Linear aspects of transformation from interictal epileptic discharges to BOLD fMRI signals in an animal model of occipital epilepsy

Epileptic disorders manifest with seizures and interictal epileptic discharges (IEDs). The hemodynamic changes that accompany IEDs are poorly understood and may be critical for understanding epileptogenesis. Despite a known linear coupling of the neurovascular elements in normal brain tissues, previous simultaneous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) studies have shown variable correlations between epileptic discharges and blood oxygenation level-dependent (BOLD) response, partly because most previous studies assumed particular hemodynamic properties in normal brain tissue. The occurrence of IEDs in human subjects is unpredictable. Therefore, an animal model with reproducible stereotyped IEDs was developed by the focal injection of penicillin into the right occipital cortex of rats anesthetized with isoflurane. Simultaneous EEG-fMRI was used to study the hemodynamic changes during IEDs. A hybrid of temporal independent component analysis (ICA) of EEG and spatial ICA of fMRI data was used to correlate BOLD fMRI signals with IEDs. A linear autoregression with exogenous input (ARX) model was used to estimate the hemodynamic impulse response function (HIRF) based on the data from simultaneous EEG-fMRI measurement. Changes in the measured BOLD signal from the right primary visual cortex and bilateral visual association cortices were consistently coupled to IEDs. The linear ARX model was applied here to confirm that a linear transform can be used to study the correlation between BOLD signal and its corresponding neural activity in this animal model of occipital epilepsy.     

Integrating EEG and fMRI in epilepsy

Integrating electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) studies enables to non-invasively investigate human brain function and to find the direct correlation of these two important measures of brain activity. Presurgical evaluation of patients with epilepsy is one of the areas where EEG and fMRI integration has considerable clinical relevance for localizing the brain regions generating interictal epileptiform activity. The conventional analysis of EEG-fMRI data is based on the visual identification of the interictal epileptiform discharges (IEDs) on scalp EEG. The convolution of these EEG events, represented as stick functions, with a model of the fMRI response, i.e. the hemodynamic response function, provides the regressor for general linear model (GLM) analysis of fMRI data. However, the conventional analysis is not automatic and suffers of some subjectivity in IEDs classification. Here, we present an easy-to-use and automatic approach for combined EEG-fMRI analysis able to improve IEDs identification based on Independent Component Analysis and wavelet analysis. EEG signal due to IED is reconstructed and its wavelet power is used as a regressor in GLM. The method was validated on simulated data and then applied on real data set consisting of 2 normal subjects and 5 patients with partial epilepsy. In all continuous EEG-fMRI recording sessions a good quality EEG was obtained allowing the detection of spontaneous IEDs and the analysis of the related BOLD activation. The main clinical finding in EEG-fMRI studies of patients with partial epilepsy is that focal interictal slow-wave activity was invariably associated with increased focal BOLD responses in a spatially related brain area. Our study extends current knowledge on epileptic foci localization and confirms previous reports suggesting that BOLD activation associated with slow activity might have a role in localizing the epileptogenic region even in the absence of clear interictal spikes.     

Analysis of EEG-fMRI data in focal epilepsy based on automated spike classification and Signal Space Projection

Simultaneous acquisition of EEG and fMRI data enables the investigation of the hemodynamic correlates of interictal epileptiform discharges (IEDs) during the resting state in patients with epilepsy. This paper addresses two issues: (1) the semi-automation of IED classification in statistical modelling for fMRI analysis and (2) the improvement of IED detection to increase experimental fMRI efficiency. For patients with multiple IED generators, sensitivity to IED-correlated BOLD signal changes can be improved when the fMRI analysis model distinguishes between IEDs of differing morphology and field. In an attempt to reduce the subjectivity of visual IED classification, we implemented a semi-automated system, based on the spatio-temporal clustering of EEG events. We illustrate the technique's usefulness using EEG-fMRI data from a subject with focal epilepsy in whom 202 IEDs were visually identified and then clustered semi-automatically into four clusters. Each cluster of IEDs was modelled separately for the purpose of fMRI analysis. This revealed IED-correlated BOLD activations in distinct regions corresponding to three different IED categories. In a second step, Signal Space Projection (SSP) was used to project the scalp EEG onto the dipoles corresponding to each IED cluster. This resulted in 123 previously unrecognised IEDs, the inclusion of which, in the General Linear Model (GLM), increased the experimental efficiency as reflected by significant BOLD activations. We have also shown that the detection of extra IEDs is robust in the face of fluctuations in the set of visually detected IEDs. We conclude that automated IED classification can result in more objective fMRI models of IEDs and significantly increased sensitivity.     

