Which is more deleterious to cognitive performance? Interictal epileptiform discharges vs anti-seizure medication.

Children with epilepsy commonly have comorbid neurocognitive impairments that severely affect their psychosocial well-being, education, and future career prospects. Although the provenance of these deficits is multifactorial, the effects of interictal epileptiform discharges (IEDs) and anti-seizure medications (ASMs) are thought to be particularly severe. Although certain ASMs can be leveraged to inhibit IED occurrence, it remains unclear whether epileptiform discharges or the medications themselves are most deleterious to cognition. To examine this question, 25 children undergoing invasive monitoring for refractory focal epilepsy performed one or more sessions of a cognitive flexibility task. Electrophysiological data were recorded to detect IEDs. Between repeated sessions, prescribed ASMs were either continued or titrated to <50% of the baseline dose. Hierarchical mixed-effects modeling assessed the relationship between task reaction time (RT), IED occurrence, ASM type, and dose while controlling for seizure frequency. Both presence (ß ± SE = 49.91 ± 16.55 ms, p = .003) and number of IEDs (ß ± SE = 49.84 ± 12.51 ms, p < .001) were associated with slowed task RT. Higher dose oxcarbazepine significantly reduced IED frequency (p = .009) and improved task performance (ß ± SE = -107.43 ± 39.54 ms, p = .007). These results emphasize the neurocognitive consequences of IEDs independent of seizure effects. Furthermore, we demonstrate that inhibition of IEDs following treatment with select ASMs is associated with improved neurocognitive function.

Epilepsy disrupts hippocampal phase precision and impairs working memory.

OBJECTIVE: Working memory deficits are prevalent in childhood epilepsy. Working memory processing is thought to be supported by the phase of hippocampal neural oscillations. Disruptions in working memory have previously been linked to the occurrence of transient epileptic activity. This study aimed to resolve the associations between oscillatory neural activity, transient epileptiform events, and working memory in children with epilepsy. METHODS: Intracranial recordings were acquired from stereotactically implanted electrodes in the hippocampi, epileptogenic zones, and working memory-related networks of children with drug-resistant epilepsy during a 1-back working memory task. Interictal epileptic activity was captured using automated detectors. Hippocampal phase and interregional connectivity within working memory networks were indexed by Rayleigh Z and the phase difference derivative, respectively. Trials with and without transient epileptiform events were compared. RESULTS: Twelve children (mean age = 14.3 ± 2.8 years) with drug-resistant epilepsy were included in the study. In the absence of transient epileptic activity, significant delta and theta hippocampal phase resetting occurred in response to working memory stimulus presentation (Rayleigh z-score = 9, Rayleigh z-score = 8). Retrieval trials that were in phase with the preferred phase angle were associated with faster reaction times (p = .01, p = .03). Concurrently, delta and theta coordinated interactions between the hippocampi and working memory-related networks were enhanced (phase difference derivative [PDD] z-scores = 6-11). During retrieval trials with pre-encoding or pre-retrieval transient epileptic activity, phase resetting was attenuated (Rayleigh z-score = 5, Rayleigh z-score = 1), interregional connectivity was altered (PDD z-scores = 1-3), and reaction times were prolonged (p = .01, p = .03). SIGNIFICANCE: This work highlights the role of hippocampal phase in working memory. We observe poststimulus hippocampal phase resetting coincident with enhanced interregional connectivity. The precision of hippocampal phase predicts optimal working memory processing, and transient epileptic activity prolongs working memory processing. These findings can help guide future treatments aimed at restoring memory function in this patient population.

Interictal discharges delay target-directed eye movements and impair attentional set-shifting in children with epilepsy.

