Proceedings of the Ninth Annual Deep Brain Stimulation Think Tank: Advances in Cutting Edge Technologies, Artificial Intelligence, Neuromodulation, Neuroethics, Pain, Interventional Psychiatry, Epilepsy, and Traumatic Brain Injury.

DBS Think Tank IX was held on August 25-27, 2021 in Orlando FL with US based participants largely in person and overseas participants joining by video conferencing technology. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers and researchers (from industry and academia) can freely discuss current and emerging deep brain stimulation (DBS) technologies as well as the logistical and ethical issues facing the field. The consensus among the DBS Think Tank IX speakers was that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. After collectively sharing our experiences, it was estimated that globally more than 230,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. As such, this year's meeting was focused on advances in the following areas: neuromodulation in Europe, Asia and Australia; cutting-edge technologies, neuroethics, interventional psychiatry, adaptive DBS, neuromodulation for pain, network neuromodulation for epilepsy and neuromodulation for traumatic brain injury.

Neurophysiological brain mapping of human sleep-wake states.

OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. SIGNIFICANCE: 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.

Functional Connectivity in Dorsolateral Frontal Cortex: Intracranial Electroencephalogram Study.

Motivation: Mechanisms underlying the variation in the appearance of electroencephalogram (EEG) over human head are not well characterized. We hypothesized that spatial variation of the EEG, being ultimately linked to variations in cortical neurobiology, was dependent on cortical connectivity patterns. Specifically, we explored the relationship of resting-state functional connectivity derived from intracranial EEG (iEEG) data in seven (N = 7) human epilepsy patients with the intrinsic dynamic variability of the local iEEG. We asked whether primary and association brain areas over the lateral frontal lobe-due to their sharply different connectivity patterns-were thus dissociable in "EEG space." Methods: Functional connectivity between pairs of subdural grid electrodes was averaged to yield an electrode connectivity (EC) whose time-average yielded mean electrode connectivity (mEC), compared with that electrode's time-averaged sample entropy (SE; mean electrode sample entropy, mESE). Results: We found that mEC and mESE were generally in inverse proportion to each other. Extreme values of mEC and mESE occurred over the Rolandic region and were part of a more general rostrocaudal gradient observed in all patients, with larger (smaller) values of mEC (mESE) occurring anteriorly. Conclusions: Brain networks influence brain dynamics. Over the lateral frontal lobe, mEC and mESE demonstrate a rostrocaudal topography, consistent with current notions regarding the structural and functional parcellation of the human frontal lobe. Our findings distinguish the frontal association cortex from primary sensorimotor cortex, effectively "diagnosing" Rolandic iEEG independent of the classical mu rhythm associated with the latter brain region. Impact statement Electroencephalographic rhythms (electroencephalogram [EEG]) exhibit well-recognized spatial variation over the brain surface. How such variation pertains to the biology of the cortex is poorly understood. Here we identify a novel relationship between sample entropy of the local EEG and the connectivity of that local cortical region to the rest of the brain. Due to the differing connectivities of primary and association motor areas, our methods identify new differences in the EEG arising from those respective brain areas. Our work demonstrates that aspects of brain dynamics (i.e., EEG entropy) may be understood in terms of brain architecture (i.e., functional connectivity) and vice versa.

Extracranial Interictal and Ictal EEG in sEEG Planning.

Analysis of scalp electroencephalogram (EEG) findings is indispensable to investigation of epilepsy surgery candidates. Maxima of slowing and epileptiform spiking on interictal EEG reflect gross localization of core epileptogenic regions within a network. Important negative scalp EEG findings are those associated with deep foci. Ictal EEG is important in confirming concordance with interictal EEG and other ancillary data. Generalized interictal and ictal EEG findings may occur in epilepsies that are otherwise focal. Detailed individual analyses of scalp EEG features are prelude to a more global synthesis, whose coherence in suggesting plausible network hypothesis presage a subsequently successful scalp EEG evaluation.

A neurophysiological brain map: Spectral parameterization of the human intracranial electroencephalogram.