Independent component analysis of interictal fMRI in focal epilepsy: comparison with general linear model-based EEG-correlated fMRI

The general linear model (GLM) has been used to analyze simultaneous EEG-fMRI to reveal BOLD changes linked to interictal epileptic discharges (IED) identified on scalp EEG. This approach is ineffective when IED are not evident in the EEG. Data-driven fMRI analysis techniques that do not require an EEG derived model may offer a solution in these circumstances. We compared the findings of independent components analysis (ICA) and EEG-based GLM analyses of fMRI data from eight patients with focal epilepsy. Spatial ICA was used to extract independent components (IC) which were automatically classified as either BOLD-related, motion artefacts, EPI-susceptibility artefacts, large blood vessels, noise at high spatial or temporal frequency. The classifier reduced the number of candidate IC by 78%, with an average of 16 BOLD-related IC. Concordance between the ICA and GLM-derived results was assessed based on spatio-temporal criteria. In each patient, one of the IC satisfied the criteria to correspond to IED-based GLM result. The remaining IC were consistent with BOLD patterns of spontaneous brain activity and may include epileptic activity that was not evident on the scalp EEG. In conclusion, ICA of fMRI is capable of revealing areas of epileptic activity in patients with focal epilepsy and may be useful for the analysis of EEG-fMRI data in which abnormalities are not apparent on scalp EEG.     

EEG-fMRI同步联合对局灶性癫痫的定位

目的 采用脑电图功能磁共振l司步联合的方法,用于局灶性癫痫患者的术前定位.方法 11例局灶性癫痫患者,术前行脑电图功能磁共振同步联合检查,观察癫痫发作间期,痫样放电所致的腩活动情况,并结合同步EEG检查结果、术后病理及定期随访的情况对fMRI结果进行分析.结果 10 例(10/11)患者均在颅内原有病灶周围发现明显的 fMRI信号激活区,并与同步EEG检查的痫样放电脑区基本一致.术后病理证实病灶周围存在导致癫痫发作的病理性改变,术后随访证实11例患者均取得满意的手术效果.讨论局灶性癫痫间期痫样放电引起的血氧水平依赖性效应可用于癫痫灶的定位,脑电图功能磁共振同步联合的检查技术结合,可用于局灶性癫痫的术前定位.     

Hemodynamic and metabolic responses to activation, deactivation and epileptic discharges

To investigate the coupling between the hemodynamic and metabolic changes following functional brain activation as well as interictal epileptiform discharges (IEDs), blood oxygenation level dependent (BOLD), perfusion and oxygen consumption responses to a unilateral distal motor task and interictal epileptiform discharges (IEDs) were examined via continuous EEG-fMRI. Seven epilepsy patients performed a periodic (1 Hz) right-hand pinch grip using approximately 8% of their maximum voluntary contraction, a paradigm previously shown to produce contralateral MI neuronal excitation and ipsilateral MI neuronal inhibition. A multi-slice interleaved pulsed arterial spin labeling and T(2)*-weighted gradient echo sequence was employed to quantify cerebral blood flow (CBF) and BOLD changes. EEG was recorded throughout the imaging session and reviewed to identify the IEDs. During the motor task, BOLD, CBF and cerebral metabolic rate of oxygen consumption (CMR(O(2))) signals increased in the contra- and decreased in the ipsilateral primary motor cortex. The relative changes in CMR(O(2)) and CBF were linearly related, with a slope of 0.46 +/- 0.05. The ratio of contra- to ipsilateral CBF changes was smaller in the present group of epilepsy patients than in the healthy subjects examined previously. IEDs produced both increases and decreases in BOLD and CBF signals. In the two case studies for which the estimation criteria were met, the coupling ratio between IED-induced CMR(O(2)) and CBF changes was estimated at 0.48 +/- 0.17. These findings provide evidence for a preserved coupling between hemodynamic and metabolic changes in response to both functional activation and, for the two case studies available, in response to interictal epileptiform activity.     

