Aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity.

Information flow in brain networks is reflected in local field potentials that have both periodic and aperiodic components. The 1/fχ aperiodic component of the power spectra tracks arousal and correlates with other physiological and pathophysiological states. Here we explored the aperiodic activity in the human thalamus and basal ganglia in relation to simultaneously recorded cortical activity. We elaborated on the parameterization of the aperiodic component implemented by specparam (formerly known as FOOOF) to avoid parameter unidentifiability and to obtain independent and more easily interpretable parameters. This allowed us to seamlessly fit spectra with and without an aperiodic knee, a parameter that captures a change in the slope of the aperiodic component. We found that the cortical aperiodic exponent χ, which reflects the decay of the aperiodic component with frequency, is correlated with Parkinson's disease symptom severity. Interestingly, no aperiodic knee was detected from the thalamus, the pallidum, or the subthalamic nucleus, which exhibited an aperiodic exponent significantly lower than in cortex. These differences were replicated in epilepsy patients undergoing intracranial monitoring that included thalamic recordings. The consistently lower aperiodic exponent and lack of an aperiodic knee from all subcortical recordings may reflect cytoarchitectonic and/or functional differences. SIGNIFICANCE STATEMENT: The aperiodic component of local field potentials can be modeled to produce useful and reproducible indices of neural activity. Here we refined a widely used phenomenological model for extracting aperiodic parameters (namely the exponent, offset and knee), with which we fit cortical, basal ganglia, and thalamic intracranial local field potentials, recorded from unique cohorts of movement disorders and epilepsy patients. We found that the aperiodic exponent in motor cortex is higher in Parkinson's disease patients with more severe motor symptoms, suggesting that aperiodic features may have potential as electrophysiological biomarkers for movement disorders symptoms. Remarkably, we found conspicuous differences in the aperiodic parameters of basal ganglia and thalamic signals compared to those from neocortex.

Specific afterdischarge properties can enhance the clinical utility of electrical stimulation mapping during intracranial monitoring.

OBJECTIVE: Extraoperative electrical cortical stimulation (ECS) facilitates defining the seizure onset zone (SOZ) and eloquent cortex. The clinical relevance of stimulation-induced afterdischarges (ADs) is not well defined. METHODS: Fifty-five patients who underwent intracranial electroencephalogram evaluations with ECS were retrospectively identified. ADs were identified in these recordings and categorized by pattern, location, and association with stimulation-induced seizures. RESULTS: ADs were generated in 1774/9285 (19%) trials. Rhythmic spikes and irregular ADs within the stimulated bipolar contact pair were predictive of location within the SOZ compared to non-epileptogenic/non-irritative cortex (rhythmic spikes OR 2.24, p = 0.0098; irregular OR 1.39; p = 0.013). ADs immediately preceding stimulated seizures occurred at lower stimulation intensity thresholds compared to other stimulations (mean 2.94 ± 0.28 mA vs. 4.16 ± 0.05 mA respectively; p = 0.0068). CONCLUSIONS: Changes in AD properties can provide clinically relevant data in extraoperative stimulation mapping. SIGNIFICANCE: Although not exclusive to the SOZ, the generation of rhythmic spikes may suggest that a stimulation location is within the SOZ, while decreased stimulation intensity thresholds eliciting ADs may alert clinicians to a heightened probability of seizure generation with subsequent stimulation.

Concordance of verbal memory and language fMRI lateralization in people with epilepsy.

