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

Sinha, Nishant; Johnson, Graham W.; Davis, Kenneth A.; Englot, Dario J.

doi:10.1177/15357597221101271

Cited by 23 publications

(23 citation statements)

References 52 publications

(51 reference statements)

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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: 86%

“…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%

“…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%

“…a network). [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).…”

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: 86%

Section: Does Imbalanced Reciprocal Connectivity Indicate Suppression?mentioning

confidence: 87%

Section: Resting-state Seeg Connectivitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Johnson

Doss

Morgan

et al. 2022

Preprint

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“…Epilepsy has been increasingly identified as a network disorder [11][12][13] . The study of brain connectomics has demonstrated the presence of large-scale network abnormalities even in focal epilepsies [14][15][16] .…”

Section: Introductionmentioning

confidence: 99%

Resting State Functional Connectivity Demonstrates Increased Segregation in Bilateral Temporal Lobe Epilepsy

Lucas

Cornblath

Sinha

et al. 2022

Preprint

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Temporal lobe epilepsy (TLE) is the most common type of focal epilepsy. An increasingly identified subset of patients with TLE consists of those who show bilaterally independent temporal lobe involvement during seizures. Bilateral TLE (BiTLE) remains understudied, likely due to its complex underlying pathophysiology and heterogeneous clinical presentation. In this study, using a multicenter resting state functional MRI (rs-fMRI) dataset, we constructed whole brain functional networks of 19 patients with BiTLE, and compared them to those of 75 patients with unilateral TLE (UTLE). We quantified resting-state, whole-brain topological properties using metrics derived from network theory, including clustering coefficient, global efficiency, participation coefficient, and modularity. For each metric, we computed an average across all brain regions, and iterated this process across network densities ranging from 0.10-0.50. Curves of network density versus each network metric were compared between groups. Finally, we derived a combined metric, which we term the integration-segregation axis, by combining whole brain average clustering coefficient and global efficiency curves and applying principal component analysis (PCA)-based dimensionality reduction. Compared to UTLE, BiTLE had decreased global efficiency (p=0.026), increased whole brain average clustering coefficient (p=0.035), and decreased whole brain average participation coefficient across a range of network densities (p=0.001). Modularity maximization yielded a larger number of smaller communities in BiTLE than in UTLE (p=0.016). Differences in network properties separate BiTLE and UTLE along the integration-segregation axis: 68% of patients with BiTLE were identified within the high segregation region, while only 41% of the UTLE patients were identified in the same region (p=0.042). Along the integration-segregation axis, UTLE patients with poor surgical outcomes were more similar to BiTLE than those with good surgical outcomes (p=0.72). Increased interictal whole brain network segregation, as measured by rs-fMRI, is specific to BiTLE, and may assist in non-invasively identifying this patient population prior to intracranial EEG or device implantation.

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Imaging and Stereotactic Electroencephalography Functional Networks to Guide Epilepsy Surgery

Doss,

Johnson,

Englot

2024

Neurosurgery Clinics of North America

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

Cited by 23 publications

References 52 publications

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

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

Resting State Functional Connectivity Demonstrates Increased Segregation in Bilateral Temporal Lobe Epilepsy

Imaging and Stereotactic Electroencephalography Functional Networks to Guide Epilepsy Surgery

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