Epilepsy surgery outcome and functional network alterations in longitudinal MEG: A minimum spanning tree analysis

ObjectivesInternet addiction (IA) has been associated with widespread brain alterations. Functional connectivity (FC) and network analysis results related to IA are inconsistent between studies, and how network hubs change is not known. The aim of this study was to evaluate functional and topological networks using an unbiased minimum spanning tree (MST) analysis on electroencephalography (EEG) data in IA and healthy control (HC) college students.MethodsIn this study, Young's internet addiction test was used as an IA severity measure. EEG recordings were obtained in IA (n = 30) and HC participants (n = 30), matched for age and sex, during rest. The phase lag index (PLI) and MST were applied to analyze FC and network topology. We expected to obtain evidence of underlying alterations in functional and topological networks related to IA.ResultsIA participants showed higher delta FC between left‐side frontal and parieto‐occipital areas compared to the HC group (p < 0.001), global MST measures revealed a more star‐like network in IA participants in the upper alpha and beta bands, and the occipital brain region was relatively less important in the IA relative to the HC group in the lower band. The correlation results were consistent with the MST results: higher IA severity correlated with higher Max degree and kappa, and lower eccentricity and diameter.ConclusionsFunctional networks of the IA group were characterized by increased FC, a more random organization, and a decrease of relative functional importance of the visual processing area. Taken together, these alterations can help us understand the influence of IA to brain mechanism.

Magnetoencephalography (MEG) records the magnetic field generated by electrical activity of cortical neurons. The signal is not distorted or attenuated, and it is contactless recording that can be performed comfortably even for longer than an hour. It has excellent and decent temporal resolution, especially when it is combined with the patient's own brain magnetic resonance imaging (magnetic source imaging). Data of MEG and electroencephalography are not mutually exclusive and it is recorded simultaneously and interpreted together. MEG has been shown to be useful in detecting the irritative zone in both lesional and nonlesional epilepsy surgery. It has provided valuable and additive information regarding the lesion that should be resected in epilepsy surgery. Better outcomes in epilepsy surgery were related to the localization of the irritative zone with MEG. The value of MEG in epilepsy surgery is recruiting more patients to epilepsy surgery and providing critical information for surgical planning. MEG cortical mapping is helpful in younger pediatric patients, especially when the epileptogenic zone is close to the eloquent cortex. MEG is also used in both basic and clinical research of epilepsy other than surgery. MEG is a valuable diagnostic modality for diagnosis and treatment, as well as research in epilepsy.

To obtain prospective data regarding seizures, anxiety, depression, and quality of life (QOL) outcomes after resective epilepsy surgery. The authors characterized resective epilepsy surgery patients prospectively at yearly intervals for seizure outcome, QOL, anxiety, and depression, using standardized instruments and patient interviews. Of 396 patients who underwent resective surgical procedures, 355 were followed for at least 1 year. Of these, 75% achieved a 1-year remission at some time during follow-up; patients with medial temporal (77%) were more likely than neocortical resections (56%) to achieve remission (p = 0.01). Relapse occurred in 59 (22%) patients who remitted, more often in medial temporal (24%) than neocortical (4%) resected patients (p = 0.02). QOL, anxiety, and depression all improved dramatically within 3 months after surgery (p < 0.0001), with no significant difference based on seizure outcome. After 3 months, QOL in seizure-free patients further improved gradually, and patients with seizures showed gradual declines. By 12 and 24 months, overall QOL and its epilepsy-targeted and physical health domains were significantly different in the two outcome groups. (Anxiety and depression scores also gradually diverged, with improvements in seizure-free and declines in continued seizure groups, but differences were not significant.) Resective surgery for treatment of epilepsy significantly reduces seizures, most strikingly after medial temporal resection (77% 1 year remission) compared to neocortical resection (56% 1 year remission). Resective epilepsy surgery has a gradual but lasting effect on QOL, but minimal effects on anxiety and depression. Longer follow-up will be essential to determine ultimate seizure, QOL, and psychiatric outcomes of epilepsy surgery.

Magnetoencephalography (MEG) is a well-known technique in the presurgical evaluation of epilepsy patients. Like EEG, it can detect and localize epileptic activity. Epilepsy surgery can be used to evaluate MEG source localizations. Resection volumes were determined in 33 epilepsy surgery patients. The resection volume, taken together with the post-operative outcome, was used to evaluate MEG results. The scattering MEG localizations of interictal epileptic activity were represented by an ellipsoidal volume. Using this MEG results ellipsoid, it was demonstrated that a high coverage by the resection volume and a small distance to the resection volume are both correlated to a favourable outcome; in addition, a homogeneous distribution of MEG localizations is correlated to a favourable outcome. This study shows that MEG source localization can help to delineate epileptic activity and, along with other techniques, should be taken into account for epilepsy surgery.

