Functional connectivity and language impairment in cryptogenic localization-related epilepsy

Conversational production and comprehension: fMRI-evidence reminiscent of but deviant from the classical Broca-Wernicke model

A key question in research on the neurobiology of language is to which extent the language production and comprehension systems share neural infrastructure, but this question has not been addressed in the context of conversation. We utilized a public fMRI dataset where 24 participants engaged in unscripted conversations with a confederate outside the scanner, via an audio-video link. We provide evidence indicating that the two systems share neural infrastructure in the left-lateralized perisylvian language network, but diverge regarding the level of activation in regions within the network. Activity in the left inferior frontal gyrus was stronger in production compared to comprehension, while comprehension showed stronger recruitment of the left anterior middle temporal gyrus and superior temporal sulcus, compared to production. Although our results are reminiscent of the classical Broca-Wernicke model, the anterior (rather than posterior) temporal activation is a notable difference from that model. This is one of the findings that may be a consequence of the conversational setting, another being that conversational production activated what we interpret as higher-level socio-pragmatic processes. In conclusion, we present evidence for partial overlap and functional asymmetry of the neural infrastructure of production and comprehension, in the above-mentioned frontal vs temporal regions during conversation.

Disruptions in modular structure and network integration of language-related network predict language performance in temporal lobe epilepsy: Evidence from graph-based analysis

OBJECTIVE

Temporal lobe epilepsy (TLE) is a network disorder that alters the total organization of the language-related network. Task-based functional magnetic resonance imaging (fMRI) aimed at functional connectivity is a direct method to investigate how the network is reorganized. However, such studies are scarce and represented mostly by the resting-state analysis of the individual connections between regions. To fill this gap, we used a graph-based analysis, which allows us to cover the total language-related network changes, such as disruptions in an integration/segregation balance, during a language task in TLE.

METHODS

We collected task-based fMRI data with sentence completion from 19 healthy controls and 28 people with left TLE. Using graph-based analysis, we estimated how the language-related network segregated into modules and tested whether they differed between groups. We evaluated the total network integration and the integration within modules. To assess intermodular integration, we considered the number and location of connector hubs-regions with high connectivity.

RESULTS

The language-related network was differently segregated during language processing in the groups. While healthy controls showed a module consisting of left perisylvian regions, people with TLE exhibited a bilateral module formed by the anterior language-related areas and a module in the left temporal lobe, reflecting hyperconnectivity within the epileptic focus. As a consequence of this reorganization, there was a statistical tendency that the dominance of the intramodular integration over the total network integration was greater in TLE, which predicted language performance. The increase in the number of connector hubs in the right hemisphere, in turn, was compensatory in TLE.

SIGNIFICANCE

Our study provides insights into the reorganization of the language-related network in TLE, revealing specific network changes in segregation and integration. It confirms reduced global connectivity and compensation across the healthy hemisphere, commonly observed in epilepsy. These findings advance the understanding of the network-based reorganizational processes underlying language processing in TLE.

Effect of Oxcarbazepine on Language Function in Patients With Newly Diagnosed Pediatric Epilepsy

BACKGROUND AND PURPOSE

This study aimed to determine the effects of oxcarbazepine (OXC) on the language function of patients with pediatric epilepsy.

METHODS

We assessed the language abilities of patients aged 5-17 years with newly diagnosed focal epilepsy and the same number of age-matched healthy children using the Test of Problem Solving (TOPS) and the Receptive and Expressive Vocabulary Test-Receptive (REVT-R). The Mean Length of Utterance-words (MLU-w) was used to estimate linguistic productivity before and after OXC initiation. All patients received OXC monotherapy with a starting dosage of 10 mg/kg/day for 1 week, which in some cases was increased to 30 mg/kg/day (or 1,200 mg/day).

RESULTS

The study finally included 41 pediatric patients (22 males and 19 females; age 9.9±3.0 years, mean±standard deviation). All language parameters of the TOPS improved significantly after initiating OXC (determining cause, 12.5±4.8-13.7±4.1 [p=0.016]; making inference, 15.6±5.6-17.4±6.4 [p<0.001]; and predicting, 9.8±5.0-11.6±4.5 [p=0.001]). However, patients who received OXC did not exhibit a significantly extended MLU-w (determining cause, p=0.493; making inference, p=0.386; and predicting, p=0.341). Receptive language scores also significantly increased after taking OXC (REVT-R: 121.0±43.1-129.4±43.8, p=0.002), but the percentage of development age to chronological age did not vary (REVT-developmental quotient: p=0.075).

CONCLUSIONS

Our results suggest that OXC is safe and preserves language function in patients with pediatric epilepsy.

Resting state network dynamic reconfiguration and neuropsychological functioning in temporal lobe epilepsy: An HD-EEG investigation

Temporal lobe epilepsy (TLE) is nowadays considered a network disorder impacting several cognitive domains. In this work we investigated dynamic network reconfiguration differences in patients with unilateral TLE compared to a healthy control group, focusing on two connectivity indices: flexibility and integration. We apply these indices for the first time to high-density EEG source-based functional connectivity. We observed that patients with TLE exhibited significantly lower flexibility than healthy controls in the Control, Default Mode and Attentive Dorsal networks, expressed in the delta, theta and alpha bands. In addition, patients with TLE displayed greater integration values across the majority of the resting state networks, especially in the delta, theta and gamma bands. Relevantly, a higher integration index in the Control, Attentive Dorsal and Visual networks in the delta band was correlated with lower performance in visual attention and executive functions. Moreover, a greater integration index in the gamma band of the Control, Somatomotor and Temporoparietal networks was related to lower long-term memory performance. These results suggest that patients with TLE display dysregulated network reconfiguration, with lower flexibility in the brain areas related to cognitive control and attention, together with excessive inter-network communication (integration index). Finally, the correlation between network integration and the reduced cognitive performance suggests a potential mechanism underlying specific alterations in neuropsychological profile of patients with TLE.

Understanding Language Reorganization With Neuroimaging: How Language Adapts to Different Focal Lesions and Insights Into Clinical Applications

When the language-dominant hemisphere is damaged by a focal lesion, the brain may reorganize the language network through functional and structural changes known as adaptive plasticity. Adaptive plasticity is documented for triggers including ischemic, tumoral, and epileptic focal lesions, with effects in clinical practice. Many questions remain regarding language plasticity. Different lesions may induce different patterns of reorganization depending on pathologic features, location in the brain, and timing of onset. Neuroimaging provides insights into language plasticity due to its non-invasiveness, ability to image the whole brain, and large-scale implementation. This review provides an overview of language plasticity on MRI with insights for patient care. First, we describe the structural and functional language network as depicted by neuroimaging. Second, we explore language reorganization triggered by stroke, brain tumors, and epileptic lesions and analyze applications in clinical diagnosis and treatment planning. By comparing different focal lesions, we investigate determinants of language plasticity including lesion location and timing of onset, longitudinal evolution of reorganization, and the relationship between structural and functional changes.

