Altered basal ganglia-cortical functional connections in frontal lobe epilepsy: A resting-state fMRI study

Epileptic brain network mechanisms and neuroimaging techniques for the brain network

Epilepsy can be defined as a dysfunction of the brain network, and each type of epilepsy involves different brain-network changes that are implicated differently in the control and propagation of interictal or ictal discharges. Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice. An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tractography, diffusion kurtosis imaging-based fiber tractography, fiber ball imaging-based tractography, electroencephalography, functional magnetic resonance imaging, magnetoencephalography, positron emission tomography, molecular imaging, and functional ultrasound imaging have been extensively used to delineate epileptic networks. In this review, we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy, and extensively analyze the imaging mechanisms, advantages, limitations, and clinical application ranges of each technique. A greater focus on emerging advanced technologies, new data analysis software, a combination of multiple techniques, and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.

Imaging biomarkers of sleep-related hypermotor epilepsy and sudden unexpected death in epilepsy: a review

In recent years, imaging has emerged as a promising source of several intriguing biomarkers in epilepsy, due to the impressive growth of imaging technology, supported by methodological advances and integrations of post-processing techniques. Bearing in mind the mutually influencing connection between sleep and epilepsy, we focused on sleep-related hypermotor epilepsy (SHE) and sudden unexpected death in epilepsy (SUDEP), aiming to make order and clarify possible clinical utility of emerging multimodal imaging biomarkers of these two epilepsy-related entities commonly occurring during sleep. Regarding SHE, advanced structural techniques might soon emerge as a promising source of diagnostic and predictive biomarkers, tailoring a targeted therapeutic (surgical) approach for MRI-negative subjects. Functional and metabolic imaging may instead unveil SHE's extensive and night-related altered brain networks, providing insights into distinctions and similarities with non-epileptic sleep phenomena, such as parasomnias. SUDEP is considered a storm that strikes without warning signals, but objective subtle structural and functional alterations in autonomic, cardiorespiratory, and arousal centers are present in patients eventually experiencing SUDEP. These alterations could be seen both as susceptibility and diagnostic biomarkers of the underlying pathological ongoing loop ultimately ending in death. Finally, given that SHE and SUDEP are rare phenomena, most evidence on the topic is derived from small single-center experiences with scarcely comparable results, hampering the possibility of performing any meta-analytic approach. Multicenter, longitudinal, well-designed studies are strongly encouraged.

Hemodynamic correlates of emotion regulation in frontal lobe epilepsy patients and healthy participants

The ability to regulate emotions is indispensable for maintaining psychological health. It heavily relies on frontal lobe functions which are disrupted in frontal lobe epilepsy. Accordingly, emotional dysregulation and use of maladaptive emotion regulation strategies have been reported in frontal lobe epilepsy patients. Therefore, it is of clinical and scientific interest to investigate emotion regulation in frontal lobe epilepsy. We studied neural correlates of upregulating and downregulating emotions toward aversive pictures through reappraisal in 18 frontal lobe epilepsy patients and 17 healthy controls using functional magnetic resonance imaging. Patients tended to report more difficulties with impulse control than controls. On the neural level, patients had diminished activity during upregulation in distributed left-sided regions, including ventrolateral and dorsomedial prefrontal cortex, angular gyrus and anterior temporal gyrus. Patients also showed less activity than controls in the left precuneus for upregulation compared to downregulation. Unlike controls, they displayed no task-related activity changes in the left amygdala, whereas the right amygdala showed task-related modulations in both groups. Upregulation-related activity changes in the left inferior frontal gyrus, insula, orbitofrontal cortex, anterior and posterior cingulate cortex, and precuneus were correlated with questionnaire data on habitual emotion regulation. Our results show that structural or functional impairments in the frontal lobes disrupt neural mechanisms underlying emotion regulation through reappraisal throughout the brain, including posterior regions involved in semantic control. Findings on the amygdala as a major target of emotion regulation are in line with the view that specifically the left amygdala is connected with semantic processing networks.

Abnormal brain functional network dynamics in sleep-related hypermotor epilepsy

AIMS

This study aimed to use resting-state functional magnetic resonance imaging (rs-fMRI) to determine the temporal features of functional connectivity states and changes in connectivity strength in sleep-related hypermotor epilepsy (SHE).