Event-related fMRI with simultaneous and continuous EEG: description of the method and initial case report

We report on the initial imaging findings with a new technique for the simultaneous and continuous acquisition of functional MRI data and EEG recording. Thirty-seven stereotyped interictal epileptiform discharges (spikes) were identified on EEG recorded continuously during the fMRI acquisition on a patient with epilepsy. Localization of the BOLD activation associated with the EEG events was consistent with previous findings and EEG source modeling. The time course of activation was comparable with the physiological hemodynamic response function (HRF). The new methodology could lead to novel and important applications in many areas of neuroscience.     

BOLD and perfusion changes during epileptic generalised spike wave activity

It is unclear whether neurovascular coupling is maintained during epileptic discharges. Knowing this is important to allow appropriate inferences from functional imaging studies of epileptic activity. Recent blood oxygen level-dependent (BOLD) functional MRI (fMRI) studies have demonstrated negative BOLD responses (NBR) in frontal, parietal and posterior cingulate cortices during generalised spike wave activity (GSW). We hypothesized that GSW-related NBR commonly reflect decreased cerebral blood flow (CBF). We measured BOLD and cerebral blood flow responses using simultaneous EEG with BOLD and arterial spin label (ASL) fMRI at 3 T. Four patients with epilepsy were studied; two with idiopathic generalized epilepsy (IGE) and two with secondary generalized epilepsy (SGE). We found GSW-related NBR in frontal, parietal and posterior cingulate cortices. We measured the coupling between BOLD and CBF changes during GSW and normal background EEG and found a positive correlation between the simultaneously measured BOLD and CBF throughout the imaged volume. Frontal and thalamic activation were seen in two patients with SGE, concordant with the electro-clinical features of their epilepsy. There was striking reproducibility of the GSW-associated BOLD response in subjects previously studied at 1.5 T. Our results show a preserved relationship between BOLD and CBF changes during rest and GSW activity consistent with normal neurovascular coupling in patients with generalized epilepsy and in particular during GSW activity. Cortical activations appear to reflect areas of discharge generation whilst deactivations reflect changes in conscious resting state activity.     

原发性复杂部分性发作癫痫的脑静息态MRI研究

目的应用局部一致性（ReHo）、低频振幅（ALFF）及功能连接（Fc）等三种技术探讨原发性复杂部分性发作（cPs）癫痫患者静息态脑功能的变化。方法对40例CPS患者和40例年龄、性别及受教育程度相匹配的正常志愿者进行静息态fMRI检查（经校正,实际研究对象为病例组和对照组各37例）,运用REST、SPM8软件进行全脑分析,比较基于ReHo、ALFF、FC技术的脑功能变化情况。结果通过以上三种技术发现CPS患者内侧颞叶及其周围脑区参与了痫样放电,默认网络和小脑受癫痫活动的破坏和抑制最大。结论在静息状态下,ReHo、ALFF和FC技术对癫痫的研究具有很大的价值,它们能监测异常的血氧水平依赖信号,帮助定位癫痫灶,还有助于癫痫病理生理机制的探索。     

