Search

Background: Despite its potential to revolutionize the treatment of memory dysfunction, the efficacy of direct electrical hippocampal stimulation for memory performance has not yet been well characterized. One of the main challenges to cross-study comparison in this area of research is the diversity of the cognitive tasks used to measure memory performance. Objective: We hypothesized that the tasks that differentially engage the hippocampus may be differentially influenced by hippocampal stimulation and the behavioral effects would be related to the underlying hippocampal activity. Methods: To investigate this issue, we recorded intracranial EEG from and directly applied stimulation to the hippocampus of 10 epilepsy patients while they performed two different verbal memory tasks – a word pair associative memory task and a single item memory task. Results: Hippocampal stimulation modulated memory performance in a task-dependent manner, improving associative memory performance, while impairing item memory performance. In addition, subjects with poorer baseline cognitive function improved much more with stimulation. iEEG recordings from the hippocampus during non-stimulation encoding blocks revealed that the associative memory task elicited stronger theta oscillations than did item memory and that stronger theta power was related to memory performance. Conclusions: We show here for the first time that stimulation-induced associative memory enhancement was linked to increased theta power during retrieval. These results suggest that hippocampal stimulation enhances associative memory but not item memory because it engages more hippocampal theta activity and that, in general, increasing hippocampal theta may provide a neural mechanism for successful memory enhancement.

Epilepsy is a very common neurological disease that has affected more than 65 million people worldwide. In more than 30 % of the cases, people affected by this disease cannot be cured with medicines or surgery. However, predicting a seizure before it actually occurs can help in its prevention; through therapeutic intervention. Studies have observed that abnormal activity inside the brain begins a few minutes before the start of a seizure, which is known as preictal state. Many researchers have tried to find a way for predicting this preictal state of a seizure but an effective prediction in terms of high sensitivity and specificity still remains a challenge. The current study, proposes a seizure prediction system that employs deep learning methods. This method includes preprocessing of scalp EEG signals, automated features extraction; using convolution neural network and classification with the support of vector machines. The proposed method has been applied on 24 subjects of scalp EEG dataset of CHBMIT resulting in successfully achieving an average sensitivity and specificity of 92.7% and 90.8% respectively.

During visual conscious perception, the earliest responses linked to signal detection are little known. The current study aims to reveal the cortical neural activity changes in the earliest stages of conscious perception using recordings from intracranial electrodes. Epilepsy patients (N=158) were recruited from a multi-center collaboration and completed a visual word recall task. Broadband gamma activity (40–115Hz) was extracted with a band-pass filter and gamma power was calculated across subjects on a common brain surface. Our results show early gamma power increases within 0-50ms after stimulus onset in bilateral visual processing cortex, right frontal cortex (frontal eye fields, ventral medial/frontopolar, orbital frontal) and bilateral medial temporal cortex regardless of whether the word was later recalled. At the same early times, decreases were seen in the left rostral middle frontal gyrus. At later times after stimulus onset, gamma power changes developed in multiple cortical regions. These included sustained changes in visual and other association cortical networks, and transient decreases in the default mode network most prominently at 300–650ms. In agreement with prior work in this verbal memory task, we also saw greater increases in visual and medial temporal regions as well as prominent later (> 300ms) increases in left hemisphere language areas for recalled versus not recalled stimuli. These results suggest an early signal detection network in the frontal, medial temporal, and visual cortex is engaged at the earliest stages of conscious visual perception.

A wide spectrum of brain rhythms are engaged throughout the human cortex in cognitive functions. How the rhythms of various frequency ranges are coordinated across the space of the human cortex and time of memory processing is inconclusive. They can either be coordinated together across the frequency spectrum at the same cortical site and time or induced independently in particular bands. We used a large dataset of human intracranial electroencephalography (iEEG) to parse the spatiotemporal dynamics of spectral activities induced during formation of verbal memories. Encoding of words for subsequent free recall activated low frequency theta, intermediate frequency alpha and beta, and high frequency gamma power in a mosaic pattern of discrete cortical sites. A majority of the cortical sites recorded activity in only one of these frequencies, except for the visual cortex where spectral power was induced across multiple bands. Each frequency band showed characteristic dynamics of the induced power specific to cortical area and hemisphere. The power of the low, intermediate, and high frequency activities propagated in independent sequences across the visual, temporal and prefrontal cortical areas throughout subsequent phases of memory encoding. Our results provide a holistic, simplified model of the spectral activities engaged in the formation of human memory, suggesting an anatomically and temporally distributed mosaic of coordinated brain rhythms.

Anticipating social and non-social incentives recruits shared brain structures and promotes behavior. However, little is known about possible age-related behavioral changes, and how the human substantia nigra (SN) signals positive and negative social information. Therefore, we recorded intracranial electroencephalography (iEEG) from the SN of Parkinson's Disease (PD) patients (n = 12, intraoperative, OFF medication) in combination with a social incentive delay task including photos of neutral, positive or negative human gestures and mimics as feedback. We also tested a group of non-operated PD patients (n = 24, ON and OFF medication), and a sample of healthy young (n = 51) and older (n = 52) adults with behavioral readouts only. Behaviorally, the anticipation of both positive and negative social feedback equally accelerated response times in contrast to neutral social feedback in healthy young and older adults. Although this effect was not significant in the group of operated PD patients – most likely due to the small sample size – iEEG recordings in their SN showed a significant increase in alpha-beta power (9–20 Hz) from 300 to 600 ms after cue onset again for both positive and negative cues. Finally, in non-operated PD patients, the behavioral effect was not modulated by medication status (ON vs OFF medication) suggesting that other processes than dopaminergic neuromodulation play a role in driving invigoration by social incentives. Together, our findings provide novel and direct evidence for a role of the SN in processing positive and negative social information via specific oscillatory mechanisms in the alpha-beta range, and they suggest that anticipating social value in simple cue-outcome associations is intact in healthy aging and PD.

Objective: Clinical visual intraoperative electrocorticography (ioECoG) reading intends to localize epileptic tissue and improve epilepsy surgery outcome. We aimed to understand whether machine learning (ML) could complement ioECoG reading, how subgroups affected performance, and which ioECoG features were most important., Methods: We included 91 ioECoG-guided epilepsy surgery patients with Engel 1A outcome. We allocated 71 training and 20 test set patients. We trained an extra trees classifier (ETC) with 14 spectral features to classify ioECoG channels as covering resected or non-resected tissue. We compared the ETC's performance with clinical ioECoG reading and assessed whether patient subgroups affected performance. Explainable artificial intelligence (xAI) unveiled the most important ioECoG features learnt by the ETC., Results: The ETC outperformed clinical reading in five test set patients, was inferior in six, and both were inconclusive in nine. The ETC performed best in the tumor subgroup (area under ROC curve: 0.84 [95%CI 0.79-0.89]). xAI revealed predictors of resected (relative theta, alpha, and fast ripple power) and non-resected tissue (relative beta and gamma power)., Conclusions: Combinations of subtle spectral ioECoG changes, imperceptible by the human eye, can aid healthy and pathological tissue discrimination., Significance: ML with spectral ioECoG features can support, rather than replace, clinical ioECoG reading, particularly in tumors., Competing Interests: Conflicts of interest All authors have no disclosers., (Copyright © 2024. Published by Elsevier B.V.)