OBJECTIVE: A library of intracranial electroencephalography (iEEG) from the normal human brain has recently been made publicly available (Frauscher et al., 2018). The library - which we term the Montreal Neurological Institute Atlas (MNIA) - comprises 30 hours of iEEG from over a hundred epilepsy patients. We present a Fourier spectrum-based model of low dimension that summarizes all of MNIA into a neurophysiological 'brain map'. METHODS: Normalized amplitude spectra of the MNIA data were modelled as log-normal distributions around individual canonical Berger frequencies. The latter were concatenated to yield the composite spectrum with high accuracy. Key model parameters were color-coded into a visual representation on cortical surface models. RESULTS: Each brain region has its own spectral characteristics that together yield a novel composite intracranial EEG brain map. CONCLUSIONS: iEEG from normal brain regions can be accurately modelled with a small number of independent parameters. Our model is based in the canonical Berger bands and naturally suits clinical electroencephalography. SIGNIFICANCE: Due to its applicability to iEEG from all sampled regions, the model suggests a certain universality to brain rhythm generation that is independent of precise cortical location. More generally, our results are a novel abstraction of resting cortical dynamics that may help diagnostics in epileptology, in addition to informing structure-function relationships in the field of human brain mapping.

Montages for Noninvasive EEG Recording.

Identifying the localization, distribution, and polarity of waveforms are the prime goals of clinical scalp EEG analysis. Appropriate choices of bipolar and referential montages are keys to emphasizing the diagnostic features of interest, and demand some understanding of the spatiotemporal physical behavior of the underlying neuronal generators. Several examples drawn from canonical epilepsy syndromes are used to illustrate this general message.

Analysis of Morbidity and Outcomes Associated With Use of Subdural Grids vs Stereoelectroencephalography in Patients With Intractable Epilepsy.

Importance: A major change has occurred in the evaluation of epilepsy with the availability of robotic stereoelectroencephalography (SEEG) for seizure localization. However, the comparative morbidity and outcomes of this minimally invasive procedure relative to traditional subdural electrode (SDE) implantation are unknown. Objective: To perform a comparative analysis of the relative efficacy, procedural morbidity, and epilepsy outcomes consequent to SEEG and SDE in similar patient populations and performed by a single surgeon at 1 center. Design, Setting and Participants: Overall, 239 patients with medically intractable epilepsy underwent 260 consecutive intracranial electroencephalographic procedures to localize their epilepsy. Procedures were performed from November 1, 2004, through June 30, 2017, and data were analyzed in June 2017 and August 2018. Interventions: Implantation of SDE using standard techniques vs SEEG using a stereotactic robot, followed by resection or laser ablation of the seizure focus. Main Outcomes and Measures: Length of surgical procedure, surgical complications, opiate use, and seizure outcomes using the Engel Epilepsy Surgery Outcome Scale. Results: Of the 260 cases included in the study (54.6% female; mean [SD] age at evaluation, 30.3 [13.1] years), the SEEG (n = 121) and SDE (n = 139) groups were similar in age (mean [SD], 30.1 [12.2] vs 30.6 [13.8] years), sex (47.1% vs 43.9% male), numbers of failed anticonvulsants (mean [SD], 5.7 [2.5] vs 5.6 [2.5]), and duration of epilepsy (mean [SD], 16.4 [12.0] vs17.2 [12.1] years). A much greater proportion of SDE vs SEEG cases were lesional (99 [71.2%] vs 53 [43.8%]; P < .001). Seven symptomatic hemorrhagic sequelae (1 with permanent neurological deficit) and 3 infections occurred in the SDE cohort with no clinically relevant complications in the SEEG cohort, a marked difference in complication rates (P = .003). A greater proportion of SDE cases resulted in resection or ablation compared with SEEG cases (127 [91.4%] vs 90 [74.4%]; P < .001). Favorable epilepsy outcomes (Engel class I [free of disabling seizures] or II [rare disabling seizures]) were observed in 57 of 75 SEEG cases (76.0%) and 59 of 108 SDE cases (54.6%; P = .003) amongst patients undergoing resection or ablation, at 1 year. An analysis of only nonlesional cases revealed good outcomes in 27 of 39 cases (69.2%) vs 9 of 26 cases (34.6%) at 12 months in SEEG and SDE cohorts, respectively (P = .006). When considering all patients undergoing evaluation, not just those undergoing definitive procedures, favorable outcomes (Engel class I or II) for SEEG compared with SDE were similar (57 of 121 [47.1%] vs 59 of 139 [42.4%] at 1 year; P = .45). Conclusions and Relevance: This direct comparison of large matched cohorts undergoing SEEG and SDE implantation reveals distinctly better procedural morbidity favoring SEEG. These modalities intrinsically evaluate somewhat different populations, with SEEG being more versatile and applicable to a range of scenarios, including nonlesional and bilateral cases, than SDE. The significantly favorable adverse effect profile of SEEG should factor into decision making when patients with pharmacoresistant epilepsy are considered for intracranial evaluations.

