Medicine (Austin & Northern Health) - Research Publications
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ItemThalamocortical functional connectivity in Lennox-Gastaut syndrome is abnormally enhanced in executive-control and default-mode networks(WILEY, 2017-12)OBJECTIVE: To identify abnormal thalamocortical circuits in the severe epilepsy of Lennox-Gastaut syndrome (LGS) that may explain the shared electroclinical phenotype and provide potential treatment targets. METHODS: Twenty patients with a diagnosis of LGS (mean age = 28.5 years) and 26 healthy controls (mean age = 27.6 years) were compared using task-free functional magnetic resonance imaging (MRI). The thalamus was parcellated according to functional connectivity with 10 cortical networks derived using group-level independent component analysis. For each cortical network, we assessed between-group differences in thalamic functional connectivity strength using nonparametric permutation-based tests. Anatomical locations were identified by quantifying spatial overlap with a histologically informed thalamic MRI atlas. RESULTS: In both groups, posterior thalamic regions showed functional connectivity with visual, auditory, and sensorimotor networks, whereas anterior, medial, and dorsal thalamic regions were connected with networks of distributed association cortex (including the default-mode, anterior-salience, and executive-control networks). Four cortical networks (left and right executive-control network; ventral and dorsal default-mode network) showed significantly enhanced thalamic functional connectivity strength in patients relative to controls. Abnormal connectivity was maximal in mediodorsal and ventrolateral thalamic nuclei. SIGNIFICANCE: Specific thalamocortical circuits are affected in LGS. Functional connectivity is abnormally enhanced between the mediodorsal and ventrolateral thalamus and the default-mode and executive-control networks, thalamocortical circuits that normally support diverse cognitive processes. In contrast, thalamic regions connecting with primary and sensory cortical networks appear to be less affected. Our previous neuroimaging studies show that epileptic activity in LGS is expressed via the default-mode and executive-control networks. Results of the present study suggest that the mediodorsal and ventrolateral thalamus may be candidate targets for modulating abnormal network behavior underlying LGS, potentially via emerging thalamic neurostimulation therapies.
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ItemCognitive network reorganization following surgical control of seizures in Lennox-Gastaut syndrome(WILEY, 2017-05)We previously observed that adults with Lennox-Gastaut syndrome (LGS) show abnormal functional connectivity among cognitive networks, suggesting that this may contribute to impaired cognition. Herein we report network reorganization following seizure remission in a child with LGS who underwent functional magnetic resonance imaging (fMRI) before and after resection of a cortical dysplasia. Concurrent electroencephalography (EEG) was acquired during presurgical fMRI. Presurgical and postsurgical functional connectivity were compared using (1) graph theoretical analyses of small-world network organization and node-wise strength; and (2) seed-based analyses of connectivity within and between five functional networks. To explore the specificity of these postsurgical network changes, connectivity was further compared to nine children with LGS who did not undergo surgery. The presurgical EEG-fMRI revealed diffuse activation of association cortex during interictal discharges. Following surgery and seizure control, functional connectivity showed increased small-world organization, stronger connectivity in subcortical structures, and greater within-network integration/between-network segregation. These changes suggest network improvement, and diverged sharply from the comparison group of nonoperated children. Following surgery, this child with LGS achieved seizure control and showed extensive reorganization of networks that underpin cognition. This case illustrates that the epileptic process of LGS can directly contribute to abnormal network organization, and that this network disruption may be reversible.
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ItemClinical benefit of presurgical EEG-fMRI in difficult-to-localize focal epilepsy: A single-institution retrospective review(WILEY, 2020-01)OBJECTIVE: The aim of this report is to present our clinical experience of electroencephalography-functional magnetic resonance imaging (EEG-fMRI) in localizing the epileptogenic focus, and to evaluate the clinical impact and challenges associated with the use of EEG-fMRI in pharmacoresistant focal epilepsy. METHODS: We identified EEG-fMRI studies (n = 118) in people with focal epilepsy performed at our center from 2003 to 2018. Participants were referred from our Comprehensive Epilepsy Program in an exploratory research effort to address often difficult clinical questions, due to complex and difficult-to-localize epilepsy. We assessed the success of each study, the clinical utility of the result, and when surgery was performed, the postoperative outcome. RESULTS: Overall, 50% of EEG-fMRI studies were successful, meaning that data were of good quality and interictal epileptiform discharges were recorded. With an altered recruitment strategy since 2012 with increased inclusion of patients who were inpatients for video-EEG monitoring, we found that this patients in this selected group were more likely to have epileptic discharges detected during EEG-fMRI (96% of inpatients vs 29% of outpatients, P<.0001). To date, 48% (57 of 118) of patients have undergone epilepsy surgery. In 10 cases (17% of the 59 successful studies) the EEG-fMRI result had a "critical impact" on the surgical decision. These patients were difficult to localize because of subtle abnormalities, apparently normal MRI, or extensive structural abnormalities. All 10 had a good seizure outcome at 1 year after surgery (mean follow-up 6.5 years). SIGNIFICANCE: EEG-fMRI results can assist identification of the epileptogenic focus in otherwise difficult-to-localize cases of pharmacoresistant focal epilepsy. Surgery determined largely by localization from the EEG-fMRI result can lead to good seizure outcomes. A limitation of this study is its retrospective design with nonconsecutive recruitment. Prospective clinical trials with well-defined inclusion criteria are needed to determine the overall benefit of EEG-fMRI for preoperative localization and postoperative outcome in focal epilepsy.
