Development and validation of a nonverbal consensus-based semantic memory paradigm in patients with epilepsy.

OBJECTIVE: Brain areas implicated in semantic memory can be damaged in patients with epilepsy (PWE). However, it is challenging to delineate semantic processing deficits from acoustic, linguistic, and other verbal aspects in current neuropsychological assessments. We developed a new Visual-based Semantic Association Task (ViSAT) to evaluate nonverbal semantic processing in PWE. METHOD: The ViSAT was adapted from similar predecessors (Pyramids & Palm Trees test, PPT; Camels & Cactus Test, CCT) comprised of 100 unique trials using real-life color pictures that avoid demographic, cultural, and other potential confounds. We obtained performance data from 23 PWE participants and 24 control participants (Control), along with crowdsourced normative data from 54 Amazon Mechanical Turk (Mturk) workers. RESULTS: ViSAT reached a consensus >90% in 91.3% of trials compared to 83.6% in PPT and 82.9% in CCT. A deep learning model demonstrated that visual features of the stimulus images (color, shape; i.e., non-semantic) did not influence top answer choices (p = 0.577). The PWE group had lower accuracy than the Control group (p = 0.019). PWE had longer response times than the Control group in general and this was augmented for the semantic processing (trial answer) stage (both p < 0.001). CONCLUSIONS: This study demonstrated performance impairments in PWE that may reflect dysfunction of nonverbal semantic memory circuits, such as seizure onset zones overlapping with key semantic regions (e.g., anterior temporal lobe). The ViSAT paradigm avoids confounds, is repeatable/longitudinal, captures behavioral data, and is open-source, thus we propose it as a strong alternative for clinical and research assessment of nonverbal semantic memory.

Ictal EEG Source Imaging With Supplemental Electrodes.

INTRODUCTION: Noninvasive brain imaging tests play a major role in guiding decision-making and the usage of invasive, costly intracranial electroencephalogram (ICEEG) in the presurgical epilepsy evaluation. This study prospectively examined the concordance in localization between ictal EEG source imaging (ESI) and ICEEG as a reference standard. METHODS: Between August 2014 and April 2019, patients during video monitoring with scalp EEG were screened for those with intractable focal epilepsy believed to be amenable to surgical treatment. Additional 10-10 electrodes (total = 31-38 per patient, "31+") were placed over suspected regions of seizure onset in 104 patients. Of 42 patients requiring ICEEG, 30 (mean age 30, range 19-59) had sufficiently localized subsequent intracranial studies to allow comparison of localization between tests. ESI was performed using realistic forward boundary element models used in dipole and distributed source analyses. RESULTS: At least partial sublobar concordance between ESI and ICEEG solutions was obtained in 97% of cases, with 73% achieving complete agreement. Median Euclidean distances between ESI and ICEEG solutions ranged from 25 to 30 mm (dipole) and 23 to 38 mm (distributed source). The latter was significantly more accurate with 31+ compared with 21 electrodes (P < 0.01). A difference of ≤25 mm was present in two thirds of the cases. No significant difference was found between dipole and distributed source analyses. CONCLUSIONS: A practical method of ictal ESI (nonuniform placement of 31-38 electrodes) yields high accuracy for seizure localization in epilepsy surgery candidates. These results support routine clinical application of ESI in the presurgical evaluation.

Interictal epileptiform discharges contribute to word-finding difficulty in epilepsy through multiple cognitive mechanisms.

OBJECTIVE: Cognitive impairment often impacts quality of life in epilepsy even if seizures are controlled. Word-finding difficulty is particularly prevalent and often attributed to etiological (static, baseline) circuit alterations. We sought to determine whether interictal discharges convey significant superimposed contributions to word-finding difficulty in patients, and if so, through which cognitive mechanism(s). METHODS: Twenty-three patients undergoing intracranial monitoring for drug-resistant epilepsy participated in multiple tasks involving word production (auditory naming, short-term verbal free recall, repetition) to probe word-finding difficulty across different cognitive domains. We compared behavioral performance between trials with versus without interictal discharges across six major brain areas and adjusted for intersubject differences using mixed-effects models. We also evaluated for subjective word-finding difficulties through retrospective chart review. RESULTS: Subjective word-finding difficulty was reported by the majority (79%) of studied patients preoperatively. During intracranial recordings, interictal epileptiform discharges (IEDs) in the medial temporal lobe were associated with long-term lexicosemantic memory impairments as indexed by auditory naming (p = .009), in addition to their established impact on short-term verbal memory as indexed by free recall (p = .004). Interictal discharges involving the lateral temporal cortex and lateral frontal cortex were associated with delayed reaction time in the auditory naming task (p = .016 and p = .018), as well as phonological working memory impairments as indexed by repetition reaction time (p = .002). Effects of IEDs across anatomical regions were strongly dependent on their precise timing within the task. SIGNIFICANCE: IEDs appear to act through multiple cognitive mechanisms to form a convergent basis for the debilitating clinical word-finding difficulty reported by patients with epilepsy. This was particularly notable for medial temporal spikes, which are quite common in adult focal epilepsy. In parallel with the treatment of seizures, the modulation of interictal discharges through emerging pharmacological means and neurostimulation approaches may be an opportunity to help address devastating memory and language impairments in epilepsy.