Patients with drug-resistant temporal lobe epilepsy often undergo intracranial EEG recording to capture multiple seizures in order to lateralize the seizure onset zone. This process is associated with morbidity and often ends in postoperative seizure recurrence. Abundant interictal (between-seizure) data are captured during this process, but these data currently play a small role in surgical planning. Our objective was to predict the laterality of the seizure onset zone using interictal intracranial EEG data in patients with temporal lobe epilepsy. We performed a retrospective cohort study (single-centre study for model development; two-centre study for model validation). We studied patients with temporal lobe epilepsy undergoing intracranial EEG at the University of Pennsylvania (internal cohort) and the Medical University of South Carolina (external cohort) between 2015 and 2022. We developed a logistic regression model to predict seizure onset zone laterality using several interictal EEG features derived from recent publications. We compared the concordance between the model-predicted seizure onset zone laterality and the side of surgery between patients with good and poor surgical outcomes. Forty-seven patients (30 female; ages 20-69; 20 left-sided, 10 right-sided and 17 bilateral seizure onsets) were analysed for model development and internal validation. Nineteen patients (10 female; ages 23-73; 5 left-sided, 10 right-sided, 4 bilateral) were analysed for external validation. The internal cohort cross-validated area under the curve for a model trained using spike rates was 0.83 for a model predicting left-sided seizure onset and 0.68 for a model predicting right-sided seizure onset. Balanced accuracies in the external cohort were 79.3% and 78.9% for the left- and right-sided predictions, respectively. The predicted concordance between the laterality of the seizure onset zone and the side of surgery was higher in patients with good surgical outcome. We replicated the finding that right temporal lobe epilepsy was harder to distinguish in a separate modality of resting-state functional MRI. In conclusion, interictal EEG signatures are distinct across seizure onset zone lateralities. Left-sided seizure onsets are easier to distinguish than right-sided onsets. A model trained on spike rates accurately identifies patients with left-sided seizure onset zones and predicts surgical outcome. A potential clinical application of these findings could be to either support or oppose a hypothesis of unilateral temporal lobe epilepsy when deciding to pursue surgical resection or ablation as opposed to device implantation., Competing Interests: The authors report no competing interests., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

The reward positivity (RewP) is an event-related brain potential (ERP) component that emerges approximately 250 to 350 milliseconds (ms) after receiving reward-related feedback stimuli and is believed to be important for reinforcement learning and reward processing. Although numerous localization studies have indicated that the anterior cingulate cortex (ACC) is the neural generator of this component, other studies have identified sources outside of the ACC, fuelling a debate about its origin. Because the results of EEG and MEG source localization studies are severely limited by the inverse problem, we addressed this question by leveraging the high spatial and temporal resolution of intracranial EEG. We predicted that we would identify a neural generator of the RewP in the caudal ACC. We recorded intracranial EEG in 19 refractory epilepsy patients who underwent invasive video-EEG monitoring at Ghent University Hospital, Belgium. Participants engaged in the virtual T-maze task (vTMT), a trial-and-error task known to elicit a canonical RewP, while scalp and intracranial EEG were simultaneously recorded. The RewP was identified using a difference wave approach for both scalp and intracranial EEG. The data were aggregated across participants to create a virtual "meta-participant" that contained all the recorded intracranial ERPs (iERPs) with respect to their intracranial contact locations. We used both a hypothesis-driven (focused on ACC) and exploratory (whole-brain analysis) approach to segment the brain into regions of interest (ROI). For each ROI, we evaluated the degree to which the time course of the absolute current density (ACD) activity mirrored the time course of the RewP, and confirmed the statistical significance of the results using permutation analysis. The grand average waveform of the scalp data revealed a RewP at 309 ms after reward feedback with a frontocentral scalp distribution, consistent with the identification of this component as the RewP. The meta-participant contained iERPs recorded from 582 intracranial contacts in total. The ACD activity of the aggregated iERPs were most similar to the RewP in left caudal ACC, left dorsolateral prefrontal cortex, left frontomedial cortex, and left white matter, with the highest score attributed to caudal ACC, as predicted. To our knowledge, this is the first study that uses intracranial EEG aggregated across multiple human epilepsy patients and current source density analysis to identify the neural generator(s) of the RewP. These results provide direct evidence that the ACC is a neural generator of the RewP., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Objective. To evaluate the inter- and intra-rater reliability for the identification of bad channels among neurologists, EEG Technologists, and naïve research personnel, and to compare their performance with the automated bad channel detection (ABCD) algorithm for detecting bad channels. Approach. Six Neurologists, ten EEG Technologists, and six naïve research personnel (22 raters in total) were asked to rate 1440 real intracranial EEG channels as good or bad. Intra- and interrater kappa statistics were calculated for each group. We then compared each group to the ABCD algorithm which uses spectral and temporal domain features to classify channels as good or bad. Main results. Analysis of channel ratings from our participants revealed variable intra-rater reliability within each group, with no significant differences across groups. Inter-rater reliability was moderate among neurologists and EEG Technologists but minimal among naïve participants. Neurologists demonstrated a slightly higher consistency in ratings than EEG Technologists. Both groups occasionally misclassified flat channels as good, and participants generally focused on low-frequency content for their assessments. The ABCD algorithm, in contrast, relied more on high-frequency content. A logistic regression model showed a linear relationship between the algorithm's ratings and user responses for predominantly good channels, but less so for channels rated as bad. Sensitivity and specificity analyses further highlighted differences in rating patterns among the groups, with neurologists showing higher sensitivity and naïve personnel higher specificity. Significance. Our study reveals the bias in human assessments of intracranial electroencephalography (iEEG) data quality and the tendency of even experienced professionals to overlook certain bad channels, highlighting the need for standardized, unbiased methods. The ABCD algorithm, outperforming human raters, suggests the potential of automated solutions for more reliable iEEG interpretation and seizure characterization, offering a reliable approach free from human biases., (Creative Commons Attribution license.)

Automatic detection of epileptic seizures is important in epilepsy control and treatment, and specific feature extraction assists in accurate detection. We developed a feature extraction method for seizure detection based on multi-site synchronous changes and an edge detection algorithm. We investigated five chronic temporal lobe epilepsy rats with 8- and 12-channel detection sites in the hippocampus and limbic system. Multi-site synchronous changes were selected as a specific feature and implemented as a seizure detection method. For preprocessing, we used magnitude-squared coherence maps and Canny edge detection algorithm to find the frequency band with the most significant change in synchronization and the important channel pairs. In detection, we used the maximal cross-correlation coefficient as an indicator of synchronization and the correlation coefficient curves’ average value and standard deviation as two detection features. The method achieved high performance, with an average 96.60% detection rate, 2.63/h false alarm rate, and 1.25 s detection delay. The experimental results show that synchronization is an appropriate feature for seizure detection. The magnitude-squared coherence map can assist in selecting a specific frequency band and channel pairs to enhance the detection result. We found that individuals have a specific frequency band that reflects the most significant synchronization changes, and our method can individually adjust parameters and has good detection performance.

Objective: Medically refractory epilepsy (MRE) often requires resection of the seizure onset zone (SOZ) for effective treatment. However, when the SOZ is in functional cortex (FC), achieving complete and safe resection becomes difficult, due to the seizure network overlap with function. The authors aimed to assess the safety and outcomes of a combined approach involving partial resection combined with focal neuromodulation for FC refractory epilepsy., Methods: The authors performed a retrospective analysis of individuals diagnosed with MRE who underwent surgical intervention from January 2015 to December 2022. Patients whose SOZ was located in FC and were treated with resection combined with simultaneous implantation of a focal neuromodulation device (responsive neurostimulation [RNS] device) with more than 12 months of follow-up data were included. All patients underwent a standard epilepsy preoperative assessment including intracranial electroencephalography and extraoperative stimulation mapping. Resections were performed under general anesthesia, followed by the concurrent implantation of an RNS device., Results: Seven patients (4 males, median age 32.3 years, all right-handed) were included. The median interval from seizure onset to surgery was 17.4 years. The epileptogenic network included sensorimotor areas (cases 2, 3, and 6), visual cortex (case 1), language areas (cases 4 and 7), and the insula (case 5). The median follow-up was 3 years (range 1-5.8 years). No significant changes in neuropsychological tests were reported. One permanent nondisabling planned neurological deficit (left inferior quadrantanopia) was observed. Six patients had stimulation activated at a median of 4.7 months after resection. All patients achieved good seizure outcomes (5 with Engel class I and 2 with Engel class II outcomes)., Conclusions: Maximal safe resection combined with focal neuromodulation presents a promising alternative to stand-alone resections for MRE epileptogenic zones overlapping with functional brain. This combined approach prioritizes the preservation of function while improving seizure outcomes.

