Maarten J. Vaessen

Functional connectivity of dissociation in patients with psychogenic non-epileptic seizures.

Introduction Psychogenic non-epileptic seizures (PNES) resemble epileptic seizures, but lack epileptiform brain activity. Instead, the cause is assumed to be psychogenic. An abnormal coping strategy may be exhibited by PNES patients, as indicated by their increased tendency to dissociate. Investigation of resting-state networks may reveal altered routes of information and emotion processing in PNES patients. The authors therefore investigated whether PNES patients differ from healthy controls in their resting-state functional connectivity characteristics and whether these connections are associated with the tendency to dissociate. Methods 11 PNES patients without psychiatric comorbidity and 12 healthy controls underwent task-related paradigms (picture-encoding and Stroop paradigms) and resting-state functional MRI (rsfMRI). Global cognitive performance was tested using the Ravens Matrices test and participants completed questionnaires for evaluating dissociation. Functional connectivity analysis on rsfMRI was based on seed regions extracted from task-related fMRI activation maps. Results The patients displayed a significantly lower cognitive performance and significantly higher dissociation scores. No significant differences were found between the picture-encoding and Stroop colour-naming activation maps between controls and patients with PNES. However, functional connectivity maps from the rsfMRI were statistically different. For PNES patients, stronger connectivity values between areas involved in emotion (insula), executive control (inferior frontal gyrus and parietal cortex) and movement (precentral sulcus) were observed, which were significantly associated with dissociation scores. Conclusion The abnormal, strong functional connectivity in PNES patients provides a neurophysiological correlate for the underlying psychoform and somatoform dissociation mechanism where emotion can influence executive control, resulting in altered motor function (eg, seizure-like episodes).

Loss of network efficiency associated with cognitive decline in chronic epilepsy.

Objective: To study the relation between possibly altered whole brain topology and intellectual decline in chronic epilepsy, a combined study of neurocognitive assessment and graph theoretical network analysis of fMRI was performed. Methods: Forty-one adult patients with cryptogenic localization-related epilepsy and 23 healthy controls underwent an intelligence test and fMRI with a silent-word generation paradigm. A set of undirected graphs was constructed by cross-correlating the signal time series of 893 cortical and subcortical regions. Possible changes in cerebral network efficiency were assessed by performing graph theoretical network analysis. Results: Healthy subjects displayed efficient small world properties, characterized by high clustering and short path lengths. On the contrary, in patients with epilepsy a disruption of both local segregation and global integration was found. An association of more pronounced intellectual decline with more disturbed local segregation was observed in the patient group. The effect of antiepileptic drug use on cognitive decline was mediated by decreased clustering. Conclusions: These findings support the hypothesis that chronic localization-related epilepsy causes cognitive deficits by inducing global cerebral network changes instead of a localized disruption only. Whether this is the result of epilepsy per se or the use of antiepileptic drugs remains to be elucidated. For application in clinical practice, future studies should address the relevance of altered cerebral network topology in prediction of cognitive deficits and monitoring of therapeutic interventions.

The effect and reproducibility of different clinical DTI gradient sets on small world brain connectivity measures

Advances in computational network analysis have enabled the characterization of topological properties in large scale networks including the human brain. Information on structural networks in the brain can be obtained in-vivo by performing tractography on diffusion tensor imaging (DTI) data. However, little is known about the reproducibility of network properties derived from whole brain tractography data, which has important consequences for minimally detectable abnormalities or changes over time. Moreover, acquisition parameters, such as the number of gradient directions and gradient strength, possibly influence network metrics and the corresponding reproducibility derived from tractography data. The aim of the present study is twofold: (i) to determine the effect of several clinically available DTI sampling schemes, differing in number of gradient directions and gradient amplitude, on small world metrics and (ii) to evaluate the interscan reproducibility of small world metrics. DTI experiments were conducted on six healthy volunteers scanned twice. Probabilistic tractography was performed to reconstruct structural connections between regions defined from an anatomical atlas. The observed reproducibility of the network measures was high, reflected by low values for the coefficient of variation (<3.8%), advocating the use of graph theoretical measurements to study neurological diseases. Small world metrics were dependent on the choice of DTI gradient scheme and showed stronger connectivity with increasing directional resolution. The interscan reproducibility was not dependent on the gradient scheme. These findings should be considered when comparing results across studies using different gradient schemes or designing new studies.

White Matter Network Abnormalities Are Associated with Cognitive Decline in Chronic Epilepsy

Patients with chronic epilepsy frequently display cognitive comorbidity and might have widespread network abnormalities outside the epileptic zone, which might affect a variety of cognitive functions and global intelligence. We aimed to study the role of white matter connectivity in cognitive comorbidity. Thirty-nine patients with nonsymptomatic localization-related epilepsy and varying degrees of cognitive impairment and 23 age-matched healthy controls were included. Whole brain white matter networks were constructed from fiber tractography. Weighted graph theoretical analysis was performed to study white matter network abnormalities associated with epilepsy and cognition. Patients with severe cognitive impairment showed lower clustering (a measure of brain network segregation) and higher path length (a measure of brain network integration) compared with the healthy controls and patients with little or no cognitive impairment, whereas whole brain white matter volume did not differ. Correlation analyses revealed that IQ and cognitive impairment were strongly associated with clustering and path lengths. This study revealed impaired white matter connectivity, associated with cognitive comorbidity in patients with chronic epilepsy. As whole brain white matter volumes were preserved in the patient group, our results suggest an important role for the network topology rather than volumetric changes, in epilepsy with cognitive decline.

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.