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ItemAn automated method for identifying artifact in independent component analysis of resting-state fMRI(FRONTIERS MEDIA SA, 2013-07-10)An enduring issue with data-driven analysis and filtering methods is the interpretation of results. To assist, we present an automatic method for identification of artifact in independent components (ICs) derived from functional MRI (fMRI). The method was designed with the following features: does not require temporal information about an fMRI paradigm; does not require the user to train the algorithm; requires only the fMRI images (additional acquisition of anatomical imaging not required); is able to identify a high proportion of artifact-related ICs without removing components that are likely to be of neuronal origin; can be applied to resting-state fMRI; is automated, requiring minimal or no human intervention. We applied the method to a MELODIC probabilistic ICA of resting-state functional connectivity data acquired in 50 healthy control subjects, and compared the results to a blinded expert manual classification. The method identified between 26 and 72% of the components as artifact (mean 55%). About 0.3% of components identified as artifact were discordant with the manual classification; retrospective examination of these ICs suggested the automated method had correctly identified these as artifact. We have developed an effective automated method which removes a substantial number of unwanted noisy components in ICA analyses of resting-state fMRI data. Source code of our implementation of the method is available.
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ItemCOMBIT: protocol of a randomised comparison trial of COMbined modified constraint induced movement therapy and bimanual intensive training with distributed model of standard upper limb rehabilitation in children with congenital hemiplegia(BMC, 2013-06-28)INTRODUCTION: Children with congenital hemiplegia often present with limitations in using their impaired upper limb which impacts on independence in activities of daily living, societal participation and quality of life. Traditional therapy has adopted a bimanual training approach (BIM) and more recently, modified constraint induced movement therapy (mCIMT) has emerged as a promising unimanual approach. Evidence of enhanced neuroplasticity following mCIMT suggests that the sequential application of mCIMT followed by bimanual training may optimise outcomes (Hybrid CIMT). It remains unclear whether more intensely delivered group based interventions (hCIMT) are superior to distributed models of individualised therapy. This study aims to determine the optimal density of upper limb training for children with congenital hemiplegia. METHODS AND ANALYSES: A total of 50 children (25 in each group) with congenital hemiplegia will be recruited to participate in this randomized comparison trial. Children will be matched in pairs at baseline and randomly allocated to receive an intensive block group hybrid model of combined mCIMT followed by intensive bimanual training delivered in a day camp model (COMBiT; total dose 45 hours direct, 10 hours of indirect therapy), or a distributed model of standard occupational therapy and physiotherapy care (SC) over 12 weeks (total 45 hours direct and indirect therapy). Outcomes will be assessed at 13 weeks after commencement, and retention of effects tested at 26 weeks. The primary outcomes will be bimanual coordination and unimanual upper-limb capacity. Secondary outcomes will be participation and quality of life. Advanced brain imaging will assess neurovascular changes in response to treatment. Analysis will follow standard principles for RCTs, using two-group comparisons on all participants on an intention-to-treat basis. Comparisons will be between treatment groups using generalized linear models. TRIAL REGISTRATION: ACTRN12613000181707.
