Hilde M. H. Braakman

Abnormal Modular Organization of Functional Networks in Cognitively Impaired Children with Frontal Lobe Epilepsy

Many children with frontal lobe epilepsy (FLE) have significant cognitive comorbidity, for which the underlying mechanism has not yet been unraveled, but is likely related to disturbed cerebral network integrity. Using resting-state fMRI, we investigated whether cerebral network characteristics are associated with epilepsy and cognitive comorbidity. We included 37 children with FLE and 41 healthy age-matched controls. Cognitive performance was determined by means of a computerized visual searching task. A connectivity matrix for 82 cortical and subcortical brain regions was generated for each subject by calculating the inter-regional correlation of the fMRI time signals. From the connectivity matrix, graph metrics were calculated and the anatomical configuration of aberrant connections and modular organization was investigated. Both patients and controls displayed efficiently organized networks. However, FLE patients displayed a higher modularity, implying that subnetworks are less interconnected. Impaired cognition was associated with higher modularity scores and abnormal modular organization of the brain, which was mainly expressed as a decrease in long-range and an increase in interhemispheric connectivity in patients. We showed that network modularity analysis provides a sensitive marker for cognitive impairment in FLE and suggest that abnormally interconnected functional subnetworks of the brain might underlie the cognitive problems in children with FLE.

Frontal lobe connectivity and cognitive impairment in pediatric frontal lobe epilepsy

Purpose:  Cognitive impairment is frequent in children with frontal lobe epilepsy (FLE), but its etiology is unknown. With functional magnetic resonance imaging (fMRI), we have explored the relationship between brain activation, functional connectivity, and cognitive functioning in a cohort of pediatric patients with FLE and healthy controls.

Cognitive and behavioral complications of frontal lobe epilepsy in children: A review of the literature

Frontal lobe epilepsy (FLE) is considered the second most common type of the localization‐related epilepsies of childhood. Still, the etiology of FLE in children, its impact on cognitive functioning and behavior, as well as the response to antiepileptic drug treatment in children has not been sufficiently studied. This review focuses on these aspects of FLE in childhood, and reveals that FLE in childhood is most often cryptogenic, and impacts on a broad range of cognitive functions. The nature and severity of cognitive deficits are highly variable, although impaired attention and executive functions are most frequent. Young age at seizure onset is the only potential risk factor for poor cognitive outcome that has been consistently reported. The behavioral disturbances associated with FLE are also highly variable, although attention deficit/hyperactivity disorder seems most frequent. In 40% of children with FLE satisfactory seizure control could not be achieved. This is a higher percentage than reported for the general population of children with epilepsy. Therefore, pediatric FLE, even if cryptogenic in nature, is frequently complicated by impairment of cognitive function, behavioral disturbances, and therapy‐resistance. Given the impact of these complications, there is a need for studies of the etiology of frontal lobe epilepsy‐associated cognitive and behavioral disturbances, as well as pharmacotherapy‐resistance.

Tract Specific Reproducibility of Tractography Based Morphology and Diffusion Metrics

Introduction The reproducibility of tractography is important to determine its sensitivity to pathological abnormalities. The reproducibility of tract morphology has not yet been systematically studied and the recently developed tractography contrast Tract Density Imaging (TDI) has not yet been assessed at the tract specific level. Materials and Methods Diffusion tensor imaging (DTI) and probabilistic constrained spherical deconvolution (CSD) tractography are performed twice in 9 healthy subjects. Tractography is based on common space seed and target regions and performed for several major white matter tracts. Tractograms are converted to tract segmentations and inter-session reproducibility of tract morphology is assessed using Dice similarity coefficient (DSC). The coefficient of variation (COV) and intraclass correlation coefficient (ICC) are calculated of the following tract metrics: fractional anisotropy (FA), apparent diffusion coefficient (ADC), volume, and TDI. Analyses are performed both for proximal (deep white matter) and extended (including subcortical white matter) tract segmentations. Results Proximal DSC values were 0.70–0.92. DSC values were 5–10% lower in extended compared to proximal segmentations. COV/ICC values of FA, ADC, volume and TDI were 1–4%/0.65–0.94, 2–4%/0.62–0.94, 3–22%/0.53–0.96 and 8–31%/0.48–0.70, respectively, with the lower COV and higher ICC values found in the proximal segmentations. Conclusion For all investigated metrics, reproducibility depended on the segmented tract. FA and ADC had relatively low COV and relatively high ICC, indicating clinical potential. Volume had higher COV but its moderate to high ICC values in most tracts still suggest subject-differentiating power. Tract TDI had high COV and relatively low ICC, which reflects unfavorable reproducibility.

