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

Functional network dynamics between the anterior thalamus and the cortex in deep brain stimulation for epilepsy

Owing to its unique connectivity profile with cortical brain regions, and its suggested role in the subcortical propagation of seizures, the anterior nucleus of the thalamus (ANT) has been proposed as a key deep brain stimulation (DBS) target in drug-resistant epilepsy. However, the spatio-temporal interaction dynamics of this brain structure, and the functional mechanisms underlying ANT DBS in epilepsy remain unknown. Here, we study how the ANT interacts with the neocortex in vivo in humans and provide a detailed neurofunctional characterization of mechanisms underlying the effectiveness of ANT DBS, aiming at defining intraoperative neural biomarkers of responsiveness to therapy, assessed at 6 months post-implantation as the reduction in seizure frequency. A cohort of 15 patients with drug-resistant epilepsy (n = 6 males, age = 41.6 ± 13.79 years) underwent bilateral ANT DBS implantation. Using intraoperative cortical and ANT simultaneous electrophysiological recordings, we found that the ANT is characterized by high amplitude θ (4-8 Hz) oscillations, mostly in its superior part. The strongest functional connectivity between the ANT and the scalp EEG was also found in the θ band in ipsilateral centro-frontal regions. Upon intraoperative stimulation in the ANT, we found a decrease in higher EEG frequencies (20-70 Hz) and a generalized increase in scalp-to-scalp connectivity. Crucially, we observed that responders to ANT DBS treatment were characterized by higher EEG θ oscillations, higher θ power in the ANT, and stronger ANT-to-scalp θ connectivity, highlighting the crucial role of θ oscillations in the dynamical network characterization of these structures. Our study provides a comprehensive characterization of the interaction dynamic between the ANT and the cortex, delivering crucial information to optimize and predict clinical DBS response in patients with drug-resistant epilepsy.

Improved Seizure Onset-Zone Lateralization in Temporal Lobe Epilepsy using 7T Resting-State fMRI: A Direct Comparison with 3T

Objective

Resting-state functional magnetic resonance imaging (rs-fMRI) at ultra high-field strengths (≥7T) is known to provide superior signal-to-noise and statistical power than comparable acquisitions at lower field strengths. In this study, we aim to provide a direct comparison of the seizure onset-zone (SOZ) lateralizing ability of 7T rs-fMRI and 3T rs-fMRI.

Methods

We investigated a cohort of 70 temporal lobe epilepsy (TLE) patients. A paired cohort of 19 patients had 3T and 7T rs-fMRI acquisitions for direct comparison between the two field strengths. Forty-three patients had only 3T, and 8 patients had only 7T rs-fMRI acquisitions. We quantified the functional connectivity between the hippocampus and other nodes within the default mode network (DMN) using seed-to-voxel connectivity, and measured how hippocampo-DMN connectivity could inform SOZ lateralization at 7T and 3T field strengths.

Results

Differences between hippocampo-DMN connectivity ipsilateral and contralateral to the SOZ were significantly higher at 7T (pFDR=0.008) than at 3T (pFDR=0.80) when measured in the same subjects. We found that our ability to lateralize the SOZ, by distinguishing subjects with left TLE from subjects with right TLE, was superior at 7T (AUC = 0.97) than 3T (AUC = 0.68). Our findings were reproduced in extended cohorts of subjects scanned at either 3T or 7T. Our rs-fMRI findings at 7T, but not 3T, are consistent and highly correlated (Spearman Rho=0.65) with clinical FDG-PET lateralizing hypometabolism.

Significance

We show superior SOZ lateralization in TLE patients when using 7T relative to 3T rs-fMRI, supporting the adoption of high-field strength functional imaging in the epilepsy presurgical evaluation.

Patient-specific structural connectivity informs outcomes of responsive neurostimulation for temporal lobe epilepsy

OBJECTIVE

Responsive neurostimulation is an effective therapy for patients with refractory mesial temporal lobe epilepsy. However, clinical outcomes are variable, few patients become seizure-free, and the optimal stimulation location is currently undefined. The aim of this study was to quantify responsive neurostimulation in the mesial temporal lobe, identify stimulation-dependent networks associated with seizure reduction, and determine if stimulation location or stimulation-dependent networks inform outcomes.

