Sources and Sinks in Interictal iEEG Networks: An iEEG Marker of the Epileptogenic Zone

Gunnarsdottir, Kristin M.; González-Martínez, Jorge; Wing, S.; Sarma, Sridevi V.

doi:10.1109/embc46164.2021.9630035

Cited by 3 publications

(6 citation statements)

References 11 publications

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“…The SOZ and PZ power was not significantly altered in the alpha band [8][9][10][11][12] Hz] (Figure 2B). The SOZ and PZ power was elevated compared to baseline in both beta [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] and gamma bands , but post-hoc multiple comparisons revealed that the SOZ elevation in power was only significantly different from non-involved regions in the beta band and only from PZs in the gamma band (Figure 2C-D, beta: SOZ single-population t-test p-value=9.00e-3, one-way ANOVA p-value=2.98e-2, post-hoc pairwise t-test comparison SOZ-Non p-value=2.24e-2; gamma: SOZ single-population t-test p-value=6.70e-3, one-way ANOVA p-value=1.11e-2, post-hoc pairwise t-test comparison SOZ-PZ p-value=1.33e-2).…”

Section: Low Frequency Power Is Attenuated In Sozs When the Network I...mentioning

confidence: 85%

“…75,[87][88][89][90][91] Overall, when presumably healthy regions were stimulated, the SOZ theta [4-8 Hz] relative band power was markedly decreased from pre-stimulation baseline. Conversely, SOZ beta [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] and gamma relative band power increased when healthy regions were stimulated. Increased inward evoked gamma band power in SOZs is in alignment with previous low-frequency stimulation findings.…”

Section: Does Imbalanced Reciprocal Connectivity Indicate Suppression?mentioning

confidence: 87%

“…Recent evidence has suggested that epileptogenic zones have increased inward connectivity which could relate to interictal suppression of epileptiform activity. 19,20,[72][73][74][75][76][77][78] Whereas other works have focused on observations of increased outward connectivity from SOZs to the rest of the network. 31,79,80 In response to the existing variety of observations and interpretations of functional connectivity in the epileptic network, this work sought to partially test the specific hypothesis of interictal suppression of SOZs (the ISH) at the electrographic network level by characterizing the direction and relative elevation or attenuation of neural activity.…”

Section: Discussionmentioning

confidence: 99%

“…To quantify the overall direction of a node's connectivity, reciprocal connectivity was calculated as the difference between each node's inward and outward connectivity. All connectivity was analyzed in the theta [4][5][6][7], alpha [8][9][10][11][12], beta [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30], and gamma oscillatory bands.…”

Section: Resting-state Seeg Connectivitymentioning

confidence: 99%

“…[21][22][23][24][25][26] Specifically, recent work has shown that SOZs exhibit increased inward interictal connectivity from other nodes of the brain. 20,27 This work has led us to propose the Interictal Suppression Hypothesis (ISH), which posits that the SOZ is tonically suppressed by other areas of the brain during the resting state to prevent seizure initiation (Figure 1). The premise of this hypothesis is intuitively based on the clinical observation that people with DRE are not continuously having seizures, so perhaps there is an interictal, widespread functional organization of the brain that is actively suppressing epileptiform activity.…”

Section: Introductionmentioning

confidence: 99%

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The Interictal Suppression Hypothesis in Focal Epilepsy: Electrographic and Structural Evaluation

Johnson

Doss

Morgan

et al. 2022

Preprint

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Why are people with focal epilepsy not constantly seizing? Previous molecular work has implicated gamma-aminobutyric acid balance as integral to seizure generation and termination, but is the high-level distributed brain network involved in suppressing seizures? Recent intracranial electrographic evidence has suggested that seizure onset zones have an increased inward connectivity. Accordingly, we hypothesize that seizure onset zones are actively suppressed by the rest of the brain network during interictal states.We tested this hypothesis on 81 subjects with drug resistant focal epilepsy undergoing presurgical evaluation. We utilized intracranial electrographic resting-state and neurostimulation recordings to evaluate the network connectivity of seizure onset, propagative, and non-involved regions. We then utilized diffusion imaging to acquire estimates of white matter connectivity to evaluate structure-function coupling effects on connectivity findings. Finally, using our observations, we generated a resting-state classification model to assist clinicians in detecting seizure onset and propagative zones without the need for multiple ictal recordings.Our findings indicate that seizure onset and propagative zones demonstrate markedly increased inward connectivity and decreased outward connectivity on both resting-state and neurostimulation analyses. When controlling for distance between regions, the difference between inward vs. outward connectivity remained stable up to 80 mm between brain connections. Structure-function coupling analyses revealed that seizure onset zones exhibit abnormally enhanced coupling (hypercoupling) of surrounding regions compared to presumably healthy tissue. Using these observations, our classification models achieved a maximum held-out testing set accuracy of 92.0±2.2%.These results indicate that seizure onset zones are actively segregated and suppressed by a widespread brain network. Furthermore, this electrographically observed functional suppression is disproportionate to any observed structural connectivity alterations of the seizure onset zones. These findings have implications for the identification of seizure onset zones using only brief resting-sate recordings to reduce patient morbidity and augment the presurgical evaluation of drug resistant epilepsy. Furthermore, testing of the interictal suppression hypothesis can provide insight into potential new resective, ablative, and neuromodulation approaches to improve surgical success rates in those suffering from drug resistant focal epilepsy.