We studied the temporal dynamics of activity within and across functional MRI (fMRI)–derived nodes of intrinsic resting-state networks of the human brain using intracranial electroencephalography (iEEG) and repeated single-pulse electrical stimulation (SPES) in neurosurgical subjects implanted with intracranial electrodes. We stimulated and recorded from 2,133 and 2,372 sites, respectively, in 29 subjects. We found that N1 and N2 segments of the evoked responses are associated with intra- and internetwork communications, respectively. In a separate cognitive experiment, evoked electrophysiological responses to visual target stimuli occurred with less temporal separation across pairs of electrodes that were located within the same fMRI-defined resting-state networks compared with those located across different resting-state networks. Our results suggest intranetwork prior to internetwork information processing at the subsecond timescale. [ABSTRACT FROM AUTHOR]

• A minimum stimulation current of 2–4 mA is needed to elicit cortico-cortical evoked potentials (CCEPs) in responsive sites. • Several metrics quantifying CCEP amplitude, distribution, and morphology all show stimulation current-dependent relationships. • 6–7 mA is an asymptotic threshold for maximizing CCEP amplitude and spatial distribution and stabilizing waveform morphology. The aim of the present study was to investigate the optimal stimulation parameters for eliciting cortico-cortical evoked potentials (CCEPs) for mapping functional and epileptogenic networks. We studied 13 patients with refractory epilepsy undergoing intracranial EEG monitoring. We systematically titrated the intensity of single-pulse electrical stimulation at multiple sites to assess the effect of increasing current on salient features of CCEPs such as N1 potential magnitude, signal to noise ratio, waveform similarity, and spatial distribution of responses. Responses at each incremental stimulation setting were compared to each other and to a final set of responses at the maximum intensity used in each patient (3.5–10 mA, median 6 mA). We found that with a biphasic 0.15 ms/phase pulse at least 2–4 mA is needed to differentiate between non-responsive and responsive sites, and that stimulation currents of 6–7 mA are needed to maximize amplitude and spatial distribution of N1 responses and stabilize waveform morphology. We determined a minimum stimulation threshold necessary for eliciting CCEPs, as well as a point at which the current-dependent relationship of several response metrics all saturate. This titration study provides practical, immediate guidance on optimal stimulation parameters to study specific features of CCEPs, which have been increasingly used to map both functional and epileptic brain networks in humans. [ABSTRACT FROM AUTHOR]

Objective: In epilepsy surgery, which aims to treat seizures and thereby to improve the lives of persons with drug‐resistant epilepsy, the chances of attaining seizure relief must be carefully weighed against the risks of complications and expected adverse events. The interpretation of data regarding complications of epilepsy surgery and invasive diagnostic procedures is hampered by a lack of uniform definitions and method of data collection. Methods: Based on a review of previous definitions and classifications of complications, we developed a proposal for a new classification. This proposal was then subject to revisions after expert opinion within E‐pilepsy, an EU‐funded European pilot network of reference centers in refractory epilepsy and epilepsy surgery, later incorporated into the ERN (European Reference Network) EpiCARE. This version was discussed with recognized experts, and a final protocol was agreed to after further revision. The final protocol was evaluated in practical use over 1 year in three of the participating centers. One hundred seventy‐four consecutive procedures were included with 35 reported complications. Results: This report presents a multidimensional classification of complications in epilepsy surgery and invasive diagnostic procedures, where complications are characterized in terms of their immediate effects, resulting permanent symptoms, and consequences on activities of daily living. Significance: We propose that the protocol will be helpful in the work to promote safety in epilepsy surgery and for future studies designed to identify risk factors for complications. Further work is needed to address the reporting of outcomes as regards neuropsychological function, activities of daily living, and quality of life. [ABSTRACT FROM AUTHOR]

Although gelastic seizures (GSs) with extrahypothalamic epileptogenic zones such as the frontal, temporal, or parietal lobes have been previously reported, reports of GSs arising from the occipital region are rare. Herein, we describe the seizure propagation pattern of mirthless GSs confirmed by intracranial EEG in a case of MRI-negative occipital lobe epilepsy. In this patient, EEG onset was localized to the right occipital lobe while the onset of laughter coincided with seizure propagation to the right basal temporal region. This finding suggested that the symptomatogenic area for GSs in the occipital lobe may reside in the basal temporal region, and the basal temporal region may play a role in laughing behaviors. This case demonstrated that an elaborate analysis of electroclinical features combined with imaging findings may lead to successful seizure localization. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The progress of therapeutic neuromodulation greatly depends on improving stimulation parameters to most efficiently induce neuroplasticity effects. Intermittent θ-burst stimulation (iTBS), a form of electrical stimulation that mimics natural brain activity patterns, has proved to efficiently induce such effects in animal studies and rhythmic transcranial magnetic stimulation studies in humans. However, little is known about the potential neuroplasticity effects of iTBS applied through intracranial electrodes in humans. This study characterizes the physiological effects of intracranial iTBS in humans and compare them with α-frequency stimulation, another frequently used neuromodulatory pattern. We applied these two stimulation patterns to well-defined regions in the sensorimotor cortex, which elicited contralateral hand muscle contractions during clinical mapping, in patients with epilepsy implanted with intracranial electrodes. Treatment effects were evaluated using oscillatory coherence across areas connected to the treatment site, as defined with corticocortical-evoked potentials. Our results show that iTBS increases coherence in the β-frequency band within the sensorimotor network indicating a potential neuroplasticity effect. The effect is specific to the sensorimotor system, the β band, and the stimulation pattern and outlasted the stimulation period by ~3 min. The effect occurred in four out of seven subjects depending on the buildup of the effect during iTBS treatment and other patterns of oscillatory activity related to ceiling effects within the β band and to preexistent coherence within the α band. By characterizing the neurophysiological effects of iTBS within well-defined cortical networks, we hope to provide an electrophysiological framework that allows clinicians/researchers to optimize brain stimulation protocols which may have translational value. [ABSTRACT FROM AUTHOR]

Interictal epileptiform discharges (IEDs) are a widely used biomarker in patients with epilepsy but lack specificity. It has been proposed that there are truly epileptogenic and less pathological or even protective IEDs. Recent studies suggest that highly pathological IEDs are characterized by high-frequency oscillations (HFOs). Here, we aimed to dissect these 'HFO-IEDs' at the single-neuron level, hypothesizing that the underlying mechanisms are distinct from 'non-HFO-IEDs'. Analysing hybrid depth electrode recordings from patients with temporal lobe epilepsy, we found that single-unit firing rates were higher in HFO- than in non-HFO-IEDs. HFO-IEDs were characterized by a pronounced pre-peak increase in firing, which coincided with the preferential occurrence of HFOs, whereas in non-HFO-IEDs, there was only a mild pre-peak increase followed by a post-peak suppression. Comparing each unit's firing during HFO-IEDs to its baseline activity, we found many neurons with a significant increase during the HFO component or ascending part, but almost none with a decrease. No such imbalance was observed during non-HFO-IEDs. Finally, comparing each unit's firing directly between HFO- and non-HFO-IEDs, we found that most cells had higher rates during HFO-IEDs and, moreover, identified a distinct subset of neurons with a significant preference for this IED subtype. In summary, our study reveals that HFO- and non-HFO-IEDs have different single-unit correlates. In HFO-IEDs, many neurons are moderately activated, and some participate selectively, suggesting that both types of increased firing contribute to highly pathological IEDs. [ABSTRACT FROM AUTHOR]