Cross-sectional and longitudinal studies in active duty and veteran cohorts have both demonstrated that deployment-acquired traumatic brain injury (TBI) is an independent risk factor for developing post-traumatic stress disorder (PTSD), beyond confounds such as combat exposure, physical injury, predeployment TBI, and pre-deployment psychiatric symptoms. This study investigated how resting-state brain networks differ between individuals who developed PTSD and those who did not following deployment-acquired TBI. Participants included postdeployment veterans with deployment-acquired TBI history both with and without current PTSD diagnosis. Graph metrics, including small-worldness, clustering coefficient, and modularity, were calculated from individually constructed whole-brain networks based on 5-min eyes-open resting-state magnetoencephalography (MEG) recordings. Analyses were adjusted for age and premorbid IQ. Results demonstrated that participants with current PTSD displayed higher levels of small-worldness, F(1,12) = 5.364, p < 0.039, partial eta squared = 0.309, and Cohen's d = 0.972, and clustering coefficient, F(1, 12) = 12.204, p < 0.004, partial eta squared = 0.504, and Cohen's d = 0.905, than participants without current PTSD. There were no between-group differences in modularity or the number of modules present. These findings are consistent with a hyperconnectivity hypothesis of the effect of TBI history on functional networks rather than a disconnection hypothesis, demonstrating increased levels of clustering coefficient rather than a decrease as might be expected; however, these results do not account for potential changes in brain structure. These results demonstrate the potential pathological sequelae of changes in functional brain networks following deployment-acquired TBI and represent potential neurobiological changes associated with deployment-acquired TBI that may increase the risk of subsequently developing PTSD.

As the Apolipoprotein E (APOE) ɛ4 allele is a major genetic risk factor for sporadic Alzheimer's disease (AD), which has been suggested as a disconnection syndrome manifested by the disruption of white matter (WM) integrity and functional connectivity (FC), elucidating the subtle brain structural and functional network changes in cognitively normal ɛ4 carriers is essential for identifying sensitive neuroimaging based biomarkers and understanding the preclinical AD-related abnormality development. We first constructed functional network on the basis of resting-state functional magnetic resonance imaging and a structural network on the basis of diffusion tensor image. Using global, local and nodal efficiencies of these two networks, we then examined (i) the differences of functional and WM structural network between cognitively normal ɛ4 carriers and non-carriers simultaneously, (ii) the sensitivity of these indices as biomarkers, and (iii) their relationship to behavior measurements, as well as to cholesterol level. For ɛ4 carriers, we found reduced global efficiency significantly in WM and marginally in FC, regional FC dysfunctions mainly in medial temporal areas, and more widespread for WM network. Importantly, the right parahippocampal gyrus (PHG.R) was the only region with simultaneous functional and structural damage, and the nodal efficiency of PHG.R in WM network mediates the APOE ɛ4 effect on memory function. Finally, the cholesterol level correlated with WM network differently than with the functional network in ɛ4 carriers. Our results demonstrated ɛ4-specific abnormal structural and functional patterns, which may potentially serve as biomarkers for early detection before the onset of the disease.

The robustness of dynamical properties of neuronal networks against structural damages is a central problem in computational and experimental neuroscience. Research has shown that the cortical network of a healthy brain works near a critical state and, moreover, that functional neuronal networks often have scale-free and small-world properties. In this work, we study how the robustness of simple functional networks at criticality is affected by structural defects. In particular, we consider a two-dimensional Ising model at the critical temperature and investigate how its functional network changes with the increasing degree of structural defects. We show that the scale-free and small-world properties of the functional network at criticality are robust against large degrees of structural lesions while the system remains below the percolation limit. Although the Ising model is only a conceptual description of a two-state neuron, our research reveals fundamental robustness properties of functional networks derived from classical statistical mechanics models.

