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Network neuroscience applied to epilepsy holds promise to map pathological networks, localize seizure generators, and inform targeted interventions to control seizures. However, incomplete sampling of the epileptic brain because of sparse placement of intracranial electrodes may affect model results. In this study, we evaluate the sensitivity of several published network measures to incomplete spatial sampling and propose an algorithm using network subsampling to determine confidence in model results. We retrospectively evaluated intracranial EEG data from 28 patients implanted with grid, strip, and depth electrodes during evaluation for epilepsy surgery. We recalculated global and local network metrics after randomly and systematically removing subsets of intracranial EEG electrode contacts. We found that sensitivity to incomplete sampling varied significantly across network metrics. This sensitivity was largely independent of whether seizure onset zone contacts were targeted or spared from removal. We present an algorithm using random subsampling to compute patient-specific confidence intervals for network localizations. Our findings highlight the difference in robustness between commonly used network metrics and provide tools to assess confidence in intracranial network localization. We present these techniques as an important step toward translating personalized network models of seizures into rigorous, quantitative approaches to invasive therapy.

The piriform cortex is recognized as highly epileptogenic in rodents, yet its electrophysiological role in human epilepsy remains understudied. Recent surgical outcomes have suggested potential benefits in resecting the piriform cortex for cases of medial temporal lobe epilepsy. However, little is known about its electrophysiological activity in human epilepsy. This case-series study aimed to explore the electrophysiological role of the piriform cortex within the epileptogenic network among patients with suspected temporal lobe epilepsy. Participants were recruited from Emory University Hospital or Children's Healthcare of Atlanta, with non-lesional frontotemporal or temporal lobe hypotheses, undergoing stereoelectroencephalographic studies. Specifically, focus was placed on patients with one or more electrode contacts in the piriform cortex. Primary objectives included determining piriform cortex involvement within the electrophysiologically defined epileptogenic network and assessing the effects of electrical stimulation. Twenty-two patients were included in the study. Notably, only one patient exhibited piriform cortex involvement at seizure onset, associated with an olfactory aura. Two patients showed early piriform cortex involvement, while others displayed late or no involvement. Electrical stimulation of the piriform cortex induced after-discharges in three patients and replicated a habitual seizure in one. These findings present a contrast to surgical outcome studies, suggesting that the piriform cortex may not typically play a significant role in the epileptogenic network among patients with non-lesional temporal lobe epilepsy.

The piriform cortex (PC) is part of the olfactory system, principally receiving input from the lateral olfactory tract and projecting to downstream components of the olfactory network, including the amygdala. Based on preclinical studies, PC is vulnerable to injury and can be easily kindled as an onset site for seizures. While the role of PC in human epilepsy has been studied indirectly and the subject of speculation, cases of demonstrated PC seizure onset from direct intracranial recording are rare. We present a pediatric patient with drug-resistant focal reflex epilepsy and right mesial temporal sclerosis with habitual seizures triggered by coconut aroma. The patient underwent stereoelectroencephalography with implantation of olfactory cortices including PC, through which we identified PC seizure onset, mapped high-frequency activity associated with presentation of olfactory stimuli and performance on cognitive tasks, and reproduced habitual seizures via cortical stimulation of PC. Coconut odor did not trigger seizures in our work with the patient. Surgical workup resulted in resection of the patient's right amygdala, PC, and mesial temporal pole, following which she has been seizure free for 20 months without functional decline in cognition or smell. Histological findings from resected tissue showed astrogliosis and subpial gliosis.

PurposeCorticocortical evoked potentials (CCEPs) resulting from single pulse electrical stimulation are increasingly used to understand seizure networks, as well as normal brain connectivity. However, we observed that when using depth electrodes, traditional measures of CCEPs amplitude using a referential montage can be falsely localizing, often to white matter.MethodsWe pooled 27 linear electrode arrays targeting the amygdala, hippocampus, or cingulate cortex from eight participants. Using postoperative imaging, we classified contacts as being in gray matter, white matter, or bordering each and measured the amplitude using the root-mean-squared deviation from baseline in a referential, common average, bipolar, or Laplacian montage.ResultsOf 27 electrode contacts, 25 (93%) had a significantly higher mean amplitude when in gray matter than in white matter using a Laplacian montage, which was significantly more than the 12 of 27 electrodes (44%) when using a referential montage ( P = 0.0003, Fisher exact test). The area under the curve for a receiver operating characteristic classifying contacts as gray or white matter was significantly higher for either the Laplacian (0.79) or the bipolar (0.72) montage when compared with either the common average (0.56) or the referential (0.51) montage ( P ≤ 0.005, bootstrap).ConclusionsBoth the Laplacian and bipolar montages were superior to the common average or referential montage in localizing CCEPs to gray matter. These montages may be more appropriate for interpreting CCEPs when using depth electrodes than the referential montage, which has typically been used in prior studies of CCEPs with subdural grids.