Background: Potentially curative epilepsy surgery can be offered if a single, discrete epileptogenic zone (EZ) can be identified. For individuals in whom there is no clear concordance between clinical localization, scalp EEG, and imaging data, intracranial EEG (icEEG) may be needed to confirm a predefined hypothesis regarding irritative zone (IZ), seizure onset zone (SOZ), and EZ prior to surgery. However, icEEG has limited spatial sampling and may fail to reveal the full extent of epileptogenic network if predefined hypothesis is not correct. Simultaneous icEEG-fMRI has been safely acquired in humans and allows exploration of neuronal activity at the whole-brain level related to interictal epileptiform discharges (IED) captured intracranially. Methods: We report icEEG-fMRI in eight patients with refractory focal epilepsy who had resective surgery and good postsurgical outcome. Surgical resection volume in seizure-free patients post-surgically reflects confirmed identification of the EZ. IEDs on icEEG were classified according to their topographic distribution and localization (Focal, Regional, Widespread, and Non-contiguous). We also divided IEDs by their location within the surgical resection volume [primary IZ (IZ1) IED] or outside [secondary IZ (IZ2) IED]. The distribution of fMRI blood oxygen level-dependent (BOLD) changes associated with individual IED classes were assessed over the whole brain using a general linear model. The concordance of resulting BOLD map was evaluated by comparing localization of BOLD clusters with surgical resection volume. Additionally, we compared the concordance of BOLD maps and presence of BOLD clusters in remote brain areas: precuneus, cuneus, cingulate, medial frontal, and thalamus for different IED classes. Results: A total of 38 different topographic IED classes were identified across the 8 patients: Focal (22) and non-focal (16, Regional = 9, Widespread = 2, Non-contiguous = 5). Twenty-nine IEDs originated from IZ1 and 9 from IZ2. All IED classes were associated with BOLD changes. BOLD maps were concordant with the surgical resection volume for 27/38 (71%) IED classes, showing statistical global maximum BOLD cluster or another cluster in the surgical resection volume. The concordance of BOLD maps with surgical resection volume was greater (p < 0.05) for non-focal (87.5%, 14/16) as compared to Focal (59%, 13/22) IED classes. Additionally, BOLD clusters in remote cortical and deep brain areas were present in 84% (32/38) of BOLD maps, more commonly (15/16; 93%) for non-focal IED-related BOLD maps. Conclusions: Simultaneous icEEG-fMRI can reveal BOLD changes at the whole-brain level for a wide range of IEDs on icEEG. BOLD clusters within surgical resection volume and remote brain areas were more commonly seen for non-focal IED classes, suggesting that a wider hemodynamic network is at play. [ABSTRACT FROM AUTHOR]

It is now widely accepted that seizures arise from the coordinated activity of epileptic networks, and as a result, traditional methods of analyzing seizures have been augmented by techniques like single‐pulse electrical stimulation (SPES) that estimate effective connectivity in brain networks. We used SPES and graph analytics in 18 patients undergoing intracranial EEG monitoring to investigate effective connectivity between recording sites within and outside mesial temporal structures. We compared evoked potential amplitude, network density, and centrality measures inside and outside the mesial temporal region (MTR) across three patient groups: focal epileptogenic MTR, multifocal epileptogenic MTR, and non‐epileptogenic MTR. Effective connectivity within the MTR had significantly greater magnitude (evoked potential amplitude) and network density, regardless of epileptogenicity. However, effective connectivity between MTR and surrounding non‐epileptogenic regions was of greater magnitude and density in patients with focal epileptogenic MTR compared to patients with multifocal epileptogenic MTR and those with non‐epileptogenic MTR. Moreover, electrodes within focal epileptogenic MTR had significantly greater outward network centrality compared to electrodes outside non‐epileptogenic regions and to multifocal and non‐epileptogenic MTR. Our results indicate that the MTR is a robustly connected subnetwork that can exert an overall elevated propagative influence over other brain regions when it is epileptogenic. Understanding the underlying effective connectivity and roles of epileptogenic regions within the larger network may provide insights that eventually lead to improved surgical outcomes. [ABSTRACT FROM AUTHOR]

• In patients with epilepsy, intracranial correlates of small sharp spikes (SSS) are spike-/polyspike-bursts. • The hippocampus is the principal, yet not only generator of SSS. • SSS cerebral sources are topographically related to the seizure onset zone. To identify cortical correlates of scalp small sharp spikes (SSS) using simultaneous scalp and intracranial EEG recordings. Patients were retrospectively evaluated based on a database of intracranial long-term recordings at the Epilepsy Center Freiburg. Inclusion criteria were: simultaneous recordings with intracranial and scalp EEGs and the presence of at least five unequivocal SSS in the scalp EEG. Intracranial recordings were analyzed regarding the co-occurring intracranial potentials during scalp SSS. 33 patients, aged 9-60y, 17 females, fulfilled the above-mentioned criteria. Almost all patients had intracranial SSS correlates in the form of spike/polyspike-waves in the temporal lobe, predominantly in the hippocampus (24/28), less frequently involving the amygdala (5/29), temporal basal (3/18), lateral neocortical (4/32), entorhinal cortices (1/12), and the parietal lobe (2/13). Amplitudes of intrahippocampal spikes or polyspikes co-occurring with SSS were significantly higher than intracranial discharges without scalp correlates. In 45% of patients, intracranial spikes accompanying SSS were located within the seizure onset zone (SOZ). Our results strongly support an epileptic origin of SSS and provide evidence about their heterogenous generators. This study suggests that SSS cannot with certainty be classified as "benign" but rather considered as one of the EEG manifestations of focal epilepsy. [ABSTRACT FROM AUTHOR]

Brain stimulation has emerged as a powerful tool in human neuroscience, becoming integral to next-generation psychiatric and neurologic therapeutics. Theta-burst stimulation (TBS), in which electrical pulses are delivered in rhythmic bouts of 3–8 Hz, seeks to recapitulate neural activity seen endogenously during cognitive tasks. A growing literature suggests that TBS can be used to alter or enhance cognitive processes, but little is known about how these stimulation events influence underlying neural activity. Our study sought to investigate the effect of direct electrical TBS on mesoscale neural activity in humans by asking (1) whether TBS evokes persistent theta oscillations in cortical areas, (2) whether these oscillations occur at the stimulated frequency, and (3) whether stimulation events propagate in a manner consistent with underlying functional and structural brain architecture. We recruited 20 neurosurgical epilepsy patients with indwelling electrodes and delivered direct cortical TBS at varying locations and frequencies. Simultaneous iEEG was recorded from non-stimulated electrodes and analyzed to understand how TBS influences mesoscale neural activity. We found that TBS rapidly evoked theta rhythms in widespread brain regions, preferentially at the stimulation frequency, and that these oscillations persisted for hundreds of milliseconds post stimulation offset. Furthermore, the functional connectivity between recording and stimulation sites predicted the strength of theta response, suggesting that underlying brain architecture guides the flow of stimulation through the brain. By demonstrating that cortical TBS induces frequency-specific oscillatory responses, our results suggest this technology can be used to directly and predictably influence the activity of cognitively-relevant brain networks. • Theta-burst stimulation of human cortex induces theta oscillations elsewhere in the brain. • Induced rhythms are specific to the stimulation frequency between 3 and 8 Hz. • Functional connections predict how stimulation flows from a target site to other regions. [ABSTRACT FROM AUTHOR]

To study the neuroanatomical correlate of involuntary unilateral blinking in humans, using the example of patients with focal epilepsy. Patients with drug resistant focal epilepsy undergoing presurgical evaluation with stereotactically implanted EEG-electrodes (sEEG) were recruited from the local epilepsy monitoring unit. Only patients showing ictal unilateral blinking or unilateral blinking elicited by direct electrical stimulation were included (n = 16). MRI and CT data were used for visualization of the electrode positions. In two patients, probabilistic tractography with seeding from the respective electrodes was additionally performed. Three main findings were made: (1) involuntary unilateral blinking was associated with activation of the anterior temporal region, (2) tractography showed widespread projections to the ipsilateral frontal, pericentral, occipital, limbic and cerebellar regions and (3) blinking was observed predominantly in female patients with temporal lobe epilepsies. Unilateral blinking was found to be associated with an ipsilateral activation of the anterior temporal region. We suggest that the identified network is not part of the primary blinking control but might have modulating influence on ipsilateral blinking by integrating contextual information. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Patients with suspected mesial temporal lobe (MTL) epilepsy typically undergo inpatient video-electroencephalography (EEG) monitoring with scalp and/or intracranial electrodes for 1 to 2 weeks to localize and lateralize the seizure focus or foci. Chronic ambulatory electrocorticography (ECoG) in patients with MTL epilepsy may provide additional information about seizure lateralization. This analysis describes data obtained from chronic ambulatory ECoG in patients with suspected bilateral MTL epilepsy in order to assess the time required to determine the seizure lateralization and whether this information could influence treatment decisions. METHODS: Ambulatory ECoG was reviewed in patients with suspected bilateral MTL epilepsy who were among a larger cohort with intractable epilepsy participating in a randomized controlled trial of responsive neurostimulation. Subjects were implanted with bilateral MTL leads and a cranially implanted neurostimulator programmed to detect abnormal interictal and ictal ECoG activity. ECoG data stored by the neurostimulator were reviewed to determine the lateralization of electrographic seizures and the interval of time until independent bilateral MTL electrographic seizures were recorded. RESULTS: Eighty-two subjects were implanted with bilateral MTL leads and followed for 4.7 years on average (median 4.9 years). Independent bilateral MTL electrographic seizures were recorded in 84%. The average time to record bilateral electrographic seizures in the ambulatory setting was 41.6 days (median 13 days, range 0-376 days). Sixteen percent had only unilateral electrographic seizures after an average of 4.6 years of recording. SIGNIFICANCE: About one third of the subjects implanted with bilateral MTL electrodes required >1 month of chronic ambulatory ECoG before the first contralateral MTL electrographic seizure was recorded. Some patients with suspected bilateral MTL seizures had only unilateral electrographic seizures. Chronic ambulatory ECoG in patients with suspected bilateral MTL seizures provides data in a naturalistic setting, may complement data from inpatient video-EEG monitoring, and can contribute to treatment decisions.