低频振幅分析及EEG-fMRI对局灶性癫痫活动定位的比较研究

目的 对比低频振幅(ALFF)分析技术与脑电联合功能磁共振成像(EEG-fMRI)技术对局灶性癫痫活动检测的能力,评估ALFF分析技术在局灶性癫痫活动定位中的应用价值。方法 纳入24例有明确病理灶存在的局灶性癫痫患者,分别利用GE 1.5T MRI仪(17例)及Siemens 3.0T MRI仪(7例)行同步EEG-fMRI数据采集。以广义线性模型(GLM)方法对间期痫样发放(IEDs)相关fMRI活动的检测为基础;再采用ALFF分析技术,对个例患者与大样本正常受试者基线数据进行两样本t检验(P<0.05,Alphasim校正),检测局灶性癫痫脑区ALFF改变的位置。最后以临床或手术癫痫定位结果为标准,对比分析两种fMRI技术对癫痫活动的检测能力。结果 36次有效癫痫EEG-fMRI数据中,两种分析技术均检出明显的BOLD结果。EEG-fMRI定位结果与临床定位结果相关者15次(15/36,41.66%);ALFF结果与临床定位结果相关者24次(24/36,66.67%)。两者定位结果一致且均与临床定位结果相关者9次(9/36,25.00%),两者定位结果均与临床定位结果不符者6次(6/36,16.67%)。结论 EEG-fMRI能有效检出癫痫活动相关脑区;基于ALFF的fMRI技术可在不须同步EEG信息的情况下更好地检测癫痫活动。     

Continuous EEG source imaging enhances analysis of EEG-fMRI in focal epilepsy

IntroductionEEG-correlated fMRI (EEG-fMRI) studies can reveal haemodynamic changes associated with Interictal Epileptic Discharges (IED). Methodological improvements are needed to increase sensitivity and specificity for localising the epileptogenic zone. We investigated whether the estimated EEG source activity improved models of the BOLD changes in EEG-fMRI data, compared to conventional « event-related » designs based solely on the visual identification of IED.MethodsTen patients with pharmaco-resistant focal epilepsy underwent EEG-fMRI. EEG Source Imaging (ESI) was performed on intra-fMRI averaged IED to identify the irritative zone. The continuous activity of this estimated IED source (cESI) over the entire recording was used for fMRI analysis (cESI model). The maps of BOLD signal changes explained by cESI were compared to results of the conventional IED-related model.ResultsESI was concordant with non-invasive data in 13/15 different types of IED. The cESI model explained significant additional BOLD variance in regions concordant with video-EEG, structural MRI or, when available, intracranial EEG in 10/15 IED. The cESI model allowed better detection of the BOLD cluster, concordant with intracranial EEG in 4/7 IED, compared to the IED model. In 4 IED types, cESI-related BOLD signal changes were diffuse with a pattern suggestive of contamination of the source signal by artefacts, notably incompletely corrected motion and pulse artefact. In one IED type, there was no significant BOLD change with either model.ConclusionContinuous EEG source imaging can improve the modelling of BOLD changes related to interictal epileptic activity and this may enhance the localisation of the irritative zone.     

Simultaneous electroencephalographic recording and functional magnetic resonance imaging during pentylenetetrazol-induced seizures in rat

Truly simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) were registered in curarized rats injected with convulsive doses of pentylenetetrazol (PTZ, 65 mg/kg, sc). Rigorous control of physiological parameters like body temperature and ventilation with control of blood gasses helped to avoid potential interference between systemic parameters, and central PTZ-induced blood oxygenation level-dependent (BOLD) changes. Simultaneous EEG/fMRI recordings demonstrated progressive epileptiform EEG discharges with concomitant BOLD changes, the latter gradually affecting most of the fore- and midbrain. Approximately 15 min after PTZ injection, the first BOLD contrast changes mainly occurred in neocortex, and coincided with the first minor EEG alterations. Most regions that displayed BOLD changes were regions with reportedly high GABA(A) receptor densities. Full-blown epileptiform discharges occurred on the EEG tracing, approximately 30 min after PTZ injection, and coincided with bilateral positive and/or negative BOLD contrast changes in cortical and subcortical regions. Behavioral observations demonstrated the first of several generalized clonic or clonic-tonic seizure episodes to occur also around this time. Approximately 90 min after injection, the electrographic paroxysms gradually decreased in amplitude and duration, whereas the BOLD signal changes still extended with alternating positive and negative traces, and spread to subcortical regions like caudate-putamen and globus pallidus.     

