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While seizure activity may be electrographically widespread, increasing evidence has suggested that ictal discharges may in fact represent travelling waves propagated from a focal seizure source. Interictal epileptiform discharges (IEDs) are an electrographic manifestation of excessive hypersynchronization of cortical activity that occur between seizures and are considered a marker of potentially epileptogenic tissue. The precise relationship between brain regions demonstrating IEDs and those involved in seizure onset, however, remains poorly understood. Here, we hypothesize that IEDs likewise reflect the receipt of travelling waves propagated from the same regions which give rise to seizures. Forty patients from our institution who underwent invasive monitoring for epilepsy, proceeded to surgery and had at least one year of follow-up were included in our study. Interictal epileptiform discharges were detected using custom software, validated by a clinical epileptologist. We show that IEDs reach electrodes in sequences with a consistent temporal ordering, and this ordering matches the timing of receipt of ictal discharges, suggesting that both types of discharges spread as travelling waves. We use a novel approach for localization of ictal discharges, in which time differences of discharge receipt at nearby electrodes are used to compute source location; similar algorithms have been used in acoustics and geophysics. We find that interictal discharges co-localize with ictal discharges. Moreover, interictal discharges tend to localize to the resection territory in patients with good surgical outcome and outside of the resection territory in patients with poor outcome. The seizure source may originate at, and also travel to, spatially distinct IED foci. Our data provide evidence that interictal discharges may represent travelling waves of pathological activity that are similar to their ictal counterparts, and that both ictal and interictal discharges emerge from common epileptogenic brain regions. Our findings have important clinical implications, as they suggest that seizure source localizations may be derived from interictal discharges, which are much more frequent than seizures.

This scientific commentary refers to ‘Thalamostriatal disconnection underpins long-term seizure freedom in frontal lobe epilepsy surgery’ by Giampiccolo et al. (https://doi.org/10.1093/brain/awad085).

The aetiology of nodding syndrome remains unclear, and comprehensive genotyping and phenotyping data from patients remain sparse. Our objectives were to characterize the phenotype of patients with nodding syndrome, investigate potential contributors to disease aetiology, and evaluate response to immunotherapy. This cohort study investigated members of a single-family unit from Lamwo District, Uganda. The participants for this study were selected by the Ugandan Ministry of Health as representative for nodding syndrome and with a conducive family structure for genomic analyses. Of the eight family members who participated in the study at the National Institutes of Health (NIH) Clinical Center, three had nodding syndrome. The three affected patients were extensively evaluated with metagenomic sequencing for infectious pathogens, exome sequencing, spinal fluid immune analyses, neurometabolic and toxicology testing, continuous electroencephalography and neuroimaging. Five unaffected family members underwent a subset of testing for comparison. A distinctive interictal pattern of sleep-activated bursts of generalized and multifocal epileptiform discharges and slowing was observed in two patients. Brain imaging showed two patients had mild generalized cerebral atrophy, and both patients and unaffected family members had excessive metal deposition in the basal ganglia. Trace metal biochemical evaluation was normal. CSF was non-inflammatory and one patient had CSF-restricted oligoclonal bands. Onchocerca volvulus-specific antibodies were present in all patients and skin snips were negative for active onchocerciasis. Metagenomic sequencing of serum and CSF revealed hepatitis B virus in the serum of one patient. Vitamin B6 metabolites were borderline low in all family members and CSF pyridoxine metabolites were normal. Mitochondrial DNA testing was normal. Exome sequencing did not identify potentially causal candidate gene variants. Nodding syndrome is characterized by a distinctive pattern of sleep-activated epileptiform activity. The associated growth stunting may be due to hypothalamic dysfunction. Extensive testing years after disease onset did not clarify a causal aetiology. A trial of immunomodulation (plasmapheresis in two patients and intravenous immunoglobulin in one patient) was given without short-term effect, but longer-term follow-up was not possible to fully assess any benefit of this intervention.