METHODS

High-resolution T1 and rs-fMRI scanning were performed on all the subjects. We used a sliding-window approach to construct a dynamic functional connectivity (dFC) network. The k-means clustering method was performed to analyze specific FC states and related temporal properties. Finally, the connectivity strength between the components was analyzed using network-based statistics (NBS) analysis. The correlations between the abovementioned measures and disease duration were analyzed.

RESULTS

After k-means clustering, the SHE patients mainly exhibited two dFC states. The frequency of state 1 was higher, which was characterized by stronger connections within the networks; state 2 occurred at a relatively low frequency, characterized by stronger connections between networks. SHE patients had greater fractional time and a mean dwell time in state 2 and had a larger number of state transitions. The NBS results showed that SHE patients had increased connectivity strength between networks. None of the properties was correlated with illness duration among patients with SHE.

CONCLUSION

The patterns of dFC patterns may represent an adaptive and protective mode of the brain to deal with epileptic seizures.

The adjustment mechanism of the spike and wave discharges in thalamic neurons: a simulation analysis

Different from many previous theoretical studies, this paper explores the regulatory mechanism of the spike and wave discharges (SWDs) in the reticular thalamic nucleus (TRN) by a dynamic computational model. We observe that the SWDs appears in the TRN by changing the coupling weights and delays in the thalamocortical circuit. The abundant poly-spikes wave discharges is also induced when the delay increases to large enough. These discharges can be inhibited by tuning the inhibitory output from the basal ganglia to the thalamus. The mechanisms of these waves can be explained in this model together with simulation results, which are different from the mechanisms in the cortex. The TRN is an important target in treating epilepsy, and the results may be a theoretical evidence for experimental study in the future.

Intracranial direct electrical mapping reveals the functional architecture of the human basal ganglia

The basal ganglia play a key role in integrating a variety of human behaviors through the cortico–basal ganglia–thalamo–cortical loops. Accordingly, basal ganglia disturbances are implicated in a broad range of debilitating neuropsychiatric disorders. Despite accumulating knowledge of the basal ganglia functional organization, the neural substrates and circuitry subserving functions have not been directly mapped in humans. By direct electrical stimulation of distinct basal ganglia regions in 35 refractory epilepsy patients undergoing stereoelectroencephalography recordings, we here offer currently the most complete overview of basal ganglia functional characterization, extending not only to the expected sensorimotor responses, but also to vestibular sensations, autonomic responses, cognitive and multimodal effects. Specifically, some locations identified responses weren’t predicted by the model derived from large-scale meta-analyses. Our work may mark an important step toward understanding the functional architecture of the human basal ganglia and provide mechanistic explanations of non-motor symptoms in brain circuit disorders.

Direct electrical stimulation of the basal ganglia using implanted SEEG electrodes produced a variety of motor and non-motor effects in human participants, providing insight into the functional architecture of this key brain region.

Clinical and imaging features of nonmotor onset seizure in poststroke epilepsy

OBJECTIVE

Motivated by the challenges raised by diagnosing poststroke epilepsy (PSE), especially in nonmotor onset seizure (non-MOS), we aimed to investigate features of non-MOS, including seizure sequences, patient characteristics, and electrophysiological and imaging findings in PSE.

METHODS

This observational cohort study enrolled patients with PSE whose seizure onset was witnessed. According to the International League Against Epilepsy 2017 seizure classification, we classified seizure onset symptoms into the non-MOS and MOS groups. We compared different clinical characteristics between the two groups.

RESULTS

Between 2011 and 2018, we enrolled 225 patients with PSE (median age, 75 years), consisting of 97 (43%) with non-MOS and 128 (57%) with MOS. Overall, 65 (67%) of the patients without MOS had no subsequent convulsions. Multivariable logistic regression analysis showed significant associations of non-MOS with absence of poststroke hemiparesis (adjusted odds ratio [OR], 1.88; 95% confidence interval [CI], 1.03-3.42), frontal stroke lobe lesions (OR, 2.11; 95% CI, 1.14-3.91), and putaminal stroke lesions (OR, 2.51; 95% CI, 1.22-5.18) as negative indicators. Postictal single-photon emission-computed tomography detected prolonged hyperperfusion in the temporal lobe more frequently in the non-MOS than in the MOS group (48% vs. 31%; p = 0.02). The detection rate was higher than spikes/sharp waves in scalp electroencephalogram both in the non-MOS group (72% vs. 33%; p < 0.001) and the MOS group (68% vs. 29%; p < 0.001).