BOLD signal increase preceeds EEG spike activity--a dynamic penicillin induced focal epilepsy in deep anesthesia

In 40-60% of cases with interictal activity in EEG, fMRI cannot locate any focus or foci with simultaneous EEG/fMRI. In experimental focal epilepsy, a priori knowledge exists of the location of the epileptogenic area. This study aimed to develop and to test an experimental focal epilepsy model, which includes dynamic induction of epileptic activity, simultaneous EEG/fMRI, and deep anesthesia. Reported results are from seven pigs (23 +/- 2 kg) studied under isoflurane anesthesia (1.2-1.6 MAC, burst-suppression EEG) and muscle relaxant. Hypo- and hypercapnia were tested in one pig. Penicillin (6000 IU) was injected via a plastic catheter (inserted into the somatosensory cortex) during fMRI (GRE-EPI, TE = 40 ms, 300 ms/two slices, acquisition delay 1700 ms) in 1.5 T (N = 6). Epileptic spikes between acquisition artifacts were reviewed and EEG total power calculated. Cross-correlation between voxel time series and three model functions resembling induced spike activity were tested. Activation map averages were calculated. Development of penicillin induced focal epileptic activity was associated with linear increase and saturation up to approximately 10-20%, in BOLD activation map average. Its initial linear increase reached 2.5-10% at the appearance of the first distinguished spike in ipsilateral EEG in all six animals. Correlated voxels were located mainly in the vicinity of the penicillin injection site and midline, but few in the thalamus. In conclusion, development of focal epileptic activity can be detected as a BOLD signal change, even preceding the spike activity in scalp EEG. This experimental model contains potential for development and testing different localization methods and revealing the characteristic time sequence of epileptic activity with fMRI during deep anesthesia.     

The BOLD response to interictal epileptiform discharges

We studied single-event and average BOLD responses to EEG interictal epileptic discharges (IEDs) in four patients with focal epilepsy, using continuous EEG-fMRI during 80-min sessions. The detection of activated areas was performed by comparing the BOLD signal at each voxel to a model of the expected signal. Since little is known about the BOLD response to IEDs, we modeled it with the response to brief auditory events (G. H., NeuroImage 9, 416-429). For each activated area, we then obtained the time course of the BOLD signal for the complete session and computed the actual average hemodynamic response function (HRF) to IEDs. In two of four patients, we observed clear BOLD responses to single IEDs. The average response was composed of a positive lobe peaking between 6 and 7 s in all patients and a negative undershoot in three patients. There were important variations in amplitude and shape between average HRFs across patients. The average HRF presented a wider positive lobe than the Glover model in three patients and a longer undershoot in two. There was a remarkable similarity in the shape of the HRF across areas for patients presenting multiple activation sites. There was no clear correlation between the amplitude of individual BOLD responses and the amplitude of the corresponding EEG spike. The possibility of a longer HRF could be used to improve statistical detection of activation in simultaneous EEG-fMRI. The variability in average HRFs across patients could reflect in part different pathophysiological mechanisms.     