BACKGROUND AND PURPOSE: This work investigates verbal memory functional MRI (fMRI) versus language fMRI in terms of lateralization, and assesses the validity of performing word recognition during the functional scan. METHODS: Thirty patients with a diagnosis of epilepsy underwent verbal memory, visuospatial memory, and language fMRI. We used word encoding, word recognition, image encoding, and image recognition memory tasks, and semantic description, reading comprehension, and listening comprehension language tasks. We used three common lateralization metrics: network spatial distribution, maximum statistical value, and laterality index (LI). RESULTS: Lateralization of signal spatial distribution resulted in poor similarity between verbal memory and language fMRI tasks. Signal maximum lateralization showed significant (>.8) but not perfect (1) similarity. Word encoding LI showed significant correlation only with listening comprehension LI (p = .016). Word recognition LI was significantly correlated with expressive language semantic description LI (p = .024) and receptive language reading and listening comprehension LIs (p = .015 and p = .019, respectively). There was no correlation between LIs of the visuospatial tasks and LIs of the language tasks. CONCLUSIONS: Our results support the association between language and verbal memory lateralization, optimally determined by LI quantification, and the introduction of quantitative means for language fMRI interpretation in clinical settings where verbal memory lateralization is imperative.

Hippocampal barques and their manifestation as 14&6 Hz positive spikes during sleep.

OBJECTIVE: This study investigates variations in hippocampal barque occurrence during sleep and compares findings to respective variations of their scalp manifestation as 14&6/sec positive spikes. METHODS: From 11 epilepsy patients, 12 non-epileptogenic hippocampi with barques were identified for this study. Using the first seizure-free whole-night sleep stereo-encephalography (sEEG) recording, we performed sleep staging and measured the occurrence of barques and 14&6/sec positive spikes variants. RESULTS: Hippocampal barques (total count: 9,183; mean count per record: 765.2 ± 251.2) occurred predominantly during non-rapid eye movement (NREM) II sleep (total: 5,744; mean: 478.6 ± 176.1; 62.2 ± 6.0%) and slow-wave sleep (SWS) (total: 2,950; mean: 245.83 ± 92.9; 32.0 ± 6.2%), with rare to occasional occurrence in NREM I (total: 85; mean: 7.0 ± 2.8; 0.9 ± 0.4%), rapid eye movement (REM) (total: 153; mean: 12.75 ± 4.0; 1.7 ± 0.6) and wakefulness (total: 251; mean: 20.9 ± 6.3; 2.9 ± 0.9%). Barque rate increased during SWS (mean: 2.7 ± 1.0 per min) compared to NREM II (2.2 ± 1.0 per min) and other states (wakefulness: 0.1 ± 0.0 per min; NREM I: 0.3 ± 0.1 per min; REM: 0.1 ± 0.0 per min). The 14&6/sec positive spikes variant (total count: 2,406; mean: 343.7 ± 106.7) was present in NREM II (total: 2,059; mean: 249.1 ± 100.2, 84.9 ± 3.6%) and SWS (total: 347; mean: 49.5 ± 12.8, 15.0 ± 3.6%) stages, and absent from the rest of sleep and wakefulness. While all 14&6/sec positive spikes correlated with barques, only 44.7 ± 6.1% of barques manifested as 14&6/sec positive spikes. CONCLUSIONS: Hippocampal barques are predominant in NREM II and SWS, and tend to increase their presence during SWS. Their scalp manifestation as 14&6/sec positive spikes is confounded by wakefulness, REM and NREM I stages, and "masked" by the co-occurrence of NREM II and SWS slow waves, and overlapping reactive micro-arousal elements. SIGNIFICANCE: Our study highlighted the overnight profile of hippocampal barques, in relation to the respective profile of their scalp manifestation, the 14&6/sec positive spikes variant.

Functional Magnetic Resonance Imaging and Diffusion Tensor Imaging-Tractography in Resective Brain Surgery: Lesion Coverage Strategies and Patient Outcomes.