METHODS

We modeled patient-specific volumes of tissue activated and created probabilistic stimulation maps of local regions of stimulation across a retrospective cohort of 22 patients with mesial temporal lobe epilepsy. We then mapped the network stimulation effects by seeding tractography from the volume of tissue activated with both patient-specific and normative diffusion-weighted imaging. We identified networks associated with seizure reduction across patients using the patient-specific tractography maps and then predicted seizure reduction across the cohort.

RESULTS

Patient-specific stimulation-dependent connectivity was correlated with responsive neurostimulation effectiveness after cross-validation (p = .03); however, normative connectivity derived from healthy subjects was not (p = .44). Increased connectivity from the volume of tissue activated to the medial prefrontal cortex, cingulate cortex, and precuneus was associated with greater seizure reduction.

SIGNIFICANCE

Overall, our results suggest that the therapeutic effect of responsive neurostimulation may be mediated by specific networks connected to the volume of tissue activated. In addition, patient-specific tractography was required to identify structural networks correlated with outcomes. It is therefore likely that altered connectivity in patients with epilepsy may be associated with the therapeutic effect and that utilizing patient-specific imaging could be important for future studies. The structural networks identified here may be utilized to target stimulation in the mesial temporal lobe and to improve seizure reduction for patients treated with responsive neurostimulation.

Thalamic deep brain stimulation paradigm to reduce consciousness: Cortico-striatal dynamics implicated in mechanisms of consciousness

Anesthetic manipulations provide much-needed causal evidence for neural correlates of consciousness, but non-specific drug effects complicate their interpretation. Evidence suggests that thalamic deep brain stimulation (DBS) can either increase or decrease consciousness, depending on the stimulation target and parameters. The putative role of the central lateral thalamus (CL) in consciousness makes it an ideal DBS target to manipulate circuit-level mechanisms in cortico-striato-thalamic (CST) systems, thereby influencing consciousness and related processes. We used multi-microelectrode DBS targeted to CL in macaques while recording from frontal, parietal, and striatal regions. DBS induced episodes of abnormally long, vacant staring with low-frequency oscillations here termed vacant, perturbed consciousness (VPC). DBS modulated VPC likelihood in a frequency-specific manner. VPC events corresponded to decreases in measures of neural complexity (entropy) and integration (Φ*), proposed indices of consciousness, and substantial changes to communication in CST circuits. During VPC, power spectral density and coherence at low frequencies increased across CST circuits, especially in thalamo-parietal and cortico-striatal pathways. Decreased consciousness and neural integration corresponded to shifts in cortico-striatal network configurations that dissociated parietal and subcortical structures. Overall, the features of VPC and implicated networks were similar to those of absence epilepsy. As this same multi-microelectrode DBS method–but at different stimulation frequencies–can also increase consciousness in anesthetized macaques, it can be used to flexibly address questions of consciousness with limited confounds, as well as inform clinical investigations of other consciousness disorders.

Deep brain stimulation (DBS) is an effective treatment for a number of neurological and psychiatric disorders. Recent evidence shows that thalamic DBS can increase consciousness under general anesthesia, and has the potential to be an effective treatment for disorders of consciousness like coma. However, past studies also imply that thalamic DBS can decrease consciousness by producing periods of inactivity with vacant staring. In this study, we use thalamic DBS to induce vacant periods of perturbed consciousness (VPC) while recording from frontal, parietal and subcortical brain areas. Much of modern research on consciousness focuses on cortical contributions, debating if frontal or more posterior areas are more important. We show via machine learning, information theoretic and functional connectivity measures that VPC involves altered neural communication between parietal cortex and subcortical regions, challenging a cortico-centric focus. Further, these mechanisms resemble those associated with absence epilepsy, suggesting a link between this disorder of consciousness and VPC. Finally, occurrence of VPC in our study was stimulation frequency-dependent and influenced by the experimental history of DBS. This provides insight to mechanisms of thalamic DBS, informative for clinical manipulations of consciousness.