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ItemConstructing carbon fiber motion-detection loops for simultaneous EEG-fMRI(FRONTIERS MEDIA SA, 2015-01-05)One of the most significant impediments to high-quality EEG recorded in an MRI scanner is subject motion. Availability of motion artifact sensors can substantially improve the quality of the recorded EEG. In the study of epilepsy, it can also dramatically increase the confidence that one has in discriminating true epileptiform activity from artifact. This is due both to the reduction in artifact and the ability to visually inspect the motion sensor signals when reading the EEG, revealing whether or not head motion is present. We have previously described the use of carbon fiber loops for detecting and correcting artifact in EEG acquired simultaneously with MRI. The loops, attached to the subject's head, are electrically insulated from the scalp. They provide a simple and direct measure of specific artifact that is contaminating the EEG, including both subject motion and residual artifact arising from magnetic field gradients applied during MRI. Our previous implementation was used together with a custom-built EEG-fMRI system that differs substantially from current commercially available EEG-fMRI systems. The present technical note extends this work, describing in more detail how to construct the carbon fiber motion-detection loops, and how to interface them with a commercially available simultaneous EEG-fMRI system. We hope that the information provided may help those wishing to utilize a motion-detection/correction solution to improve the quality of EEG recorded within an MRI scanner.
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ItemDe-noising with a SOCK can improve the performance of event-related ICA(FRONTIERS MEDIA SA, 2014-09-19)Event-related ICA (eICA) is a partially data-driven analysis method for event-related fMRI that is particularly suited to analysis of simultaneous EEG-fMRI of patients with epilepsy. EEG-fMRI studies in epileptic patients are typically analyzed using the general linear model (GLM), often with assumption that the onset and offset of neuronal activity match EEG event onset and offset, the neuronal activation is sustained at a constant level throughout the epileptiform event and that associated fMRI signal changes follow the canonical HRF. The eICA method allows for less constrained analyses capable of detecting early, non-canonical responses. A key step of eICA is the initial deconvolution which can be confounded by various sources of structured noise present in the fMRI signal. To help overcome this, we have extend the eICA procedure by utilizing a fully standalone and automated fMRI de-noising procedure to process the fMRI data from an EEG-fMRI acquisition prior to running eICA. Specifically we first apply ICA to the entire fMRI time-series and use a classifier to remove noise-related components. The automated objective de-noiser, "Spatially Organized Component Klassificator" (SOCK) is used; it has previously been shown to distinguish a substantial fraction of noise from true activation, without rejecting the latter, in resting-state fMRI. A second ICA is then performed, this time on the event-related response estimates derived from the denoised data (according to the usual eICA procedure). We hypothesize that SOCK + eICA has the potential to be more sensitive than eICA alone. We test the effectiveness of SOCK by comparing activation obtained in an eICA analysis of EEG-fMRI data with and without the use of SOCK for 14 patients with rolandic epilepsy who exhibited stereotypical IEDs arising from a focus in the rolandic fissure.
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ItemConceptualizing Lennox-Gastaut syndrome as a secondary network epilepsy(FRONTIERS MEDIA SA, 2014)Lennox-Gastaut Syndrome (LGS) is a category of severe, disabling epilepsy, characterized by frequent, treatment-resistant seizures, and cognitive impairment. Electroencephalography (EEG) shows characteristic generalized epileptic activity that is similar in those with lesional, genetic, or unknown causes, suggesting a common underlying mechanism. The condition typically begins in young children, leaving many severely disabled with recurring seizures throughout their adult life. Scalp EEG of the tonic seizures of LGS is characterized by a diffuse high-voltage slow transient evolving into generalized low-voltage fast activity, likely reflecting sustained fast neuronal firing over a wide cortical area. The typical interictal discharges (runs of slow spike-and-wave and bursts of generalized paroxysmal fast activity) also have a "generalized" electrical field, suggesting widespread cortical involvement. Recent brain mapping studies have begun to reveal which cortical and subcortical regions are active during these "generalized" discharges. In this critical review, we examine findings from neuroimaging studies of LGS and place these in the context of the electrical and clinical features of the syndrome. We suggest that LGS can be conceptualized as "secondary network epilepsy," where the epileptic activity is expressed through large-scale brain networks, particularly the attention and default-mode networks. Cortical lesions, when present, appear to chronically interact with these networks to produce network instability rather than triggering each individual epileptic discharge. LGS can be considered as "secondary" network epilepsy because the epileptic manifestations of the disorder reflect the networks being driven, rather than the specific initiating process. In this review, we begin with a summation of the clinical manifestations of LGS and what this has revealed about the underlying etiology of the condition. We then undertake a systematic review of the functional neuroimaging literature in LGS, which leads us to conclude that LGS can best be conceptualized as "secondary network epilepsy."
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ItemInterictal Epileptiform Discharges Might Be More Likely During Particular Phases of Brain Activity(FRONTIERS MEDIA SA, 2015-12-04)