No abstract

Patients with drug-resistant epilepsy often require surgery to become seizure-free. While laser ablation and implantable stimulation devices have lowered the morbidity of these procedures, seizure-free rates have not dramatically improved, particularly for patients without focal lesions. This is in part because it is often unclear where to intervene in these cases. To address this clinical need, several research groups have published methods to map epileptic networks but applying them to improve patient care remains a challenge. In this study we advance clinical translation of these methods by: (i) presenting and sharing a robust pipeline to rigorously quantify the boundaries of the resection zone and determining which intracranial EEG electrodes lie within it; (ii) validating a brain network model on a retrospective cohort of 28 patients with drug-resistant epilepsy implanted with intracranial electrodes prior to surgical resection; and (iii) sharing all neuroimaging, annotated electrophysiology, and clinical metadata to facilitate future collaboration. Our network methods accurately forecast whether patients are likely to benefit from surgical intervention based on synchronizability of intracranial EEG (area under the receiver operating characteristic curve of 0.89) and provide novel information that traditional electrographic features do not. We further report that removing synchronizing brain regions is associated with improved clinical outcome, and postulate that sparing desynchronizing regions may further be beneficial. Our findings suggest that data-driven network-based methods can identify patients likely to benefit from resective or ablative therapy, and perhaps prevent invasive interventions in those unlikely to do so.

Filtering information on the basis of what is relevant to accomplish our goals is a critical process supporting optimal cognitive performance. However, it is not known whether exposure to irrelevant environmental stimuli impairs our ability to accurately retrieve longterm memories. We hypothesized that visual processing of irrelevant visual information would interfere with mental visualization engaged during recall of the details of a prior experience, despite goals to direct full attention to the retrieval task. In the current study, we compared performance on a cued-recall test of previously studied visual items when participants' eyes were closed to performance when their eyes were open and irrelevant visual stimuli were presented. A behavioral experiment revealed that recollection of episodic details was diminished in the presence of the irrelevant information. A functional magnetic resonance imaging experiment using the same paradigm replicated the behavioral results and found that diminished recollection was associated with the disruption of functional connectivity in a network involving the left inferior frontal gyrus, hippocampus and visual association cortex. Network connectivity supported recollection of contextual details based on visual imagery when eyes were closed, but declined in the presence of irrelevant visual information. We conclude that bottom-up influences from irrelevant visual information interfere with top-down selection of episodic details mediated by a capacity-limited frontal control region, resulting in impaired recollection.

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. 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. Using image coregistration and segmentation, 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 further associate these metrics with post-surgical outcomes. 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 spatially-constrained null model. 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.

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.

Objective The importance of the cholinergic system for cognitive function has been well-documented in animal and human studies. The objective of this study was to elucidate the cognitive and functional connectivity changes associated with enhanced acetylcholine (ACh) levels. We hypothesized older adults with mild memory deficits would show behavioral and functional network enhancements with an acetylcholinesterase inhibitor treatment (donepezil) when compared to a placebo control group. Methods We conducted a 3-month, double-blind, placebo-controlled study on the effects of donepezil in twenty-seven older adults with mild memory deficits. Participants completed a delayed recognition memory task. FMRI scans were collected at baseline prior to treatment and at 3-month follow-up while on a 10 mg daily dose of donepezil or placebo. Results Donepezil treatment significantly enhanced the response time for face and scene memory probes when compared to the placebo group. A group-by-visit interaction was identified for the functional network connectivity of the left fusiform face area (FFA) with the hippocampus and inferior frontal junction, such that the treatment group showed increased connectivity over time when compared to the placebo group. Additionally, the enhanced functional network connectivity of the FFA and hippocampus significantly predicted memory response time at 3-month follow-up in the treatment group. Interpretation These findings suggest that increased cholinergic transmission improves goal-directed neural processing and cognitive ability and may serve to facilitate communication across functionally-connected attention and memory networks. Longitudinal fMRI is a useful method for elucidating the neural changes associated with pharmacological modulation and is a potential tool for monitoring intervention efficacy in clinical trials.

Objective: Evaluating patients with drug-resistant epilepsy often requires inducing seizures by tapering antiseizure medications (ASMs) in the epilepsy monitoring unit (EMU). The relationship between ASM taper strategy, seizure timing, and severity remains unclear. In this study, we developed and validated a pharmacokinetic model of total ASM load and tested its association with seizure occurrence and severity in the EMU. Methods:We studied 80 patients who underwent intracranial electroencephalographic recording for epilepsy surgery planning. We developed a first order pharmacokinetic model of the ASMs administered in the EMU to generate a continuous metric of overall ASM load. We then related modeled ASM load to seizure likelihood and severity. We determined the association between the rate of ASM load reduction, the length of hospital stay, and the probability of having a severe seizure. Finally, we used modeled ASM load to predict oncoming seizures.Results: Seizures occurred in the bottom 50th percentile of sampled ASM loads across the cohort (p < .0001, Wilcoxon signed-rank test), and seizures requiring rescue therapy occurred at lower ASM loads than seizures that did not require rescue therapy (logistic regression mixed effects model, odds ratio = .27, p = .01).Greater ASM decrease early in the EMU was not associated with an increased likelihood of having a severe seizure, nor with a shorter length of stay.

No abstract