SIGNIFICANCE

This study provides clinical features of non-MOS in patients with PSE. Compared with the patients with MOS, the ones with non-MOS showed less likely subsequent convulsive seizures, highlighting the clinical challenges. Postictal perfusion imaging and negative indicators of non-MOS type may help diagnose and stratify PSE.

Shared gray matter alterations in subtypes of addiction: a voxel-wise meta-analysis

BACKGROUND

Numerous studies based on voxel-based morphometry (VBM) have revealed gray matter (GM) alterations in multiple brain regions for addiction. However, findings are poorly replicated, and it remains elusive whether distinct diagnoses of addiction are underpinned by shared abnormalities. Our aim was to conduct a quantitative meta-analysis of structural neuroimaging studies investigating GM abnormalities in two main categories of addiction: substance use disorders (SUD) and behavioral addictions (BA).

METHOD

A systematic database search was conducted in several databases from Jan 1, 2010, to Oct 23, 2020, to identify eligible VBM studies. Meta-analysis was performed with the seed-based d mapping software package to compare alternations between individuals with addiction-related disorders and healthy controls (HC).

RESULTS

A total of 59 VBM studies including 2096 individuals with addiction-related disorders and 2637 HC met the inclusion criteria. Individuals with addiction-related disorders showed shared GM volume decrease in bilateral prefrontal cortex, bilateral insula, bilateral rolandic operculum, left superior temporal gyrus, and right Heschl gyrus and GM increase in right lingual gyrus and right fusiform gyrus comparing with HC (p < 0.005). Subgroup analysis found heterogeneity between SUD and BA mainly in left inferior occipital gyrus and right striatum (p < 0.005). Meta-regression revealed that GM atrophy in right anterior cingulate (r = 0.541, p = 0.03 (uncorrected)) and left inferior frontal gyrus (r = 0.595, p = 0.015) were positively correlated with higher impulsivity.

CONCLUSIONS

This meta-analysis identified a concordance across subtypes of addiction in terms of the brain structural changes in prefrontal and insula areas, which may relate to higher impulsivity observed across addiction diagnoses. This concordance provides an organizing model that emphasizes the importance of shared neural substrates in addiction.

Reliability and availability of granger causality density in localization of Rolandic focus in BECTS

A new method, called granger causality density (GCD), could reflect the directed information flow of the epileptiform activity, which is much closely match with excitatory and inhibitory imbalance theory of epilepsy. Here, we investigated if GCD could effectively localize the Rolandic focus in 50 patients with benign childhood epilepsy with central-temporal spikes (BECTS) from 27 normal children. The BECTS were classified into ictal epileptiform discharges (IEDs; 12 females, 15 males;age, 8.15 ± 1.68 years) and non-IEDs (10 females, 13 males; age, 9.09 ± 1.98 years) subgroups depending on the presence of central-temporal spikes. Multiple correlation-modality analyses (Pearson, across-voxel and across-subject correlations) were used to calculate the couplings between the GCD maps and IEDs-related brain activation map. The individual lateralization coefficient of localize IEDs and multiple regression analysis were used to identify the reliability of the GCD method in localizing the Rolandic focus. In this study, multiple correlation-modality analyses showed that the IEDs-related brain activation map and the GCD maps had highly temporal (coefficient ׀r\= 0.56 ~ 0.65) and spatial (\r\=0.53~0.91) (r\=~ couplings. The proposed GCD method and multiple regression analyses showed consistent findings with the clinical EEG recordings in lateralization of Rolandic focus. Furthermore, the GCD method could reflect the epilepsy-related brain activity during non-IEDs substate. Therefore, the proposed GCD method has the potential to be served as an effective and reliable neuroimaging biomarker to localize the Rolandic focus of BECTS. These findings are critical for clinical early diagnosis, and may promote the progression of treatment and management of pediatric epilepsy.