Clinical Reasoning: A Young Adult With New Seizures and Chapeau de Gendarme.

The evaluation of new seizures is a common clinical query for neurologists. It can be challenging to delineate between the numerous etiologies of new focal or generalized seizures and, if focal, to localize their onset. In this case report, we present a 26-year-old patient with a new onset of stereotyped events concerning for seizures featuring facial grimacing, dystonic left-hand posturing, and convulsions with immediate return to baseline. Throughout the case, we highlight a stepwise diagnostic approach to the evaluation of new-onset seizures, discuss clues that seizure semiology can provide for localization of ictal onset, and review a novel and atypical presentation of a disease entity frequently encountered by neurologists.

Intact speech perception after resection of dominant hemisphere primary auditory cortex for the treatment of medically refractory epilepsy: illustrative case.

BACKGROUND: In classic speech network models, the primary auditory cortex is the source of auditory input to Wernicke's area in the posterior superior temporal gyrus (pSTG). Because resection of the primary auditory cortex in the dominant hemisphere removes inputs to the pSTG, there is a risk of speech impairment. However, recent research has shown the existence of other, nonprimary auditory cortex inputs to the pSTG, potentially reducing the risk of primary auditory cortex resection in the dominant hemisphere. OBSERVATIONS: Here, the authors present a clinical case of a woman with severe medically refractory epilepsy with a lesional epileptic focus in the left (dominant) Heschl's gyrus. Analysis of neural responses to speech stimuli was consistent with primary auditory cortex localization to Heschl's gyrus. Although the primary auditory cortex was within the proposed resection margins, she underwent lesionectomy with total resection of Heschl's gyrus. Postoperatively, she had no speech deficits and her seizures were fully controlled. LESSONS: While resection of the dominant hemisphere Heschl's gyrus/primary auditory cortex warrants caution, this case illustrates the ability to resect the primary auditory cortex without speech impairment and supports recent models of multiple parallel inputs to the pSTG.

Bidirectional propagation of low frequency oscillations over the human hippocampal surface.

The hippocampus is diversely interconnected with other brain systems along its axis. Cycles of theta-frequency activity are believed to propagate from the septal to temporal pole, yet it is unclear how this one-way route supports the flexible cognitive capacities of this structure. We leveraged novel thin-film microgrid arrays conformed to the human hippocampal surface to track neural activity two-dimensionally in vivo. All oscillation frequencies identified between 1-15 Hz propagated across the tissue. Moreover, they dynamically shifted between two roughly opposite directions oblique to the long axis. This predominant propagation axis was mirrored across participants, hemispheres, and consciousness states. Directionality was modulated in a participant who performed a behavioral task, and it could be predicted by wave amplitude topography over the hippocampal surface. Our results show that propagation directions may thus represent distinct meso-scale network computations, operating along versatile spatiotemporal processing routes across the hippocampal body.

Measuring synchrony in bio-medical timeseries.