Neuroimaging and thalamic connectomics in epilepsy neuromodulation

Neuromodulation is an increasingly utilized therapy for the treatment of people with drug-resistant epilepsy. To date, the most common and effective target has been the thalamus, which is known to play a key role in multiple forms of epilepsy. Neuroimaging has facilitated rapid developments in the understanding of functional targets, surgical and programming techniques, and the effects of thalamic stimulation. In this review, the role of neuroimaging in neuromodulation is explored. First, the structural and functional changes of the thalamus in common epilepsy syndromes are discussed as the rationale for neuromodulation of the thalamus. Next, methods for imaging different thalamic nuclei are presented, as well as rationale for the need of direct surgical targeting rather than reliance on traditional stereotactic coordinates. Lastly, we discuss the potential role of neuroimaging in assessing the effects of thalamic stimulation and as a potential biomarker for neuromodulation outcomes.

Functional network connectivity imprint in febrile seizures

Complex febrile seizures (CFS), a subset of paediatric febrile seizures (FS), have been studied for their prognosis, epileptogenic potential and neurocognitive outcome. We evaluated their functional connectivity differences with simple febrile seizures (SFS) in children with recent-onset FS. Resting-state fMRI (rs-fMRI) datasets of 24 children with recently diagnosed FS (SFS-n = 11; CFS-n = 13) were analysed. Functional connectivity (FC) was estimated using time series correlation of seed region–to-whole-brain-voxels and network topology was assessed using graph theory measures. Regional connectivity differences were correlated with clinical characteristics (FDR corrected p < 0.05). CFS patients demonstrated increased FC of the bilateral middle temporal pole (MTP), and bilateral thalami when compared to SFS. Network topology study revealed increased clustering coefficient and decreased participation coefficient in basal ganglia and thalamus suggesting an inefficient-unbalanced network topology in patients with CFS. The number of seizure recurrences negatively correlated with the integration of Left Thalamus (r = − 0.58) and FC of Left MTP to 'Right Supplementary Motor and left Precentral' gyrus (r = − 0.53). The FC of Right MTP to Left Amygdala, Putamen, Parahippocampal, and Orbital Frontal Cortex (r = 0.61) and FC of Left Thalamus to left Putamen, Pallidum, Caudate, Thalamus Hippocampus and Insula (r 0.55) showed a positive correlation to the duration of the longest seizure. The findings of the current study report altered connectivity in children with CFS proportional to the seizure recurrence and duration. Regardless of the causal/consequential nature, such observations demonstrate the imprint of these disease-defining variables of febrile seizures on the developing brain.

Seizure Frequency Is Associated with Effective Connectivity of the Hippocampal-Diencephalic-Cingulate in Epilepsy with Unilateral Mesial Temporal Sclerosis

Background: Temporal lobe epilepsy (TLE) with mesial temporal sclerosis (MTS) is a common intractable epilepsy. To seek neural correlates of seizure recurrence, this study investigated aberrant intrinsic effective connectivity (iEC) in TLE with unilateral MTS and their associations with seizure frequency. Methods: Thirty patients with unilateral MTS (left/right MTS = 14/16) and 37 age-matched healthy controls underwent resting-state functional magnetic resonance imaging (rsfMRI) on a 3-Tesla magnetic resonance imaging (MRI) system. The structural equation modeling was employed to estimate the iEC of the three candidate epilepsy models, including the Papez circuit, hippocampal-diencephalic-cingulate (HDC) model, and simplified HDC model. After comparing the performance of model fitting, the best model was selected to compare iEC among the study groups. The linear regression analysis was performed to associate abnormal iEC with seizure frequency. Results: The simplified HDC model was the best model to estimate iEC across the three study groups (p < 0.05), and it composed of the 26 interconnected pathway between the mesial temporal lobe, thalamus, and cingulate cortices. The linear regression analysis revealed a significant relationship between the shared iEC alterations in both patient groups and seizure frequency (adjusted-R² = 0.350; p = 0.037), including the three paths of mammillary body (MB) → bilateral anterior thalamic nuclei (left: standardized β-value = 0.580, p = 0.013; right: standardized β-value = -0.711, p = 0.006) and right hippocampus → MB (standardized β-value = 0.541, p = 0.045). Conclusions: Our findings provide new insights into neurophysiological significance relevant to seizure recurrence. Aberrant iEC on the neural paths connected to the MB can be a potential imaging marker, aiding the therapeutic management in TLE with unilateral MTS. Impact statement Within the simplified hippocampal-diencephalic-cingulate model, we identified that altered intrinsic effective connectivity (iEC) on the three paths connecting to the mammillary body was common in temporal lobe epilepsy (TLE) with left and right mesial temporal sclerosis (MTS) and was associated with seizure frequency. Therefore, these common iEC alterations could be a potential imaging marker, aiding the therapeutic management in patients with TLE with unilateral MTS.