Cortico-striato-thalamo-cerebellar networks of structural covariance underlying different epilepsy syndromes associated with generalized tonic-clonic seizures

Generalized tonic-clonic seizures (GTCS) are the severest and most remarkable clinical expressions of human epilepsy. Cortical, subcortical, and cerebellar structures, organized with different network patterns, underlying the pathophysiological substrates of genetic associated epilepsy with GTCS (GE-GTCS) and focal epilepsy associated with focal to bilateral tonic-clonic seizure (FE-FBTS). Structural covariance analysis can delineate the features of epilepsy network related with long-term effects from seizure. Morphometric MRI data of 111 patients with GE-GTCS, 111 patients with FE-FBTS and 111 healthy controls were studied. Cortico-striato-thalao-cerebellar networks of structural covariance within the gray matter were constructed using a Winner-take-all strategy with five cortical parcellations. Comparisons of structural covariance networks were conducted using permutation tests, and module effects of disease duration on networks were conducted using GLM model. Both patient groups showed increased connectivity of structural covariance relative to controls, mainly within the striatum and thalamus, and mostly correlated with the frontal, motor, and somatosensory cortices. Connectivity changes increased as a function of epilepsy durations. FE-FBTS showed more intensive and extensive gray matter changes with volumetric loss and connectivity increment than GE-GTCS. Our findings implicated cortico-striato-thalamo-cerebellar network changes at a large temporal scale in GTCS, with FE-FBTS showing more severe network disruption. The study contributed novel imaging evidence for understanding the different epilepsy syndromes associated with generalized seizures.

Cannabidiol normalizes resting-state functional connectivity in treatment-resistant epilepsy

OBJECTIVE

Resting-state (rs) network dysfunction is a contributing factor to treatment resistance in epilepsy. In treatment-resistant epilepsy (TRE), pharmacological and nonpharmacological therapies have been shown to improve such dysfunction. In this study, our goal was to prospectively evaluate the effect of highly purified plant-derived cannabidiol (CBD; Epidiolex®) on rs functional magnetic resonance imaging (fMRI) functional connectivity (rs-FC). We hypothesized that CBD would change and potentially normalize the rs-FC in TRE.

METHODS

Twenty-two of 27 participants with TRE completed all study procedures including longitudinal pre-/on-CBD rs-fMRI (8M/14F, mean age = 36.2 ± 15.9 years, TRE duration = 18.3 ± 12.6 years); there were no differences in age (p = 0.99) or sex (p = 0.15) between groups. Assessments collected included seizure frequency (SF), Chalfont Seizure Severity Scale (CSSS), Columbia Suicide Severity Rating Scale (C-SSRS), Adverse Events Profile (AEP), and Profile of Mood States (POMS). Twenty-three healthy controls (HCs) received rs-fMRI and POMS once.

RESULTS

Participants with TRE showed average decrease of 71.7% in SF (p < 0.0001) and improved CSSS, AEP, and POMS confusion, depression, and fatigue subscores (all p < 0.05) on-CBD with POMS scores becoming similar to those of HCs. Paired t-tests showed significant pre-/on-CBD changes in rs-FC in cerebellum, frontal areas, temporal areas, hippocampus, and amygdala with some of them correlating with improvement in behavioral measures. Significant differences in rs-FC between pre-CBD and HCs were found in cerebellum, frontal, and occipital regions. After controlling for changes in SF with CBD, these differences were no longer present when comparing on-CBD to HCs.

SIGNIFICANCE

This study indicates that highly purified CBD modulates and potentially normalizes rs-FC in the epileptic brain. This effect may underlie its efficacy. This study provides Class III evidence for CBD's normalizing effect on rs-FC in TRE.