How reliable are fMRI-EEG studies of epilepsy? A nonparametric approach to analysis validation and optimization

Simultaneously acquired functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) data hold great promise for localizing the spatial source of epileptiform events detected in the EEG trace. Despite a number of studies applying this method, there has been no independent and systematic validation of the approach. The present study uses a nonparametric method to show that interictal discharges lead to a blood oxygen level dependent (BOLD) response that is significantly different to that obtained by examining random 'events'. We also use this approach to examine the optimization of analysis strategy for detecting these BOLD responses. Two patients with frequent epileptiform events and a healthy control were studied. The fMRI data for each patient were analyzed using a model derived from the timings of the epileptiform events detected on EEG during fMRI scanning. Twenty sets of random pseudoevents were used to generate a null distribution representing the level of chance correlation between the EEG events and fMRI data. The same pseudoevents were applied to control data. We demonstrate that it is possible to detect blood oxygen level-dependent (BOLD) changes related to interictal discharges with specific and independent knowledge about the reliability of this activation. Biologically generated events complicate the fMRI-EEG experiment. Our proposed validation examines whether identified events have an associated BOLD response beyond chance and allows optimization of analysis strategies. This is an important step beyond standard analysis. It informs clinical interpretation because it permits assessment of the reliability of the connection between interictal EEG events and the BOLD response to those events.     

fMRI temporal clustering analysis in patients with frequent interictal epileptiform discharges: comparison with EEG-driven analysis

Temporal clustering analysis (TCA) is an exploratory data-driven technique that has been proposed for the analysis of resting fMRI to localise epileptiform activity without need for simultaneous EEG. Conventionally, fMRI of epileptic activity has been limited to those patients with subtle clinical events or frequent interictal epileptiform EEG discharges, requiring simultaneous EEG recording, from which a linear model is derived to make valid statistical inferences from the fMRI data. We sought to evaluate TCA by comparing the results with those of EEG correlated fMRI in eight selected cases. Cases were selected with clear epileptogenic localisation or lateralisation on the basis of concordant EEG and structural MRI findings, in addition to concordant activations seen on EEG-derived fMRI analyses. In three, areas of activation were seen with TCA but none corresponding to the electro-clinical localisation or activations obtained with EEG driven analysis. Temporal clusters were closely coincident with times of maximal head motion. We feel this is a serious confound to this approach and recommend that interpretation of TCA that does not address motion and physiological noise be treated with caution. New techniques to localise epileptogenic activity with fMRI alone require validation with an appropriate independent measure. In the investigation of interictal epileptiform activity, this is best done with simultaneous EEG recording.     

A framework to integrate EEG-correlated fMRI and intracerebral recordings

EEG-correlated functional MRI (EEG-fMRI) has been used to indicate brain regions associated with interictal epileptiform discharges (IEDs). This technique enables the delineation of the complete epileptiform network, including multifocal and deeply situated cortical areas. Before EEG-fMRI can be used as an additional diagnostic tool in the preoperative work-up, its added value should be assessed in relation to intracranial EEG recorded from depth electrodes (SEEG) or from the cortex (ECoG), currently the clinical standard. In this study, we propose a framework for the analysis of the SEEG data to investigate in a quantitative way whether EEG-fMRI reflects the same cortical areas as identified by the IEDs present in SEEG recordings. For that purpose, the data of both modalities were analyzed with a general linear model at the same time scale and within the same spatial domain. The IEDs were used as predictors in the model, yielding for EEG-fMRI the brain voxels that were related to the IEDs and, similarly for SEEG, the electrodes that were involved. Finally, the results of the regression analysis were projected on the anatomical MRI of the patients. To explore the usefulness of this quantitative approach, a sample of five patients was studied who both underwent EEG-fMRI and SEEG recordings. For clinical validation, the results of the SEEG analysis were compared to the standard visual review of IEDs in SEEG and to the identified seizure onset zone, the resected area, and outcome of surgery. SEEG analysis revealed a spatial pattern for the most frequent and dominant IEDs present in the data of all patients. The electrodes with the highest correlation values were in good concordance with the electrodes that showed maximal amplitude during those events in the SEEG recordings. These results indicate that the analysis of SEEG data at the time scale of EEG-fMRI, using the same type of regression model, is a promising way to validate EEG-fMRI data. In fact, the BOLD areas with a positive hemodynamic response function were closely related to the spatial pattern of IEDs in the SEEG recordings in four of the five patients. The areas of significant BOLD that were not located in the vicinity of depth electrodes, were mainly characterized by negative hemodynamic responses. Furthermore, the area with a positive hemodynamic response function overlapped with the resected area in three patients, while it was located at the edge of the resection area for one. To conclude, the results of this study encourage the application of EEG-fMRI to guide the implantation of depth electrodes as prerequisite for successful epilepsy surgery.     

