Benjamin R. Morgan

Resilience of developing brain networks to interictal epileptiform discharges is associated with cognitive outcome

The effects of interictal epileptiform discharges on neurocognitive development in children with medically-intractable epilepsy are poorly understood. Such discharges may have a deleterious effect on the brains intrinsic connectivity networks, which reflect the organization of functional networks at rest, and in turn on neurocognitive development. Using a combined functional magnetic resonance imaging-magnetoencephalography approach, we examine the effects of interictal epileptiform discharges on intrinsic connectivity networks and neurocognitive outcome. Functional magnetic resonance imaging was used to determine the location of regions comprising various intrinsic connectivity networks in 26 children (7-17 years), and magnetoencephalography data were reconstructed from these locations. Inter-regional phase synchronization was then calculated across interictal epileptiform discharges and graph theoretical analysis was applied to measure event-related changes in network topology in the peri-discharge period. The magnitude of change in network topology (network resilience/vulnerability) to interictal epileptiform discharges was associated with neurocognitive outcomes and functional magnetic resonance imaging networks using dual regression. Three main findings are reported: (i) large-scale network changes precede and follow interictal epileptiform discharges; (ii) the resilience of network topologies to interictal discharges is associated with stronger resting-state network connectivity; and (iii) vulnerability to interictal discharges is associated with worse neurocognitive outcomes. By combining the spatial resolution of functional magnetic resonance imaging with the temporal resolution of magnetoencephalography, we describe the effects of interictal epileptiform discharges on neurophysiological synchrony in intrinsic connectivity networks and establish the impact of interictal disruption of functional networks on cognitive outcome in children with epilepsy. The association between interictal discharges, network changes and neurocognitive outcomes suggests that it is of clinical importance to suppress discharges to foster more typical brain network development in children with focal epilepsy.

Impaired development of intrinsic connectivity networks in children with medically intractable localization-related epilepsy

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. Hum Brain Mapp 35:5686–5700, 2014.

The neural correlates of visuo-spatial working memory in children with autism spectrum disorder: effects of cognitive load

BackgroundResearch on the neural bases of cognitive deficits in autism spectrum disorder (ASD) has shown that working memory (WM) difficulties are associated with abnormalities in the prefrontal cortex. However, cognitive load impacts these findings, and no studies have examined the relation between WM load and neural underpinnings in children with ASD. Thus, the current study determined the effects of cognitive load on WM, using a visuo-spatial WM capacity task in children with and without ASD with functional magnetic resonance imaging (fMRI).MethodsWe used fMRI and a 1-back colour matching task (CMT) task with four levels of difficulty to compare the cortical activation patterns associated with WM in children (7–13 years old) with high functioning autism (N = 19) and matched controls (N = 17) across cognitive load.ResultsPerformance on CMT was comparable between groups, with the exception of one difficulty level. Using linear trend analyses, the control group showed increasing activation as a function of difficulty level in frontal and parietal lobes, particularly between the highest difficulty levels, and decreasing activation as a function of difficulty level in the posterior cingulate and medial frontal gyri. In contrast, children with ASD showed increasing activation only in posterior brain regions and decreasing activation in the posterior cingulate and medial frontal gyri, as a function of difficulty level. Significant differences were found in the precuneus, dorsolateral prefrontal cortex and medial premotor cortex, where control children showed greater positive linear relations between cortical activity and task difficulty level, particularly at the highest difficulty levels, but children with ASD did not show these trends.ConclusionsChildren with ASD showed differences in activation in the frontal and parietal lobes—both critical substrates for visuo-spatial WM. Our data suggest that children with ASD rely mainly on posterior brain regions associated with visual and lower level processing, whereas controls showed activity in frontal lobes related to the classic WM network. Findings will help guide future work by localizing areas of vulnerability to developmental disturbances.

Deep grey matter growth predicts neurodevelopmental outcomes in very preterm children.