Diffusion tensor imaging (DTI)-tractography and functional magnetic resonance imaging (fMRI) have dynamically entered the presurgical evaluation context of brain surgery during the past decades, providing novel perspectives in surgical planning and lesion access approaches. However, their application in the presurgical setting requires significant time and effort and increased costs, thereby raising questions regarding efficiency and best use. In this work, we set out to evaluate DTI-tractography and combined fMRI/DTI-tractography during intra-operative neuronavigation in resective brain surgery using lesion-related preoperative neurological deficit (PND) outcomes as metrics. We retrospectively reviewed medical records of 252 consecutive patients admitted for brain surgery. Standard anatomical neuroimaging protocols were performed in 127 patients, 69 patients had additional DTI-tractography, and 56 had combined DTI-tractography/fMRI. fMRI procedures involved language, motor, somatic sensory, sensorimotor and visual mapping. DTI-tractography involved fiber tracking of the motor, sensory, language and visual pathways. At 1 month postoperatively, DTI-tractography patients were more likely to present either improvement or preservation of PNDs (p = 0.004 and p = 0.007, respectively). At 6 months, combined DTI-tractography/fMRI patients were more likely to experience complete PND resolution (p < 0.001). Low-grade lesion patients (N = 102) with combined DTI-tractography/fMRI were more likely to experience complete resolution of PNDs at 1 and 6 months (p = 0.001 and p < 0.001, respectively). High-grade lesion patients (N = 140) with combined DTI-tractography/fMRI were more likely to have PNDs resolved at 6 months (p = 0.005). Patients with motor symptoms (N = 80) were more likely to experience complete remission of PNDs at 6 months with DTI-tractography or combined DTI-tractography/fMRI (p = 0.008 and p = 0.004, respectively), without significant difference between the two imaging protocols (p = 1). Patients with sensory symptoms (N = 44) were more likely to experience complete PND remission at 6 months with combined DTI-tractography/fMRI (p = 0.004). The intraoperative neuroimaging modality did not have a significant effect in patients with preoperative seizures (N = 47). Lack of PND worsening was observed at 6 month follow-up in patients with combined DTI-tractography/fMRI. Our results strongly support the combined use of DTI-tractography and fMRI in patients undergoing resective brain surgery for improving their postoperative clinical profile.

Deep net detection and onset prediction of electrographic seizure patterns in responsive neurostimulation.

OBJECTIVE: Managing the progress of drug-resistant epilepsy patients implanted with the Responsive Neurostimulation (RNS) System requires the manual evaluation of hundreds of hours of intracranial recordings. The generation of these large amounts of data and the scarcity of experts' time for evaluation necessitate the development of automatic tools to detect intracranial electroencephalographic (iEEG) seizure patterns (iESPs) with expert-level accuracy. We developed an intelligent system for identifying the presence and onset time of iESPs in iEEG recordings from the RNS device. METHODS: An iEEG dataset from 24 patients (36 293 recordings) recorded by the RNS System was used for training and evaluating a neural network model (iESPnet). The model was trained to identify the probability of seizure onset at each sample point of the iEEG. The reliability of the net was assessed and compared to baseline methods, including detections made by the device. iESPnet performance was measured using balanced accuracy and the F1 score for iESP detection. The prediction time was assessed via both the error and the mean absolute error. The model was evaluated following a hold-one-out strategy, and then validated in a separate cohort of 26 patients from a different medical center. RESULTS: iESPnet detected the presence of an iESP with a mean accuracy value of 90% and an onset time prediction error of approximately 3.4 s. There was no relationship between electrode location and prediction outcome. Model outputs were well calibrated and unbiased by the RNS detections. Validation on a separate cohort further supported iESPnet applicability in real clinical scenarios. Importantly, RNS device detections were found to be less accurate and delayed in nonresponders; therefore, tools to improve the accuracy of seizure detection are critical for increasing therapeutic efficacy. SIGNIFICANCE: iESPnet is a reliable and accurate tool with the potential to alleviate the time-consuming manual inspection of iESPs and facilitate the evaluation of therapeutic response in RNS-implanted patients.

Implantation accuracy and operative variables in robot-assisted stereoelectroencephalography.