Multimodal connectome biomarkers of cognitive and affective dysfunction in the common epilepsies

Epilepsy is one of the most common chronic neurological conditions, traditionally defined as a disorder of recurrent seizures. Cognitive and affective dysfunction are increasingly recognized as core disease dimensions and can affect patient well-being, sometimes more than the seizures themselves. Connectome-based approaches hold immense promise for revealing mechanisms that contribute to dysfunction and to identify biomarkers. Our review discusses emerging multimodal neuroimaging and connectomics studies that highlight network substrates of cognitive/affective dysfunction in the common epilepsies. We first discuss work in drug-resistant epilepsy syndromes, that is, temporal lobe epilepsy, related to mesiotemporal sclerosis (TLE), and extratemporal epilepsy (ETE), related to malformations of cortical development. While these are traditionally conceptualized as ‘focal’ epilepsies, many patients present with broad structural and functional anomalies. Moreover, the extent of distributed changes contributes to difficulties in multiple cognitive domains as well as affective-behavioral challenges. We also review work in idiopathic generalized epilepsy (IGE), a subset of generalized epilepsy syndromes that involve subcortico-cortical circuits. Overall, neuroimaging and network neuroscience studies point to both shared and syndrome-specific connectome signatures of dysfunction across TLE, ETE, and IGE. Lastly, we point to current gaps in the literature and formulate recommendations for future research.

Epilepsy is increasingly recognized as a network disorder characterized by recurrent seizures as well as broad-ranging cognitive difficulties and affective dysfunction. Our manuscript reviews recent literature highlighting brain network substrates of cognitive and affective dysfunction in common epilepsy syndromes, namely temporal lobe epilepsy secondary to mesiotemporal sclerosis, extratemporal epilepsy secondary to malformations of cortical development, and idiopathic generalized epilepsy syndromes arising from subcortico-cortical pathophysiology. We discuss prior work that has indicated both shared and distinct brain network signatures of cognitive and affective dysfunction across the epilepsy spectrum, improves our knowledge of structure-function links and interindividual heterogeneity, and ultimately aids screening and monitoring of therapeutic strategies.

Functional Connectivity and Speech Entrainment Speech Entrainment Improves Connectivity Between Anterior and Posterior Cortical Speech Areas in Non-fluent Aphasia

BACKGROUND

Speech entrainment (SE), the online mimicking of an audio-visual speech model, has been shown to increase speech fluency in individuals with non-fluent aphasia. One theory that may explain why SE improves speech output is that it synchronizes functional connectivity between anterior and posterior language regions to be more similar to that of neurotypical speakers.

OBJECTIVES

The present study tested this by measuring functional connectivity between 2 regions shown to be necessary for speech production, and their right hemisphere homologues, in 24 persons with aphasia compared to 20 controls during both free (spontaneous) speech and SE.

METHODS

Regional functional connectivity in participants with aphasia were normalized to the control data. Two analyses were then carried out: (1) normalized functional connectivity was compared between persons with aphasia and controls during free speech and SE and (2) stepwise linear models with leave-one-out cross-validation including normed functional connectivity during both tasks and proportion damage to the left hemisphere as independent variables were created for each language score.

RESULTS

Left anterior-posterior functional connectivity and left posterior to right anterior functional connectivity were significantly more similar to connectivity of the control group during SE compared to free speech. Additionally, connectivity during free speech was more associated with language measures than connectivity during SE.

CONCLUSIONS

Overall, these results suggest that SE promotes normalization of functional connectivity (i.e., return to patterns observed in neurotypical controls), which may explain why individuals with non-fluent aphasia produce more fluent speech during SE compared to spontaneous speech.

Disrupted Functional Connectivity Within and Between Resting-State Networks in the Subacute Stage of Post-stroke Aphasia

Background: Post-stroke aphasia (PSA) results from brain network disorders caused by focal stroke lesions. However, it still remains largely unclear whether the impairment is present in intra- and internetwork functional connectivity (FC) within each resting-state network (RSN) and between RSNs in the subacute stage of PSA.

Objectives: This study aimed to investigate the resting-state FC within and between RSNs in patients with PSA and observe the relationships between FC alterations and Western Aphasia Battery (WAB) measures.

Methods: A total of 20 individuals with subacute PSA and 20 healthy controls (HCs) were recruited for functional MRI (fMRI) scanning, and only patients with PSA underwent WAB assessment. Independent component analysis was carried out to identify RSNs. Two-sample t-tests were used to calculate intra- and internetwork FC differences between patients with PSA and HCs. The results were corrected for multiple comparisons using the false discovery rate (FDR correction, p < 0.05). Partial correlation analysis was performed to observe the relationship between FC and WAB scores with age, gender, mean framewise displacement, and lesion volume as covariates (p < 0.05).

Results: Compared to HCs, patients with PSA showed a significant increase in intranetwork FC in the salience network (SN). For internetwork FC analysis, patients showed a significantly increased coupling between left frontoparietal network (lFPN) and SN and decreased coupling between lFPN and right frontoparietal network (rFPN) as well as between lFPN and posterior default mode network (pDMN) (FDR correction, p < 0.05). Finally, a significant positive correlation was found between the intergroup difference of FC (lFPN-rFPN) and auditory-verbal comprehension (p < 0.05).

Conclusion: Altered FC was revealed within and between multiple RSNs in patients with PSA at the subacute stage. Reduced FC between lFPN and rFPN was the key element participating in language destruction. These findings proved that PSA is a brain network disorder caused by focal lesions; besides, it may improve our understanding of the pathophysiological mechanisms of patients with PSA at the subacute stage.

Surviving (but not thriving) after cranial vault trauma: A case study from Transylvania

OBJECTIVE

To link an antemortem cranial injury on the left parietal bone with potential neurocognitive consequences.

MATERIALS

The skeleton of a male individual from a Székely archaeological site in Transylvania was examined. The skeleton was radiocarbon dated to Cal AD 1450 and AD 1640 and presented a well-healed antemortem penetrating cranial injury on the left parietal bone.

METHODS

Macroscopic and radiographic analyses were conducted and the cranium was also archived digitally with a Faro FreeStyle3D scanner. In addition, well-known literature from neuroscience was synthesized in order to better understand the likely neurological consequences of the injury.

RESULTS

The literature suggests that tasks of attention and working memory, sensory processing, language processing, and vision are affected when the parietal lobe of the brain is injured.