We evaluated whether the volume and growth rate of critical brain structures measured by MRI in the first weeks of life following very preterm (<32/40 weeks) birth could predict subsequent neurodevelopmental outcomes at 4 years of age. A significant proportion of children born very prematurely have cognitive deficits, but these problems are often only detected at early school age. Structural T2-weighted magnetic resonance images were acquired in 96 very preterm neonates scanned within 2 weeks of birth and 70 of these at term-equivalent age. An automated 3D image analysis procedure was used to measure the volume of selected brain structures across all scans and time points. At 4 years of age, 53 children returned for neuropsychological assessments evaluating IQ, language and visual motor integration. Associations with maternal education and perinatal measures were also explored. Multiple regression analyses revealed that growth of the caudate and globus pallidus between preterm birth and term-equivalent age predicted visual motor integration scores after controlling for sex and gestational age. Further associations were found between caudate and putamen growth with IQ and language scores. Analyses at either preterm or term-equivalent age only found associations between normalized deep grey matter growth and visual motor integration scores at term-equivalent age. Maternal education levels were associated with measures of IQ and language, but not visual motor integration. Thalamic growth was additionally linked with perinatal measures and presence of white matter lesions. These results highlight deep grey matter growth rates as promising biomarkers of long-term outcomes following very preterm birth, and contribute to our understanding of the brain-behaviour relations in these children.

Oscillations, Networks, and Their Development: MEG Connectivity Changes with Age

Magnetoencephalographic (MEG) investigations of inter‐regional amplitude correlations have yielded new insights into the organization and neurophysiology of resting‐state networks (RSNs) first identified using fMRI. Inter‐regional MEG amplitude correlations in adult RSNs have been shown to be most prominent in alpha and beta frequency ranges and to express strong congruence with RSN topologies found using fMRI. Despite such advances, little is known about how oscillatory connectivity in RSNs develops throughout childhood and adolescence. This study used a novel fMRI‐guided MEG approach to investigate the maturation of resting‐state amplitude correlations in physiologically relevant frequency ranges within and among six RSNs in 59 participants, aged 6–34 years. We report age‐related increases in inter‐regional amplitude correlations that were largest in alpha and beta frequency bands. In contrast to fMRI reports, these changes were observed both within and between the various RSNs analyzed. Our results provide the first evidence of developmental changes in spontaneous neurophysiological connectivity in source‐resolved RSNs, which indicate increasing integration within and among intrinsic functional brain networks throughout childhood, adolescence, and early adulthood. Hum Brain Mapp 35:5249–5261, 2014.

The neurodevelopmental differences of increasing verbal working memory demand in children and adults

Working memory (WM) – temporary storage and manipulation of information in the mind – is a key component of cognitive maturation, and structural brain changes throughout development are associated with refinements in WM. Recent functional neuroimaging studies have shown that there is greater activation in prefrontal and parietal brain regions with increasing age, with adults showing more refined, localized patterns of activations. However, few studies have investigated the neural basis of verbal WM development, as the majority of reports examine visuo-spatial WM. We used fMRI and a 1-back verbal WM task with six levels of difficulty to examine the neurodevelopmental changes in WM function in 40 participants, twenty-four children (ages 9–15 yr) and sixteen young adults (ages 20–25 yr). Children and adults both demonstrated an opposing system of cognitive processes with increasing cognitive demand, where areas related to WM (frontal and parietal regions) increased in activity, and areas associated with the default mode network decreased in activity. Although there were many similarities in the neural activation patterns associated with increasing verbal WM capacity in children and adults, significant changes in the fMRI responses were seen with age. Adults showed greater load-dependent changes than children in WM in the bilateral superior parietal gyri, inferior frontal and left middle frontal gyri and right cerebellum. Compared to children, adults also showed greater decreasing activation across WM load in the bilateral anterior cingulate, anterior medial prefrontal gyrus, right superior lateral temporal gyrus and left posterior cingulate. These results demonstrate that while children and adults activate similar neural networks in response to verbal WM tasks, the extent to which they rely on these areas in response to increasing cognitive load evolves between childhood and adulthood.

