia , Adulto , Biomarcadores Tumorais/fisiologia , Neoplasias Encefálicas/fisiopatologia , Proteínas Correpressoras , Feminino , Glioma/fisiopatologia , Humanos , Magnetoencefalografia , Masculino , Período Pós-Operatório , Prognóstico , Intervalo Livre de Progressão , Estudos Retrospectivos
16.
Radiology ; 294(3): 622-627, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-31961245

RESUMO

Background Although most patients with medically refractory temporal lobe epilepsy (TLE) experience seizure freedom after anterior temporal lobectomy, approximately 40% may continue to have seizures. Functional network integration, as measured with preoperative resting-state functional MRI, may help stratify patients who are more likely to experience postoperative seizure freedom. Purpose To relate preoperative resting-state functional MRI and surgical outcome in patients with medically refractory TLE. Materials and Methods Data from patients with medically intractable TLE were retrospectively analyzed. Patients underwent preoperative resting-state functional MRI between March 2010 and April 2013 and subsequent unilateral anterior temporal lobectomy. Postoperative seizure-free status was categorized using the Engel Epilepsy Surgery Outcome Scale. Global and regional resting-state functional MRI network properties on preoperative functional MRI scans related to integration were calculated and statistically compared between patients who experienced complete postoperative seizure freedom (Engel class IA) and all others (Engel class IB to class IV) using t tests and multiple logistic regression. Results Forty patients (mean age, 34 years ± 15 [standard deviation]; 21 female) were evaluated. Preoperative global network integration was different (P = .01) between patients who experienced seizure freedom after surgery and all other patients, with 9% lower leaf fraction and 10% lower tree hierarchy in patients with ongoing seizures. Preoperative regional network integration in the contralateral temporoinsular region was different (P = .04) between patients in these two groups. Specifically, the group-level leaf proportion was 59% lower in the entorhinal cortex, 73% lower in the inferior temporal gyrus, 43% lower in the temporal pole, and 69% lower in the insula in patients with ongoing seizures after surgery. When using multivariate regression, contralateral temporoinsular leaf proportion (P = .002) and epilepsy duration (P = .04) were predictive of postoperative seizure freedom, while age (P > .70) and age at seizure onset (P > .50) were not. Conclusion Lower network integration globally and involving the contralateral temporoinsular cortex on preoperative resting-state functional MRI scans is associated with ongoing postoperative seizures in patients with temporal lobe epilepsy. © RSNA, 2020.


Assuntos
Encéfalo , Epilepsia do Lobo Temporal , Imageamento por Ressonância Magnética , Descanso/fisiologia , Adulto , Encéfalo/diagnóstico por imagem , Encéfalo/fisiopatologia , Epilepsia do Lobo Temporal/diagnóstico por imagem , Epilepsia do Lobo Temporal/fisiopatologia , Epilepsia do Lobo Temporal/cirurgia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Período Pré-Operatório , Estudos Retrospectivos , Resultado do Tratamento , Adulto Jovem
17.
Brain ; 143(1): 150-160, 2020 01 01.
Artigo em Inglês | MEDLINE | ID: mdl-31730165

RESUMO

An efficient network such as the human brain features a combination of global integration of information, driven by long-range connections, and local processing involving short-range connections. Whether these connections are equally damaged in multiple sclerosis is unknown, as is their relevance for cognitive impairment and brain function. Therefore, we cross-sectionally investigated the association between damage to short- and long-range connections with structural network efficiency, the functional connectome and cognition. From the Amsterdam multiple sclerosis cohort, 133 patients (age = 54.2 ± 9.6) with long-standing multiple sclerosis and 48 healthy controls (age = 50.8 ± 7.0) with neuropsychological testing and MRI were included. Structural connectivity was estimated from diffusion tensor images using probabilistic tractography (MRtrix 3.0) between pairs of brain regions. Structural connections were divided into short- (length < quartile 1) and long-range (length > quartile 3) connections, based on the mean distribution of tract lengths in healthy controls. To determine the severity of damage within these connections, (i) fractional anisotropy as a measure for integrity; (ii) total number of fibres; and (iii) percentage of tract affected by lesions were computed for each connecting tract and averaged for short- and long-range connections separately. To investigate the impact of damage in these connections for structural network efficiency, global efficiency was computed. Additionally, resting-state functional connectivity was computed between each pair of brain regions, after artefact removal with FMRIB's ICA-based X-noiseifier. The functional connectivity similarity index was computed by correlating individual functional connectivity matrices with an average healthy control connectivity matrix. Our results showed that the structural network had a reduced efficiency and integrity in multiple sclerosis relative to healthy controls (both P < 0.05). The long-range connections showed the largest reduction in fractional anisotropy (z = -1.03, P < 0.001) and total number of fibres (z = -0.44, P < 0.01), whereas in the short-range connections only fractional anisotropy was affected (z = -0.34, P = 0.03). Long-range connections also demonstrated a higher percentage of tract affected by lesions than short-range connections, independent of tract length (P < 0.001). Damage to long-range connections was more strongly related to structural network efficiency and cognition (fractional anisotropy: r = 0.329 and r = 0.447. number of fibres r = 0.321 and r = 0.278. and percentage of lesions: r = -0.219; r = -0.426, respectively) than damage to short-range connections. Only damage to long-distance connections correlated with a more abnormal functional network (fractional anisotropy: r = 0.226). Our findings indicate that long-range connections are more severely affected by multiple sclerosis-specific damage than short-range connections. Moreover compared to short-range connections, damage to long-range connections better explains network efficiency and cognition.