Although epilepsy surgery, especially temporal lobe epilepsy surgery, is well established to control seizures in patients remaining on antiepileptic drug (AED) treatment, less information is available about how many seizure-free surgical patients will relapse after discontinuation of AEDs under medical supervision. A literature review yielded six retrospective clinical observations. After planned discontinuation of AEDs in patients rendered seizure free after epilepsy surgery, most often various forms of temporal lobe surgery, the mean percentage recurrence rate in adults in four studies was 33.8%[95% confidence interval (CI), 32.4-35.2%], with maximum follow-up ranging from 1 to 5 years. Seizure recurrence increased during the follow-up of 1 to 3 years and occurred within 3 years of AED discontinuation. In one study of children with temporal lobe epilepsy, the recurrence rate was 20%. More than 90% of adult patients with seizure recurrence regained seizure control with reinstitution of previous AED therapy. Seizure recurrence was unaffected by the duration of postoperative AED treatment; as a consequence, delaying discontinuation beyond 1 to 2 years of complete postoperative seizure control seems to have no added benefit. The occurrence of rare seizures or auras after surgery did not eliminate the possibility of eventual successful AED discontinuation. AED discontinuation is associated with a seizure recurrence in one in three patients rendered seizure free by epilepsy surgery. These results will be useful in counseling patients about discontinuing AED treatment after successful epilepsy surgery.

Neurological disorder can cause functional network changes in white matter (WM). However, changes in the WM functional network in children with drug-resistant temporal lobe epilepsy (DRTLE) require further clarification. Therefore, we combine graph theory with resting-state functional magnetic resonance imaging (rs-fMRI) and T1-weighted imaging (T1WI) to investigate the topological features of the WM network in children with DRTLE, discover potential biomarkers, and understand the underlying neurological mechanisms. We included 91 children (43 with DRTLE and 48 healthy controls), acquiring structural and functional MRI data to construct WM functional networks. Graph theory was applied to evaluate topological differences and their correlation with onset age, disease duration and cognitive measures. A Support Vector Machine model classified individuals with DRTLE based on WM connectivity, with accuracy validated through leave-one-out cross-validation. The global topological properties of the WM network in children with DRTLE were altered, manifesting as an imbalance between global integration and segregation Local nodal efficiency changes in the association fibers exhibited reduced information transfer and centrality at several nodes. Conversely, commissural and projection fibers displayed increased network properties. Cognitive metrics correlated with nodal disturbances. The classification model achieved 73.6 % accuracy and an area under the curve (AUC) of 0.744. This indicates that the WM functional network in DRTLE presents with anomalies in the topological attributes, which are associated with cognitive impairments. The WM functional connectivity may serve as valuable indicators for clinical classification of the condition. The insights provided have augmented our understanding of the complex neurological mechanisms involved in epilepsy.

Recent evidence increasingly associates network disruption in brain organization with multiple neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), a rare terminal disease. However, the comparability of brain network characteristics across different studies remains a challenge for conventional graph theoretical methods. One suggested method to address this issue is minimum spanning tree (MST) analysis, which provides a less biased comparison. Here, we assessed the novel application of MST network analysis to hemodynamic responses recorded by functional near-infrared spectroscopy (fNIRS) neuroimaging modality, during an activity-based paradigm to investigate hypothetical disruptions in frontal functional brain network topology as a marker of the executive dysfunction, one of the most prevalent cognitive deficit reported across ALS studies. We analyzed data recorded from nine participants with ALS and ten age-matched healthy controls by first estimating functional connectivity, using phase-locking value (PLV) analysis, and then constructing the corresponding individual and group MSTs. Our results showed significant between-group differences in several MST topological properties, including leaf fraction, maximum degree, diameter, eccentricity, and degree divergence. We further observed a global shift toward more centralized frontal network organizations in the ALS group, interpreted as a more random or dysregulated network in this cohort. Moreover, the similarity analysis demonstrated marginally significantly increased overlap in the individual MSTs from the control group, implying a reference network with lower topological variation in the healthy cohort. Our nodal analysis characterized the main local hubs in healthy controls as distributed more evenly over the frontal cortex, with slightly higher occurrence in the left prefrontal cortex (PFC), while in the ALS group, the most frequent hubs were asymmetrical, observed primarily in the right prefrontal cortex. Furthermore, it was demonstrated that the global PLV (gPLV) synchronization metric is associated with disease progression, and a few topological properties, including leaf fraction and tree hierarchy, are linked to disease duration. These results suggest that dysregulation, centralization, and asymmetry of the hemodynamic-based frontal functional network during activity are potential neuro-topological markers of ALS pathogenesis. Our findings can possibly support new bedside assessments of the functional status of ALS’ brain network and could hypothetically extend to applications in other neurodegenerative diseases.

