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Children and adults with genetic generalized epilepsy may have focal clinical seizure symptoms as well as electroencephalographic (EEG) findings. This may pose a diagnostic challenge to clinicians, especially when concomitant focal neuroimaging findings exist and the epilepsy is medically refractory. We sought to highlight the challenges that clinicians may face through the description of 2 children with suspected genetic generalized epilepsy who had both focal seizure symptoms and EEG/neuroimaging findings and underwent invasive EEG monitoring. Ultimately, invasive monitoring failed to demonstrate a focal origin for the seizures in both cases, and instead confirmed the presence of genetic generalized epilepsy. We demonstrate that ≥3-Hz generalized monomorphic spike and waves are less likely to represent secondary bilateral synchrony, that focal neuroimaging findings may not always be causal and that repeated hyperventilation is an essential activation procedure for genetic generalized epilepsy.

Treatment-resistant epilepsy is a common and debilitating neurological condition, for which neurosurgical cure is possible. Despite undergoing nearly identical ablation procedures however, individuals with treatment-resistant epilepsy frequently exhibit heterogeneous outcomes. We hypothesized that treatment response may be related to the brain regions to which MR-guided laser ablation volumes are functionally connected. To test this, we mapped the resting-state functional connectivity of surgical ablations that either resulted in seizure freedom (N = 11) or did not result in seizure freedom (N = 16) in over 1,000 normative connectomes. There was no difference seizure outcome with respect to the anatomical location of the ablations, and very little overlap between ablation areas was identified using the Dice Index. Ablations that did not result in seizure-freedom were preferentially connected to a number of cortical and subcortical regions, as well as multiple canonical resting-state networks. In contrast, ablations that led to seizure-freedom were more functionally connected to prefrontal cortices. Here, we demonstrate that underlying normative neural circuitry may in part explain heterogenous outcomes following ablation procedures in different brain regions. These findings may ultimately inform target selection for ablative epilepsy surgery based on normative intrinsic connectivity of the targeted volume.

Epilepsy is associated with disruption of integration in distributed networks, together with altered localization for functions such as expressive language. The relation between atypical network connectivity and altered localization is unknown. In the current study we tested whether atypical expressive language laterality was associated with the alteration of large-scale network integration in children with medically-intractable localization-related epilepsy (LRE). Twenty-three right-handed children (age range 8-17) with medically-intractable LRE performed a verb generation task in fMRI. Language network activation was identified and the Laterality index (LI) was calculated within the pars triangularis and pars opercularis. Resting-state data from the same cohort were subjected to independent component analysis. Dual regression was used to identify associations between resting-state integration and LI values. Higher positive values of the LI, indicating typical language localization were associated with stronger functional integration of various networks including the default mode network (DMN). The normally symmetric resting-state networks showed a pattern of lateralized connectivity mirroring that of language function. The association between atypical language localization and network integration implies a widespread disruption of neural network development. These findings may inform the interpretation of localization studies by providing novel insights into reorganization of neural networks in epilepsy., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Typical childhood development is characterized by the emergence of intrinsic connectivity networks (ICNs) by way of internetwork segregation and intranetwork integration. The impact of childhood epilepsy on the maturation of ICNs is, however, poorly understood. The developmental trajectory of ICNs in 26 children (8-17 years) with localization-related epilepsy and 28 propensity-score matched controls was evaluated using graph theoretical analysis of whole brain connectomes from resting-state functional magnetic resonance imaging (fMRI) data. Children with epilepsy demonstrated impaired development of regional hubs in nodes of the salience and default mode networks (DMN). Seed-based connectivity and hierarchical clustering analysis revealed significantly decreased intranetwork connections, and greater internetwork connectivity in children with epilepsy compared to controls. Significant interactions were identified between epilepsy duration and the expected developmental trajectory of ICNs, indicating that prolonged epilepsy may cause progressive alternations in large-scale networks throughout childhood. DMN integration was also associated with better working memory, whereas internetwork segregation was associated with higher full-scale intelligence quotient scores. Furthermore, subgroup analyses revealed the thalamus, hippocampus, and caudate were weaker hubs in children with secondarily generalized seizures, relative to other patient subgroups. Our findings underscore that epilepsy interferes with the developmental trajectory of brain networks underlying cognition, providing evidence supporting the early treatment of affected children., (Copyright © 2014 Wiley Periodicals, Inc.)