CONCLUSIONS

Burial 195 did not likely return to a 'normal' life after he survived the cranial injury.

SIGNIFICANCE

This study demonstrates that bioarcheological interpretations involving antemortem cranial injuries can be enhanced by collaboration with neuroscientists. Bioarcheological interpretations are improved when the consequences of soft tissue injuries are understood.

LIMITATIONS

This study was limited by a lack of historical documents relevant to the region, time period, and specific case study. In addition, interpretations are cautionary because brain functioning cannot be assessed in vivo in the absence of life.

SUGGESTIONS FOR FURTHER RESEARCH

Bioarcheologists who study antemortem cranial injuries should continue to collaborate with neuroscientists.

Reconfiguration dynamics of a language-and-memory network in healthy participants and patients with temporal lobe epilepsy

Current theoretical frameworks suggest that human behaviors are based on strong and complex interactions between cognitive processes such as those underlying language and memory functions in normal and neurological populations. We were interested in assessing the dynamic cerebral substrate of such interaction between language and declarative memory, as the composite function, in healthy controls (HC, N = 19) and patients with temporal lobe epilepsy (TLE, N = 16). Our assumption was that the language and declarative memory integration is based on a language-and-memory network (LMN) that is dynamic and reconfigures according to task demands and brain status. Therefore, we explored two types of LMN dynamics, a state reconfiguration (intrinsic resting-state compared to extrinsic state assessed with a sentence recall task) and a reorganization of state reconfiguration (TLE compared to HC). The dynamics was evaluated in terms of segregation (community or module detection) and integration (connector hubs). In HC, the level of segregation was the same in both states and the mechanism of LMN state reconfiguration was shown through module change of key language and declarative memory regions with integrative roles. In TLE patients, the reorganization of LMN state reconfiguration was reflected in segregation increase and extrinsic modules that were based on shorter-distance connections. While lateral and mesial temporal regions enabled state reconfiguration in HC, these regions showed reduced flexibility in TLE. We discuss our results in a connectomic perspective and propose a dynamic model of language and declarative memory functioning. We claim that complex and interactive cognitive functions, such as language and declarative memory, should be investigated dynamically, considering the interaction between cognitive networks.

Dynamic functional connectivity in temporal lobe epilepsy: a graph theoretical and machine learning approach

PURPOSE

Functional magnetic resonance imaging (fMRI) in resting state can be used to evaluate the functional organization of the human brain in the absence of any task or stimulus. The functional connectivity (FC) has non-stationary nature and consented to be varying over time. By considering the dynamic characteristics of the FC and using graph theoretical analysis and a machine learning approach, we aim to identify the laterality in cases of temporal lobe epilepsy (TLE).

METHODS

Six global graph measures are extracted from static and dynamic functional connectivity matrices using fMRI data of 35 unilateral TLE subjects. Alterations in the time trend of the graph measures are quantified. The random forest (RF) method is used for the determination of feature importance and selection of dynamic graph features including mean, variance, skewness, kurtosis, and Shannon entropy. The selected features are used in the support vector machine (SVM) classifier to identify the left and right epileptogenic sides in patients with TLE.

RESULTS

Our results for the performance of SVM demonstrate that the utility of dynamic features improves the classification outcome in terms of accuracy (88.5% for dynamic features compared with 82% for static features). Selecting the best dynamic features also elevates the accuracy to 91.5%.

CONCLUSION

Accounting for the non-stationary characteristics of functional connectivity, dynamic connectivity analysis of graph measures along with machine learning approach can identify the temporal trend of some specific network features. These network features may be used as potential imaging markers in determining the epileptogenic hemisphere in patients with TLE.

Evolution of Graph Theory in Dynamic Functional Connectivity for Lateralization of Temporal Lobe Epilepsy

Resting-state functional magnetic resonance imaging (rsfMRI) has described the functional architecture of the human brain in the absence of any task or stimulus. Since the functional connectivity (FC), has non-stationary nature, it is evidenced to be varying over time. Using dynamic functional connectivity, six graph theoretical characteristics were measured and compared between left and right temporal lobe epilepsy (TLE). We also obtain a trend for each characteristic in the time course of experiments. The results demonstrated that the static connectivity analysis failed to fully separate the left and right TLE patients for some characteristics, whereby the dynamic analysis has been shown capable of identifying the laterality. Furthermore, the results suggest that the temporal trend of some graph theoretical characteristics can be exploited as a novel marker for TLE laterality.

Neuroimaging and connectomics of drug-resistant epilepsy at multiple scales: From focal lesions to macroscale networks

Epilepsy is among the most common chronic neurologic disorders, with 30%-40% of patients having seizures despite antiepileptic drug treatment. The advent of brain imaging and network analyses has greatly improved the understanding of this condition. In particular, developments in magnetic resonance imaging (MRI) have provided measures for the noninvasive characterization and detection of lesions causing epilepsy. MRI techniques can probe structural and functional connectivity, and network analyses have shaped our understanding of whole-brain anomalies associated with focal epilepsies. This review considers the progress made by neuroimaging and connectomics in the study of drug-resistant epilepsies due to focal substrates, particularly temporal lobe epilepsy related to mesiotemporal sclerosis and extratemporal lobe epilepsies associated with malformations of cortical development. In these disorders, there is evidence of widespread disturbances of structural and functional connectivity that may contribute to the clinical and cognitive prognosis of individual patients. It is hoped that studying the interplay between macroscale network anomalies and lesional profiles will improve our understanding of focal epilepsies and assist treatment choices.

Brain network alterations of mesial temporal lobe epilepsy with cognitive dysfunction following anterior temporal lobectomy

The aims of this study were to investigate the brain network connectivity alterations of intractable unilateral mesial temporal lobe epilepsy (MTLE) with cognitive dysfunction before and after anterior temporal lobectomy (ATL) using resting-state functional magnetic resonance imaging (rs-fMRI) study and to further observe the correlation between the brain network connectivity with cognitive performance. Fourteen patients with unilateral left MTLE before and after ATL were compared with thirty healthy controls (HCs) on functional connectivity (FC) between resting-state networks (RSNs). The correlation between the neuropsychological tests of patients and abnormal FC was further investigated. When compared with the HCs, patients before surgery showed significantly changed FC between special RSNs. No difference of FC was found between each RSN when patients were compared with the HCs after surgery. Compared with patients before surgery, patients after surgery showed significantly decreased FC between RSNs. Abnormal FC between RSNs significantly correlated with Montreal Cognitive Assessment (MoCA) scores. Our study suggested that dynamic alterations of RSN after ATL in unilateral MTLE may be closely related with seizure generating. However, unchanged FC between RSN before and after ATL may be closely related with cognitive performance. The present findings may help us understand the feature of brain network alterations in patients with left MTLE who became seizure-free following ATL.