Interictal Epileptiform Discharge Detection in EEG in Different Practice Settings.

OBJECTIVE: The goal of the study was to measure the performance of academic and private practice (PP) neurologists in detecting interictal epileptiform discharges in routine scalp EEG recordings. METHODS: Thirty-five EEG scorers (EEGers) participated (19 academic and 16 PP) and marked the location of ETs in 200 30-second EEG segments using a web-based EEG annotation system. All participants provided board certification status, years of Epilepsy Fellowship Training (EFT), and years in practice. The Persyst P13 automated IED detection algorithm was also run on the EEG segments for comparison. RESULTS: Academic EEGers had an average of 1.66 years of EFT versus 0.50 years of EFT for PP EEGers (P < 0.0001) and had higher rates of board certification. Inter-rater agreement for the 35 EEGers was fair. There was higher performance for EEGers in academics, with at least 1.5 years of EFT, and with American Board of Clinical Neurophysiology and American Board of Psychiatry and Neurology-E specialty board certification. The Persyst P13 algorithm at its default setting (perception value = 0.4) did not perform as well at the EEGers, but at substantially higher perception value settings, the algorithm performed almost as well human experts. CONCLUSIONS: Inter-rater agreement among EEGers in both academic and PP settings varies considerably. Practice location, years of EFT, and board certification are associated with significantly higher performance for IED detection in routine scalp EEG. Continued medical education of PP neurologists and neurologists without EFT is needed to improve routine scalp EEG interpretation skills. The performance of automated detection algorithms is approaching that of human experts.

Ictal-Interictal Continuum.

The term "ictal-interictal" continuum has seen wide adoption in the critical care EEG domain, referring to the presence of abnormal periodic activity on the scalp EEG variably associated with seizures. The historical origin of the ictal-interictal continuum concept is discussed with a review of known and surmised physiological mechanisms for their origin and relationship to seizures. Therapeutic approaches to patients exhibiting ictal-interictal continuum EEG patterns are reviewed, and some open scientific questions highlighted. Further understanding of the ictal-interictal continuum is likely to significantly improve the care of the critically ill neurological patient.

The interictal mesial temporal lobe epilepsy network.

OBJECTIVE: Identification of patient-specific epileptogenic networks is critical to designing successful treatment strategies. Multiple noninvasive methods have been used to characterize epileptogenic networks. However, these methods lack the spatiotemporal resolution to allow precise localization of epileptiform activity. We used intracranial recordings, at much higher spatiotemporal resolution, across a cohort of patients with mesial temporal lobe epilepsy (MTLE) to delineate features common to their epileptogenic networks. We used interictal rather than seizure data because interictal spikes occur more frequently, providing us greater power for analyzing variances in the network. METHODS: Intracranial recordings from 10 medically refractory MTLE patients were analyzed. In each patient, hour-long recordings were selected for having frequent interictal discharges and no ictal events. For all possible pairs of electrodes, conditional probability of the occurrence of interictal spikes within a 150-millisecond bin was computed. These probabilities were used to construct a weighted graph between all electrodes, and the node degree was estimated. To assess the relationship of the highly connected regions in this network to the clinically identified seizure network, logistic regression was used to model the regions that were surgically resected using weighted node degree and number of spikes in each channel as factors. Lastly, the conditional spike probability was normalized and averaged across patients to visualize the MTLE network at group level. RESULTS: We generated the first graph of connectivity across a cohort of MTLE patients using interictal activity. The most consistent connections were hippocampus to amygdala, anterior fusiform cortex to hippocampus, and parahippocampal gyrus projections to amygdala. Additionally, the weighted node degree and number of spikes modeled the brain regions identified as seizure networks by clinicians. SIGNIFICANCE: Apart from identifying interictal measures that can model patient-specific epileptogenic networks, we also produce a group map of network connectivity from a cohort of MTLE patients.