This article describes a pattern classification algorithm for pediatric epilepsy using fMRI language-related activation maps. 122 fMRI datasets from a control group (64) and localization related epilepsy patients (58) provided by five children's hospitals were used. Each subject performed an auditory description decision task. Using the artificial data as training data, incremental Principal Component Analysis was used in order to generate the feature space while overcoming memory requirements of large datasets. The nearest-neighbor classifier (NNC) and the distance-based fuzzy classifier (DFC) were used to perform group separation into left dominant, right dominant, bilateral, and others. The results show no effect of age, age at seizure onset, seizure duration, or seizure etiology on group separation. Two sets of parameters were significant for group separation, the patient vs. control populations and handedness. Of the 122 real datasets, 90 subjects gave the same classification results across all the methods (three raters, LI, bootstrap LI, NNC, and DFC). For the remaining datasets, 18 cases for the IPCA-NNC and 21 cases for the IPCA-DFC agreed with the majority of the five classification results (three visual ratings and two LI results). Kappa values vary from 0.59 to 0.73 for NNC and 0.61 to 0.75 for DFC, which indicate good agreement between NNC or DFC with traditional methods. The proposed method as designed can serve as an alternative method to corroborate existing LI and visual rating classification methods and to resolve some of the cases near the boundaries in between categories., (Copyright © 2013 Wiley Periodicals, Inc.)

Synchronization of neural oscillations is thought to integrate distributed neural populations into functional cell assemblies. Epilepsy is widely regarded as a disorder of neural synchrony. Knowledge is scant, however, regarding whether ictal changes in synchrony involving epileptogenic cortex are expressed similarly across various frequency ranges. Cortical regions involved in epileptic networks also exhibit pathological high-frequency oscillations (pHFOs, >80 Hz), which are increasingly utilized as biomarkers of epileptogenic tissue. It is uncertain how pHFO amplitudes are related to epileptic network connectivity. By calculating phase-locking values among intracranial electrodes implanted in children with intractable epilepsy, we constructed ictal connectivity networks and performed graph theoretical analysis to characterize their network properties at distinct frequency bands. Ictal data from 17 children were analyzed with a hierarchical mixed-effects model adjusting for patient-level covariates. Epileptogenic cortex was defined in two ways: 1) a hypothesis-driven method using the visually defined seizure-onset zone and 2) a data-agnostic method using the high-frequency amplitude of each electrode. Epileptogenic cortex exhibited a logarithmic decrease in interregional functional connectivity at high frequencies (>30 Hz) during seizure initiation and propagation but not at termination. At slower frequencies, conversely, epileptogenic cortex expressed a relative increase in functional connectivity. Our findings suggest that pHFOs reflect epileptogenic network interactions, yielding theoretical support for their utility in the presurgical evaluation of intractable epilepsy. The view that abnormal network synchronization plays a critical role in ictogenesis and seizure dynamics is supported by the observation that functional isolation of epileptogenic cortex at high frequencies is absent at seizure termination.

Atypical functional magnetic resonance imaging (fMRI) language patterns may be identified by visual inspection or by region of interest (ROI)-based laterality indices (LI) but are constrained by a priori assumptions. We compared a data-driven novel application of principal component analysis (PCA) to conventional methods. We studied 122 fMRI data sets from control and localization-related epilepsy patients provided by five children's hospitals. Each subject performed an auditory description decision task. The data sets, acquired with different scanners but similar acquisition parameters, were processed through fMRIB software library to obtain 3D activation maps in standard space. A PCA analysis was applied to generate the decisional space and the data cluster into three distinct activation patterns. The classified activation maps were interpreted by (1) blinded reader rating based on predefined language patterns and (2) by language area ROI-based LI (i.e., fixed threshold vs. bootstrap approaches). The different classification results were compared through κ inter-rater agreement statistics. The unique decisional space classified activation maps into three clusters (a) lower intensity typical language representation, (b) higher intensity typical, as well as (c) higher intensity atypical representation. Inter-rater agreements among the three raters were excellent (Fleiss κ = 0.85, P = 0.05). There was substantial to excellent agreement between the conventional visual rating and LI methods (κ = 0.69-0.82, P = 0.05). The PCA-based method yielded excellent agreement with conventional methods (κ = 0.82, P = 0.05). The automated and data-driven PCA decisional space segregates language-related activation patterns in excellent agreement with current clinical rating and ROI-based methods., (Copyright © 2012 Wiley Periodicals, Inc., a Wiley company.)