OBJECTIVE: The stereoelectroencephalography (SEEG) procedure provides a unique 3D overview of the seizure-onset zone. Although the success of SEEG relies on the accuracy of depth electrode implantation, few studies have investigated how different implantation techniques and operative variables affect accuracy. This study examined the effect of two different electrode implantation techniques (external vs internal stylet) on implantation accuracy while controlling for other operative variables. METHODS: The implantation accuracy of 508 depth electrodes from 39 SEEG cases was measured after coregistration of postimplantation CT or MR images with planned trajectories. Two different implantation techniques were compared: preset length with internal stylet use and measured length with external stylet use. Correlations between implantation accuracy and technique type, entry angle, intended implantation depth, and other operative variables were determined statistically using multiple regression analysis. RESULTS: Multiple regression analysis showed that the internal stylet technique exhibited a larger target radial error (p = 0.046) and angular deviation (p = 0.039) with a smaller depth error (p < 0.001) than the external stylet technique. Entry angle and implantation depth were positively correlated with target radial error (p = 0.007 and < 0.001, respectively) only for the internal stylet technique. CONCLUSIONS: Better target radial accuracy was achieved when an external stylet was used to open the intraparenchymal pathway for the depth electrode. In addition, more oblique trajectories were equally accurate to orthogonal ones with the usage of an external stylet, while more oblique trajectories were associated with larger target radial errors with the usage of an internal stylet (without an external stylet).

Broadband aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity.

Information flow in brain networks is reflected in intracerebral local field potential (LFP) measurements that have both periodic and aperiodic components. The 1/fχ broadband aperiodic component of the power spectra has been shown to track arousal level and to correlate with other physiological and pathophysiological states, with consistent patterns across cortical regions. Previous studies have focused almost exclusively on cortical neurophysiology. Here we explored the aperiodic activity of subcortical nuclei from the human thalamus and basal ganglia, in relation to simultaneously recorded cortical activity. We elaborated on the FOOOF (fitting of one over f) method by creating a new parameterization of the aperiodic component with independent and more easily interpretable parameters, which allows seamlessly fitting spectra with and without an aperiodic knee, a component of the signal that reflects the dominant timescale of aperiodic fluctuations. First, we found that the aperiodic exponent from sensorimotor cortex in Parkinson's disease (PD) patients correlated with disease severity. Second, although the aperiodic knee frequency changed across cortical regions as previously reported, no aperiodic knee was detected from subcortical regions across movement disorders patients, including the ventral thalamus (VIM), globus pallidus internus (GPi) and subthalamic nucleus (STN). All subcortical region studied exhibited a relatively low aperiodic exponent (χSTN=1.3±0.2, χVIM=1.4±0.1, χGPi =1.4±0.1) that differed markedly from cortical values (χCortex=3.2±0.4, fkCortex=17±5 Hz). These differences were replicated in a second dataset from epilepsy patients undergoing intracranial monitoring that included thalamic recordings. The consistently lower aperiodic exponent and lack of an aperiodic knee from all subcortical recordings may reflect cytoarchitectonic and/or functional differences between subcortical nuclei and the cortex.

Interictal SEEG Resting-State Connectivity Localizes the Seizure Onset Zone and Predicts Seizure Outcome.

Localization of epileptogenic zone currently requires prolonged intracranial recordings to capture seizure, which may take days to weeks. The authors developed a novel method to identify the seizure onset zone (SOZ) and predict seizure outcome using short-time resting-state stereotacticelectroencephalography (SEEG) data. In a cohort of 27 drug-resistant epilepsy patients, the authors estimated the information flow via directional connectivity and inferred the excitation-inhibition ratio from the 1/f power slope. They hypothesized that the antagonism of information flow at multiple frequencies between SOZ and non-SOZ underlying the relatively stable epilepsy resting state could be related to the disrupted excitation-inhibition balance. They found flatter 1/f power slope in non-SOZ regions compared to the SOZ, with dominant information flow from non-SOZ to SOZ regions. Greater differences in resting-state information flow between SOZ and non-SOZ regions are associated with favorable seizure outcome. By integrating a balanced random forest model with resting-state connectivity, their method localized the SOZ with an accuracy of 88% and predicted the seizure outcome with an accuracy of 92% using clinically determined SOZ. Overall, this study suggests that brief resting-state SEEG data can significantly facilitate the identification of SOZ and may eventually predict seizure outcomes without requiring long-term ictal recordings.

Responsive neurostimulation of the thalamus improves seizure control in idiopathic generalised epilepsy: initial case series.