Paroxysms are sudden, unpredictable, short-lived events that abound in physiological processes and pathological disorders, from cellular functions (e.g., hormone secretion and neuronal firing) to life-threatening attacks (e.g., cardiac arrhythmia, epileptic seizures, and diabetic ketoacidosis). With the increasing use of personal chronic monitoring (e.g., electrocardiography, electroencephalography, and glucose monitors), the discovery of cycles in health and disease, and the emerging possibility of forecasting paroxysms, the need for suitable methods to evaluate synchrony-or phase-clustering-between events and related underlying physiological fluctuations is pressing. Here, based on examples in epilepsy, where seizures occur preferentially in certain brain states, we characterize different methods that evaluate synchrony in a controlled timeseries simulation framework. First, we compare two methods for extracting the phase of event occurrence and deriving the phase-locking value, a measure of synchrony: (M1) fitting cycles of fixed period-length vs (M2) deriving continuous cycles from a biomarker. In our simulations, M2 provides stronger evidence for cycles. Second, by systematically testing the sensitivity of both methods to non-stationarity in the underlying cycle, we show that M2 is more robust. Third, we characterize errors in circular statistics applied to timeseries with different degrees of temporal clustering and tested with different strategies: Rayleigh test, Poisson simulations, and surrogate timeseries. Using epilepsy data from 21 human subjects, we show the superiority of testing against surrogate time-series to minimize false positives and false negatives, especially when used in combination with M1. In conclusion, we show that only time frequency analysis of continuous recordings of a related bio-marker reveals the full extent of cyclical behavior in events. Identifying and forecasting cycles in biomedical timeseries will benefit from recordings using emerging wearable and implantable devices, so long as conclusions are based on conservative statistical testing.

Accuracy of omni-planar and surface casting of epileptiform activity for intracranial seizure localization.

OBJECTIVE: Intracranial electroencephalography (ICEEG) recordings are performed for seizure localization in medically refractory epilepsy. Signal quantifications such as frequency power can be projected as heatmaps on personalized three-dimensional (3D) reconstructed cortical surfaces to distill these complex recordings into intuitive cinematic visualizations. However, simultaneously reconciling deep recording locations and reliably tracking evolving ictal patterns remain significant challenges. METHODS: We fused oblique magnetic resonance imaging (MRI) slices along depth probe trajectories with cortical surface reconstructions and projected dynamic heatmaps using a simple mathematical metric of epileptiform activity (line-length). This omni-planar and surface casting of epileptiform activity approach (OPSCEA) thus illustrated seizure onset and spread among both deep and superficial locations simultaneously with minimal need for signal processing supervision. We utilized the approach on 41 patients at our center implanted with grid, strip, and/or depth electrodes for localizing medically refractory seizures. Peri-ictal data were converted into OPSCEA videos with multiple 3D brain views illustrating all electrode locations. Five people of varying expertise in epilepsy (medical student through epilepsy attending level) attempted to localize the seizure-onset zones. RESULTS: We retrospectively compared this approach with the original ICEEG study reports for validation. Accuracy ranged from 73.2% to 97.6% for complete or overlapping onset lobe(s), respectively, and ~56.1% to 95.1% for the specific focus (or foci). Higher answer certainty for a given case predicted better accuracy, and scorers had similar accuracy across different training levels. SIGNIFICANCE: In an era of increasing stereo-EEG use, cinematic visualizations fusing omni-planar and surface functional projections appear to provide a useful adjunct for interpreting complex intracranial recordings and subsequent surgery planning.

Early seizure spread and epilepsy surgery: A systematic review.

OBJECTIVE: A fundamental question in epilepsy surgery is how to delineate the margins of cortex that must be resected to result in seizure freedom. Whether and which areas showing seizure activity early in ictus must be removed to avoid postoperative recurrence of seizures is an area of ongoing research. Seizure spread dynamics in the initial seconds of ictus are often correlated with postoperative outcome; there is neither a consensus definition of early spread nor a concise summary of the existing literature linking seizure spread to postsurgical seizure outcomes. The present study is intended to summarize the literature that links seizure spread to postoperative seizure outcome and to provide a framework for quantitative assessment of early seizure spread. METHODS: A systematic review was carried out according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A Medline search identified clinical studies reporting data on seizure spread measured by intracranial electrodes, having at least 10 subjects and reporting at least 1-year postoperative outcome in the English literature from 1990 to 2019. Studies were evaluated regarding support for a primary hypothesis: Areas of early seizure spread represent cortex with seizure-generating potential. RESULTS: The search yielded 4562 studies: 15 studies met inclusion criteria and 7 studies supported the primary hypothesis. The methods and metrics used to describe seizure spread were heterogenous. The timeframe of seizure spread associated with seizure outcome ranged from 1-14 seconds, with large, well-designed, retrospective studies pointing to 3-10 seconds as most likely to provide meaningful correlates of postoperative seizure freedom. SIGNIFICANCE: The complex correlation between electrophysiologic seizure spread and the potential for seizure generation needs further elucidation. Prospective cohort studies or trials are needed to evaluate epilepsy surgery targeting cortex involved in the first 3-10 seconds of ictus.