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Section: Low Frequency Power Is Attenuated In Sozs When the Network I...mentioning

confidence: 85%

Section: Does Imbalanced Reciprocal Connectivity Indicate Suppression?mentioning

confidence: 87%

Section: Discussionmentioning

confidence: 99%

Section: Resting-state Seeg Connectivitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Interictal Suppression Hypothesis in Focal Epilepsy: Electrographic and Structural Evaluation

Johnson

Doss

Morgan

et al. 2022

Preprint

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The Interictal Suppression Hypothesis in focal epilepsy: network-level supporting evidence

Johnson

Doss

Morgan

et al. 2023

Brain

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Why are people with focal epilepsy not continuously having seizures? Previous neuronal signaling work has implicated gamma-aminobutyric acid balance as integral to seizure generation and termination, but is a high-level distributed brain network involved in suppressing seizures? Recent intracranial electrographic evidence has suggested that seizure onset zones have increased inward connectivity which could be associated with interictal suppression of seizure activity. Accordingly, we hypothesize that seizure onset zones are actively suppressed by the rest of the brain network during interictal states. Full testing of this hypothesis would require collaboration across multiple domains of neuroscience. We focused on partially testing this hypothesis at the electrographic network level within 81 individuals with drug resistant focal epilepsy undergoing presurgical evaluation. We utilized intracranial electrographic resting-state and neurostimulation recordings to evaluate the network connectivity of seizure onset, early propagation, and non-involved zones. We then utilized diffusion imaging to acquire estimates of white matter connectivity to evaluate structure-function coupling effects on connectivity findings. Finally, we generated a resting-state classification model to assist clinicians in detecting seizure onset and propagation zones without the need for multiple ictal recordings. Our findings indicate that seizure onset and early propagation zones demonstrate markedly increased inward connectivity and decreased outward connectivity using both resting-state (one-way ANOVA, p-value=3.13e-13) and neurostimulation analyses to evaluate evoked responses (one-way ANOVA, p-value=2.5e-3). When controlling for the distance between regions, the difference between inward and outward connectivity remained stable up to 80 mm between brain connections (two-way repeated measures ANOVA, group effect p-value of 2.6e-12). Structure-function coupling analyses revealed that seizure onset zones exhibit abnormally enhanced coupling (hypercoupling) of surrounding regions compared to presumably healthy tissue (two-way repeated measures ANOVA, interaction effect p-value of 9.76e-21). Using these observations, our support vector classification models achieved a maximum held-out testing set accuracy of 92.0±2.2% to classify early propagation and seizure onset zones. These results suggest that seizure onset zones are actively segregated and suppressed by a widespread brain network. Furthermore, this electrographically observed functional suppression is disproportionate to any observed structural connectivity alterations of the seizure onset zones. These findings have implications for the identification of seizure onset zones using only brief electrographic recordings to reduce patient morbidity and augment the presurgical evaluation of drug resistant epilepsy. Further testing of the interictal suppression hypothesis can provide insight into potential new resective, ablative, and neuromodulation approaches to improve surgical success rates in those suffering from drug resistant focal epilepsy.

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Integrating Network Neuroscience Into Epilepsy Care: Progress, Barriers, and Next Steps

et al. 2022

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Drug resistant epilepsy is a disorder involving widespread brain network alterations. Recently, many groups have reported neuroimaging and electrophysiology network analysis techniques to aid medical management, support presurgical planning, and understand postsurgical seizure persistence. While these approaches may supplement standard tests to improve care, they are not yet used clinically or influencing medical or surgical decisions. When will this change? Which approaches have shown the most promise? What are the barriers to translating them into clinical use? How do we facilitate this transition? In this review, we will discuss progress, barriers, and next steps regarding the integration of brain network analysis into the medical and presurgical pipeline.

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Sources and Sinks in Interictal iEEG Networks: An iEEG Marker of the Epileptogenic Zone

Cited by 3 publications

References 11 publications

The Interictal Suppression Hypothesis in Focal Epilepsy: Electrographic and Structural Evaluation

The Interictal Suppression Hypothesis in Focal Epilepsy: Electrographic and Structural Evaluation

The Interictal Suppression Hypothesis in focal epilepsy: network-level supporting evidence

Integrating Network Neuroscience Into Epilepsy Care: Progress, Barriers, and Next Steps

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