A simple clinical score for prediction of nonepileptic seizures.

Psychogenic nonepileptic seizures (PNES), often mistaken for epilepsy in community practice, require inpatient video-EEG (VEEG) monitoring for diagnostic confirmation. We developed a simple score designed for use in an outpatient setting to predict the subsequent VEEG diagnosis of PNES. We retrospectively compared fifty-five consecutive patients with VEEG-proven PNES (N1=55) with a group of randomly selected patients with VEEG-proven epilepsy (N2=55). Patients were divided into two groups: I) a 'truly retrospective' group of 27 patients with PNES and 27 patients with epilepsy whose data served to develop the score, and II) a 'pseudoprospective' group of 28 patients each with PNES and epilepsy to whom the score was applied. Six features in the history of the Group I cohort appeared more prominent in patients with PNES than patients with epilepsy and were assigned escalating numerical values as follows: number of declared drug allergies (0, 0.5, 1), number of declared comorbidities (0, 0.5, 1), number of previous invasive medical interventions of any type (0, 0.5, 1), and a history of significant psychological or physical trauma (0 or 1). In addition, a score was assigned to verbal description of the seizures themselves as being consistent (=0), atypical (=1), or indeterminate (=0.5) for epilepsy. The values were added to yield an omnibus score ranging from 0 to 6. Scoring of Group II subjects in a blinded fashion revealed that in general patients with PNES had higher scores, and the majority obtained a score >2; most patients with epilepsy scored <1.5. Group difference in the mean between the PNES and epilepsy cohort was highly significant (p<0.0001, Wilcoxon rank-sum test). Our score is a simple clinical instrument based on the patient history that may find use in the triage of patients awaiting hospitalization for VEEG and in pre-VEEG counseling.

Characteristics of EEG Interpreters Associated With Higher Interrater Agreement.

PURPOSE: The goal of the project is to determine characteristics of academic neurophysiologist EEG interpreters (EEGers), which predict good interrater agreement (IRA) and to determine the number of EEGers needed to develop an ideal standardized testing and training data set for epileptiform transient (ET) detection algorithms. METHODS: A three-phase scoring method was used. In phase 1, 19 EEGers marked the location of ETs in two hundred 30-second segments of EEG from 200 different patients. In phase 2, EEG events marked by at least 2 EEGers were annotated by 18 EEGers on a 5-point scale to indicate whether they were ETs. In phase 3, a third opinion was obtained from EEGers on any inconsistencies between phase 1 and phase 2 scoring. RESULTS: The IRA for the 18 EEGers was only fair. A select group of the EEGers had good IRA and the other EEGers had low IRA. Board certification by the American Board of Clinical Neurophysiology was associated with better IRA performance but other board certifications, years of fellowship training, and years of practice were not. As the number of EEGers used for scoring is increased, the amount of change in the consensus opinion decreases steadily and is quite low as the group size approaches 10. CONCLUSIONS: The IRA among EEGers varies considerably. The EEGers must be tested before use as scorers for ET annotation research projects. The American Board of Clinical Neurophysiology certification is associated with improved performance. The optimal size for a group of experts scoring ETs in EEG is probably in the 6 to 10 range.

Stereo-EEG Implantation Strategy.

Stereoelectroencephalography denotes the strategic placement of multiple depth electrodes for invasive localization of focal epilepsy in surgical patients. It differs significantly from the alternative subdural grid approach, in both conceptualization of partial epilepsy-as a 3-D distributed network, rather than as focal pathology with contiguous spread-and by the method of sampling used-which is sparse and directed rather than continuous over adjacent brain areas. The electrode implantation strategy in stereoelectroencephalography involves appreciation of these features, which are illustrated by four cases drawn from distinct electroclinical epilepsy syndromes.

Surgical Resection for Epilepsy Following Cerebral Gunshot Wounds.