Background: Potentially curative epilepsy surgery can be offered if a single, discrete epileptogenic zone (EZ) can be identified. For individuals in whom there is no clear concordance between clinical localization, scalp EEG, and imaging data, intracranial EEG (icEEG) may be needed to confirm a predefined hypothesis regarding irritative zone (IZ), seizure onset zone (SOZ), and EZ prior to surgery. However, icEEG has limited spatial sampling and may fail to reveal the full extent of epileptogenic network if predefined hypothesis is not correct. Simultaneous icEEG-fMRI has been safely acquired in humans and allows exploration of neuronal activity at the whole-brain level related to interictal epileptiform discharges (IED) captured intracranially.Methods: We report icEEG-fMRI in eight patients with refractory focal epilepsy who had resective surgery and good postsurgical outcome. Surgical resection volume in seizure-free patients post-surgically reflects confirmed identification of the EZ. IEDs on icEEG were classified according to their topographic distribution and localization (Focal, Regional, Widespread, and Non-contiguous). We also divided IEDs by their location within the surgical resection volume [primary IZ (IZ1) IED] or outside [secondary IZ (IZ2) IED]. The distribution of fMRI blood oxygen level-dependent (BOLD) changes associated with individual IED classes were assessed over the whole brain using a general linear model. The concordance of resulting BOLD map was evaluated by comparing localization of BOLD clusters with surgical resection volume. Additionally, we compared the concordance of BOLD maps and presence of BOLD clusters in remote brain areas: precuneus, cuneus, cingulate, medial frontal, and thalamus for different IED classes.Results: A total of 38 different topographic IED classes were identified across the 8 patients: Focal (22) and non-focal (16, Regional = 9, Widespread = 2, Non-contiguous = 5). Twenty-nine IEDs originated from IZ1 and 9 from IZ2. All IED classes were associated with BOLD changes. BOLD maps were concordant with the surgical resection volume for 27/38 (71%) IED classes, showing statistical global maximum BOLD cluster or another cluster in the surgical resection volume. The concordance of BOLD maps with surgical resection volume was greater (p < 0.05) for non-focal (87.5%, 14/16) as compared to Focal (59%, 13/22) IED classes. Additionally, BOLD clusters in remote cortical and deep brain areas were present in 84% (32/38) of BOLD maps, more commonly (15/16; 93%) for non-focal IED-related BOLD maps.Conclusions: Simultaneous icEEG-fMRI can reveal BOLD changes at the whole-brain level for a wide range of IEDs on icEEG. BOLD clusters within surgical resection volume and remote brain areas were more commonly seen for non-focal IED classes, suggesting that a wider hemodynamic network is at play.

Multimodal image integration (MMII) is a promising tool to help delineate the epileptogenic zone (EZ) in patients with medically intractable focal epilepsies undergoing presurgical evaluation. We report here the detailed methodology of MMII and an overview of the utility of MMII at the Cleveland Clinic Epilepsy Center from 2014 to 2018, exemplified by illustrative cases. The image integration was performed using the Curry platform (Compumedics Neuroscan™, Charlotte, NC, USA), including all available diagnostic modalities such as Magnetic resonance imaging (MRI), Positron Emission Tomography (PET), single-photon emission computed tomography (SPECT) and Magnetoencephalography (MEG), with additional capability of trajectory planning for intracranial EEG (ICEEG), particularly stereo-EEG (SEEG), as well as surgical resection planning. In the 5-year time span, 467 patients underwent MMII; of them, 98 patients (21%) had a history of prior neurosurgery and recurring seizures. Of the 467 patients, 425 patients underwent ICEEG implantation with further CT co-registration to identify the electrode locations. A total of 351 patients eventually underwent surgery after MMII, including 197 patients (56%) with non-lesional MRI and 223 patients (64%) with extra-temporal lobe epilepsy. Among 269 patients with 1-year post-operative follow up, 134 patients (50%) had remained completely seizure-free. The most common histopathological finding is focal cortical dysplasia. Our study illustrates the usefulness of MMII to enhance SEEG electrode trajectory planning, assist non-invasive/invasive data interpretation, plan resection strategy, and re-evaluate surgical failures. Information presented by MMII is essential to the understanding of the anatomo-functional-electro-clinical correlations in individual cases, which leads to the ultimate success of presurgical evaluation of patients with medically intractable focal epilepsies.

Dual-tasking is extremely prominent nowadays, despite ample evidence that it comes with a performance cost: the Dual-Task (DT) cost. Neuroimaging studies have established that tasks are more likely to interfere if they rely on common brain regions, but the precise neural origin of the DT cost has proven elusive so far, mostly because fMRI does not record neural activity directly and cannot reveal the key effect of timing, and how the spatio-temporal neural dynamics of the tasks coincide. Recently, DT electrophysiological studies in monkeys have recorded neural populations shared by the two tasks with millisecond precision to provide a much finer understanding of the origin of the DT cost. We used a similar approach in humans, with intracranial EEG, to assess the neural origin of the DT cost in a particularly challenging naturalistic paradigm which required accurate motor responses to frequent visual stimuli (task T1) and the retrieval of information from long-term memory (task T2), as when answering passengers’ questions while driving. We found that T2 elicited neuroelectric interferences in the gamma-band (>40 Hz), in key regions of the T1 network including the Multiple Demand Network. They reproduced the effect of disruptive electrocortical stimulations to create a situation of dynamical incompatibility, which might explain the DT cost. Yet, participants were able to flexibly adapt their strategy to minimize interference, and most surprisingly, reduce the reliance of T1 on key regions of the executive control network-the anterior insula and the dorsal anterior cingulate cortex-with no performance decrement.

A central challenge in today's care of epilepsy patients is that the disease dynamics are severely under-sampled in the currently typical setting with appointment-based clinical and electroencephalographic examinations. Implantable devices to monitor electrical brain signals and to detect epileptic seizures may significantly improve this situation and may inform personalized treatment on an unprecedented scale. These implantable devices should be optimized for energy efficiency and compact design. Energy efficiency will ease their maintenance by reducing the time of recharging, or by increasing the lifetime of their batteries. Biological nervous systems use an extremely small amount of energy for information processing. In recent years, a number of methods, often collectively referred to as brain-inspired computing, have also been developed to improve computation in non-biological hardware. Here, we give an overview of one of these methods, which has in particular been inspired by the very size of brains' circuits and termed hyperdimensional computing. Using a tutorial style, we set out to explain the key concepts of hyperdimensional computing including very high-dimensional binary vectors, the operations used to combine and manipulate these vectors, and the crucial characteristics of the mathematical space they inhabit. We then demonstrate step-by-step how hyperdimensional computing can be used to detect epileptic seizures from intracranial electroencephalogram (EEG) recordings with high energy efficiency, high specificity, and high sensitivity. We conclude by describing potential future clinical applications of hyperdimensional computing for the analysis of EEG and non-EEG digital biomarkers.