OBJECTIVES: Up to 40% of patients with idiopathic generalised epilepsy (IGE) are drug resistant and potentially could benefit from intracranial neuromodulation of the seizure circuit. We present outcomes following 2 years of thalamic-responsive neurostimulation for IGE. METHODS: Four patients with pharmacoresistant epilepsy underwent RNS System implantation in the bilateral centromedian (CM) nucleus region. Electrophysiological data were extracted from the clinical patient data management system and analysed using a specialised platform (BRAINStim). Postoperative visualisation of electrode locations was performed using Lead-DBS. Seizure outcomes were reported using the Engel scale. RESULTS: Patients experienced a 75%-99% reduction in seizure frequency with decreased seizure duration and severity (Engel class IB, IC, IIA and IIIA), as well as significant improvements in quality of life. Outcomes were durable through at least 2 years of therapy. Detection accuracy for all patients overall decreased over successive programming epochs from a mean of 96.5% to 88.3%. Most electrodes used to deliver stimulation were located in the CM (7/10) followed by the posterior dorsal ventral lateral (2/2), posterior ventral posterior lateral (3/4) and posterior ventral ventral lateral (2/3). In all patients, stimulation varied from 0.2 to 2.0 mA and amplitude only increased over successive epochs. The raw percentage of intracranial electroencephalography recordings with stimulations delivered to electrographic seizures was 24.8%, 1.2%, 7.6% and 8.8%. CONCLUSION: Closed-loop stimulation of the CM region may provide significant improvement in seizure control and quality of life for patients with drug-resistant IGE. Optimal detection and stimulation locations and parameters remain an active area of investigation for accelerating and fine-tuning clinical responses.

Barques are generated in posterior hippocampus and phase reverse over lateral posterior hippocampal surface.

OBJECTIVE: To investigate whether barques can be localized across the hippocampal longitudinal axis with sufficient specificity. METHODS: We identified 51 focal epilepsy patients implanted with a minimum of two electrodes - unilateral anterior and posterior - in either hippocampus. We used visual inspection of the intracranial electroencephalogram (iEEG) and 3D brain volume spectrum-based statistical parametric mapping (SPM) to localize barques. RESULTS: In 18/51 patients (35.29%), barques were identified in 22/70 (31.42%) hippocampi. In all hippocampi (100%), barques were present in the posterior hippocampus, while 9 (40.90%) showed concurrent non-independent barque activity anteriorly (P < 0.0001). Statistical parametric mapping confirmed the posterior barque localization, with significant differences in t-values (t(27) = 8.08, P < 0.0001) and z-scores (t(24) = 6.85, P < 0.0001) between anterior and posterior hippocampal barque activity. Posterior lateral extrahippocampal contacts demonstrated phase reversals of positive polarity during barque activity (P = 0.0092, compared to anterior extrahippocampal contacts). CONCLUSIONS: This study highlights the posterior hippocampal predominance of barques. Our findings are concordant with the posterior distribution of the scalp manifestation of barques as "14&6/sec positive spikes". The posterio-lateral hippocampal barque phase reversal can explain the positive polarity of scalp 14&6/sec spikes. SIGNIFICANCE: Understanding the properties of barques is critical for the iEEG interpretation in epilepsy surgery evaluations that include the hippocampus.

Development and Validation of the 5-SENSE Score to Predict Focality of the Seizure-Onset Zone as Assessed by Stereoelectroencephalography.