Purpose: This pilot study aims to test the reliability and clinical validity of the assessment of cerebrovascular reactivity (CVR) with real-time blood-oxygen-level-dependent (BOLD) fMRI (rtCVR) in comparison with standard off-line processing in children with moyamoya disease., Methods: Eight consecutive pediatric patients with moyamoya cerebral arteriopathy underwent BOLD fMRI CVR studies either on a 1.5-T or on a 3-T scanner with breath-holding techniques in six patients and under general anesthesia (GA) in three patients. One patient had undergone CVR study initially without and later with GA, and another had undergone CVR study before and after a revascularization procedure. The off-line and real-time processing of the data was done, and the results were compared for general quality and adequacy of the study (scale 0-3, 3 being the best) and for the presence or absence of abnormal reactivity and the location, pattern, and extent of abnormal reactivity., Results: A total of 20 CVR series each was studied on real-time functional MRI and off-line analysis (eight patients, ten sessions, two series per session). All eight sessions done under GA were rated as quality class 3 (100 %), whereas only 5 of the 12 (41.7 %) studies with breath-holding technique were considered to be of best quality (class 3). In comparison to the off-line processing, the overall sensitivity of the rtCVR technique was 90 % with a specificity of 100 %., Conclusions: rtCVR assessment in children with moyamoya disease is feasible, and the results are comparable to that of standard off-line analysis. The results from off-line analysis are only available, at the earliest, several hours after the MRI has been completed. rtCVR can overcome this difficulty and may be equally reliable.

Individuals born preterm can demonstrate reductions in brain volume, cortical surface area and thickness. However, the extent of these neuroanatomical deficits and the relation among these measures in middle childhood, a critical developmental period, have not been determined. We assessed differences in brain structure by acquiring high-resolution T(1)-weighted scans in 25 children born very preterm (<32 weeks gestational age) without significant post-natal neurological sequelae and 32 age-matched term-born children (7-10 years). Children born very preterm had decreased brain volume, surface area and cortical thickness compared to term-born children. Furthermore, children born preterm did not display the robust relation between total brain volume and basal ganglia and thalamic volume apparent in the term-born children. Cortical thickness analyses revealed that the cortex was thinner for children born preterm than term-born children in the anterior cingulate cortex/supplementary motor area, isthmus of the cingulate gyrus, right superior temporal sulcus, right anterior insula, postcentral gyrus and precuneus. Follow-up analyses revealed that right precuneus thickness was correlated with gestational age. Thus, even without significant postnatal medical sequelae, very preterm-born children showed atypical brain structure and developmental patterns in areas related to higher cognitive function. Disruptions of the typical neurodevelopmental trajectory in the third trimester of pregnancy likely underlie these differences persisting into middle childhood.

To study the neural networks reorganization in pediatric epilepsy, a consortium of imaging centers was established to collect functional imaging data. Common paradigms and similar acquisition parameters were used. We studied 122 children (64 control and 58 LRE patients) across five sites using EPI BOLD fMRI and an auditory description decision task. After normalization to the MNI atlas, activation maps generated by FSL were separated into three sub-groups using a distance method in the principal component analysis (PCA)-based decisional space. Three activation patterns were identified: (1) the typical distributed network expected for task in left inferior frontal gyrus (Broca's) and along left superior temporal gyrus (Wernicke's) (60 controls, 35 patients); (2) a variant left dominant pattern with greater activation in IFG, mesial left frontal lobe, and right cerebellum (three controls, 15 patients); and (3) activation in the right counterparts of the first pattern in Broca's area (one control, eight patients). Patients were over represented in Groups 2 and 3 (P < 0.0004). There were no scanner (P = 0.4) or site effects (P = 0.6). Our data-driven method for fMRI activation pattern separation is independent of a priori notions and bias inherent in region of interest and visual analyses. In addition to the anticipated atypical right dominant activation pattern, a sub-pattern was identified that involved intensity and extent differences of activation within the distributed left hemisphere language processing network. These findings suggest a different, perhaps less efficient, cognitive strategy for LRE group to perform the task., (Copyright © 2010 Wiley-Liss, Inc.)