Dual-tasking is extremely prominent nowadays, despite ample evidence that it comes with a performance cost: the Dual-Task (DT) cost. Neuroimaging studies have established that tasks are more likely to interfere if they rely on common brain regions, but the precise neural origin of the DT cost has proven elusive so far, mostly because fMRI does not record neural activity directly and cannot reveal the key effect of timing, and how the spatio-temporal neural dynamics of the tasks coincide. Recently, DT electrophysiological studies in monkeys have recorded neural populations shared by the two tasks with millisecond precision to provide a much finer understanding of the origin of the DT cost. We used a similar approach in humans, with intracranial EEG, to assess the neural origin of the DT cost in a particularly challenging naturalistic paradigm which required accurate motor responses to frequent visual stimuli (task T1) and the retrieval of information from long-term memory (task T2), as when answering passengers' questions while driving. We found that T2 elicited neuroelectric interferences in the gamma-band (>40 Hz), in key regions of the T1 network including the Multiple Demand Network. They reproduced the effect of disruptive electrocortical stimulations to create a situation of dynamical incompatibility, which might explain the DT cost. Yet, participants were able to flexibly adapt their strategy to minimize interference, and most surprisingly, reduce the reliance of T1 on key regions of the executive control network-the anterior insula and the dorsal anterior cingulate cortex-with no performance decrement. [ABSTRACT FROM AUTHOR]

Multimodal image integration (MMII) is a promising tool to help delineate the epileptogenic zone (EZ) in patients with medically intractable focal epilepsies undergoing presurgical evaluation. We report here the detailed methodology of MMII and an overview of the utility of MMII at the Cleveland Clinic Epilepsy Center from 2014 to 2018, exemplified by illustrative cases. The image integration was performed using the Curry platform (Compumedics Neuroscan™, Charlotte, NC, USA), including all available diagnostic modalities such as Magnetic resonance imaging (MRI), Positron Emission Tomography (PET), single-photon emission computed tomography (SPECT) and Magnetoencephalography (MEG), with additional capability of trajectory planning for intracranial EEG (ICEEG), particularly stereo-EEG (SEEG), as well as surgical resection planning. In the 5-year time span, 467 patients underwent MMII; of them, 98 patients (21%) had a history of prior neurosurgery and recurring seizures. Of the 467 patients, 425 patients underwent ICEEG implantation with further CT co-registration to identify the electrode locations. A total of 351 patients eventually underwent surgery after MMII, including 197 patients (56%) with non-lesional MRI and 223 patients (64%) with extra-temporal lobe epilepsy. Among 269 patients with 1-year post-operative follow up, 134 patients (50%) had remained completely seizure-free. The most common histopathological finding is focal cortical dysplasia. Our study illustrates the usefulness of MMII to enhance SEEG electrode trajectory planning, assist non-invasive/invasive data interpretation, plan resection strategy, and re-evaluate surgical failures. Information presented by MMII is essential to the understanding of the anatomo-functional-electro-clinical correlations in individual cases, which leads to the ultimate success of presurgical evaluation of patients with medically intractable focal epilepsies. [ABSTRACT FROM AUTHOR]

• Decreased effective gamma-band connectivity represents a seizure-related reconfiguration of the epileptic network. • Ictogenic nodes discriminate areas actively generating seizure activity from areas of passive propagation. • Resection of ictogenic nodes is a key factor associated with favorable surgical outcome. Epilepsy surgery fails in > 30% of patients with focal cortical dysplasia (FCD). The seizure persistence after surgery can be attributed to the inability to precisely localize the tissue with an endogenous potential to generate seizures. In this study, we aimed to identify the critical components of the epileptic network that were actively involved in seizure genesis. The directed transfer function was applied to intracranial EEG recordings and the effective connectivity was determined with a high temporal and frequency resolution. Pre-ictal network properties were compared with ictal epochs to identify regions actively generating ictal activity and discriminate them from the areas of propagation. Analysis of 276 seizures from 30 patients revealed the existence of a seizure-related network reconfiguration in the gamma-band (25–170 Hz; p < 0.005) – ictogenic nodes. Unlike seizure onset zone, resecting the majority of ictogenic nodes correlated with favorable outcomes (p < 0.012). The prerequisite to successful epilepsy surgery is the accurate identification of brain areas from which seizures arise. We show that in FCD-related epilepsy, gamma-band network markers can reliably identify and distinguish ictogenic areas in macroelectrode recordings, improve intracranial EEG interpretation and better delineate the epileptogenic zone. Ictogenic nodes localize the critical parts of the epileptogenic tissue and increase the diagnostic yield of intracranial evaluation. [ABSTRACT FROM AUTHOR]

Objective: Stereoelectroencephalography (SEEG) is being used more frequently in the pre‐surgical evaluation of children with focal epilepsy. It has been shown to be safe in children, but there are no multicenter studies assessing the rates and factors associated with the identification of a putative seizure‐onset zone (SOZ) and subsequent seizure freedom following SEEG‐guided epilepsy surgery. Methods: Multicenter retrospective cohort study of all children undergoing SEEG at six of seven UK Children's Epilepsy Surgery Service centers from 2014 to 2019. Demographics, noninvasive evaluation, SEEG, and operative factors were analyzed to identify variables associated with the identification of a putative SOZ and subsequent seizure freedom following SEEG‐guided epilepsy surgery. Results: One hundred thirty‐five patients underwent 139 SEEG explorations using a total of 1767 electrodes. A putative SOZ was identified in 117 patients (85.7%); odds of successfully finding an SOZ were 6.4 times greater for non‐motor seizures compared to motor seizures (p = 0.02) and 3.6 times more if four or more seizures were recorded during SEEG (p = 0.03). Of 100 patients undergoing surgical treatment, 47 (47.0%) had an Engel class I outcome at a median follow‐up of 1.3 years; the only factor associated with outcome was indication for SEEG (p = 0.03); an indication of "recurrence following surgery/treatment" had a 5.9 times lower odds of achieving seizure freedom (p = 0.002) compared to the "lesion negative" cohort, whereas other indications ("lesion positive, define extent," "lesion positive, discordant noninvasive investigations" and "multiple lesions") were not statistically significantly different. Significance: This large nationally representative cohort illustrates that SEEG‐guided surgery can still achieve high rates of seizure freedom. Seizure semiology and the number of seizures recorded during SEEG are important factors in the identification of a putative SOZ, and the indication for SEEG is an important factor in postoperative outcomes. [ABSTRACT FROM AUTHOR]

A central challenge in today's care of epilepsy patients is that the disease dynamics are severely under-sampled in the currently typical setting with appointment-based clinical and electroencephalographic examinations. Implantable devices to monitor electrical brain signals and to detect epileptic seizures may significantly improve this situation and may inform personalized treatment on an unprecedented scale. These implantable devices should be optimized for energy efficiency and compact design. Energy efficiency will ease their maintenance by reducing the time of recharging, or by increasing the lifetime of their batteries. Biological nervous systems use an extremely small amount of energy for information processing. In recent years, a number of methods, often collectively referred to as brain-inspired computing, have also been developed to improve computation in non-biological hardware. Here, we give an overview of one of these methods, which has in particular been inspired by the very size of brains' circuits and termed hyperdimensional computing. Using a tutorial style, we set out to explain the key concepts of hyperdimensional computing including very high-dimensional binary vectors, the operations used to combine and manipulate these vectors, and the crucial characteristics of the mathematical space they inhabit. We then demonstrate step-by-step how hyperdimensional computing can be used to detect epileptic seizures from intracranial electroencephalogram (EEG) recordings with high energy efficiency, high specificity, and high sensitivity. We conclude by describing potential future clinical applications of hyperdimensional computing for the analysis of EEG and non-EEG digital biomarkers. [ABSTRACT FROM AUTHOR]