Structural covariance networks relate to the severity of epilepsy with focal-onset seizures

PURPOSE

The brains of patients with epilepsy may exhibit various morphological abnormalities, which are often not directly visible on structural MR images, as they may be focally subtle or related to a more large-scale inconspicuous disorganization of brain structures. To explore the relation between structural brain organization and epilepsy characteristics, including severity and cognitive co-morbidity, we determined structural covariance networks (SCNs). SCNs represent interregional correlations of morphologic measures, for instance in terms of cortical thickness, between various large-scale distributed brain regions.

METHODS

Thirty-eight patients with focal seizures of all subtypes and 21 healthy controls underwent structural MRI, neurological, and IQ assessment. Cortical thickness was derived from the structural MRIs using FreeSurfer. Subsequently, SCNs were constructed on a group-level based on correlations of the cortical thicknesses between various brain regions. Individual SCNs for the epilepsy patients were extracted by adding the respective patient to the control group prior to the SCN construction (i.e. add-one-patient approach). Calculated network measures, i.e. path length, clustering coefficient and betweenness centrality were correlated with characteristics related to the severity of epilepsy, including seizure history and age at onset of epilepsy, and cognitive performance.

RESULTS

Stronger clustering in the individual SCN was associated with a higher number of focal to bilateral tonic-clonic seizures during life time, a younger age at onset, and lower cognitive performance. The path length of the individual SCN was not related to the severity of epilepsy or cognitive performance. Higher betweenness centrality of the left cuneus and lower betweenness centrality of the right rostral middle frontal gyrus were associated with increased drug load and younger age at onset, respectively.

CONCLUSIONS

These results indicate that the correlations between interregional variations of cortical thickness reflect disease characteristics or responses to the disease and deficits in patients with epilepsy with focal seizures.

Brain network alteration in patients with temporal lobe epilepsy with cognitive impairment

The aims of this study were to investigate the brain network alternation in patients with temporal lobe epilepsy (TLE) with and without cognitive impairment (CI) using functional magnetic resonance imaging (fMRI) and to further explore the potential mechanisms of epilepsy-induced CI. Forty patients with TLE and nineteen healthy controls (HCs) were recruited for this study. All participants received the Montreal Cognitive Assessment (MoCA) test, and the patients were divided into CI (n=21) and cognitive nonimpairment (CNI) groups (n=19) according to MoCA performance. Functional connectivity (FC) differences of resting state networks (RSNs) were compared among the CI, CNI, and HC groups. Correlation between FC and MoCA scores was also observed. When compared with the HC group, significantly decreased FC between medial visual network (mVN) and left frontoparietal network (lFPN) as well as between visuospatial network (VSN) and the anterior default mode network (aDMN) were revealed in both CI and CNI groups. In addition, significantly decreased FC between lFPN and executive control network (ECN) and increased FC between ECN and sensorimotor-related network (SMN) were found in CNI and CI groups, respectively. When compared with the CNI group, the CI group exhibited significant increased FC between ECN and lFPN as well as between ECN and SMN. Moreover, in the CI group, FC between ECN and lFPN showed negative correlation with attention scores. Our findings suggested that cognitive networks are different from epileptic networks, and the increased FC between RSNs closely related to cognitive function changes may help us to further understand the mechanism of CI in TLE.

Cognitive impairment in epilepsy: the role of reduced network flexibility

Objective

The dominant model of cognitive impairment in focal epilepsy has emphasised structural bases for cognitive deficits. Current theories of cognition in the healthy brain emphasise the importance of the reweighting of brain network interactions in support of task performance. Here, we explore the hypothesis that cognitive deficits in epilepsy arise through abnormalities of dynamic functional network interactions.

Method

We studied 19 healthy controls and 37 temporal lobe epilepsy (TLE) patients, using a behavioural measure of verbal fluency (the Controlled Oral Word Association Test) and an fMRI verbal fluency paradigm (Orthographic Lexical Retrieval).

Results

Behaviourally, verbal fluency was significantly impaired in TLE. Psychophysiological interaction analyses of the fMRI data, which capture state-dependent changes in network connectivity, revealed reduced task-dependent modulations of connectivity from left superior medial frontal cortex to left middle frontal gyrus in TLE patients. Individual differences in verbal fluency among TLE cases was correlated with task-dependent changes in connectivity from left posterior cingulate to left superior medial frontal cortex, and from left superior medial frontal cortex to a range of right predominant brain areas.

Interpretation

These data reveal that the typical pattern of task-driven shifts in network connectivity is not observed in TLE. Our observations go beyond simple structure-function associations and suggest that failure of network flexibility can be an important contributor to cognitive impairment in epilepsy.

Testosterone affects language areas of the adult human brain

Although the sex steroid hormone testosterone is integrally involved in the development of language processing, ethical considerations mostly limit investigations to single hormone administrations. To circumvent this issue we assessed the influence of continuous high-dose hormone application in adult female-to-male transsexuals. Subjects underwent magnetic resonance imaging before and after 4 weeks of testosterone treatment, with each scan including structural, diffusion weighted and functional imaging. Voxel-based morphometry analysis showed decreased gray matter volume with increasing levels of bioavailable testosterone exclusively in Broca's and Wernicke's areas. Particularly, this may link known sex differences in language performance to the influence of testosterone on relevant brain regions. Using probabilistic tractography, we further observed that longitudinal changes in testosterone negatively predicted changes in mean diffusivity of the corresponding structural connection passing through the extreme capsule. Considering a related increase in myelin staining in rodents, this potentially reflects a strengthening of the fiber tract particularly involved in language comprehension. Finally, functional images at resting-state were evaluated, showing increased functional connectivity between the two brain regions with increasing testosterone levels. These findings suggest testosterone-dependent neuroplastic adaptations in adulthood within language-specific brain regions and connections. Importantly, deteriorations in gray matter volume seem to be compensated by enhancement of corresponding structural and functional connectivity. Hum Brain Mapp 37:1738-1748, 2016. © 2016 Wiley Periodicals, Inc.

Time-dependence of graph theory metrics in functional connectivity analysis

Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations.

Seizure Frequency Can Alter Brain Connectivity: Evidence from Resting-State fMRI

BACKGROUND AND PURPOSE

The frequency of seizures is an important factor that can alter functional brain connectivity. Analysis of this factor in patients with epilepsy is complex because of disease- and medication-induced confounders. Because patients with hot-water epilepsy generally are not on long-term drug therapy, we used seed-based connectivity analysis in these patients to assess connectivity changes associated with seizure frequency without confounding from antiepileptic drugs.