Altered Static and Dynamic Spontaneous Neural Activity in Drug-Naïve and Drug-Receiving Benign Childhood Epilepsy With Centrotemporal Spikes

The present study aims to investigate intrinsic abnormalities of brain and the effect of antiepileptic treatment on brain activity in Benign childhood epilepsy with centrotemporal spikes (BECTS). Twenty-six drug-naïve patients (DNP) and 22 drug-receiving patients (DRP) with BECTS were collected in this study. Static amplitude of low frequency fluctuation (sALFF) and dynamic ALFF (dALFF) were applied to resting-state fMRI data. Functional connectivity (FC) analysis was further performed for affected regions identified by static and dynamic analysis. One-way analysis of variance and post hoc statistical analyses were performed for between-group differences. Abnormal sALFF and dALFF values were correlated with clinical features of patients. Compared with healthy controls (HC), DNP group demonstrated alterations of sALFF and/or dALFF in medial prefrontal cortex (MPFC), supplementary motor areas (SMA), cerebellum, hippocampus, pallidum and cingulate cortex, in which the values were close to normal in DRP. Notably, sALFF and dALFF showed specific sensitivity in detecting abnormalities in basal ganglia and cerebellum. Additionally, DRP showed additional changes in precuneus, inferior temporal gyrus, superior frontal gyrus and occipital visual cortex. Compared with HC, the DNP showed increased FC in default network and motion-related networks, and the DRP showed decreased FC in default network. The MPFC, hippocampus, SMA, basal ganglia and cerebellum are indicated to be intrinsically affected regions and effective therapeutic targets. And the FC profiles of default and motion-related networks might be potential core indicators for clinical treatment. This study revealed potential neuromodulatory targets and helped understand pathomechanism of BECTS. Static and dynamic analyses should be combined to investigate neuropsychiatric disorders.

Cortico-striatal synchronization in human focal seizures

Although a number of experimental and clinical studies have pointed out participation or an even more prominent role of basal ganglia in focal seizures, the mode of interaction between cortical and striatal signals remains unclear. In the present study, we took stereoelectroencephalographic (SEEG) recordings in drug-resistant epilepsy patients, to qualitatively and quantitatively analyse the ictal striatum activity as well as its synchronization with cerebral cortex. Eleven patients who underwent SEEG evaluation were prospectively included if they fulfilled two inclusion criteria: (i) at least one orthogonal intracerebral electrode contact explored the basal ganglia, in either their putaminal or caudate part; and (ii) at least two SEEG seizures were recorded. Cortical and subcortical regions of interest were defined and different periods of interest were analysed. SEEG was visually inspected and h2 non-linear correlation analysis performed to study functional connectivity between cortical region of interest and striatum. Six correlation indices were calculated. Two main patterns of striatal activation were recorded: the most frequent was characterized by an early alpha/beta activity that started within the first 5 s after seizure onset, sometimes concomitant with it. The second one was characterized by late, slower, theta/delta activity. A significant difference in h2 correlation indices was observed during the preictal and seizure onset period compared to background for global striatal index, mesio-temporal/striatal index, latero-temporal/striatal index, insular/striatal index, prefrontal/striatal index. In addition, a significant difference in h2 correlation indices was observed during the seizure termination period compared to all the other periods of interest for the six indices calculated. These results indicate that cortico-striatal synchronization can arise from the start of focal seizures. Depending on the ictal frequency pattern, desynchronization can occur later, but a late and terminal hypersynchronization progressively takes over. These changes in synchronization level between cortical and striatal activity might be part of an endogenous mechanism controlling the duration of abnormal oscillations within the striato-thalamo-cortical loop and thereby their termination. Pathophysiology of basal ganglia in focal seizures appears to be much more interlinked with the cortex than expected. Beyond the stereotypical features they could imprint to seizure semiology, their role in strengthening mechanisms underlying cessation of ictal propagation should inspire new rationales for deep brain stimulation in patients with intractable focal epilepsies.

Altered Default Mode Network Dynamics in Civil Aviation Pilots

Background

Airlines occupy an increasingly important place in the economy of many countries. Because air disasters may cause substantial losses, comprehensive surveys of the psychophysiological mechanism of flying are needed; however, relatively few studies have focused on pilots. The default mode network (DMN) is an important intrinsic connectivity network involved in a range of functions related to flying. This study aimed to examine functional properties of the DMN in pilots.

Method

Resting-state functional magnetic resonance imaging data from 26 pilots and 24 controls were collected. Independent component analysis, a data-driven approach, was combined with functional connectivity analysis to investigate functional properties of the DMN in pilots.