Thalamocortical connectivity is enhanced following functional hemispherotomy for intractable lateralized epilepsy

Although developmental outcomes may improve following functional hemispherotomy for lateralized, catastrophic childhood epilepsy, the neuronal processes mediating these improvements are unknown. We report the case of a 14-year-old child with neurocognitive impairment who underwent functional hemispherotomy with longitudinal resting-state fMRI. Compared with preoperative fMRI, we report significantly more robust thalamo-default mode network connectivity on postoperative neuroimaging. Furthermore, we show decreased connectivity to nodes within the disconnected hemisphere, providing direct evidence that functional interactions are dependent upon structural connectivity. Since the vascular supply to these nodes remains intact, although they are disconnected from the remainder of the brain, these findings also confirm that blood-oxygen level dependent oscillations are driven primarily by neuronal activity. The current study highlights the importance of thalamocortical interactions in the understanding of neural oscillations and cognitive function, and their impairment in childhood epilepsy.

Patient Phenotypes Associated With Outcomes After Aneurysmal Subarachnoid Hemorrhage A Principal Component Analysis

Background and Purpose— Predictors of outcome after aneurysmal subarachnoid hemorrhage have been determined previously through hypothesis-driven methods that often exclude putative covariates and require a priori knowledge of potential confounders. Here, we apply a data-driven approach, principal component analysis, to identify baseline patient phenotypes that may predict neurological outcomes. Methods— Principal component analysis was performed on 120 subjects enrolled in a prospective randomized trial of clazosentan for the prevention of angiographic vasospasm. Correlation matrices were created using a combination of Pearson, polyserial, and polychoric regressions among 46 variables. Scores of significant components (with eigenvalues >1) were included in multivariate logistic regression models with incidence of severe angiographic vasospasm, delayed ischemic neurological deficit, and long-term outcome as outcomes of interest. Results— Sixteen significant principal components accounting for 74.6% of the variance were identified. A single component dominated by the patients’ initial hemodynamic status, World Federation of Neurosurgical Societies score, neurological injury, and initial neutrophil/leukocyte counts was significantly associated with poor outcome. Two additional components were associated with angiographic vasospasm, of which one was also associated with delayed ischemic neurological deficit. The first was dominated by the aneurysm-securing procedure, subarachnoid clot clearance, and intracerebral hemorrhage, whereas the second had high contributions from markers of anemia and albumin levels. Conclusions— Principal component analysis, a data-driven approach, identified patient phenotypes that are associated with worse neurological outcomes. Such data reduction methods may provide a better approximation of unique patient phenotypes and may inform clinical care as well as patient recruitment into clinical trials. Clinical Trial Registration— URL: http://www.clinicaltrials.gov. Unique identifier: NCT00111085.

Associations of Perinatal Clinical and Magnetic Resonance Imaging Measures with Developmental Outcomes in Children Born Very Preterm.

OBJECTIVE To identify perinatal risk factors associated with long-term neurocognitive and behavioral impairments in children born very preterm using a multivariate, partial least squares approach. STUDY DESIGN Twenty-seven perinatal clinical and magnetic resonance imaging measures were collected at birth and during the neonatal intensive care stay for 105 neonates born very preterm (≤ 32 weeks gestational age). One-half of the children returned for neuropsychological assessments at 2 and 4 years of age. Parent-reported behavioral measures were also obtained at 4 years of age. Three partial least squares analyses were performed to determine associations between clinical and radiologic measures with cognitive outcomes at 2 and 4 years of age, as well as with behavioral measures at 4 years of age. RESULTS Within the first components of each analysis, only intrauterine growth restriction, male sex, and absence of antenatal corticosteroid use were associated with poorer cognitive and language ability at 2 and 4 years of age, accounting for 79.6% and 71.4% of the total variance, respectively. In addition, white matter injury at term-equivalent age contributed to more problematic internalizing behaviors, behavioral symptoms, and impaired executive function at 4 years of age, accounting for 67.9% of the total variance. CONCLUSIONS Using this data-driven multivariate approach, specific measures in prenatal and early postnatal life are shown to be selectively and significantly associated with cognitive and behavioral outcomes in children born very preterm. Early detection of risk factors can help inform prognoses of children at greatest risk of long-term impairments.

Atypical language laterality is associated with large-scale disruption of network integration in children with intractable focal epilepsy

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.