Interictal Epileptiform Discharges and the Quality of Human Intracranial Neurophysiology Data.

Intracranial electroencephalography (IEEG) involves recording from electrodes placed directly onto the cortical surface or deep brain locations. It is performed on patients with medically refractory epilepsy, undergoing pre-surgical seizure localization. IEEG recordings, combined with advancements in computational capacity and analysis tools, have accelerated cognitive neuroscience. This Perspective describes a potential pitfall latent in many of these recordings by virtue of the subject population-namely interictal epileptiform discharges (IEDs), which can cause spurious results due to the contamination of normal neurophysiological signals by pathological waveforms related to epilepsy. We first discuss the nature of IED hazards, and why they deserve the attention of neurophysiology researchers. We then describe four general strategies used when handling IEDs (manual identification, automated identification, manual-automated hybrids, and ignoring by leaving them in the data), and discuss their pros, cons, and contextual factors. Finally, we describe current practices of human neurophysiology researchers worldwide based on a cross-sectional literature review and a voluntary survey. We put these results in the context of the listed strategies and make suggestions on improving awareness and clarity of reporting to enrich both data quality and communication in the field.

Prospective validation study of an epilepsy seizure risk system for outpatient evaluation.

OBJECTIVE: We conducted clinical testing of an automated Bayesian machine learning algorithm (Epilepsy Seizure Assessment Tool [EpiSAT]) for outpatient seizure risk assessment using seizure counting data, and validated performance against specialized epilepsy clinician experts. METHODS: We conducted a prospective longitudinal study of EpiSAT performance against 24 specialized clinician experts at three tertiary referral epilepsy centers in the United States. Accuracy, interrater reliability, and intra-rater reliability of EpiSAT for correctly identifying changes in seizure risk (improvements, worsening, or no change) were evaluated using 120 seizures from four synthetic seizure diaries (seizure risk known) and 120 seizures from four real seizure diaries (seizure risk unknown). The proportion of observed agreement between EpiSAT and clinicians was evaluated to assess compatibility of EpiSAT with clinical decision patterns by epilepsy experts. RESULTS: EpiSAT exhibited substantial observed agreement (75.4%) with clinicians for assessing seizure risk. The mean accuracy of epilepsy providers for correctly assessing seizure risk was 74.7%. EpiSAT accurately identified seizure risk in 87.5% of seizure diary entries, corresponding to a significant improvement of 17.4% (P = .002). Clinicians exhibited low-to-moderate interrater reliability for seizure risk assessment (Krippendorff's α = 0.46) with good intrarater reliability across a 4- to 12-week evaluation period (Scott's π = 0.89). SIGNIFICANCE: These results validate the ability of EpiSAT to yield objective clinical recommendations on seizure risk which follow decision patterns similar to those from specialized epilepsy providers, but with improved accuracy and reproducibility. This algorithm may serve as a useful clinical decision support system for quantitative analysis of clinical seizure frequency in clinical epilepsy practice.

Multi-day rhythms modulate seizure risk in epilepsy.

Epilepsy is defined by the seemingly random occurrence of spontaneous seizures. The ability to anticipate seizures would enable preventative treatment strategies. A central but unresolved question concerns the relationship of seizure timing to fluctuating rates of interictal epileptiform discharges (here termed interictal epileptiform activity, IEA), a marker of brain irritability observed between seizures by electroencephalography (EEG). Here, in 37 subjects with an implanted brain stimulation device that detects IEA and seizures over years, we find that IEA oscillates with circadian and subject-specific multidien (multi-day) periods. Multidien periodicities, most commonly 20-30 days in duration, are robust and relatively stable for up to 10 years in men and women. We show that seizures occur preferentially during the rising phase of multidien IEA rhythms. Combining phase information from circadian and multidien IEA rhythms provides a novel biomarker for determining relative seizure risk with a large effect size in most subjects.

Unsupervised Learning of Spatiotemporal Interictal Discharges in Focal Epilepsy.