OBJECTIVE: The theory of transient cognitive impairment in epilepsy posits that lapses in attention result from ephemeral disruption of attentional circuitry by interictal events. Eye movements are intimately associated with human attention and can be monitored in real time using eye-tracking technologies. Here, we sought to characterize the associations between interictal epileptiform discharges (IEDs), gaze, and attentional behavior in children with epilepsy. METHODS: Eleven consecutive children undergoing invasive monitoring with stereotactic electrodes for localization-related epilepsy performed an attentional set-shifting task while tandem intracranial electroencephalographic signals and eye-tracking data were recorded. Using an established algorithm, IEDs were detected across all intracranial electrodes on a trial-by-trial basis. Hierarchical mixed-effects modeling was performed to delineate associations between trial reaction time (RT), eye movements, and IEDs. RESULTS: Hierarchical mixed-effects modeling revealed that both the presence of an IED (ß ± SE = 72.74 ± 24.21 ms, p = .003) and the frequency of epileptiform events (ß ± SE = 67.54 ± 17.30 ms, p < .001) were associated with prolonged RT on the attentional set-shifting task. IED occurrence at the time of stimulus presentation was associated with delays in gaze initiation toward the visual targets (p = .017). SIGNIFICANCE: The occurrence of epileptiform activity in close temporal association with stimulus presentation is associated with delays in target-directed gaze and prolonged response time, hallmarks of momentary lapses in attention. These findings provide novel insights into the mechanisms of transient impairments in children and support the use of visual tracking as a correlate of higher order attentional behavior.

Phase Resetting in the Anterior Cingulate Cortex Subserves Childhood Attention and Is Impaired by Epilepsy.

The neural mechanisms that underlie selective attention in children are poorly understood. By administering a set-shifting task to children with intracranial electrodes stereotactically implanted within anterior cingulate cortex (ACC) for epilepsy monitoring, we demonstrate that selective attention in a set-shifting task is dependent upon theta-band phase resetting immediately following stimulus onset and that the preferred theta phase angle is predictive of reaction time during attentional shift. We also observe selective enhancement of oscillatory coupling between the ACC and the dorsal attention network and decoupling with the default mode network during task performance. When transient focal epileptic activity occurs around the time of stimulus onset, phase resetting is impaired, connectivity changes with attentional and default mode networks are abolished, and reaction times are prolonged. The results of the present work highlight the fundamental mechanistic role of oscillatory phase in ACC in supporting attentional circuitry and present novel opportunities to remediate attention deficits in children with epilepsy.

Spectral changes following resective epilepsy surgery and neurocognitive function in children with epilepsy.

Decelerated resting cortical oscillations, high-frequency activity, and enhanced cross-frequency interactions are features of focal epilepsy. The association between electrophysiological signal properties and neurocognitive function, particularly following resective surgery, is, however, unclear. In the current report, we studied intraoperative recordings from intracranial electrodes implanted in seven children with focal epilepsy and analyzed the spectral dynamics both before and after surgical resection of the hypothesized seizure focus. The associations between electrophysiological spectral signatures and each child's neurocognitive profiles were characterized using a partial least squares analysis. We find that extent of spectral alteration at the periphery of surgical resection, as indexed by slowed resting frequency and its acceleration following surgery, is associated with baseline cognitive deficits in children. The current report provides evidence supporting the relationship between altered spectral properties in focal epilepsy and neuropsychological deficits in children. In particular, these findings suggest a critical role of disrupted thalamocortical rhythms, which are believed to underlie the spectral alterations we describe, in both epileptogenicity and neurocognitive function.NEW & NOTEWORTHY Spectral alterations marked by decelerated resting oscillations and ectopic high-frequency activity have been noted in focal epilepsy. We leveraged intraoperative recordings from chronically implanted electrodes pre- and postresection to understand the association between these electrophysiological phenomena and neuropsychological function. We find that the extent of spectral alteration, indexed by slowed resting frequency and its acceleration following resection, is associated with baseline cognitive deficits. These findings provide novel insights into neurocognitive impairments in focal epilepsy.

Biomarkers of seizure response to vagus nerve stimulation: A scoping review.

Although vagus nerve stimulation (VNS) is a common procedure, seizure outcomes are heterogeneous, with few available means to preoperatively identify the ideal surgical candidate. Here, we perform a scoping review of the literature to identify biomarkers of VNS response in patients with drug-resistant epilepsy. Several databases (Ovid MEDLINE, Ovid Embase, BIOSIS Previews, and Web of Science) were searched for all relevant articles that reported at least one biomarker of VNS response following implantation for intractable epilepsy. Patient demographics, seizure data, and details related to biomarkers were abstracted from all studies. From the 288 records screened, 28 articles reporting on 16 putative biomarkers were identified. These were grouped into four categories: network/connectomic-based biomarkers, electrophysiological signatures, structural findings on neuroimaging, and systemic assays. Differences in brain network organization, connectivity, and electrophysiological synchronicity demonstrated the most robust ability to identify VNS responders. Structural findings on neuroimaging yielded inconsistent associations with VNS responsiveness. With regard to systemic biomarkers, heart rate variability was shown to be an independent marker of VNS response, whereas inflammatory markers were not useful. There is an unmet need to preoperatively identify candidates who are likely to benefit from VNS. Several biomarkers demonstrate promise in predicting seizure responsiveness to VNS, particularly measures of brain network connectivity. Further efforts are required to validate existing biomarkers to inform clinical decision-making.