Results

The pilot group exhibited increased functional integration in the precuneus/posterior cingulate cortex (PCC) and left middle occipital gyrus. Subsequent functional connectivity analysis identified enhanced functional connection between the precuneus/PCC and medial superior frontal gyrus.

Conclusion

The pilot group exhibited increased functional connections within the DMN. These findings highlight the importance of the DMN in the neurophysiological mechanism of flying.

Regulation and control roles of the basal ganglia in the development of absence epileptiform activities

Absence epileptiform activities are traditionally considered to be primarily induced by abnormal interactions between the cortical and thalamic neurons, which form the thalamocortical circuit in the brain. The basal ganglia, as an organizational unit in the brain, has close input and output relationships with the thalamocortical circuit. Although several studies report that the basal ganglia may participate in controlling and regulating absence epileptiform activities, to date, there have been no studies regarding whether the basal ganglia directly cause absence epileptiform activities. In this paper, we built a basal ganglia-corticothalamic network model to determine the role of basal ganglia in this disease. We determined that absence epileptiform activities might be directly induced by abnormal coupling strengths on certain pivotal pathways in the basal ganglia. These epileptiform activities can be well controlled by the coupling strengths of three major pathways that project from the thalamocortical network to the basal ganglia. The results implied that the substantia nigra pars compacta (SNc) can be considered to be the effective treatment target area for inhibiting epileptiform activities, which supports the observations of previous studies. Particularly, as a major contribution of this paper, we determined that the final presentation position of the epileptic slow spike waves is not limited to the cerebral cortex; these waves may additionally appear in the thalamus, striatal medium spiny neurons, striatal fast spiking interneuron, the SNc, subthalamic nucleus, substantia nigra pars reticulata and globus pallidus pars externa. In addition, consistent with several previous studies, the delay in the network was observed to be a critical factor for inducing transitions between different types of absence epileptiform activities. Our new model not only explains the onset and control mechanism but also provides a unified framework to study similar problems in neuron systems.

Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review

Background: Analysis of the human connectome using functional magnetic resonance imaging (fMRI) started in the mid-1990s and attracted increasing attention in attempts to discover the neural underpinnings of human cognition and neurological disorders. In general, brain connectivity patterns from fMRI data are classified as statistical dependencies (functional connectivity) or causal interactions (effective connectivity) among various neural units. Computational methods, especially graph theory-based methods, have recently played a significant role in understanding brain connectivity architecture. Objectives: Thanks to the emergence of graph theoretical analysis, the main purpose of the current paper is to systematically review how brain properties can emerge through the interactions of distinct neuronal units in various cognitive and neurological applications using fMRI. Moreover, this article provides an overview of the existing functional and effective connectivity methods used to construct the brain network, along with their advantages and pitfalls. Methods: In this systematic review, the databases Science Direct, Scopus, arXiv, Google Scholar, IEEE Xplore, PsycINFO, PubMed, and SpringerLink are employed for exploring the evolution of computational methods in human brain connectivity from 1990 to the present, focusing on graph theory. The Cochrane Collaboration's tool was used to assess the risk of bias in individual studies. Results: Our results show that graph theory and its implications in cognitive neuroscience have attracted the attention of researchers since 2009 (as the Human Connectome Project launched), because of their prominent capability in characterizing the behavior of complex brain systems. Although graph theoretical approach can be generally applied to either functional or effective connectivity patterns during rest or task performance, to date, most articles have focused on the resting-state functional connectivity. Conclusions: This review provides an insight into how to utilize graph theoretical measures to make neurobiological inferences regarding the mechanisms underlying human cognition and behavior as well as different brain disorders.

Altered structural and causal connectivity in frontal lobe epilepsy

Background

Albeit the few resting-state fMRI neuroimaging studies in frontal lobe epilepsy (FLE) patients, these studies focused on functional connectivity. The aim of this current study was to examine the effective connectivity based on voxel-based morphometry in FLE patients.