BACKGROUND: Interictal epileptiform discharges are an important biomarker for localization of focal epilepsy, especially in patients who undergo chronic intracranial monitoring. Manual detection of these pathophysiological events is cumbersome, but is still superior to current rule-based approaches in most automated algorithms. OBJECTIVE: To develop an unsupervised machine-learning algorithm for the improved, automated detection and localization of interictal epileptiform discharges based on spatiotemporal pattern recognition. METHODS: We decomposed 24 h of intracranial electroencephalography signals into basis functions and activation vectors using non-negative matrix factorization (NNMF). Thresholding the activation vector and the basis function of interest detected interictal epileptiform discharges in time and space (specific electrodes), respectively. We used convolutive NNMF, a refined algorithm, to add a temporal dimension to basis functions. RESULTS: The receiver operating characteristics for NNMF-based detection are close to the gold standard of human visual-based detection and superior to currently available alternative automated approaches (93% sensitivity and 97% specificity). The algorithm successfully identified thousands of interictal epileptiform discharges across a full day of neurophysiological recording and accurately summarized their localization into a single map. Adding a temporal window allowed for visualization of the archetypal propagation network of these epileptiform discharges. CONCLUSION: Unsupervised learning offers a powerful approach towards automated identification of recurrent pathological neurophysiological signals, which may have important implications for precise, quantitative, and individualized evaluation of focal epilepsy.

Chronic ambulatory electrocorticography from human speech cortex.

Direct intracranial recording of human brain activity is an important approach for deciphering neural mechanisms of cognition. Such recordings, usually made in patients with epilepsy undergoing inpatient monitoring for seizure localization, are limited in duration and depend on patients' tolerance for the challenges associated with recovering from brain surgery. Thus, typical intracranial recordings, similar to most non-invasive approaches in humans, provide snapshots of brain activity in acute, highly constrained settings, limiting opportunities to understand long timescale and natural, real-world phenomena. A new device for treating some forms of drug-resistant epilepsy, the NeuroPace RNS® System, includes a cranially-implanted neurostimulator and intracranial electrodes that continuously monitor brain activity and respond to incipient seizures with electrical counterstimulation. The RNS System can record epileptic brain activity over years, but whether it can record meaningful, behavior-related physiological responses has not been demonstrated. Here, in a human subject with electrodes implanted over high-level speech-auditory cortex (Wernicke's area; posterior superior temporal gyrus), we report that cortical evoked responses to spoken sentences are robust, selective to phonetic features, and stable over nearly 1.5 years. In a second subject with RNS System electrodes implanted over frontal cortex (Broca's area, posterior inferior frontal gyrus), we found that word production during a naming task reliably evokes cortical responses preceding speech onset. The spatiotemporal resolution, high signal-to-noise, and wireless nature of this system's intracranial recordings make it a powerful new approach to investigate the neural correlates of human cognition over long timescales in natural ambulatory settings.

Injection Therapy for Headache and Facial Pain.

Peripheral nerve blocks are an increasingly viable treatment option for selected groups of headache patients, particularly those with intractable headache or facial pain. Greater occipital nerve block, the most widely used local anesthetic procedure in headache conditions, is particularly effective, safe, and easy to perform in the office. Adverse effects are few and infrequent. These procedures can result in rapid relief of pain and allodynia, and effects last for several weeks or months. Use of nerve block procedures and potentially onabotulinum toxin therapy should be expanded for patients with intractable headache disorders who may benefit, although more studies are needed for efficacy and clinical safety.

Oscillation Phase Locking and Late ERP Components of Intracranial Hippocampal Recordings Correlate to Patient Performance in a Working Memory Task.

In working memory tasks, stimulus presentation induces a resetting of intracranial temporal lobe oscillations in multiple frequency bands. To further understand the functional relevance of this phenomenon, we investigated whether working memory performance depends on the phase precision of ongoing oscillations in the hippocampus. We recorded intra-hippocampal local field potentials in individuals performing a working memory task. Two types of trials were administered. For high memory trials presentation of a list of four letters ("List") was followed by a single letter memory probe ("Test"). Low memory load trials, consisting of four identical letters (AAAA) followed by a probe with the same letter (A), were interspersed. Significant phase locking of ongoing oscillations across trials, estimated by the Pairwise Phase Consistency Index (PPCI) was observed in delta (0.5-4 Hz), theta (5-7 Hz), and alpha (8-12 Hz) bands during stimulus presentation and recall but was increased in low memory load trials. Across patients however, higher delta PPCIs during recall in the left hippocampus were associated with faster reaction times. Because phase locking could also be interpreted as a consequence of a stimulus evoked potential, we performed event related potential analysis (ERP) and examined the relationship of ERP components with performance. We found that both amplitude and latency of late ERP components correlated with both reaction time and accuracy. We propose that, in the Sternberg task, phase locking of oscillations, or alternatively its ERP correlate, synchronizes networks within the hippocampus and connected structures that are involved in working memory.