An automated algorithm for stereoelectroencephalography electrode localization and labelling.

PURPOSE: Stereoelectroencephalography (sEEG) is increasingly utilized for localization of seizure foci, functional mapping, and neurocognitive research due to its ability to target deep and difficult to reach anatomical locations and to study in vivo brain function with a high signal-to-noise ratio. The research potential of sEEG is constrained by the need for accurate localization of the implanted electrodes in a common template space for group analyses. METHODS: We present an algorithm to automate the grouping of sEEG electrodes by trajectories, labelled by target and insertion point. This algorithm forms the core of a pipeline that fully automates the entire process of electrode localization in standard space, using raw CT and MRI images to produce atlas labelled MNI coordinates. RESULTS: Across 196 trajectories from 20 patients, the pipeline successfully processed 190 trajectories with localizations within 0.25±0.55 mm of the manual annotation by two reviewers. Six electrode trajectories were not directly identified due to metal artifacts and locations were interpolated based on the first and last contact location and the number of contacts in that electrode as listed in the surgical record. CONCLUSION: We introduce our algorithm and pipeline for automatically localizing, grouping, and classifying sEEG electrodes from raw CT and MRI. Our algorithm adds to existing pipelines and toolboxes for electrode localization by automating the manual step of marking and grouping electrodes, thereby expedites the analyses of sEEG data, particularly in large datasets.

Dissociable default-mode subnetworks subserve childhood attention and cognitive flexibility: Evidence from deep learning and stereotactic electroencephalography.

Cognitive flexibility encompasses the ability to efficiently shift focus and forms a critical component of goal-directed attention. The neural substrates of this process are incompletely understood in part due to difficulties in sampling the involved circuitry. We leverage stereotactic intracranial recordings to directly resolve local-field potentials from otherwise inaccessible structures to study moment-to-moment attentional activity in children with epilepsy performing a flexible attentional task. On an individual subject level, we employed deep learning to decode neural features predictive of task performance indexed by single-trial reaction time. These models were subsequently aggregated across participants to identify predictive brain regions based on AAL atlas and FIND functional network parcellations. Through this approach, we show that fluctuations in beta (12-30 Hz) and gamma (30-80 Hz) power reflective of increased top-down attentional control and local neuronal processing within relevant large-scale networks can accurately predict single-trial task performance. We next performed connectomic profiling of these highly predictive nodes to examine task-related engagement of distributed functional networks, revealing exclusive recruitment of the dorsal default mode network during shifts in attention. The identification of distinct substreams within the default mode system supports a key role for this network in cognitive flexibility and attention in children. Furthermore, convergence of our results onto consistent functional networks despite significant inter-subject variability in electrode implantations supports a broader role for deep learning applied to intracranial electrodes in the study of human attention.

The anterior and centromedian thalamus: Anatomy, function, and dysfunction in epilepsy.

The thalamus is a densely connected collection of nuclei that play a critical role in gating information flow across the neocortex. Through diffuse reciprocal cortico-thalamo-cortical connectivity, the anterior and centromedian nuclei exert remarkable control over cortically expressed activity. Consequently, mounting evidence implicates these thalamic centres in both the genesis and propagation of aberrant epileptiform activity across the brain. The present work reviews existing literature with regards to the anatomy, function, and dysfunction of the anterior and centromedian thalamic nuclei as they relate to epileptogenesis and ictal dynamics in humans. A confluence of electrophysiological, anatomical, and neuromodulatory evidence links these thalamic hubs to a variety of epilepsy syndromes. These data are discussed as they relate to targeted thalamic neuromodulation.

Connectomic Profiles and Cognitive Trajectories After Epilepsy Surgery in Children.