Importance: Stereoelectroencephalography (SEEG) has become the criterion standard in case of inconclusive noninvasive presurgical epilepsy workup. However, up to 40% of patients are subsequently not offered surgery because the seizure-onset zone is less focal than expected or cannot be identified. Objective: To predict focality of the seizure-onset zone in SEEG, the 5-point 5-SENSE score was developed and validated. Design, Setting, and Participants: This was a monocentric cohort study for score development followed by multicenter validation with patient selection intervals between February 2002 to October 2018 and May 2002 to December 2019. The minimum follow-up period was 1 year. Patients with drug-resistant epilepsy undergoing SEEG at the Montreal Neurological Institute were analyzed to identify a focal seizure-onset zone. Selection criteria were 2 or more seizures in electroencephalography and availability of complete neuropsychological and neuroimaging data sets. For validation, patients from 9 epilepsy centers meeting these criteria were included. Analysis took place between May and July 2021. Main Outcomes and Measures: Based on SEEG, patients were grouped as focal and nonfocal seizure-onset zone. Demographic, clinical, electroencephalography, neuroimaging, and neuropsychology data were analyzed, and a multiple logistic regression model for developing a score to predict SEEG focality was created and validated in an independent sample. Results: A total of 128 patients (57 women [44.5%]; median [range] age, 31 [13-58] years) were analyzed for score development and 207 patients (97 women [46.9%]; median [range] age, 32 [16-70] years) were analyzed for validation. The score comprised the following 5 predictive variables: focal lesion on structural magnetic resonance imaging, absence of bilateral independent spikes in scalp electroencephalography, localizing neuropsychological deficit, strongly localizing semiology, and regional ictal scalp electroencephalography onset. The 5-SENSE score had an optimal mean (SD) probability cutoff for identifying a focal seizure-onset zone of 37.6 (3.5). Area under the curve, specificity, and sensitivity were 0.83, 76.3% (95% CI, 66.7-85.8), and 83.3% (95% CI, 72.30-94.1), respectively. Validation showed 76.0% (95% CI, 67.5-84.0) specificity and 52.3% (95% CI, 43.0-61.5) sensitivity. Conclusions and Relevance: High specificity in score development and validation confirms that the 5-SENSE score predicts patients where SEEG is unlikely to identify a focal seizure-onset zone. It is a simple and useful tool for assisting clinicians to reduce unnecessary invasive diagnostic burden on patients and overutilization of limited health care resources.

Intracranial monitoring contributes to seizure freedom for temporal lobectomy patients with nonconcordant preoperative data.

OBJECTIVE: The question of whether a patient with presumed temporal lobe seizures should proceed directly to temporal lobectomy surgery versus undergo intracranial monitoring arises commonly. We evaluate the effect of intracranial monitoring on seizure outcome in a retrospective cohort of consecutive subjects who specifically underwent an anterior temporal lobectomy (ATL) for refractory temporal lobe epilepsy (TLE). METHODS: We performed a retrospective analysis of 85 patients with focal refractory TLE who underwent ATL following: (a) intracranial monitoring via craniotomy and subdural/depth electrodes (SDE/DE), (b) intracranial monitoring via stereotactic electroencephalography (sEEG), or (c) no intracranial monitoring (direct ATL-dATL). For each subject, the presurgical primary hypothesis for epileptogenic zone localization was characterized as unilateral TLE, unilateral TLE plus (TLE+), or TLE with bilateral/poor lateralization. RESULTS: At one-year and most recent follow-up, Engel Class I and combined I/II outcomes did not differ significantly between the groups. Outcomes were better in the dATL group compared to the intracranial monitoring groups for lesional cases but were similar in nonlesional cases. Those requiring intracranial monitoring for a hypothesis of TLE+had similar outcomes with either intracranial monitoring approach. sEEG was the only approach used in patients with bilateral or poorly lateralized TLE, resulting in 77.8% of patients seizure-free at last follow-up. Importantly, for 85% of patients undergoing SEEG, recommendation for ATL resulted from modifying the primary hypothesis based on iEEG data. SIGNIFICANCE: Our study highlights the value of intracranial monitoring in equalizing seizure outcomes in difficult-to-treat TLE patients undergoing ATL.

Hippocampal spindles and barques are normal intracranial electroencephalographic entities.