• We present a spectrum-based model of the intracranial electroencephalogram applicable to all sleep-wake stages, based on an open-access database. • Color-coding key model parameters on a cortical surface yields a 'neurophysiological brain map' of human sleep-wake transitions. • The results suggest a certain uniformity to the process of brain rhythm generation across cortical areas in all states of arousal. We recently proposed a spectrum-based model of the awake intracranial electroencephalogram (iEEG) (Kalamangalam et al., 2020), based on a publicly-available normative database (Frauscher et al., 2018). The latter has been expanded to include data from non-rapid eye movement (NREM) and rapid eye movement (REM) sleep (von Ellenrieder et al., 2020), and the present work extends our methods to those data. Normalized amplitude spectra on semi-logarithmic axes from all four arousal states (wake, N2, N3 and REM) were averaged region-wise and fitted to a multi-component Gaussian distribution. A reduced model comprising five key parameters per brain region was color-coded on to cortical surface models. The lognormal Gaussian mixture model described the iEEG accurately from all brain regions, in all sleep-wake states. There was smooth variation in model parameters as sleep and wake states yielded to each other. Specific observations unrelated to the model were that the primary cortical areas of vision, motor function and audition, in addition to the hippocampus, did not participate in the 'awakening' of the cortex during REM sleep. Despite the significant differences in the appearance of the time-domain EEG in wakefulness and sleep, the iEEG in all arousal states was successfully described by a parametric spectral model of low dimension. Spectral variation in the iEEG is continuous in space (across different cortical regions) and time (stage of circadian cycle), arguing for a 'continuum' hypothesis in the generative processes of sleep and wakefulness in human brain. [ABSTRACT FROM AUTHOR]

• Acute effects of brain responsive stimulation were studied in a large ambulatory intracranial EEG (iEEG) dataset captured with the NeuroPace® RNS® System. • 20.7% relative reduction in spectral power was observed in a 2-second window following active stimulation compared to sham in iEEG records. • Modest to strong associations between acute effects of stimulation and clinical outcomes were observed on individual detection channels. Understanding the acute effects of responsive stimulation (AERS) based on intracranial EEG (iEEG) recordings in ambulatory patients with drug-resistant partial epilepsy, and correlating these with changes in clinical seizure frequency, may help clinicians more efficiently optimize responsive stimulation settings. In patients implanted with the NeuroPace® RNS® System, acute changes in iEEG spectral power following active and sham stimulation periods were quantified and compared within individual iEEG channels. Additionally, acute stimulation-induced acute iEEG changes were compared within iEEG channels before and after patients experienced substantial reductions in clinical seizure frequency. Responsive stimulation resulted in a 20.7% relative decrease in spectral power in the 2–4 second window following active stimulation, compared to sham stimulation. On several detection channels, the AERS features changed when clinical outcomes improved but were relatively stable otherwise. AERS change direction associated with clinical improvement was generally consistent within detection channels. In this retrospective analysis, patients with drug-resistant partial epilepsy treated with direct brain-responsive neurostimulation showed an acute stimulation related reduction in iEEG spectral power that was associated with reductions in clinical seizure frequency. Identifying favorable stimulation related changes in iEEG activity could help physicians to more rapidly optimize stimulation settings for each patient. [ABSTRACT FROM AUTHOR]

• We visualized the phase-amplitude coupling phenomenon related to seizures by showing rhythmic fluctuation of high-frequency activities. • The low frequency band mainly coupled ictal-ripple activities was the θ band (4–8 Hz). • The seizure-related ripple power started to increase, and then spread, with fluctuations, and not with linear increases. High-frequency activities (HFAs) and phase-amplitude coupling (PAC) are key neurophysiological biomarkers for studying human epilepsy. We aimed to clarify and visualize how HFAs are modulated by the phase of low-frequency bands during seizures. We used intracranial electrodes to record seizures of focal epilepsy (12 focal-to-bilateral tonic-clonic seizures and three focal-aware seizures in seven patients). The synchronization index, representing PAC, was used to analyze the coupling between the amplitude of ripples (80–250 Hz) and the phase of lower frequencies. We created a video in which the intracranial electrode contacts were scaled linearly to the power changes of ripple. The main low frequency band modulating ictal-ripple activities was the θ band (4–8 Hz), and after completion of ictal-ripple burst, δ (1–4 Hz)-ripple PAC occurred. The ripple power increased simultaneously with rhythmic fluctuations from the seizure onset zone, and spread to other regions. Ripple activities during seizure evolution were modulated by the θ phase. The PAC phenomenon was visualized as rhythmic fluctuations. Ripple power associated with seizure evolution increased and spread with fluctuations. The θ oscillations related to the fluctuations might represent the common neurophysiological processing involved in seizure generation. [ABSTRACT FROM AUTHOR]

• The strength of TI electric field distributed across non-human primate brain was simulated and directly measured using invasively implanted multiple depth electrodes. • TI amplitude in deep brain regions under safety current can reach the strength that has shown subthreshold modulation effect in tACS. • The distribution of TI electric field obtained from experimental data can fit to the predicted distribution of computational simulation. • A pilot test in clinical patients showed that the potential effect of TI stimulation to the substantia nigra can improve specific symptoms of tremor in motor disorder. Temporal interference (TI) stimulation, a novel non-invasive stimulation strategy, has recently been shown to modulate neural activity in deep brain regions of living mice. Yet, it is uncertain if this method is applicable to larger brains and whether the electric field produced under traditional safety currents can penetrate deep regions as observed in mice. Despite recent model-based simulation studies offering positive evidence at both macro- and micro-scale levels, the absence of electrophysiological data from actual brains hinders comprehensive understanding and potential application of TI. This study aims to directly measure the spatiotemporal properties of the interfered electric field in the rhesus monkey brain and to validate the effects of TI on the human brain. Two monkeys were involved in the measurement, with implantation of several stereo-electroencephalography (SEEG) depth electrodes. TI stimulation was applied to anesthetized monkeys using two pairs of surface electrodes at differing stimulation parameters. Model-based simulations were also conducted and subsequently compared with actual recordings. Additionally, TI stimulation was administered to patients with motor disorders to validate its effects on motor symptoms. Through the integration of computational electric field simulation with empirical measurements, it was determined that the temporally interfering electric fields in the deep central regions are capable of attaining a magnitude sufficient to induce a subthreshold modulation effect on neural signals. Additionally, an improvement in movement disorders was observed as a result of TI stimulation. This study is the first to systematically measure the TI electric field in living non-human primates, offering empirical evidence that TI holds promise as a more focal and precise method for modulating neural activities in deep regions of a large brain. This advancement paves the way for future applications of TI in treating neuropsychiatric disorders. [ABSTRACT FROM AUTHOR]

Sleep inertia refers to the transient physiological state of hypoarousal upon awakening, associated with various degrees of impaired neurobehavioral performance, confusion, a desire to return to sleep and often a negative emotional state. Scalp and intracranial electro-encephalography as well as functional imaging studies have provided evidence that the sleep inertia phenomenon is underpinned by an heterogenous cerebral state mixing local sleep and local wake patterns of activity, at the neuronal and network levels. Sleep inertia is modulated by homeostasis and circadian processes, sleep stage upon awakening, and individual factors; this translates into a huge variability in its intensity even under physiological conditions. In sleep disorders, especially in hypersomnolence disorders such as idiopathic hypersomnia, sleep inertia may be a daily, serious and long-lasting symptom leading to severe impairment. To date, few tools have been developed to assess sleep inertia in clinical practice. They include mainly questionnaires and behavioral tests such as the psychomotor vigilance task. Only one neurophysiological protocol has been evaluated in hypersomnia, the forced awakening test which is based on an event-related potentials paradigm upon awakening. This contrasts with the major functional consequences of sleep inertia and its potentially dangerous consequences in subjects required to perform safety-critical tasks soon after awakening. There is a great need to identify reproducible biomarkers correlated with sleep inertia-associated cognitive and behavioral impairment. These biomarkers will aim at better understanding and measuring sleep inertia in physiological and pathological conditions, as well as objectively evaluating wake-promoting treatments or non-pharmacological countermeasures to reduce this phenomenon. [ABSTRACT FROM AUTHOR]