Roughly two-thirds of all people report having experienced déjà vu-the odd feeling that a current experience is both novel and a repeat or replay of a previous, unrecalled experience. Reports of an association between déjà vu and seizure aura symptomatology have accumulated for over a century, and frequent déjà vu is also now known to be associated with focal seizures, particularly those of a medial temporal lobe (MTL) origin. A longstanding question is whether seizure-related déjà vu has the same basis and is the same subjective experience as non-seizure déjà vu. Survey research suggests that people who experience both seizure-related and non-seizure déjà vu can often subjectively distinguish between the two. We present a case of a person with a history of focal MTL seizures who reports having experienced both seizure-related and non-seizure common déjà vu, though the non-seizure type was more frequent during this person's youth than it is currently. The patient was studied with a virtual tour paradigm that has previously been shown to elicit déjà vu among non-clinical, young adult participants. The patient reported experiencing déjà vu of the common non-seizure type during the virtual tour paradigm, without associated abnormalities of the intracranial EEG. We situate this work in the context of broader ongoing projects examining the subjective correlates of seizures. The importance for memory research of virtual scenes, spatial tasks, virtual reality (VR), and this paradigm for isolating familiarity in the context of recall failure are discussed.

The purpose of this review is to describe the functional anatomy of the precuneal cortex and outline some semiological features of precuneal seizures. The precuneal cortex is a structure that occupies the posterior medial portion of the parietal lobe, and it has broad cortical and subcortical connections. Neuroanatomical tracing, functional imaging, as well as electrical stimulation studies of humans and other primates have elucidated many complex integrative functions of the precuneus including visuo-spatial imagery, sensorimotor functions, and consciousness. Based on the understanding of its functions and connectivity, descriptions of potential seizure semiologies are hypothesized and compared to what is available in the literature. The latter is mostly in the form of case reports or case series. Seizures may involve simple or complex motor or sensory manifestations including abnormal eye movements, visual hallucinations, sensation of motion, or medial temporal-like seizures.

Mapping of cortical functions is critical for the best clinical care of patients undergoing epilepsy and tumor surgery, but also to better understand human brain function and connectivity. The purpose of this review is to explore existing and potential means of mapping higher cortical functions, including stimulation mapping, passive mapping, and connectivity analyses. We examine the history of mapping, differences between subdural and stereoelectroencephalographic approaches, and some risks and safety aspects, before examining different types of functional mapping. Much of this review explores the prospects for new mapping approaches to better understand other components of language, memory, spatial skills, executive, and socio-emotional functions. We also touch on brain-machine interfaces, philosophical aspects of aligning tasks to brain circuits, and the study of consciousness. We end by discussing multi-modal testing and virtual reality approaches to mapping higher cortical functions.

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.

Objective: To predict one‐year seizure freedom, using a combination of relevant clinical variables, following stereotactic laser amygdalohippocampotomy for mesial temporal lobe epilepsy in a series of 101 patients. Methods: Eight predictors of seizure freedom were selected based on their association with medial temporal lobe epilepsy: (1) MRI evidence of mesial temporal sclerosis (MTS); (2) unitemporal interictal epileptiform discharges; (3) absence of generalized tonic–clonic seizures; (4) history of febrile seizures; (5) onset of epilepsy ≤16 years; (6) absence of an auditory, visual, or vertiginous aura; and (7) unitemporal ictal onset; (8) unitemporal PET hypometabolism. We compared four multivariate models: "MTS," using just evidence of MTS; "FULL," using all eight binary predictors; "AIC" using backwards selection of variables; and "SCORE," using a 0‐to‐8‐point ordinal score awarding one point for each binary predictor. Results: In univariate analysis, significant predictors for seizure freedom were evidence of mesial temporal sclerosis (p = 0.011, Fisher exact) and unitemporal interictal discharges (p = 0.005). For multivariate prediction (using leave one‐out cross‐validation), the ordinal SCORE model had a significantly higher area under the curve (AUC 0.70) than the other three models: MTS (AUC 0.54, p = 0.002, Delong's test), FULL (AUC 0.62, p = 0.003), or AIC (AUC 0.53, p < 0.001). Interpretation: An ordinal score incorporating eight independent binary clinical variables predicted seizure freedom better on novel data than a model using MTS alone, a full multivariate model, or a backwards selected model. The ordinal score model represents a simple clinical heuristic to identify which patients should be offered minimally invasive laser surgery. [ABSTRACT FROM AUTHOR]