Methods

Resting-state structural and functional magnetic resonance imaging (fMRI) data were acquired from 19 FLE patients and 19 age and gender-matched healthy controls using the 3.0 Tesla magnetic resonance imaging (3.0 T MRI). The investigations were done by acquiring the structural information through voxel-based morphometry, then based on the seed obtained, Granger causality analysis was used to evaluate the causal flow of the designated seed to and from other significant voxels.

Results

Our results showed altered structural and effective connectivity. Compared with healthy controls, FLE patients showed reduced grey matter volume in bilateral putamen and right caudate as well as altered causality with increased, and decreased causal outflow from the right caudate (seed region) to inferior frontal gyrus-triangular, from bilateral putamen (seed regions) to right middle frontal gyrus and frontal gyrus medial-orbital representing the frontal executive areas, respectively. Also, significantly increased and decreased inflow from left calcarine to right caudate and from cerebellum_6 and vermis_6 to bilateral putamen, respectively. Moreover, we found that the causal alterations to and from the seed regions (from vermis_6 to right putamen and from left putamen to right middle frontal gyrus) negatively correlated with clinical scores (duration of epilepsy).

Conclusions

The findings point to the impairment within the executive and motor-controlled system including the cerebellum, frontal, caudate and putamen regions in FLE patients. These results would therefore enhance our understanding of structural and effective mechanisms in FLE.

Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review

Background: Analysis of the human connectome using functional magnetic resonance imaging (fMRI) started in the mid-1990s and attracted increasing attention in attempts to discover the neural underpinnings of human cognition and neurological disorders. In general, brain connectivity patterns from fMRI data are classified as statistical dependencies (functional connectivity) or causal interactions (effective connectivity) among various neural units. Computational methods, especially graph theory-based methods, have recently played a significant role in understanding brain connectivity architecture. Objectives: Thanks to the emergence of graph theoretical analysis, the main purpose of the current paper is to systematically review how brain properties can emerge through the interactions of distinct neuronal units in various cognitive and neurological applications using fMRI. Moreover, this article provides an overview of the existing functional and effective connectivity methods used to construct the brain network, along with their advantages and pitfalls. Methods: In this systematic review, the databases Science Direct, Scopus, arXiv, Google Scholar, IEEE Xplore, PsycINFO, PubMed, and SpringerLink are employed for exploring the evolution of computational methods in human brain connectivity from 1990 to the present, focusing on graph theory. The Cochrane Collaboration's tool was used to assess the risk of bias in individual studies. Results: Our results show that graph theory and its implications in cognitive neuroscience have attracted the attention of researchers since 2009 (as the Human Connectome Project launched), because of their prominent capability in characterizing the behavior of complex brain systems. Although graph theoretical approach can be generally applied to either functional or effective connectivity patterns during rest or task performance, to date, most articles have focused on the resting-state functional connectivity. Conclusions: This review provides an insight into how to utilize graph theoretical measures to make neurobiological inferences regarding the mechanisms underlying human cognition and behavior as well as different brain disorders.

Neuroscience Information Toolbox: An Open Source Toolbox for EEG-fMRI Multimodal Fusion Analysis

Recently, scalp electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) multimodal fusion has been pursued in an effort to study human brain function and dysfunction to obtain more comprehensive information on brain activity in which the spatial and temporal resolutions are both satisfactory. However, a more flexible and easy-to-use toolbox for EEG–fMRI multimodal fusion is still lacking. In this study, we therefore developed a freely available and open-source MATLAB graphical user interface toolbox, known as the Neuroscience Information Toolbox (NIT), for EEG–fMRI multimodal fusion analysis. The NIT consists of three modules: (1) the fMRI module, which has batch fMRI preprocessing, nuisance signal removal, bandpass filtering, and calculation of resting-state measures; (2) the EEG module, which includes artifact removal, extracting EEG features (event onset, power, and amplitude), and marking interesting events; and (3) the fusion module, in which fMRI-informed EEG analysis and EEG-informed fMRI analysis are included. The NIT was designed to provide a convenient and easy-to-use toolbox for researchers, especially for novice users. The NIT can be downloaded for free at http://www.neuro.uestc.edu.cn/NIT.html, and detailed information, including the introduction of NIT, user’s manual and example data sets, can also be observed on this website. We hope that the NIT is a promising toolbox for exploring brain information in various EEG and fMRI studies.