OBJECTIVE: To assess whether hippocampal spindles and barques are markers of epileptogenicity. METHODS: Focal epilepsy patients that underwent stereo-electroencephalography implantation with at least one electrode in their hippocampus were selected (n = 75). The occurrence of spindles and barques in the hippocampus was evaluated in each patient. We created pairs of pathologic and pathology-free groups according to two sets of criteria: 1. Non-invasive diagnostic criteria (patients grouped according to focal epilepsy classification). 2. Intracranial neurophysiological criteria (patient's hippocampi grouped according to their seizure onset involvement). RESULTS: Hippocampal spindles and barques appear equally often in both pathologic and pathology-free groups, both for non-invasive (Pspindles = 0.73; Pbarques = 0.46) and intracranial criteria (Pspindles = 0.08; Pbarques = 0.26). In Engel Class I patients, spindles occurred with similar incidence both within the non-invasive (P = 0.67) and the intracranial criteria group (P = 0.20). Barques were significantly more frequent in extra-temporal lobe epilepsy defined by either non-invasive (P = 0.01) or intracranial (P = 0.01) criteria. CONCLUSIONS: Both spindles and barques are normal entities of the hippocampal intracranial electroencephalogram. The presence of barques may also signify lack of epileptogenic properties in the hippocampus. SIGNIFICANCE: Understanding that hippocampal spindles and barques do not reflect epileptogenicity is critical for correct interpretation of epilepsy surgery evaluations and appropriate surgical treatment selection.

Extrapial Hippocampal Resection in Anterior Temporal Lobectomy: Technical Description and Clinical Outcomes in a 62-Patient Case Series.

BACKGROUND: Anterior temporal lobectomy (ATL) is the most effective treatment for drug-resistant mesial temporal lobe epilepsy. Extrapial en bloc hippocampal resection facilitates complete removal of the hippocampus. With increasing use of minimally invasive treatments, considering open resection techniques that optimize the integrity of tissue specimens is important both for obtaining the correct histopathological diagnosis and for further study. OBJECTIVE: To describe the operative strategy and clinical outcomes associated with an extrapial approach to hippocampal resection during ATL. METHODS: A database of epilepsy surgeries performed by a single surgeon between October 2011 and February 2019 was reviewed to identify all patients who underwent ATL using an extrapial approach to hippocampal resection. To reduce confounding variables for outcome analysis, subjects with prior resections, tumors, and cavernous malformations were excluded. Seizure outcomes were classified using the Engel scale. RESULTS: The surgical technique is described and illustrated with intraoperative images. A total of 62 patients met inclusion criteria (31 females) for outcome analysis. Patients with most recent follow-up <3 yr (n = 33) and >3 yr (n = 29) exhibited 79% and 52% class I outcomes, respectively. An infarct was observed on postoperative magnetic resonance imaging in 3 patients (1 asymptomatic and 2 temporarily symptomatic). An en bloc specimen in which the subiculum and all hippocampal subfields were preserved was obtained in each case. Examples of innovative research opportunities resulting from this approach are presented. CONCLUSION: Extrapial resection of the hippocampus can be performed safely with seizure freedom and complication rates at least as good as those reported with the use of subpial techniques.

The sensitivity of ECG contamination to surgical implantation site in brain computer interfaces.

BACKGROUND: Brain sensing devices are approved today for Parkinson's, essential tremor, and epilepsy therapies. Clinical decisions for implants are often influenced by the premise that patients will benefit from using sensing technology. However, artifacts, such as ECG contamination, can render such treatments unreliable. Therefore, clinicians need to understand how surgical decisions may affect artifact probability. OBJECTIVES: Investigate neural signal contamination with ECG activity in sensing enabled neurostimulation systems, and in particular clinical choices such as implant location that impact signal fidelity. METHODS: Electric field modeling and empirical signals from 85 patients were used to investigate the relationship between implant location and ECG contamination. RESULTS: The impact on neural recordings depends on the difference between ECG signal and noise floor of the electrophysiological recording. Empirically, we demonstrate that severe ECG contamination was more than 3.2x higher in left-sided subclavicular implants (48.3%), when compared to right-sided implants (15.3%). Cranial implants did not show ECG contamination. CONCLUSIONS: Given the relative frequency of corrupted neural signals, we conclude that implant location will impact the ability of brain sensing devices to be used for "closed-loop" algorithms. Clinical adjustments such as implant location can significantly affect signal integrity and need consideration.