Intrinsic hippocampal and thalamic networks in temporal lobe epilepsy with hippocampal sclerosis according to drug response

PURPOSE

The aim of this study was to investigate whether intrinsic hippocampal or thalamic networks in patients with temporal lobe epilepsy (TLE) with hippocampal sclerosis (HS) were different according to antiepileptic drug (AED) response.

METHODS

We enrolled 80 patients with TLE with HS and 40 healthy controls. Of the patients with TLE with HS, 43 were classified as a drug-resistant epilepsy (DRE) group, whereas 37 patients were enrolled as a drug-controlled epilepsy (DCE) group. We investigated the structural connectivity of the global brain, intrinsic hippocampal, and intrinsic thalamic networks based on structural volumes in the patients with DRE and DCE, and analyzed the differences between them.

RESULTS

There were significant alterations of the intrinsic hippocampal network compared with healthy controls. The average degree and the global efficiency were decreased, whereas the characteristic path length was increased in the patients with DRE compared with those in healthy controls. In the patients with DCE, only the small-worldness index was decreased compared with healthy controls. Compared to the patients with DCE, the mean clustering coefficient was increased in the patients with DRE.

CONCLUSION

We found that the intrinsic hippocampal network in patients with TLE with HS was different according to AED response. The patients with DRE had more severe disruptions of the intrinsic hippocampal network than those with DCE compared with healthy controls. These findings suggested that the hippocampal network might be related to AED response and could be a new biomarker of medical outcome in patients with TLE with HS.

Predicting the antiepileptic drug response by brain connectivity in newly diagnosed focal epilepsy

OBJECTIVE

Growing evidence has suggested that epilepsy is a disease with alterations in brain connectivity. The aim of this study was to investigate whether the changes in brain connectivity can predict the response to an antiepileptic drug (AED) in patients with a newly diagnosed focal epilepsy of unknown etiology.

METHODS

This observational study was independently performed at two tertiary hospitals (Group A and B). Thirty-eight patients with newly diagnosed focal epilepsy of unknown etiology were enrolled in Group A and 46 patients in Group B. We divided these patients into two groups according to their seizure control after AED treatment: AED good and poor responders. We defined the AED good responders as those in whom had seizure free for at least the last 6 months while AED poor responders who were not. All of the subjects underwent diffusion tensor imaging, and graph theoretical analysis was applied to reveal the brain connectivity. We investigated the difference in the clinical characteristics and network measurements between the two groups.

RESULTS

Of the network measures, the assortativity coefficient in the AED good responders was significantly higher than that in the AED poor responders in both Groups A and B (- 0.0239 vs. - 0.0473, p = 0.0110 in Group A; 0.0173 vs. - 0.0180, p = 0.0024 in Group B). The Kaplan-Meier survival analysis revealed that the time to failure to retain the first AED was significantly longer in the patients with assortative networks (assortativity coefficient > 0) than in those with disassortative networks (assortativity coefficient < 0) in Group B.

CONCLUSION

We demonstrated that the assortativity coefficient differed between patients with newly diagnosed focal epilepsy of unknown etiology according to their AED responses, which suggests that the changes in brain connectivity could be a biomarker for predicting the responses to AED.

