FlywheelTools: Data Curation and Manipulation on the Flywheel Platform

The recent and growing focus on reproducibility in neuroimaging studies has led many major academic centers to use cloud-based imaging databases for storing, analyzing, and sharing complex imaging data. Flywheel is one such database platform that offers easily accessible, large-scale data management, along with a framework for reproducible analyses through containerized pipelines. The Brain Imaging Data Structure (BIDS) is the de facto standard for neuroimaging data, but curating neuroimaging data into BIDS can be a challenging and time-consuming task. In particular, standard solutions for BIDS curation are limited on Flywheel. To address these challenges, we developed “FlywheelTools,” a software toolbox for reproducible data curation and manipulation on Flywheel. FlywheelTools includes two elements: fw-heudiconv, for heuristic-driven curation of data into BIDS, and flaudit, which audits and inventories projects on Flywheel. Together, these tools accelerate reproducible neuroscience research on the widely used Flywheel platform

Analyse de connectivité EEG régime reposant dans l'épilepsie bénigne de l'enfance et des nouveau-nés

The thesis investigated the functional connectivity in children with benign childhood epilepsy with centrotemporal spike and functional brain network organization in preterm and full-term neonates. The patients with the epilepsy had functional brain disruption and the alterations of resting state functional connectivity is frequency dependent in comparison to the healthy controls. The epileptic brain network is disrupted in the presence and absence of interictal epileptic discharges. The regions involved in the generation and propagation of epilepsy were identified including epileptic zone (central region), rolandic region and the supplementary motor areas. In the neonates, preterm neonates were characterized with the high functional connectivity at the frontal and posterior regions. The presence of endogenous activity in preterm such as theta temporal activity revealed high functional connectivity at the temporal region. Similar functional brain network organization was observed in full-term neonates with the high functional activity at the frontal, temporal and posterior regions in both active and quite sleep periodsLe travail réalisé au cours de cette thèse a porté sur l'étude de la connectivité cérébrale fonctionnelle des réseaux épileptiques chez des enfants présentant des épilepsies avec pointes centro temporales (EPCT), et sur l'organisation fonctionnelle des réseaux de repos chez des nouveaux-nés sains et des prématurés. Les patients épileptiques présentent une désorganisation fonctionnelle cérébrale qui participe à une altération des réseaux de repos selon la gamme de fréquence des activités cérébrales. Cette désorganisation fonctionnelle bien que plus importante durant les périodes de pointes épileptiques intercritiques est aussi observée dans les périodes sans pointes intercritiques. Les régions impliquées dans la genèse et la propagation des pointes intercritiques englobent la région centrale (zone épileptiques), la région rolandique et l'aire prémotrice. Chez le nouveau-né et le prématuré la connectivité fonctionnelle est majeure dans les régions frontales et postérieures. Les activités endogènes thêta temporales du prématuré présentent une connectivité restreinte aux seules régions temporales. Chez le nouveau-né à terme l'organisation fonctionnelle est similaire avec une forte connectivité dans les régions frontales temporales et postérieures dans le sommeil calme et le sommeil agit

Analyse de connectivité EEG régime reposant dans l'épilepsie bénigne de l'enfance et des nouveau-nés

The thesis investigated the functional connectivity in children with benign childhood epilepsy with centrotemporal spike and functional brain network organization in preterm and full-term neonates. The patients with the epilepsy had functional brain disruption and the alterations of resting state functional connectivity is frequency dependent in comparison to the healthy controls. The epileptic brain network is disrupted in the presence and absence of interictal epileptic discharges. The regions involved in the generation and propagation of epilepsy were identified including epileptic zone (central region), rolandic region and the supplementary motor areas. In the neonates, preterm neonates were characterized with the high functional connectivity at the frontal and posterior regions. The presence of endogenous activity in preterm such as theta temporal activity revealed high functional connectivity at the temporal region. Similar functional brain network organization was observed in full-term neonates with the high functional activity at the frontal, temporal and posterior regions in both active and quite sleep periodsLe travail réalisé au cours de cette thèse a porté sur l'étude de la connectivité cérébrale fonctionnelle des réseaux épileptiques chez des enfants présentant des épilepsies avec pointes centro temporales (EPCT), et sur l'organisation fonctionnelle des réseaux de repos chez des nouveaux-nés sains et des prématurés. Les patients épileptiques présentent une désorganisation fonctionnelle cérébrale qui participe à une altération des réseaux de repos selon la gamme de fréquence des activités cérébrales. Cette désorganisation fonctionnelle bien que plus importante durant les périodes de pointes épileptiques intercritiques est aussi observée dans les périodes sans pointes intercritiques. Les régions impliquées dans la genèse et la propagation des pointes intercritiques englobent la région centrale (zone épileptiques), la région rolandique et l'aire prémotrice. Chez le nouveau-né et le prématuré la connectivité fonctionnelle est majeure dans les régions frontales et postérieures. Les activités endogènes thêta temporales du prématuré présentent une connectivité restreinte aux seules régions temporales. Chez le nouveau-né à terme l'organisation fonctionnelle est similaire avec une forte connectivité dans les régions frontales temporales et postérieures dans le sommeil calme et le sommeil agit

Identifying neural drivers of benign childhood epilepsy with centrotemporal spikes