MATERIALS AND METHODS

Resting-state fMRI data from 36 patients with hot-water epilepsy (18 with frequent seizures [>2 per month] and 18 with infrequent seizures [≤2 per month]) and 18 healthy age- and sex-matched controls were analyzed for seed-to-voxel connectivity by using 106 seeds. Voxel wise paired t-test analysis (P < .005, corrected for false-discovery rate) was used to identify significant intergroup differences between these groups.

RESULTS

Connectivity analysis revealed significant differences between the 2 groups (P < .001). Patients in the frequent-seizure group had increased connectivity within the medial temporal structures and widespread areas of poor connectivity, even involving the default mode network, in comparison with those in the infrequent-seizure group. Patients in the infrequent-seizure group had focal abnormalities with increased default mode network connectivity and decreased left entorhinal cortex connectivity.

CONCLUSIONS

The results of this study suggest that seizure frequency can alter functional brain connectivity, which can be visualized by using resting-state fMRI. Imaging features such as diffuse network abnormalities, involvement of the default mode network, and recruitment of medial temporal lobe structures were seen only in patients with frequent seizures. Future studies in more common epilepsy groups, however, will be required to further establish this finding.

Reduced language connectivity in pediatric epilepsy

OBJECTIVE

Functional connectivity (FC) among language regions is decreased in adults with epilepsy compared to controls, but less is known about FC in children with epilepsy. We sought to determine if language FC is reduced in pediatric epilepsy, and examined clinical factors that associate with language FC in this population.

METHODS

We assessed FC during an age-adjusted language task in children with left-hemisphere focal epilepsy (n = 19) compared to controls (n = 19). Time series data were extracted for three left regions of interest (ROIS) and their right homologues: inferior frontal gyrus (IFG), middle frontal gyrus (MFG), and Wernicke's area (WA) using SPM8. Associations between FC and factors such as cognitive performance, language dominance, and epilepsy duration were assessed.

RESULTS

Children with epilepsy showed decreased interhemispheric connectivity compared to controls, particularly between core left language regions (IFG, WA) and their right hemisphere homologues, as well as decreased intrahemispheric right frontal FC. Increased intrahemispheric FC between left IFG and left WA was a positive predictor of language skills overall, and naming ability in particular. FC of language areas was not affected by language dominance, as the effects remained only when examining participants with left language dominance. Overall FC did not differ according to duration of epilepsy or age of onset.

SIGNIFICANCE

FC during a language task is reduced in children, similar to findings in adults. In specific, children with left focal epilepsy demonstrated decreased interhemispheric FC in temporal and frontal language connections and decreased intrahemispheric right frontal FC. These differences were present near the onset of epilepsy. Greater FC between left language centers is related to better language ability. Our results highlight that connectivity of language areas has a developmental pattern and is related to cognitive ability.

Brain Graph Topology Changes Associated with Anti-Epileptic Drug Use

Neuroimaging studies of functional connectivity using graph theory have furthered our understanding of the network structure in temporal lobe epilepsy (TLE). Brain network effects of anti-epileptic drugs could influence such studies, but have not been systematically studied. Resting-state functional MRI was analyzed in 25 patients with TLE using graph theory analysis. Patients were divided into two groups based on anti-epileptic medication use: those taking carbamazepine/oxcarbazepine (CBZ/OXC) (n=9) and those not taking CBZ/OXC (n=16) as a part of their medication regimen. The following graph topology metrics were analyzed: global efficiency, betweenness centrality (BC), clustering coefficient, and small-world index. Multiple linear regression was used to examine the association of CBZ/OXC with graph topology. The two groups did not differ from each other based on epilepsy characteristics. Use of CBZ/OXC was associated with a lower BC. Longer epilepsy duration was also associated with a lower BC. These findings can inform graph theory-based studies in patients with TLE. The changes observed are discussed in relation to the anti-epileptic mechanism of action and adverse effects of CBZ/OXC.

Functional network alterations and their structural substrate in drug-resistant epilepsy

The advent of MRI has revolutionized the evaluation and management of drug-resistant epilepsy by allowing the detection of the lesion associated with the region that gives rise to seizures. Recent evidence indicates marked chronic alterations in the functional organization of lesional tissue and large-scale cortico-subcortical networks. In this review, we focus on recent methodological developments in functional MRI (fMRI) analysis techniques and their application to the two most common drug-resistant focal epilepsies, i.e., temporal lobe epilepsy related to mesial temporal sclerosis and extra-temporal lobe epilepsy related to focal cortical dysplasia. We put particular emphasis on methodological developments in the analysis of task-free or “resting-state” fMRI to probe the integrity of intrinsic networks on a regional, inter-regional, and connectome-wide level. In temporal lobe epilepsy, these techniques have revealed disrupted connectivity of the ipsilateral mesiotemporal lobe, together with contralateral compensatory reorganization and striking reconfigurations of large-scale networks. In cortical dysplasia, initial observations indicate functional alterations in lesional, peri-lesional, and remote neocortical regions. While future research is needed to critically evaluate the reliability, sensitivity, and specificity, fMRI mapping promises to lend distinct biomarkers for diagnosis, presurgical planning, and outcome prediction.

Applications of blood-oxygen-level-dependent functional magnetic resonance imaging and diffusion tensor imaging in epilepsy

The lifetime prevalence of epilepsy ranges from 2.7 to 12.4 per 1000 in Western countries. Around 30% of patients with epilepsy remain refractory to antiepileptic drugs and continue to have seizures. Noninvasive imaging techniques such as functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) have helped to better understand mechanisms of seizure generation and propagation, and to localize epileptic, eloquent, and cognitive networks. In this review, the clinical applications of fMRI and DTI are discussed, for mapping cognitive and epileptic networks and organization of white matter tracts in individuals with epilepsy.

Effects of topiramate on language functions in newly diagnosed pediatric epileptic patients

BACKGROUND

The aim of this study was to characterize the effects of topiramate on language functions in newly diagnosed pediatric epileptic patients.

METHODS

Thirty-eight newly diagnosed epileptic patients were assessed using standard language tests. Data were collected before and after beginning topiramate during which time a monotherapy treatment regimen was maintained. Language tests included the Test of Language Problem Solving Abilities, a Korean version of the Peabody Picture Vocabulary Test. We used language tests in the Korean version because all the patients were spoken Korean exclusively in their families.

