Data integration: Combined imaging and electrophysiology data in the cloud

Kini, Lohith G.; Davis, Kathryn A.; Wagenaar, Joost B.

doi:10.1016/j.neuroimage.2015.05.075

Cited by 48 publications

(35 citation statements)

References 21 publications

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“…All patients gave consent to have their anonymized iEEG data publicly available on the International Epilepsy Electrophysiology Portal (www.ieeg.org). 24,25 Clinical and demographic information is available in…”

Section: Subjectsmentioning

confidence: 99%

High interictal connectivity within the resection zone is associated with favorable post-surgical outcomes in focal epilepsy patients

Shah

Bernabei

Kini

et al. 2018

Preprint

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Objective: Patients with drug-resistant focal epilepsy are often candidates for invasive surgical therapies. In these patients, it is necessary to accurately localize seizure-generators to ensure seizure freedom following intervention. While intracranial electroencephalography (iEEG) is the gold standard for mapping networks for surgery, this approach requires inducing and recording seizures, which may cause patient morbidity. The goal of this study is to evaluate the utility of mapping interictal (non-seizure) iEEG networks to identify targets for surgical treatment. Methods:We analyze interictal iEEG recordings and neuroimaging from 27 focal epilepsy patients treated via surgical resection. We generate interictal functional networks by calculating pairwise correlation of iEEG signals across different frequency bands. We identify electrodes falling within surgically resected tissue (i.e. the resection zone), and compute node-level and edge-level synchrony in relation to the resection zone. We associate these metrics with postsurgical outcomes.Results: Greater overlap between resected electrodes and highly synchronous electrodes is associated with favorable post-surgical outcomes. Additionally, good outcome patients have significantly higher connectivity localized within the resection zone compared to those with poorer postoperative seizure control. This finding persists following normalization by a spatiallyconstrained null model. Conclusions:This study suggests that spatially-informed interictal network synchrony measures can distinguish between good and poor post-surgical outcomes. By capturing clinically relevant information during interictal periods, our method may ultimately reduce the need for prolonged invasive implants and provide insights into the pathophysiology of an epileptic brain. We discuss next steps for translating these findings into a prospectively useful clinical tool.

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Section: Subjectsmentioning

confidence: 99%

High interictal connectivity within the resection zone is associated with favorable post-surgical outcomes in focal epilepsy patients

Shah

Bernabei

Kini

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…To ensure consistency and validity of the captured seizures, we discarded seizures that contained substantial artifacts in all electrodes, events that were very short (< 15 seconds), or those that occurred during sleep. Deidentified iEEG recordings are available online on the International Epilepsy Electrophysiology Portal (www.ieeg.org, IEEG Portal) [Kini et al, 2016;Wagenaar et al, 2013].…”

Section: Intracranial Eeg Acquisitionmentioning

confidence: 99%

Local structural connectivity directs seizure spread in focal epilepsy

Shah

Ashourvan

Mikhail

et al. 2018

Preprint

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How does the human brain's structural scaffold give rise to its intricate functional dynamics? This is a central challenge in translational neuroscience, particularly in epilepsy, a disorder that affects over 50 million people worldwide. Treatment for medication-resistant focal epilepsy is often structural -through surgery, devices or focal laser ablation -but structural targets, particularly in patients without clear lesions, are largely based on functional mapping via intracranial EEG (iEEG). Unfortunately, the relationship between structural and functional connectivity in the seizing brain is poorly understood. In this study, we quantify structurefunction coupling, specifically between white matter connections and iEEG, across preictal and ictal periods in 45 seizures from 9 patients with unilateral drug-resistant focal epilepsy. We use High Angular Resolution Diffusion Imaging (HARDI) tractography to construct structural connectivity networks and correlate these networks with time-varying broadband and frequencyspecific functional networks derived from coregistered iEEG. Across all frequency bands, we find significant increases in structure-function coupling from preictal to ictal periods. We demonstrate that short-range structural connections are primarily responsible for this increase in coupling. Finally, we find that spatiotemporal patterns of structure-function coupling are stereotyped, and a function of each patient's individual anatomy. These results suggest that seizures harness the underlying structural connectome as they propagate. Our findings suggest that the relationship between structural and functional connectivity in epilepsy may inform current and new therapies to map and alter seizure spread, and pave the way for better-targeted, patient-specific interventions.

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“…Patients were then deemed candidates for implantation of intracranial electrodes to better define the epileptic network. De-identified patient data was retrieved from the online International Epilepsy Electrophysiology Portal (IEEG Portal) [59].…”

Section: Methodsmentioning

confidence: 99%

Genetic and neuroanatomical support for functional brain network dynamics in epilepsy

Reddy

Betzel

Khambhati

et al. 2018

Preprint

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Focal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients worldwide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective methods to fuse multimodal neuroimaging data to map anatomical targets driving seizure dynamics. Here we propose a parsimonious model that explains how large-scale anatomical networks and shared genetic constraints shape inter-regional communication in focal epilepsy. In extensive ECoG recordings acquired from a group of patients with medically refractory focal-onset epilepsy, we find that ictal and preictal functional brain network dynamics can be accurately predicted from features of brain anatomy and geometry, patterns of white matter connectivity, and constraints complicit in patterns of gene coexpression, all of which are conserved across healthy adult populations. Moreover, we uncover evidence that markers of non-conserved architecture, potentially driven by idiosyncratic pathology of single subjects, are most prevalent in high frequency ictal dynamics and low frequency preictal dynamics. Finally, we find that ictal dynamics are better predicted by white matter features and more poorly predicted by geometry and genetic constraints than preictal dynamics, suggesting that the functional brain network dynamics manifest in seizures rely on -and may directly propagate alongunderlying white matter structure that is largely conserved across humans. Broadly, our work offers insights into the generic architectural principles of the human brain that impact seizure dynamics, and could be extended to further our understanding, models, and predictions of subject-level pathology and response to intervention.

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Data integration: Combined imaging and electrophysiology data in the cloud

Cited by 48 publications

References 21 publications

High interictal connectivity within the resection zone is associated with favorable post-surgical outcomes in focal epilepsy patients

High interictal connectivity within the resection zone is associated with favorable post-surgical outcomes in focal epilepsy patients

Local structural connectivity directs seizure spread in focal epilepsy

Genetic and neuroanatomical support for functional brain network dynamics in epilepsy

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