Epilepsy is a neurological disorder characterized by abnormal electrical discharges in a group of brain cells. Benign childhood epilepsy, which affect children under the age of 12years, has been reported to contribute to the cognitive impairment of these children, even in the absence of structural abnormalities. Functional connectivity models have been applied to provide a deeper understanding of the processes that control and regulate interictal activity of benign childhood epilepsy. These studies have shown regions of increased connectivity and activity, particularly at the epileptic zone, which is usually the central region around the sensorimotor cortex, and in the immediate regions surrounding the zone and reduced activity in distant regions, such as the frontal lobe and temporal regions. The present study was designed to identify the neural drivers involved in the initiation and propagation of epileptic activity and the causal relationships between brain regions with increased and decreased connectivity and functional activity. We used three different models to identify neural drivers and casual connectivity with dynamic causal modelling (DCM) of EEG data. All models showed that the central region, the source of the epileptic activity, is the major driver of the brain network during interictal discharges. Other regions include the temporoparietal junction and temporal pole. The central region also had influence on the frontal and contralateral hemisphere, which might explain the cognitive deficits observed in these patients. Keywords: Benign childhood epilepsy, EEG, Dynamic causal modelling, Interictal activit

EEG resting state analysis of cortical sources in patients with benign epilepsy with centrotemporal spikes

AbstractBenign epilepsy with centrotemporal spikes (BECTS) is the most common idiopathic childhood epilepsy, which is often associated with developmental disorders in children. In the present study, we analyzed resting state EEG spectral changes in the sensor and source spaces in eight BECTS patients compared with nine age-matched controls. Using high-resolution scalp EEG data, we assessed statistical differences in spatial distributions of EEG power spectra and cortical sources of resting state EEG rhythms in five frequency bands: δ (0.5–3.5 Hz), θ (4–8 Hz), α (8.5–13 Hz), β1 (13.5–20 Hz) and β2 (20.5–30 Hz) under the eyes-closed resting state condition. To further investigate the impact of centrotemporal spikes on EEG spectra, we split the EEG data of the patient group into EEG portions with and without spikes. Source localization demonstrated the homogeneity of our population of BECTS patients with a common epileptic zone over the right centrotemporal region. Significant differences in terms of both spectral power and cortical source densities were observed between controls and patients. Patients were characterized by significantly increased relative power in θ, α, β1 and β2 bands in the right centrotemporal areas over the spike zone and in the right temporo-parieto-occipital junction. Furthermore, the relative power in all bands significantly decreased in the bilateral frontal and parieto-occipital areas of patients regardless of the presence or absence of spikes in EEG segments. However, the spectral differences between patients and controls were more pronounced in the presence of spikes. This observation emphasized the impact of benign epilepsy on cortical source power, especially in the right centrotemporal regions. Spectral changes in bilateral frontal and parieto-occipital areas may also suggest alterations in the default mode network in BECTS patients

Functional Brain Dysfunction in Patients with Benign Childhood Epilepsy as Revealed by Graph Theory.

There is growing evidence that brain networks are altered in epileptic subjects. In this study, we investigated the functional connectivity and brain network properties of benign childhood epilepsy with centrotemporal spikes using graph theory. Benign childhood epilepsy with centrotemporal spikes is the most common form of idiopathic epilepsy in young children under the age of 16 years. High-density EEG data were recorded from patients and controls in resting state with eyes closed. Data were preprocessed and spike and spike-free segments were selected for analysis. Phase locking value was calculated for all paired combinations of channels and for five frequency bands (δ, θ, α, β1 and β2). We computed the degree and small-world parameters--clustering coefficient (C) and path length (L)--and compared the two patient conditions to controls. A higher degree at epileptic zones during interictal epileptic spikes (IES) was observed in all frequency bands. Both patient conditions reduced connection at the occipital and right frontal regions close to the epileptic zone in the α band. The "small-world" features (high C and short L) were deviated in patients compared to controls. A changed from an ordered network in the δ band to a more randomly organized network in the α band was observed in patients compared to healthy controls. These findings show that the benign epileptic brain network is disrupted not only at the epileptic zone, but also in other brain regions especially frontal regions

Statistical difference (t-value) maps of degree between the control (CON) and the epileptic groups (WSC and NSC).

<p>The color bar indicates the t values projected onto a standardized head shape. The significant increase (indicated by red) and decrease (indicated by blue) in degree have been represented, respectively, by positive and negative t values resulted from statistical comparisons between (WSC and CON), (NSC and CON), and (WSC and NSC).</p

Mean and range of changes (at 95% confidence interval) of phase locking value (PLV), threshold (<i>τ</i>) and degree (K) computed for each group and frequency band.

<p>Mean and range of changes (at 95% confidence interval) of phase locking value (PLV), threshold (<i>τ</i>) and degree (K) computed for each group and frequency band.</p

Mean clustering coefficient (C) and mean path length (L) as a function of network density for each frequency band.

<p>The error bars represent standard error with 95% confidence intervals. CON, WSC and NSC indicate the control, with spike and no spike conditions, respectively. Statistical significance is denoted by * (WSC vs. CON), + (NSC vs. CON) and × (WSC vs. NSC) with p<0.05.</p