Cognitive and behavioural findings in children with frontal lobe epilepsy

BACKGROUND Frontal Lobe Epilepsy (FLE) is the second most frequent type of partial epilepsy and its onset is generally in childhood. Though cognitive and behavioural impairments have been described as co-morbid disorders in epilepsy, their extent in FLE, particularly in children, remains unknown. AIMS In this study, we assess cognitive skills and behaviour in a cohort of paediatric FLE patients. METHODS We measured the performance of 71 children with cryptogenic FLE on intelligence tests, neuropsychological tests, and behavioural questionnaires. Age-dependent normative values were used for reference. Results were related to epilepsy-factors including age at epilepsy onset, duration of epilepsy, seizure frequency, localisation of the epileptic focus and drug load. RESULTS Paediatric FLE patients performed worse on intellectual and neuropsychological tests compared to reference values, and had a delay in school achievement. The performance of patients was typically worse on tasks measuring visual-spatial functions, memory, psychomotor speed and alertness. High seizure frequency was associated with lower scores on the arithmetic subtest of the intelligence scale; the other epilepsy-factors had no statistically significant influence on intelligence test or neuropsychological test outcome. Behavioural problems included attention problems, anxiety and internalising behaviour. These were not significantly related to epilepsy-factors. CONCLUSIONS Children with cryptogenic FLE show a broad range of cognitive and behavioural impairments, compared to reference values. While high seizure frequency may affect performance on selected cognitive measures, other epilepsy-factors do not seem to influence cognition and behaviour. Study of micro-structural or functional brain abnormalities that underlie these cognitive and behavioural impairments are warranted.

Functional and structural network impairment in childhood frontal lobe epilepsy.

In childhood frontal lobe epilepsy (FLE), cognitive impairment and educational underachievement are serious, well-known co-morbidities. The broad scale of affected cognitive domains suggests wide-spread network disturbances that not only involves, but also extends beyond the frontal lobe. In this study we have investigated whole brain connectional properties of children with FLE in relation to their cognitive impairment and compared them with healthy controls. Functional connectivity (FC) of the networks was derived from dynamic fluctuations of resting state fMRI and structural connectivity (SC) was obtained from fiber tractograms of diffusion weighted MRI. The whole brain network was characterized with graph theoretical metrics and decomposed into modules. Subsequently, the graph metrics and the connectivity within and between modules were related to cognitive performance. Functional network disturbances in FLE were related to increased clustering, increased path length, and stronger modularity compared to healthy controls, which was accompanied by stronger within- and weaker between-module functional connectivity. Although structural path length and clustering appeared normal in children with FLE, structural modularity increased with stronger cognitive impairment. It is concluded that decreased coupling between large-scale functional network modules is a hallmark for impaired cognition in childhood FLE.

Rimonabant induces partial seizures in a patient with a history of generalized epilepsy.