Differences in functional connectivity profiles as a predictor of response to anterior thalamic nucleus deep brain stimulation for epilepsy: a hypothesis for the mechanism of action and a potential biomarker for outcomes

OBJECTIVE Deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) is a promising therapy for refractory epilepsy. Unfortunately, the variability in outcomes from ANT DBS is not fully understood. In this pilot study, the authors assess potential differences in functional connectivity related to the volume of tissue activated (VTA) in ANT DBS responders and nonresponders as a means for better understanding the mechanism of action and potentially improving DBS targeting. METHODS This retrospective analysis consisted of 6 patients who underwent ANT DBS for refractory epilepsy. Patients were classified as responders (n = 3) if their seizure frequency decreased by at least 50%. The DBS electrodes were localized postoperatively and VTAs were computationally generated based on DBS programming settings. VTAs were used as seed points for resting-state functional MRI connectivity analysis performed using a control dataset. Differences in cortical connectivity to the VTA were assessed between the responder and nonresponder groups. RESULTS The ANT DBS responders showed greater positive connectivity with the default mode network compared to nonresponders, including the posterior cingulate cortex, medial prefrontal cortex, inferior parietal lobule, and precuneus. Interestingly, there was also a consistent anticorrelation with the hippocampus seen in responders that was not present in nonresponders. CONCLUSIONS Based on their pilot study, the authors observed that successful ANT DBS in patients with epilepsy produces increased connectivity in the default mode network, which the authors hypothesize increases the threshold for seizure propagation. Additionally, an inhibitory effect on the hippocampus mediated through increased hippocampal γ-aminobutyric acid (GABA) concentration may contribute to seizure suppression. Future studies are planned to confirm these findings.

Bayesian framework for robust seed-based correlation analysis

PURPOSE

One popular method of assessing brain functional connectivity (FC) is through seed-based correlation (SCA) analysis. One drawback of this method is when the seed location is varied slightly, the FC can vary dramatically. We propose a method superior to SCA, robust to variations in seed location, which confers a probabilistic interpretation.

METHODS

We introduce a probabilistic method which generates a cloud of highly connected voxels to determine a stable set of voxels connected to the seed location (SC-SCA). This cloud can generate a correlation map or a probabilistic map. The method is applied to the default mode network (DMN) based on a posterior cingulate cortex (PCC) seed, and the auditory network (AN) as validation on a smaller network. A Bayesian interpretation is demonstrated through performing a maximum a posteriori (MAP) estimation on the DMN. The advantages of the method are tested by performing stability analyses on its influential parameters. The method is extended to region-based SC-SCA, and then comparisons are made based on seed-based vs region-based versions of the methods SC-SCA vs traditional SCA. The statistical significance between the methods is assessed via a bootstrap method using the difference in medians of the standard deviation of the voxels for 16 subjects.

RESULTS

The proposed method, SC-SCA, is able to identify a set of regions - the DMN - that are known to be associated with and have high correlation with the PCC, and the method is also extensible to smaller networks as shown by its performance on the AN. Based on the certainty of the a priori distribution for MAP analysis, the method is able to identify regions with high probability of belonging to the DMN. The stability analyses demonstrated that substantial deviations from the initial seed locations in the sagittal, posterior transverse, and axial directions by ±10 mm do not cause substantial variation in the correlation network produced. Qualitative inspection of the average correlation maps garnered from the four methods showed that SC-SCA shows a larger amount of detail in FC connectivity as compared to SCA. Seed-based methods show higher detail and contrast in the maps in comparison with region-based methods. Quantitatively, the statistical tests between seed-based vs region-based and SC-SCA vs SCA revealed that there is no significant difference between the following methods: region-based SCA or region-based SC-SCA, and seed-based SC-SCA or region-based SC-SCA. However, there are statistically significant differences and advantages conferred between the following methods: seed-based SC-SCA over seed-based SCA, region-based SC-SCA over seed-based SCA, region-based SCA over seed-based SCA, and region-based SCA over seed-based SC-SCA. Finally, seed-based SC-SCA outperforms sphere-based SCA.

CONCLUSIONS

The proposed method offers several advantages over traditional SCA: robust single-seed FC estimation, novel Bayesian estimation capabilities, enhanced detail of brain structures, robustness to initial seed location, and enhanced consistency in the correlation maps generated. Region-based SC-SCA is equivalent or superior to all investigated methods, where seed-based SCA is inferior to all methods. The method confers improved single-seed SCA with the additional benefit of Bayesian estimation.