• A broad theta-alpha-beta phase (5–25 Hz)-gamma amplitude (80–100 Hz) elevated Phase Amplitude Coupling signal differentiated depressed from non-depressed epilepsy patients. • Phase Amplitude Coupling may be an anatomically specific, putative biomarker candidate of active sustained depressive symptoms in patients with epilepsy. • Phase Amplitude Coupling signal differed in brain regions between neocortical epilepsy and mesial temporal epilepsy patients. Depression is prevalent in epilepsy patients and their intracranial brain activity recordings can be used to determine the types of brain activity that are associated with comorbid depression. We performed case-control comparison of spectral power and phase amplitude coupling (PAC) in 34 invasively monitored drug resistant epilepsy patients' brain recordings. The values of spectral power and PAC for one-minute segments out of every hour in a patient's study were correlated with pre-operative assessment of depressive symptoms by Beck Depression Inventory-II (BDI). We identified an elevated PAC signal (theta-alpha–beta phase (5–25 Hz)/gamma frequency (80–100 Hz) band) that is present in high BDI scores but not low BDI scores adult epilepsy patients in brain regions implicated in primary depression, including anterior cingulate cortex, amygdala and orbitofrontal cortex. Our results showed the application of PAC as a network-specific, electrophysiologic biomarker candidate for comorbid depression and its potential as treatment target for neuromodulation. [ABSTRACT FROM AUTHOR]

[Display omitted] • While OCD is a co-morbidity of epilepsy, the pathophysiological basis of the disease is not known. • Early-life seizures (ELS) in rats was not found to result in OCD-like behaviors. • ELS causes changes in the theta-slow gamma comodulation in a state-, site- and sex-dependent manner. • CBD alters theta-slow gamma comodulation in a state-, site- and sex-related manner. Obsessive compulsive disorder (OCD) is a comorbid condition of epilepsy and often adds to the burden of epilepsy. Both OCD and epilepsy are disorders of hyperexcitable circuits. Fronto-striatal circuit dysfunction is implicated in OCD. Prior work in our laboratory has shown that in rat pups following a series of flurothyl-induced early life seizures (ELS) exhibit frontal-lobe dysfunction along with alterations in electrographic temporal coordination between the orbitofrontal cortex (OFC) and dorsomedial striatum (DMS), circuits implicated in OCD. Here, we studied the effects of ELS in male and female rat pups on OCD-like behaviors as adults using the marble burying test (MBT). Because cannabidiol (CBD) is an effective antiseizure medication and has shown efficacy in the treatment of individuals with OCD, we also randomized rats to CBD or vehicle treatment following ELS to determine if CBD had any effect on OCD-like behaviors. While the flurothyl model of ELS did not induce OCD-like behaviors, as measured in the MBT, ELS did alter neural signaling in structures implicated in OCD and CBD had sex-dependent effects of temporal coordination in a way which suggests it may have a beneficial effect on epilepsy-related OCD. [ABSTRACT FROM AUTHOR]

Background: The development of automated seizure detection methods using EEG signals could be of great importance for the diagnosis and the monitoring of patients with epilepsy. These methods are often patient-specific and require high accuracy in detecting seizures but also very low false-positive rates. The aim of this study is to evaluate the performance of a seizure detection method using EEG signals by investigating its performance in correctly identifying seizures and in minimizing false alarms and to determine if it is generalizable to different patients. Methods: We tested the method on about two hours of preictal/ictal and about ten hours of interictal EEG recordings of one patient from the Freiburg Seizure Prediction EEG database using machine learning techniques for data mining. Then, we tested the obtained model on six other patients of the same database. Results: The method achieved very high performance in detecting seizures (close to 100% of correctly classified positive elements) with a very low false-positive rate when tested on one patient. Furthermore, the model portability or transfer analysis revealed that the method achieved good performance in one out of six patients from the same dataset. Conclusions: This result suggests a strategy to discover clusters of similar patients, for which it would be possible to train a general-purpose model for seizure detection.

Objective: Scalp electroencephalographic (EEG)–functional magnetic resonance imaging (fMRI) studies suggest that the maximum blood oxygen level‐dependent (BOLD) response to an interictal epileptiform discharge (IED) identifies the area of IED generation. However, the maximum BOLD response has also been reported in distant, seemingly irrelevant areas. Given the poor postoperative outcomes associated with extra‐temporal lobe epilepsy, we hypothesized this finding is more common when analyzing extratemporal IEDs as compared to temporal IEDs. We further hypothesized that a subjective, holistic assessment of other significant BOLD clusters to identify the most clinically relevant cluster could be used to overcome this limitation and therefore better identify the likely origin of an IED. Specifically, we also considered the second maximum cluster and the cluster closest to the electrode contacts where the IED was observed. Methods: Maps of significant IED‐related BOLD activation were generated for 48 different IEDs recorded from 33 patients who underwent intracranial EEG‐fMRI. The locations of the maximum, second maximum, and closest clusters were identified for each IED. An epileptologist, blinded to these cluster assignments, selected the most clinically relevant BOLD cluster, taking into account all available clinical information. The distances between these BOLD clusters and their corresponding IEDs were then measured. Results: The most clinically relevant cluster was the maximum cluster for 56% (27/48) of IEDs, the second maximum cluster for 13% (6/48) of IEDs, and the closest cluster for 31% (15/48) of IEDs. The maximum clusters were closer to IED contacts for temporal than for extratemporal IEDs (p =.022), whereas the most clinically relevant clusters were not significantly different (p =.056). Significance: The maximum BOLD response to IEDs may not always be the most indicative of IED origin. We propose that available clinical information should be used in conjunction with EEG‐fMRI data to identify a BOLD cluster representative of the IED origin. [ABSTRACT FROM AUTHOR]

We describe the spatiotemporal course of cortical high-gamma activity, hippocampal ripple activity and interictal epileptiform discharges during an associative memory task in 15 epilepsy patients undergoing invasive EEG. Successful encoding trials manifested significantly greater high-gamma activity in hippocampus and frontal regions. Successful cued recall trials manifested sustained high-gamma activity in hippocampus compared to failed responses. Hippocampal ripple rates were greater during successful encoding and retrieval trials. Interictal epileptiform discharges during encoding were associated with 15% decreased odds of remembering in hippocampus (95% confidence interval 6-23%). Hippocampal interictal epileptiform discharges during retrieval predicted 25% decreased odds of remembering (15-33%). Odds of remembering were reduced by 25-52% if interictal epileptiform discharges occurred during the 500-2000 ms window of encoding or by 41% during retrieval. During encoding and retrieval, hippocampal interictal epileptiform discharges were followed by a transient decrease in ripple rate. We hypothesize that interictal epileptiform discharges impair associative memory in a regionally and temporally specific manner by decreasing physiological hippocampal ripples necessary for effective encoding and recall. Because dynamic memory impairment arises from pathological interictal epileptiform discharge events competing with physiological ripples, interictal epileptiform discharges represent a promising therapeutic target for memory remediation in patients with epilepsy. [ABSTRACT FROM AUTHOR]

Purpose: To provide a descriptive analysis on the presurgical evaluation and surgical management of a cohort of patients with stroke related epilepsy (SRE).Methods: We retrospectively examined the clinical characteristics, results of non-invasive and invasive presurgical evaluation, surgical management and outcome of consecutive patients with drug-resistant SRE in our institution from January 1, 2013 to January 1, 2020.Results: Twenty-one of 420 patients (5%) who underwent intracranial EEG (iEEG), resective epilepsy surgery and/or vagus nerve stimulation (VNS) placement, had SRE. Of 13 patients who had iEEG, the ictal onset (IO) was exclusively within the stroke lesion in only one patient. In five patients the IO was extra-lesional and in the remaining seven patients it included the stroke lesion as well as extra-lesional structures. The IO included the mesial temporal region in 11 of the 13 patients (85%). The posterior margin of the stroke lesion was always involved. Five patients underwent surgery without iEEG. In total, 10 patients underwent resective surgery, four VNS placement and two had both corpus callosotomy and VNS placement. Of the patients who had resective surgery, nine were Engel I or II at last follow up.Conclusion: We found that seizures in patients with drug resistant SRE were more frequently originated in the mesial temporal region than in the stroke lesion itself. Despite the complex epileptic network underlying drug-resistant SRE, a thorough presurgical assessment and adequate use of surgical options can lead to excellent surgical outcomes. [ABSTRACT FROM AUTHOR]