RESULTS

All the language parameters of Test of Language Problem Solving Abilities worsened after initiation of topiramate (determine cause, 13.2 ± 4.8 to 11.2 ± 4.3; problem solving, 14.8 ± 6.0 to 12.8 ± 5.0; predicting, 9.8 ± 3.6 to 8.8 ± 4.6). Patients given topiramate exhibited a shortened mean length of utterance in words during response (determine cause, 4.8 ± 0.9 to 4.3 ± 0.7; making inference, 4.5 ± 0.8 to 4.1 ± 1.1; predicting, 5.2 ± 1.0 to 4.7 ± 0.6; P < 0.05), provided ambiguous answers during the testing, exhibited difficulty in selecting appropriate words, took more time to provide answers, and used incorrect grammar. However, there were no statistically significant changes in the receptive language of patients after taking topiramate (95.4 ± 20.4 to 100.8 ± 19.1).

CONCLUSIONS

Our data suggest that topiramate may have negative effects on problem-solving abilities in children. We recommend performing language tests should be considered in children being treated with topiramate.

The effects of pediatric epilepsy on a language connectome

This study introduces a new approach for assessing the effects of pediatric epilepsy on a language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI. An auditory word definition decision task paradigm was used to activate the language network for 29 patients and 30 controls. Evaluations illustrated that pediatric epilepsy is associated with a network efficiency reduction. Patients showed a propensity to inefficiently use the whole brain network to perform the language task; whereas, controls seemed to efficiently use smaller segregated network components to achieve the same task. To explain the causes of the decreased efficiency, graph theoretical analysis was performed. The analysis revealed substantial global network feature differences between the patients and controls for the extent of activation network. It also showed that for both subject groups the language network exhibited small-world characteristics; however, the patient's extent of activation network showed a tendency toward randomness. It was also shown that the intensity of activation network displayed ipsilateral hub reorganization on the local level. We finally showed that a clustering scheme was able to fairly separate the subjects into their respective patient or control groups. The clustering was initiated using local and global nodal measurements. Compared to the intensity of activation network, the extent of activation network clustering demonstrated better precision. This ascertained that the network differences presented by the networks were associated with pediatric epilepsy.

Evolution of functional connectivity of brain networks and their dynamic interaction in temporal lobe epilepsy

This study presents a cross-sectional investigation of functional networks in temporal lobe epilepsy (TLE) as they evolve over years of disease. Networks of interest were identified based on a priori hypotheses: the network of seizure propagation ipsilateral to the seizure focus, the same regions contralateral to seizure focus, the cross hemisphere network of the same regions, and a cingulate midline network. Resting functional magnetic resonance imaging data were acquired for 20 min in 12 unilateral TLE patients, and 12 age- and gender-matched healthy controls. Functional changes within and between the four networks as they evolve over years of disease were quantified by standard measures of static functional connectivity and novel measures of dynamic functional connectivity. The results suggest an initial disruption of cross-hemispheric networks and an increase in static functional connectivity in the ipsilateral temporal network accompanying the onset of TLE seizures. As seizures progress over years, the static functional connectivity across the ipsilateral network diminishes, while dynamic functional connectivity measures show the functional independence of this ipsilateral network from the network of midline regions of the cingulate declines. This implies a gradual breakdown of the seizure onset and early propagation network involving the ipsilateral hippocampus and temporal lobe as it becomes more synchronous with the network of regions responsible for secondary generalization of the seizures, a process that may facilitate the spread of seizures across the brain. Ultimately, the significance of this evolution may be realized in relating it to symptoms and treatment outcomes of TLE.

Vulnerability of the ventral language network in children with focal epilepsy

Croft et al. present fMRI and functional connectivity analyses of the language network in children with epilepsy and healthy controls. In both groups, the network is organised into dorsal and ventral systems. Activation of the ventral network is reduced in children with epilepsy, in association with poorer language function.

Children with focal epilepsy are at increased risk of language impairment, yet the neural substrate of this dysfunction is not yet known. Using functional magnetic resonance imaging we investigated the impact of focal epilepsy on the developing language system using measures of network topology (spatial organization of activation) and synchrony (functional connectivity). We studied healthy children (n = 48, 4–12 years, 24 females) and children with focal epilepsy (n = 21, 5–12 years, nine females) with left hemisphere language dominance. Participants performed an age-adjusted auditory description decision task during functional magnetic resonance imaging, to identify perisylvian language regions. Mean signal change was extracted from eight left perisylvian regions of interest and compared between groups. Paired region of interest functional connectivity analysis was performed on time course data from the same regions, to investigate left network synchrony. Two principal component analyses were performed to extract (i) patterns of activation (using mean signal change data); and (ii) patterns of synchronized regions (using functional connectivity data). For both principal component analyses two components (networks) were extracted, which mapped onto the functional anatomy of dorsal and ventral language systems. Associations among network variables, age, epilepsy-related factors and verbal ability were assessed. Activated networks were affected by age and epilepsy [F(2,60) = 3.74, P = 0.03]: post hoc analyses showed, for healthy children, activation in both ventral and dorsal networks decreased with age (P = 0.02). Regardless of age and task performance, children with epilepsy showed reduced activation of the ventral network (P < 0.001). They also showed a trend for increased activation of the dorsal network (P = 0.08) associated with improved task performance (r = 0.62, P = 0.008). Crucially, decreased activation of the ventral network in patients predicted poorer language outcome ( = 0.47, P = 0.002). This suggests childhood onset epilepsy preferentially alters maturation of the ventral language system, and this is related to poorer language ability.

Structural connectivity differences in left and right temporal lobe epilepsy

Our knowledge on temporal lobe epilepsy (TLE) with hippocampal sclerosis has evolved towards the view that this syndrome affects widespread brain networks. Diffusion weighted imaging studies have shown alterations of large white matter tracts, most notably in left temporal lobe epilepsy, but the degree of altered connections between cortical and subcortical structures remains to be clarified. We performed a whole brain connectome analysis in 39 patients with refractory temporal lobe epilepsy and unilateral hippocampal sclerosis (20 right and 19 left) and 28 healthy subjects. We performed whole-brain probabilistic fiber tracking using MRtrix and segmented 164 cortical and subcortical structures with Freesurfer. Individual structural connectivity graphs based on these 164 nodes were computed by mapping the mean fractional anisotropy (FA) onto each tract. Connectomes were then compared using two complementary methods: permutation tests for pair-wise connections and Network Based Statistics to probe for differences in large network components. Comparison of pair-wise connections revealed a marked reduction of connectivity between left TLE patients and controls, which was strongly lateralized to the ipsilateral temporal lobe. Specifically, infero-lateral cortex and temporal pole were strongly affected, and so was the perisylvian cortex. In contrast, for right TLE, focal connectivity loss was much less pronounced and restricted to bilateral limbic structures and right temporal cortex. Analysis of large network components revealed furthermore that both left and right hippocampal sclerosis affected diffuse global and interhemispheric connectivity. Thus, left temporal lobe epilepsy was associated with a much more pronounced pattern of reduced FA, that included major landmarks of perisylvian language circuitry. These distinct patterns of connectivity associated with unilateral hippocampal sclerosis show how a focal pathology influences global network architecture, and how left or right-sided lesions may have differential and specific impacts on cerebral connectivity.