Relationship Between Seizure Frequency and Functional Abnormalities in Limbic Network of Medial Temporal Lobe Epilepsy

Background: We compared resting-state functional connectivity (RSFC) among limbic and temporal lobe regions between patients with medial temporal lobe epilepsy (mTLE) and healthy control subjects to identify imaging evidence of functional networks related to seizure frequency, age of seizure onset, and duration of epilepsy.

Methods: Twelve patients with drug-resistant, unilateral medial temporal lobe epilepsy and 12 healthy control subjects matched for age, sex, and handedness participated in the imaging experiments. We used network-based statistics to compare functional connectivity graphs in patients with mTLE and healthy controls to investigate the relationship between functional connectivity abnormalities and seizure frequency.

Results: Among mTLE patients, we found functional network abnormalities throughout the limbic system, but primarily in the hemisphere ipsilateral to the seizure focus. The RSFCs between ipsilateral hypothalamus and ventral anterior cingulate cortex and between ipsilateral subiculum and contralateral posterior cingulate cortex were highly correlated with seizure frequency.

Discussion: These findings suggest that in mTLE, changes in limbic networks ipsilateral to the epileptic focus are common. The pathological changes in connectivity between cingulate cortex, hypothalamus and subiculum ipsilateral to the seizure focus were correlated with increased seizure frequency.

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.

Regional cortical thickness changes accompanying generalized tonic-clonic seizures

Objective

Generalized tonic-clonic seizures are accompanied by cardiovascular and respiratory sequelae that threaten survival. The frequency of these seizures is a major risk factor for sudden unexpected death in epilepsy (SUDEP), a leading cause of untimely death in epilepsy. The circumstances accompanying such fatal events suggest a cardiovascular or respiratory failure induced by unknown neural processes rather than an inherent cardiac or lung deficiency. Certain cortical regions, especially the insular, cingulate, and orbitofrontal cortices, are key structures that integrate sensory input and influence diencephalic and brainstem regions regulating blood pressure, cardiac rhythm, and respiration; output from those cortical regions compromised by epilepsy-associated injury may lead to cardiorespiratory dysregulation. The aim here was to assess changes in cortical integrity, reflected as cortical thickness, relative to healthy controls. Cortical alterations in areas that influence cardiorespiratory action could contribute to SUDEP mechanisms.

Methods

High-resolution T1-weighted images were collected with a 3.0-Tesla MRI scanner from 53 patients with generalized tonic-clonic seizures (Mean age ± SD: 37.1 ± 12.6 years, 22 male) at Case Western Reserve University, University College London, and the University of California at Los Angeles. Control data included 530 healthy individuals (37.1 ± 12.6 years; 220 male) from UCLA and two open access databases (OASIS and IXI). Cortical thickness group differences were assessed at all non-cerebellar brain surface locations (P < 0.05 corrected).

Results

Increased cortical thickness appeared in post-central gyri, insula, and subgenual, anterior, posterior, and isthmus cingulate cortices. Post-central gyri increases were greater in females, while males showed more extensive cingulate increases. Frontal and temporal cortex, lateral orbitofrontal, frontal pole, and lateral parietal and occipital cortices showed thinning. The extents of thickness changes were sex- and hemisphere-dependent, with only males exhibiting right-sided and posterior cingulate thickening, while females showed only left lateral orbitofrontal thinning. Regional cortical thickness showed modest correlations with seizure frequency, but not epilepsy duration.

Significance

Cortical thickening and thinning occur in patients with generalized tonic-clonic seizures, in cardiovascular and somatosensory areas, with extent of changes sex- and hemisphere-dependent. The data show injury in key autonomic and respiratory cortical areas, which may contribute to dysfunctional cardiorespiratory patterns during seizures, as well as to longer-term SUDEP risk.

Can we predict drug response by volumes of the corpus callosum in newly diagnosed focal epilepsy?

OBJECTIVE

The aim of this study was to investigate whether volumes of the corpus callosum could predict a response to antiepileptic drugs in patients with newly diagnosed focal epilepsy.