We compared frequency and power of neonatal EEG delta brush rapid oscillatory activity (ROA) using multiple band frequency analysis (MBFA) in three groups; pre-term (PT, post-conceptional age 33-35.6 weeks, n=5); full-term (FT, 39.4-40.6 weeks, n=5) and pre-term or full-term with phenobarbital exposure (PB, n=5). Mean number of delta brushes analyzed was 29.4 (range 26-47) in PT, 20.8 (14-33) in FT and 20 (7-37) in PB. Mean frequency+/-standard deviation (s.d.) was 16.9+/-2.1 Hz (range 15-20 Hz) in PT, 17.3+/-1.9 Hz (15-20 Hz) in FT and 16.1+/-1.6 Hz (14-19 Hz) in PB. Mean power+/-s.d. was 22.9+/-6.2 microV(2) (range 16-39 microV(2)) in PT, 11.9+/-4.1 microV(2) (7-19 microV(2)) in FT and 17.1+/-6.2 microV(2) (9-26 microV(2)) in PB. Power was significantly higher in PT than FT (p<0.005). Power after merging PB into respective PT (PT', n=8) and FT (FT', n=7) groups, remained significantly higher in PT' (mean+/-s.d. 21.8+/-7.4 microV(2)) than FT' (11.4+/-3.6 microV(2)) (p<0.05). We characterise ROA in delta brushes in maturing neonates using MBFA, which may provide additional information for assessing future seizure recurrence and epilepsy risk., (Copyright (c) 2009 Elsevier B.V. All rights reserved.)

Purpose: To understand the rapid dynamic changes of ictal intracranial high-frequency oscillations (HFOs) in neocortical epilepsy. Methods: We integrated multiple band frequency analysis and brain-surface topographic maps of HFOs from ictal subdural EEG (SDEEG) recordings. We used SDEEG to record partial seizures consisting of right-arm jerks with secondary generalization in a 17-year-old right-handed girl. We selected 20-s EEG sections that included preclinical seizure recordings. We averaged the HFO power between 60 and 120 Hz for 25 selected electrodes, made topographic maps from these averaged powers, and superimposed the maps on the brain-surface image. We filmed consecutive HFO maps at a 10-ms frame rate. Results: Before clinical seizure onset, high-power HFOs emerged at the superior portion of the left precentral gyrus, then appeared in the middle of the left postcentral gyrus, and subsequently reverberated between both regions as well as the posterior portion of the left postcentral gyrus. Right-arm extension and facial grimacing started as the HFO power decreased. As generalized tonic–clonic seizures evolved, HFO power increased but remained within the central region. Conclusions: Topographic movies of intracranial HFOs on the brain surface allow visualization of the dynamic ictal changes in neocortical epilepsy. [ABSTRACT FROM AUTHOR]

Electrophysiological and hemodynamic measures of human brain activity have been shown to distinguish between episodes of encoding items that are later recalled versus those that are not recalled (Paller and Wagner, 2002). Using intracranial recordings from 793 widespread cortical and subcortical sites in 10 epileptic patients undergoing invasive monitoring, we compared oscillatory power at frequencies ranging from 2 to 64 Hz as participants studied lists of common nouns. Significant increases in oscillatory power during encoding predicted subsequent recall, with this effect predominantly in the 4-8 Hz (theta) and 28-64 Hz (gamma) frequency bands. Sites exhibiting increased theta activity during successful encoding were clustered in right temporal and frontal cortex, whereas those exhibiting increased gamma activity appeared bilaterally at widespread cortical locations. These findings implicate theta and gamma oscillatory activity, across a widespread network of cortical regions, in the formation of new episodic memories. [ABSTRACT FROM AUTHOR]