[Neuronet restructuring in focal and generalized epilepsy according to resting state fMRI]

AIM

To compare neuronet restructuring in focal and generalized epilepsy.

MATERIAL AND METHODS

Seventy-seven patients, aged from 18 to 65 years, with the diagnosis of epilepsy, including 63 patients with focal epilepsy and 14 with generalized epilepsy, were examined. A control group included 23 healthy people. Neuronet restructuring was studied using fMRI.

RESULTS AND CONCLUSION

According to resting state fMRI, there were between-group differences in spatial organization (activity map) of the brain structures as well as in the results of cross-correlation analysis of interaction maps of resting-state networks. It has been concluded that functional restructuring in connectomes in focal and generalized epilepsy have the opposite patterns of disorganization (toward increase or decrease) in most structures studied though there are structures with the same direction of connectivity changes.

Brain functional connectivity in sleep-related hypermotor epilepsy

Objectives

To evaluate functional connectivity (FC) in patients with sleep-related hypermotor epilepsy (SHE) compared to healthy controls.

Methods

Resting state fMRI was performed in 13 patients with a clinical diagnosis of SHE (age = 38.3 ± 11.8 years, 6 M) and 13 matched healthy controls (age = 38.5 ± 10.8 years, 6 M).

Data were first analysed using probabilistic independent component analysis (ICA), then a graph theoretical approach was applied to assess topological and organizational properties at the whole brain level. We evaluated node degree (ND), betweenness centrality (BC), clustering coefficient (CC), local efficiency (LE) and global efficiency (GE). The differences between the two groups were evaluated non-parametrically.

Results

At the group level, we distinguished 16 RSNs (Resting State Networks). Patients showed a significantly higher FC in sensorimotor and thalamic regions (p < 0.05 corrected). Compared to controls, SHE patients showed no significant differences in network global efficiency, while ND and BC were higher in regions of the limbic system and lower in the occipital cortex, while CC and LE were higher in regions of basal ganglia and lower in limbic areas (p < 0.05 uncorrected).

Discussion and conclusions

The higher FC of the sensorimotor cortex and thalamus might be in agreement with the hypothesis of a peculiar excitability of the motor cortex during thalamic K-complexes. This sensorimotor-thalamic hyperconnection might be regarded as a consequence of an alteration of the arousal regulatory system in SHE. An altered topology has been found in structures like basal ganglia and limbic system, hypothesized to be involved in the pathophysiology of the disease as suggested by the dystonic-dyskinetic features and primitive behaviours observed during the seizures.

•

Resting state functional connectivity was studied for the first time in SHE.

•

SHE patients showed higher connectivity in thalamic and motor regions.

•

Motor cortex might show a higher excitability in response to thalamic projections.

•

Brain network topology was altered mainly in basal ganglia and limbic system.

The role of the basal ganglia in the control of seizure

Epilepsy is a network disorder and each type of seizure involves distinct cortical and subcortical network, differently implicated in the control and propagation of the ictal activity. The role of the basal ganglia has been revealed in several cases of focal and generalized seizures. Here, we review the data that show the implication of the basal ganglia in absence, temporal lobe, and neocortical seizures in animal models (rodent, cat, and non-human primate) and in human. Based on these results and the advancement of deep brain stimulation for Parkinson's disease, basal ganglia neuromodulation has been tested with some success that can be equally seen as promising or disappointing. The effect of deep brain stimulation can be considered promising with a 76% in seizure reduction in temporal lobe epilepsy patients, but also disappointing, since only few patients have become seizure free and the antiepileptic effects have been highly variable among patients. This variability could probably be explained by the heterogeneity among the patients included in these clinical studies. To illustrate the importance of specific network identification, electrophysiological activity of the putamen and caudate nucleus has been recorded during penicillin-induced pre-frontal and motor seizures in one monkey. While an increase of the firing rate was found in putamen and caudate nucleus during pre-frontal seizures, only the activity of the putamen cells was increased during motor seizures. These preliminary results demonstrate the implication of the basal ganglia in two types of neocortical seizures and the necessity of studying the network to identify the important nodes implicated in the propagation and control of each type of seizure.