Assuntos
Encéfalo/diagnóstico por imagem , Disfunção Cognitiva/diagnóstico por imagem , Esclerose Múltipla/diagnóstico por imagem , Substância Branca/diagnóstico por imagem , Adulto , Anisotropia , Encéfalo/fisiopatologia , Estudos de Casos e Controles , Disfunção Cognitiva/fisiopatologia , Disfunção Cognitiva/psicologia , Imagem de Tensor de Difusão , Feminino , Neuroimagem Funcional , Humanos , Imageamento por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Esclerose Múltipla/fisiopatologia , Esclerose Múltipla/psicologia , Vias Neurais/diagnóstico por imagem , Vias Neurais/fisiopatologia , Testes Neuropsicológicos , Substância Branca/fisiopatologia
18.
Brain Stimul ; 13(2): 318-326, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-31679906

RESUMO

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive neuromodulation technique to treat psychiatric disorders, such as obsessive-compulsive disorder (OCD). However, the rTMS response varies across subjects. OBJECTIVE/HYPOTHESIS: We hypothesize that baseline network properties of the rTMS target may help understand this variation and predict response. METHODS: Excitatory rTMS to the dorsolateral prefrontal cortex (dlPFC) was applied in 19 unmedicated OCD patients, while inhibitory dlPFC-rTMS was applied in 17 healthy controls. The vertex was used as an active control target (19 patients, 18 controls). The rTMS response was operationalized as the individual change in state distress rating during an emotion regulation task. At baseline, subjects underwent resting-state functional MRI. The brain network was constructed by calculating wavelet coherence between regional activity of regions in the Brainnetome atlas. Local and integrative static connectivity and the dynamic network role of the target were calculated. Baseline target region network features were non-parametrically correlated to rTMS response. RESULTS: In the dlPFC-stimulated patients, greater local connectivity (Kendall's Tau = -0.415, p = 0.013) and less promiscuous role of the target (Kendall's Tau = 0.389, p = 0.025) at baseline were related to greater distress reduction after excitatory rTMS. There were no significant associations in healthy subjects nor in the active control stimulated patients. CONCLUSIONS: Pre-treatment network topological indices predict rTMS-induced emotional response changes in OCD, such that greater baseline resting-state local connectivity and less temporal integration of the target region imply greater stimulation effects. These results may lead the way towards personalized neuromodulation in OCD.


Assuntos
Conectoma , Regulação Emocional , Transtorno Obsessivo-Compulsivo/terapia , Estimulação Magnética Transcraniana/métodos , Adulto , Feminino , Humanos , Imageamento por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Transtorno Obsessivo-Compulsivo/fisiopatologia , Córtex Pré-Frontal/diagnóstico por imagem , Córtex Pré-Frontal/fisiopatologia
19.
Neuroimage Clin ; 28: 102468, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33383608

RESUMO

Deficits in cognitive functioning are a common yet poorly understood symptom in Parkinson's disease (PD). Recent studies have highlighted the importance of (dynamic) interactions between resting-state networks for cognition, which remains understudied in PD. We investigated how altered (dynamic) functional interactions between brain networks relate to cognitive dysfunction in PD patients. In this fMRI study, 50 PD patients (mean age 65.5 years ± 6.27) on dopaminergic medication were studied cross-sectionally, and of this cohort 31 PD patients were studied longitudinally. MRI imaging and neuropsychological testing was performed at two time points, with a follow-up duration of approximately three years. Functional connectivity within and between seven resting-state networks was calculated (both statically and dynamically) and correlated with four neuropsychological test scores; a combined score of (four) executive tasks, a motor perseveration, memory, and category fluency task. Cognitive dysfunction was determined based on a longitudinal sample of age-matched healthy controls (n = 13). PD patients showed dysfunction on six out of seven cognitive tasks when compared to healthy controls. Severity of executive dysfunction was correlated with higher static and lower dynamic functional connectivity between deep gray matter regions and the frontoparietal network (DGM-FPN). Over time, declining executive function was related to increasing static DGM-FPN connectivity, together with changes of connectivity involving the dorsal attention network (amongst others with the ventral attention network). Static functional connectivity between the ventral and dorsal attention network correlated with motor perseveration. Our findings demonstrate that in PD patients, dysfunctional communication between (i) subcortical, fronto-parietal and attention networks mostly underlies worsening of executive functioning, (ii) attention networks are involved in motor perseveration.


Assuntos
Imageamento por Ressonância Magnética , Doença de Parkinson , Idoso , Encéfalo/diagnóstico por imagem , Mapeamento Encefálico , Função Executiva , Humanos , Vias Neurais/diagnóstico por imagem , Testes Neuropsicológicos , Doença de Parkinson/complicações , Doença de Parkinson/diagnóstico por imagem
20.
Netw Neurosci ; 3(4): 969-993, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31637334

RESUMO

Clinical network neuroscience, the study of brain network topology in neurological and psychiatric diseases, has become a mainstay field within clinical neuroscience. Being a multidisciplinary group of clinical network neuroscience experts based in The Netherlands, we often discuss the current state of the art and possible avenues for future investigations. These discussions revolve around questions like "How do dynamic processes alter the underlying structural network?" and "Can we use network neuroscience for disease classification?" This opinion paper is an incomplete overview of these discussions and expands on ten questions that may potentially advance the field. By no means intended as a review of the current state of the field, it is instead meant as a conversation starter and source of inspiration to others.

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