To the Editors: Rimonabant (N-piperidino-5-(4-chlorophenyl)-1-(2,4dichlorophenyl)-4-methyl-3-pyrazole-carboxamide) was the first U.S. Food and Drug Administration (FDA)– approved cannabinoid CB1 receptor antagonist for the treatment of overweight. Rimonabant is effective in the treatment of obesity-related disorders, as it reduces food intake and body weight, and it is associated with a beneficial effect on different metabolic parameters and cardiovascular risk factors linked to overweight (Despr s et al., 2005; Pi-Sunyer et al., 2006; Scheen et al., 2006). We report herein on a 52-year-old obese man with a history of hypertension, diabetes mellitus, and idiopathic generalized epilepsy. Between the age of 4 and 15 years, he had absences and two generalized tonic–clonic seizures. Except for one generalized seizure triggered by the consumption of too much alcohol at the age of 30, he had been seizure free and discontinued antiepileptic drug treatment more than 20 years ago. Because of overweight and other cardiovascular risk factors, including hypertension and diabetes mellitus, he started rimonabant 20 mg/day in order to reduce weight. Two months later, he had nocturnal partial seizures consisting of a stereotypical feeling of falling into a deep hole. Often, this sensation was followed by right leg jerks lasting, on average, 3 min. These seizures were totally different from the generalized seizures he had in his youth. After rimonabant withdrawal the seizures disappeared. A few weeks later he restarted rimonabant and 3 days later, his partial seizures returned. While on rimonabant, routine and sleep-deprivation encephalography (EEG) studies were performed, showing frequent epileptiform paroxysms, consisting of generalized irregular slow waves intermingled with frontal and temporal spikes and focal epileptiform abnormalities in the left temporal lobe. Revision of older EEG studies (1982–1990) showed the same generalized and focal epileptiform abnormalities. Magnetic resonance imaging (MRI) of the brain and an ictal glucose level were normal. Because neither structural nor metabolic causes of these partial seizures could be revealed and a strong relationship with the use of rimonabant was supposed, he was strongly advised to discontinue rimonabant. Again the seizures disappeared immediately after rimonabant withdrawal. Three months after rimonabant withdrawal a sleep-deprived EEG showed mainly focal (left > right) temporally located epileptiform discharges and generalized irregular slow-wave paroxysms. This case report is the first to describe that rimonabant induces seizures in humans with a history of epilepsy and/or with epileptiform discharges on EEG. Mouse models have demonstrated that activation of the cannabinoid CB1 receptor is responsible for neuroprotection, as cannabinoids possess anticonvulsive properties (Wallace et al., 2002; Monory et al., 2006). Cannabinoid CB1 receptor blockade by rimonabant significantly reduced seizure threshold in mice (Wallace et al., 2002). Endocannabinoid signaling is impaired in patients with epilepsy, as the expression of CB1 receptor mRNA is downregulated and CB1 receptors are lost in key regions in epileptogenesis, including the dental gyrus (Lud nyi et al., 2008). Cannabinoid CB1 receptor antagonists, such as rimonabant, are thus theoretically likely to also reduce seizure threshold in humans due to blocking of CB1 receptors. Hence, the information leaflet reads that rimonabant should be used with caution by patients with epilepsy, because it may aggravate existing seizures. However, seizure occurrence in humans using rimonabant has not been reported previously. In October 2008, the approval of rimonabant was withdrawn in the European Union owing to concerns over potential side effects, mainly its association with depressive disorders and suicide. In conclusion, cannabinoid CB1 receptor antagonists can provoke epileptic seizures in formerly seizure-free epileptic patients, especially in cases in which EEG shows epileptiform discharges. This observation adds to the already known side effects of depression and suicide, and to observations on the key role of cannabinoid CB1 receptors in epileptogenesis in mouse models. Because new cannabinoid receptor antagonists are now being developed and will enter clinical trials in the near future, it is very important to monitor the development of epileptic seizures.

Microstructural and functional MRI studies of cognitive impairment in epilepsy.

Cognitive impairment is the most common comorbidity in children with epilepsy, but its pathophysiology and predisposing conditions remain unknown. Clinical epilepsy characteristics are not conclusive in determining cognitive outcome. Because many children with epilepsy do not have macrostructural magnetic resonance imaging (MRI) abnormalities, the underlying substrate for cognitive impairment may be found at the microstructural or functional level. In the last two decades, new MRI techniques have been developed that have the potential to visualize microstructural or functional abnormalities associated with cognitive impairment. These include volumetric MRI, voxel‐based morphometry (VBM), diffusion tensor imaging (DTI), MR spectroscopy (MRS), and functional MRI (fMRI). All of these techniques have shed new light on various aspects associated with, or underlying, cognitive impairment, although their use in epilepsy has been limited and focused mostly on adults. Therefore, in this review, the use of all these different MRI techniques to unravel cognitive impairment in epilepsy is discussed both in adults and children with epilepsy. Volumetric MRI and VBM have revealed significant volume losses in the area of the seizure focus as well as in distant areas. DTI adds evidence of loss of integrity of connections from the seizure focus to distant areas as well as between distant areas. MRS and fMRI have shown impaired function both in the area of the seizure focus as well as in distant structures. For this review we have compiled and compared findings from the various techniques to conclude that cognitive impairment in epilepsy results from a network disorder in which the (micro)structures as well as the functionality can be disturbed.

Pediatric frontal lobe epilepsy: white matter abnormalities and cognitive impairment.

Cognitive impairment is frequent in children with frontal lobe epilepsy (FLE). Its etiology remains unknown. With diffusion tensor imaging, we have studied cerebral white matter properties and associations with cognitive functioning in children with FLE and healthy controls.

Aetiology of cognitive impairment in children with frontal lobe epilepsy

Cognitive impairment is frequent in children with frontal lobe epilepsy (FLE), but its aetiology is unknown. MRI scans often reveal no structural brain abnormalities that could explain the cognitive impairment. This does not exclude more subtle morphological abnormalities that can only be detected by automated morphometric techniques.