OBJECTIVE: The surgical management of epilepsy after penetrating gunshot wounds (GSWs) to the head has not been described in the modern era. Given the extensive damage to the cranium and cortex from such injuries, the safety and efficacy of surgical intervention are unclear. We report surgical strategy and outcomes after resection for medically refractory epilepsy following GSWs in 4 patients. METHODS: A prospectively compiled database of 325 patients with epilepsy was used to identify patients undergoing surgery for medically refractory epilepsy after a GSW to the brain. Seizure frequency, scalp and intracranial electroencephalography evaluation, type of resection, and seizure outcomes were compiled. RESULTS: All 4 patients underwent direct electrocorticography recordings either with implanted electrodes or intraoperatively that were used to drive surgical decision making. All patients had intracranial shrapnel fragments and large areas of encephalomalacia on imaging. Intracranial electrodes were placed in 2 patients to localize seizure onsets. Two patients underwent frontal lobe resections, and the other 2 patients underwent multilobar resections. Latency between injury and epilepsy surgery was 12 years, and mean age at surgery was 28 years. In all cases, epilepsy surgery led to a significant improvement in seizure control (Engel class I, 2 patients; II, 1 patient; and III, 1 patient). CONCLUSIONS: Epilepsy is common after penetrating head injury, and the incidence is likely to increase given the growing numbers of armed conflicts in urban centers worldwide. In selected cases, intracranial monitoring and surgical resections may be safely performed and can lead to favorable seizure outcomes.

Intracranial evaluation and laser ablation for epilepsy with periventricular nodular heterotopia.

Surgical treatment of focal epilepsy in the presence of periventricular nodular heterotopia (PVNH) poses a challenge, as the relative roles of the nodular tissue and the overlying cortex in the generation of seizures can be complex and variable. Here, we review the literature on chronic invasive EEG recordings in humans with this substrate and present two illustrative cases from our practice. We found that while inter-ictal spiking from nodules is common, clinical seizures rarely arise solely from nodular tissue. More typically, ictal onset is simultaneous with overlying neocortex or mesial temporal structures. Surgical outcome is more favorable in cases with unilateral (as opposed to bilateral) PVNH, and when a substantial or complete ablation of PVNH is performed. In rare cases, nodular ablation alone may be sufficient, as may be completed by MRI-guided laser interstitial thermal therapy. The mechanism(s) by which PNVH interacts with overlying cortex are not fully understood, but we suggest that PVNH either orchestrates or amplifies local network epileptogenicity. At present, invasive recordings with penetrating depth electrodes are required prior to surgical therapy, as illustrated in our cases.

A unified statistical model for the human electrocorticogram.

OBJECTIVE: Extracellular field potentials (ECFs) generated in the cerebral cortex span a vast range of spatiotemporal scales. The process(es) leading to this large dynamic range remain debatable. Here we propose a novel statistical description of the amplitude spectrum of the human electrocorticogram (ECoG). METHODS: Spectral analysis was performed on long-term recordings from epilepsy patients undergoing pre-surgical evaluation with intracranial electrodes. Amplitude spectra were fit with a multi-component Gaussian model on semi-logarithmic axes. RESULTS: The Gaussian formulation provided excellent fits to the data. It also suggested how the changes accompanying the sleep-wake cycle and certain epileptiform transitions could be understood by variation in the parameters of the model. CONCLUSIONS: The proposed continuum model synthesizes several previous observations regarding the statistical structure of the resting human ECoG. It offers a conceptual platform for understanding the EEG changes accompanying the sleep-wake cycle and pathologically hypersynchronous behaviour. SIGNIFICANCE: Statistical characterisation of the spectral distribution of field potentials yield insight into the cortico-cortical interactions that underlie the summated cortical ECFs comprising the ECoG. Such insight is relevant for a synoptic understanding of major state changes in the brain that are diagnosed in clinical practice by visual inspection of the ECoG.

Reactivation of visual-evoked activity in human cortical networks.

In the absence of sensory input, neuronal networks are far from being silent. Whether spontaneous changes in ongoing activity reflect previous sensory experience or stochastic fluctuations in brain activity is not well understood. Here we demonstrate reactivation of stimulus-evoked activity that is distributed across large areas in the human brain. We performed simultaneous electrocorticography recordings from occipital, parietal, temporal, and frontal areas in awake humans in the presence and absence of sensory stimulation. We found that, in the absence of visual input, repeated exposure to brief natural movies induces robust stimulus-specific reactivation at individual recording sites. The reactivation sites were characterized by greater global connectivity compared with those sites that did not exhibit reactivation. Our results indicate a surprising degree of short-term plasticity across multiple networks in the human brain as a result of repeated exposure to unattended information.