METHODS

Fifty-three patients with newly diagnosed focal epilepsy of unknown etiology and healthy subjects were enrolled in this study. First, we analyzed the differences in the volumes of the corpus callosum between patients with epilepsy and healthy subjects. Second, we divided patients with epilepsy into antiepileptic drug responders and drug nonresponders groups, according to their seizure controls, and evaluated the differences in the volumes of the corpus callosum between the groups. Third, we conducted correlation analyses between the volumes of the corpus callosum and mean diffusion measures in healthy subjects.

RESULTS

The volumes of the corpus callosum in patients with epilepsy were significantly lower than those in normal controls (p = .0001). Among epilepsy patients, the volumes of the corpus callosum were significantly lower in antiepileptic drug responders compared with nonresponders (p = .0481), which was the only independent variable for predicting antiepileptic drug response (OR = 10.07, p = .0434). In addition, we found that the volumes of the corpus callosum were significantly correlated with the mean diffusion measures (fractional anisotropy, r = .408, p = .0027; mean diffusivity, r = -0.403, p = .0028) in normal controls.

CONCLUSIONS

We demonstrated that the volumes of the corpus callosum were different according to antiepileptic drug responses in patients with newly diagnosed focal epilepsy, which might suggest that the volumes of the corpus callosum could be a new biomarker for predicting responses to antiepileptic drugs.

Reduced small world brain connectivity in probands with a family history of epilepsy

BACKGROUND AND PURPOSE

The role of inheritance in ascertaining susceptibility to epilepsy is well established, although the pathogenetic mechanisms are still not very clear. Interviewing for a positive family history is a popular epidemiological tool in the understanding of this susceptibility. Our aim was to visualize and localize network abnormalities that could be associated with a positive family history in a group of patients with hot water epilepsy (HWE) using resting-state functional magnetic resonance imaging (rsfMRI).

METHODS

Graph theory analysis of rsfMRI (clustering coefficient γ; path length λ; small worldness σ) in probands with a positive family history of epilepsy (FHE+, 25) were compared with probands without FHE (FHE-, 33). Whether a closer biological relationship was associated with a higher likelihood of network abnormalities was also ascertained.

RESULTS

A positive family history of epilepsy had decreased γ, increased λ and decreased σ in bilateral temporofrontal regions compared to FHE- (false discovery rate corrected P ≤ 0.0062). These changes were more pronounced in probands having first degree relatives and siblings with epilepsy. Probands with multiple types of epilepsy in the family showed decreased σ in comparison to only HWE in the family.

CONCLUSION

Graph theory analysis of the rsfMRI can be used to understand the neurobiology of diseases like genetic susceptibility in HWE. Reduced small worldness, proportional to the degree of relationship, is consistent with the current understanding that disease severity is higher in closer biological relations.

Recovery of resting brain connectivity ensuing mild traumatic brain injury

Brains reveal amplified plasticity as they recover from an injury. We aimed to define time dependent plasticity changes in patients recovering from mild traumatic brain injury (mTBI). Twenty-five subjects with mild head injury were longitudinally evaluated within 36 h, 3 and 6 months using resting state functional connectivity (RSFC). Region of interest (ROI) based connectivity differences over time within the patient group and in comparison with a healthy control group were analyzed at p < 0.005. We found 33 distinct ROI pairs that revealed significant changes in their connectivity strength with time. Within 3 months, the majority of the ROI pairs had decreased connectivity in mTBI population, which increased and became comparable to healthy controls at 6 months. Within this diffuse decreased connectivity in the first 3 months, there were also few regions with increased connections. This hyper connectivity involved the salience network and default mode network within 36 h, and lingual, inferior frontal and fronto-parietal networks at 3 months. Our findings in a fairly homogenous group of patients with mTBI evaluated during the 6 month window of recovery defines time varying brain connectivity changes as the brain recovers from an injury. A majority of these changes were seen in the frontal and parietal lobes between 3 and 6 months after injury. Hyper connectivity of several networks supported normal recovery in the first 6 months and it remains to be seen in future studies whether this can predict an early and efficient recovery of brain function.