Brain activation using triggered event-related fMRI

EEG-triggered fMRI provides a method for localizing the sources of brain electrical activity, such as epileptic discharges. Extending single-image acquisitions, following an event on the EEG, into triggered image series acquisitions may allow BOLD time courses to be obtained, such as those observed in event-related (ER) fMRI experiments. However, in contrast to the standard ER-fMRI, triggered image series are greatly affected by magnetization non-steady-state effects. The purpose of this paper is to show that the BOLD responses can be recovered using subtraction between two triggered image series having different functional contrasts. In order to evaluate this technique, a comparison with standard ER-fMRI using motor cortex activation task was made in 5 volunteers. We conclude that this can be a useful technique for studying brain activation associated with irregularly appearing stimuli.     

间期痫样发放对内侧颞叶癫痫脑网络的影响

目的探讨间期痫样发放对内侧颞叶癫痫患者脑静息态网络的影响,揭示间期癫痫活动发放对全脑功能的损害机制。材料与方法从45例行同步脑电f MRI数据采集单侧颞叶癫痫患者中,挑选35例(左侧颞叶癫痫患者18例、右侧颞叶癫痫患者17例),以同步脑电图监测,每一患者均采集间期痫样发放及无痫样发放状态静息态f MRI数据。采用独立成分分析方法,分别提取患者两种状态的核心网络、背侧注意网络、执行控制网络、默认网络及感觉运动网络等7套内在连接网络。采用配对t检验比较痫样发放及无痫样发放状态m TLE患者脑内在连接网络的差异。结果相比未发放状态,发放状态下颞叶癫痫患者核心网络的前扣带回功能连接增强,听觉网络的脑岛及颞上回功能连接减低。此外,背侧注意网络的顶上小叶在左侧颞叶癫痫患者表现为功能连接增强,而在右侧表现为连接减弱。前默认网络的额中回在右侧表现为功能连接减弱,而后默认网络颞中回及后扣带回在右侧表现为功能连接增强。执行控制网络的中扣带回和视觉网络枕叶皮层在左侧表现为功能连接增强。相关分析结果显示,左侧组视觉网络及右侧组听觉网络内连接强度的变化与发放状态下IEDs发放次数呈正相关。结论内侧颞叶癫痫发作间期痫样发放对脑高级认知网络及感知觉网络均产生了广泛影响,尤其是对参与脑高级认知功能网络的损害,这有助于进一步了解海马硬化这一特异性内侧颞叶癫痫在发作间期脑功能受损机制。     

Multispectral intraoperative imaging for the detection of the hemodynamic response to interictal epileptiform discharges

Interictal epileptiform discharges (IEDs) are brief neuronal discharges occurring between seizures in patients with epilepsy. The characterization of the hemodynamic response function (HRF) specific to IEDs could increase the accuracy of other functional imaging techniques to localize epileptiform activity, including functional near-infrared spectroscopy and functional magnetic resonance imaging. This study evaluated the possibility of using an intraoperative multispectral imaging system combined with electrocorticography (ECoG) to measure the average HRF associated with IEDs in eight patients. Inter-patient variability of the HRF is illustrated in terms of oxygenated hemoglobin peak latency, oxygenated hemoglobin increase/decrease following IEDs, and signal-to-noise ratio. A sub-region was identified using an unsupervised clustering algorithm in three patients that corresponded to the most active area identified by ECoG.