Functional connectivity MRI and post-operative language performance in temporal lobe epilepsy: initial experience

Anterior temporal lobectomy is an effective treatment for drug-resistant epilepsy of temporal origin, although new language impairment may develop after surgery. Since correlations between functional connectivity (FC) MRI of the language network and verbal-IQ performance before surgery have recently been reported, we investigated the existence of correlations between the preoperative FC of the language network and post-operative verbal-IQ decline. FC between nodes of the language network of the two hemispheres (Interhemispheric-FC) and within nodes of the left hemisphere (LH-FC) and language lateralization indexes were estimated in five right-handed patients with non-tumoral left temporal lobe epilepsy undergoing anterior temporal lobectomy. Correlations between preoperative FC measures and lateralization indexes, and the post-operative (12 months) neuropsychological verbal-IQ decline were investigated. Verbal-IQ decline was inversely correlated with the degree of left lateralization and directly correlated with the strength of Interhemispheric-FC. No significant correlation was found between LH-FC and post-operative verbal-IQ change. The results from this limited number of patients suggest that a stronger preoperative connectivity between homologue regions, associated with the absence of a definite hemispheric lateralization, appears to be an unfavorable prognostic biomarker.

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.

Advantages of sentence-level fMRI language tasks in presurgical language mapping for temporal lobe epilepsy

fMRI language mapping has become increasingly utilized for determining language dominance before surgical intervention for temporal lobe epilepsy (TLE). This study aimed to examine the differences between two classes of fMRI word generation tasks used in our clinic: tasks using a single word cue, referred to as simple generative tasks (SGTs), and tasks also involving sentence-level processing, referred to as sentence-level language tasks (SLTs). Specifically, we aimed to investigate the extent and laterality of activation and frontal-temporal connectivity during these language tasks and their relationship to clinical language measures. Thirty-one patients with TLE (18 patients with left TLE and 13 patients with right TLE) performed four language tasks during an fMRI scan, two SGTs and two SLTs. We found significantly greater activity for SLTs over SGTs in bilateral inferior frontal and middle temporal gyri and the left temporal pole. Sentence-level language tasks also showed greater lateralization compared with SGTs. Finally, we found that while activation extent did not correlate with clinical language tests, the degree of left frontal-temporal connectivity was significantly correlated with naming and semantic fluency performance. These correlations also were more robust for SLTs than for SGTs. Taken together, these results provide a compelling argument for including some form of SLTs in fMRI language lateralization protocols for TLE as they allow for better characterization of language networks, particularly in the temporal lobes which are at risk in surgery.

Reduced structural connectivity between sensorimotor and language areas in rolandic epilepsy

Introduction

Rolandic epilepsy (RE) is a childhood epilepsy with centrotemporal (rolandic) spikes, that is increasingly associated with language impairment. In this study, we tested for a white matter (connectivity) correlate, employing diffusion weighted MRI and language testing.

Methods

Twenty-three children with RE and 23 matched controls (age: 8–14 years) underwent structural (T1-weighted) and diffusion-weighted MRI (b = 1200 s/mm², 66 gradient directions) at 3T, as well as neuropsychological language testing. Combining tractography and a cortical segmentation derived from the T1-scan, the rolandic tract were reconstructed (pre- and postcentral gyri), and tract fractional anisotropy (FA) values were compared between patients and controls. Aberrant tracts were tested for correlations with language performance.

Results

Several reductions of tract FA were found in patients compared to controls, mostly in the left hemisphere; the most significant effects involved the left inferior frontal (p = 0.005) and supramarginal (p = 0.004) gyrus. In the patient group, lower tract FA values were correlated with lower language performance, among others for the connection between the left postcentral and inferior frontal gyrus (p = 0.043, R = 0.43).

Conclusion

In RE, structural connectivity is reduced for several connections involving the rolandic regions, from which the epileptiform activity originates. Most of these aberrant tracts involve the left (typically language mediating) hemisphere, notably the pars opercularis of the inferior frontal gyrus (Broca’s area) and the supramarginal gyrus (Wernicke’s area). For the former, reduced language performance for lower tract FA was found in the patients. These findings provide a first microstructural white matter correlate for language impairment in RE.

Functional connectivity of hippocampal networks in temporal lobe epilepsy

OBJECTIVE

Temporal lobe epilepsy (TLE) affects brain areas beyond the temporal lobes due to connections of the hippocampi and other temporal lobe structures. Using functional connectivity magnetic resonance imaging (MRI), we determined the changes of hippocampal networks in TLE to assess for a more complete distribution of abnormality.

METHODS

Regions of interest (ROIs) were defined in the right and left hippocampi in three groups of participants: left TLE (n = 13), right TLE (n = 11), and healthy controls (n = 16). Brain regions functionally connected to these ROIs were identified by correlating resting-state low-frequency functional MRI (fMRI) blood oxygenation level-dependent (BOLD) signal fluctuations. The grouped results were compared using independent sample t-test.

RESULTS

TLE was associated with increased hippocampal connectivity involving several key areas of the limbic network (temporal lobe, insula, thalamus), frontal lobes, angular gyrus, basal ganglia, brainstem, and cerebellum, along with reduced connectivity involving areas of the sensorimotor cortex (visual, somatosensory, auditory, primary motor) and the default mode network (precuneus). Left TLE had more marked connectivity changes than right TLE.

SIGNIFICANCE

The observed connectivity changes in TLE indicate dysfunctional networks that underlie widespread brain involvement in TLE. There are identifiable differences in the connectivity of the hippocampi between left and right TLE.