The correlation of magnetoencephalography to intracranial EEG in localizing the epileptogenic zone: A study of the surgical resection outcome

Thalamic atrophy is known to be one of the most important predictors for clinical dysfunction in multiple sclerosis (MS). As the thalamus is highly connected to many cortical areas, this suggests that thalamic atrophy is associated with disruption of cortical functional networks. We investigated this thalamo-cortical system to explain the presence of physical and cognitive problems in MS. Functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) were performed in 86 MS patients and 21 healthy subjects. We computed cortical functional networks for fMRI and MEG by respectively the Pearson's correlation coefficient and the phase lag index using the same automated anatomical labeling atlas for both modalities. Thalamo-cortical functional connectivity was only estimated using fMRI. We computed conventional network metrics such as clustering coefficient and path length and analyzed the minimum spanning tree (MST), a subnetwork and backbone of the original network. MS patients showed reduced thalamic volumes and increased thalamo-cortical connectivity. MEG cortical functional networks showed a lower level of integration in MS in terms of the MST, whereas fMRI cortical networks did not differ between groups. Lower integration of MEG cortical functional networks was both related to thalamic atrophy as well as to increased thalamo-cortical functional connectivity in fMRI and to worse cognitive and clinical status. This study demonstrated for the first time that thalamic atrophy is associated with global disruption of cortical functional networks in MS and this global disruption of network activity was related to worse cognitive and clinical function in MS. Hum Brain Mapp 36:603-618, 2015. © 2014 Wiley Periodicals, Inc.

Characterization of EEG-based functional brain networks in myotonic dystrophy type 1

SummaryInfant-directed speech (IDS) plays a central role in early communication, initially expressing emotion and later supporting language development. This study examined how the brain’s functional network organization responds to infant-directed speech (IDS) versus adult-directed speech (ADS) during early infancy. Electroencephalography (EEG) data were collected from 49 healthy infants at 0, 4, and 9 months as they listened to the same fairy tale spoken in both IDS and ADS. Brain connectivity was assessed using phase lag synchronization across six frequency bands, and network topology was characterized using minimum spanning tree analysis. The delta network showed greater hierarchical and cost-efficient organization in response to IDS, particularly over frontal regions, with these differences becoming more pronounced with age. Over time, network integration increased and shifted toward the left hemisphere. These findings highlight how functional brain networks dynamically adapt to socially relevant speech input, reflecting the evolving communicative function of IDS during the first year of life.

Epilepsy surgery has been questioned for patients with low IQ, since a low cognitive level is taken to indicate a widespread disturbance of cerebral function with unsatisfactory prognosis following resective surgery. The prevalence of epilepsy in patients with cognitive dysfunction is, however, higher than in the general population and the epilepsy is often more severe and difficult to treat. It is therefore important to try to clarify whether IQ predicts seizure outcome after resective epilepsy surgery. The Swedish National Epilepsy Surgery Register, which includes data on all epilepsy surgery procedures in Sweden since 1990, was analysed for all resective procedures performed 1990-99. Sustained seizure freedom with or without aura at the 2-year follow-up was analysed as a function of pre-operative IQ level categorized as IQ <50, IQ 50-69 and IQ >or=70 and was also adjusted for the following variables: age at epilepsy onset, age at surgery, pre-operative seizure frequency, pre-operative neurological impairment, resection type and histopathological diagnosis. Four hundred and forty-eight patients underwent resective epilepsy surgery in Sweden from 1990 to 1999 and completed the 2-year follow-up: 72 (16%) had IQ <70, (18 with IQ <50 and 54 with IQ 50-69) and 376 IQ >or=70. There were 313 adults and 135 children <or=18 years. Three hundred and twenty-five patients underwent temporal lobe resections (TLR) and 123 underwent various extratemporal resections (XTLR). At the 2-year follow-up, 56% (252/448) of the patients were seizure free: 22% (4/18) in the IQ <50 group, 37% (20/54) in the IQ 50-69 group and 61% (228/376) in the IQ >or=70 group. There was a significant relation between IQ category and seizure freedom [odds ratio (OR) 0.41, 95% confidence interval (CI) 0.27-0.62] and this held also when adjusting for clinical variables [OR 0.58 (95% CI 0.35-0.95)]. In this population-based epilepsy surgery series, IQ level was shown to be an independent predictor of seizure freedom at the 2-year follow-up. However, many of the low-IQ patients benefit from surgery, especially patients with lesions. Low IQ should not exclude patients from resective epilepsy surgery, but is an important prognostic factor to consider in the counselling process.