BACKGROUND AND OBJECTIVES: Neurocognitive outcomes after surgery for temporal lobe epilepsy in childhood are variable. Postoperative changes are not directly predicted by seizure freedom, and associations between epilepsy, neuropsychological function, and developing neural networks are poorly understood. Here, we leveraged whole-brain connectomic profiling in magnetoencephalography (MEG) to retrospectively study associations between brain connectivity and neuropsychological function in children with temporal lobe epilepsy undergoing resective surgery. METHODS: Clinical and MEG data were retrospectively analyzed for children who underwent temporal lobe epilepsy surgery at the Hospital for Sick Children from 2000 to 2021. Resting-state connectomes were constructed from neuromagnetic oscillations via the weighted-phase lag index. Using a partial least-squares (PLS) approach, we assessed multidimensional associations between patient connectomes, neuropsychological scores, and clinical covariates. Bootstrap resampling statistics were performed to assess statistical significance. RESULTS: A total of 133 medical records were reviewed, and 5 PLS analyses were performed. Each PLS analysis probed a particular neuropsychological domain and the associations between its baseline and postoperative scores and the connectomic data. In each PLS analysis, a significant latent variable was identified, representing a specific percentage of the variance in the data and relating neural networks to clinical covariates, which included changes in rote verbal memory (n = 41, p = 0.01, σ2 = 0.38), narrative/verbal memory (n = 57, p = 0.00, σ2 = 0.52), visual memory (n = 51, p = 0.00, σ2 = 0.43), working memory (n = 44, p = 0.00, σ2 = 0.52), and overall intellectual function (n = 59, p = 0.00, σ2 = 0.55). Children with more diffuse, bilateral intrinsic connectivity across several frequency bands showed lower scores on all neuropsychological assessments but demonstrated a greater propensity for gains after resective surgery. DISCUSSION: Here, we report that connectomes characterized by diffuse connectivity, reminiscent of developmentally immature networks, are associated with lower preoperative cognition and postoperative cognitive improvement. These findings provide a potential means to understand neurocognitive function in children with temporal lobe epilepsy and expected changes postoperatively.

Detection of high-frequency oscillations in electroencephalography: A scoping review and an adaptable open-source framework.

PURPOSE: High frequency oscillations (HFOs) are putative biomarkers of epileptogenicity. These electrophysiological phenomena can be effectively detected in electroencephalography using automated methods. Nonetheless, the implementation of these methods into clinical practice remains challenging as significant variability exists between algorithms and their characterizations of HFOs. Here, we perform a scoping review of the literature pertaining to automated HFO detection methods. In addition, we propose a framework for defining and detecting HFOs based on a simplified single-stage time-frequency based detection algorithm with clinically-familiar parameters. METHODS: Several databases (OVID Medline, Web of Science, PubMed) were searched for articles presenting novel, automated HFO detection methods. Details related to the algorithm and various stages of data acquisition, pre-processing, and analysis were abstracted from included studies. RESULTS: From the 261 records screened, 57 articles presented novel, automated HFO detection methods and were included in the scoping review. These algorithms were categorized into 3 groups based on their most salient features: energy thresholding, time-frequency analysis, and data mining/machine learning. Algorithms were optimized for specific datasets and suffered from low specificity. A framework for user-constrained inputs is proposed to circumvent some of the weaknesses of highly performant detectors. CONCLUSIONS: Further efforts are required to optimize and validate existing automated HFO detection methods for clinical utility. The proposed framework may be applied to understand and standardize the variations in HFO definitions across institutions.

The Oscillatory Basis of Working Memory Function and Dysfunction in Epilepsy.

Working memory (WM) deficits are pervasive co-morbidities of epilepsy. Although the pathophysiological mechanisms underpinning these impairments remain elusive, it is thought that WM depends on oscillatory interactions within and between nodes of large-scale functional networks. These include the hippocampus and default mode network as well as the prefrontal cortex and frontoparietal central executive network. Here, we review the functional roles of neural oscillations in subserving WM and the putative mechanisms by which epilepsy disrupts normative activity, leading to aberrant oscillatory signatures. We highlight the particular role of interictal epileptic activity, including interictal epileptiform discharges and high frequency oscillations (HFOs) in WM deficits. We also discuss the translational opportunities presented by greater understanding of the oscillatory basis of WM function and dysfunction in epilepsy, including potential targets for neuromodulation.