Disrupted segregation of working memory networks in temporal lobe epilepsy

Working memory is a critical building block for almost all cognitive tasks, and impairment can cause significant disruption to daily life routines. We investigated the functional connectivity (FC) of the visuo-spatial working memory network in temporal lobe epilepsy and its relationship to the underlying white matter tracts emanating from the hippocampus. Fifty-two patients with unilateral hippocampal sclerosis (HS) (30 left) and 30 healthy controls underwent working memory functional MRI (fMRI) and Diffusion Tensor Imaging (DTI). Six seed regions were identified for FC analysis; 4 within a task-positive network (left and right middle frontal gyri and superior parietal lobes), and 2 within a task-negative network (left and right hippocampi). FC maps were created by extracting the time-series of the fMRI signal in each region in each subject and were used as regressors of interest for additional GLM fMRI analyses. Structural connectivity (SC) corresponding to areas to which the left and right hippocampi were connected was determined using tractography, and a mean FA for each hippocampal SC map was calculated. Both left and right HS groups showed atypical FC between task-positive and task-negative networks compared to controls. This was characterised by co-activation of the task-positive superior parietal lobe ipsilateral to the typically task-negative sclerosed hippocampus. Correlational analysis revealed stronger FC between superior parietal lobe and ipsilateral hippocampus, was associated with worse performance in each patient group. The SC of the hippocampus was associated with the intra-hemispheric FC of the superior parietal lobe, in that greater SC was associated with weaker parieto-frontal FC. The findings suggest that the segregation of the task-positive and task-negative FC networks supporting working memory in TLE is disrupted, and is associated with abnormal structural connectivity of the sclerosed hippocampus. Co-activation of parieto-temporal regions was associated with poorer working memory and this may be associated with working memory dysfunction in TLE.

Functional networks in temporal-lobe epilepsy: a voxel-wise study of resting-state functional connectivity and gray-matter concentration

Temporal-lobe epilepsy (TLE) involves seizures that typically originate in the hippocampus. There is evidence that seizures involve anatomically and functionally connected brain networks within and beyond the temporal lobe. Many studies have explored the effect of TLE on gray matter and resting-state functional connectivity in the brain. However, the relationship between structural and functional changes has not been fully explored. The goal of this study was to investigate the relationship between gray matter concentration (GMC) and functional connectivity in TLE at the voxel level. A voxel-wise linear regression analysis was performed between GMC maps and whole-brain resting-state functional connectivity maps to both the left thalamus (Lthal) and the left hippocampus (LH) in a group of 15 patients with left TLE. Twenty regions were found that exhibited GMC decreases linearly correlated with resting-state functional connectivity to either the LH or the Lthal in the patient group only. A subset of these regions had significantly reduced GMC, and one of these regions also had reduced functional connectivity to the LH in TLE compared to the controls. These results suggest a network of impairment in left TLE where more severe reductions in GMC accompany decreases (LH, Lthal, right midcingulate gyrus, left precuneus, and left postcentral gyrus) or increases (LH to right thalamus) in resting functional connectivity. However, direct relationships between these imaging parameters and disease characteristics in these regions have yet to be established.

Network reconfiguration and working memory impairment in mesial temporal lobe epilepsy

Mesial temporal lobe epilepsy (mTLE) is the most prevalent form of focal epilepsy, and hippocampal sclerosis (HS) is considered the most frequent associated pathological finding. Recent connectivity studies have shown that abnormalities, either structural or functional, are not confined to the affected hippocampus, but can be found in other connected structures within the same hemisphere, or even in the contralesional hemisphere. Despite the role of hippocampus in memory functions, most of these studies have explored network properties at resting state, and in some cases compared connectivity values with neuropsychological memory scores. Here, we measured magnetoencephalographic responses during verbal working memory (WM) encoding in left mTLE patients and controls, and compared their effective connectivity within a frontotemporal network using dynamic causal modelling. Bayesian model comparison indicated that the best model included bilateral, forward and backward connections, linking inferior temporal cortex (ITC), inferior frontal cortex (IFC), and the medial temporal lobe (MTL). Test for differences in effective connectivity revealed that patients exhibited decreased ipsilesional MTL-ITC backward connectivity, and increased bidirectional IFC-MTL connectivity in the contralesional hemisphere. Critically, a negative correlation was observed between these changes in patients, with decreases in ipsilesional coupling among temporal sources associated with increases contralesional frontotemporal interactions. Furthermore, contralesional frontotemporal interactions were inversely related to task performance and level of education. The results demonstrate that unilateral sclerosis induced local and remote changes in the dynamic organization of a distributed network supporting verbal WM. Crucially, pre-(peri) morbid factors (educational level) were reflected in both cognitive performance and (putative) compensatory changes in physiological coupling.

Resting state functional connectivity of the hippocampus associated with neurocognitive function in left temporal lobe epilepsy

The majority of patients with temporal lobe epilepsy (TLE) experience disturbances of episodic memory from structural damage or dysfunction of the hippocampus. The objective of this study was to use functional Magnetic Resonance Imaging (fMRI) to identify regions where resting state connectivity to the left hippocampus (LH) is correlated with neuropsychological measures of verbal memory retention in TLE patients. Eleven left TLE (LTLE) patients and 15 control subjects participated in resting state fMRI scans. All LTLE patients underwent neuropsychological testing. Resting state functional connectivity maps to the LH were calculated for each patient, and subsequently used in a multiple regression analysis with verbal memory retention scores as a covariate. The analysis identified brain regions whose connectivity to the LH was linearly related to memory retention scores across the group of patients. In LTLE patients, right sided (contralateral) clusters in the precuneus and inferior parietal lobule (IPL) exhibited increased connectivity to the LH with increased memory retention score; left sided (ipsilateral) regions in the precuneus and IPL showed increased connectivity to the LH with decreased retention score. Patients with high memory retention scores had greater connectivity between the LH-right parietal clusters than between the LH-left parietal clusters; in contrast, control subjects had significantly and consistently greater LH-left hemisphere than LH-right hemisphere connectivity. Our results suggest that increased connectivity in contralateral hippocampal functional pathways within the episodic verbal memory network represents a strengthening of alternative pathways in LTLE patients with strong verbal memory retention abilities.

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.

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.

Memory in frontal lobe epilepsy: an fMRI study

PURPOSE

Focal epilepsies are often associated with structural and functional changes that may extend beyond the area of seizure onset. In this study we investigated the functional anatomy of memory in patients with frontal lobe epilepsy (FLE), focusing on the local and remote effects of FLE on the networks supporting memory encoding.

METHODS

We studied 32 patients with drug-resistant FLE and 18 controls using a functional magnetic resonance imaging (fMRI) memory encoding paradigm.

KEY FINDINGS

During encoding of stimuli, patients with FLE recruited more widely distributed areas than healthy controls, in particular within the frontal lobe contralateral to the seizure onset. Normal memory performance was associated with increased recruitment of frontal areas, and conversely a poor performance was associated with an absence of this increased recruitment and decreased activation in mesial temporal lobe areas.

SIGNIFICANCE

In patients with FLE, recruitment of wider areas, particularly in the contralateral frontal lobe, appears to be an effective compensatory mechanism to maintain memory function. Impaired hippocampal activation is relatively rare and, in turn, associated with poor recognition memory.

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.