Background Uncontrolled seizures in patients with gliomas have a significant impact on quality of life and morbidity, yet the mechanisms through which these tumors cause seizures remain unknown. Here, we hypothesize that the active metabolite d-2-hydroxyglutarate (d-2-HG) produced by the IDH-mutant enzyme leads to metabolic disruptions in surrounding cortical neurons that consequently promote seizures. Methods We use a complementary study of in vitro neuron-glial cultures and electrographically sorted human cortical tissue from patients with IDH-mutant gliomas to test this hypothesis. We utilize micro-electrode arrays for in vitro electrophysiological studies in combination with pharmacological manipulations and biochemical studies to better elucidate the impact of d-2-HG on cortical metabolism and neuronal spiking activity. Results We demonstrate that d-2-HG leads to increased neuronal spiking activity and promotes a distinct metabolic profile in surrounding neurons, evidenced by distinct metabolomic shifts and increased LDHA expression, as well as upregulation of mTOR signaling. The increases in neuronal activity are induced by mTOR activation and reversed with mTOR inhibition. Conclusion Together, our data suggest that metabolic disruptions in the surrounding cortex due to d-2-HG may be a driving event for epileptogenesis in patients with IDH-mutant gliomas.

Recent studies suggest that changes in neuronal metabolism are associated with epilepsy. High rates of ATP depletion, lactate dehydrogenase A and lactate production have all been found in epilepsy patients, animal and tissue culture models. As such, it can be hypothesized that chronic seizures lead to continuing elevations in neuronal energy demand which may lead to an adapted metabolic response and elevations of lactate dehydrogenase A. In this study, we examine elevations in the lactate dehydrogenase A protein as a long-term cellular adaptation to elevated metabolic demand from chronic neuronal activation. We investigate this cellular adaptation in human tissue samples and explore the mechanisms of lactate dehydrogenase A upregulation using cultured neurones treated with low Mg2+, a manipulation that leads to NMDA-mediated neuronal activation. We demonstrate that human epileptic tissue preferentially upregulates neuronal lactate dehydrogenase A, and that in neuronal cultures chronic and repeated elevations in neural activity lead to upregulation of neuronal lactate dehydrogenase A. Similar to states of hypoxia, this metabolic change occurs through the AMP-activated protein kinase/hypoxia-inducible factor-1α pathway. Our data therefore reveal a novel long-term bioenergetic adaptation that occurs in chronically activated neurones and provide a basis for understanding the interplay between metabolism and neural activity during epilepsy.

We investigated the association between human herpesvirus 6 (HHV‐6) and mesial temporal sclerosis (MTS) in 87 patients who had surgery for drug‐resistant epilepsy. Fifty‐four had MTS, 22 focal cortical dysplasia (FCD), four tumors, three vascular malformations, and three a history of encephalitis. We extracted DNA from fresh brain tissue immediately after surgery and performed viral detection with quantitative real‐time polymerase chain reaction (PCR) or digital droplet PCR specific for HHV‐6A and HHV‐6B. Tissue was studied with standard clinical techniques, including hematoxylin and eosin, glial fibrillary acidic protein, and NeuN stains. Twenty‐nine of 54 patients with MTS, six of 23 with focal cortical dysplasia (FCD), and one of three with a history of encephalitis were positive for HHV‐6 (P

Treatment of patients with drug-resistant focal epilepsy relies upon accurate seizure localization. Ictal activity captured by intracranial EEG has traditionally been interpreted to suggest that the underlying cortex is actively involved in seizures. Here, we hypothesize that such activity instead reflects propagated activity from a relatively focal seizure source, even during later time points when ictal activity is more widespread. We used the time differences observed between ictal discharges in adjacent electrodes to estimate the location of the hypothesized focal source and demonstrated that the seizure source, localized in this manner, closely matches the clinically and neurophysiologically determined brain region giving rise to seizures. Moreover, we determined this focal source to be a dynamic entity that moves and evolves over the time course of a seizure. Our results offer an interpretation of ictal activity observed by intracranial EEG that challenges the traditional conceptualization of the seizure source.

CLN3 disease is a pediatric neurodegenerative condition wherein seizures are common. The most common disease-causing variant is an ~1-kb deletion in CLN3. We investigated seizure phenotype in relation to genotype and to adaptive behavior, MR spectroscopy and CSF biochemical markers in a CLN3 cohort. We performed seizure phenotyping using clinical history, EEG, and the Unified Batten Disease Rating Scale (UBDRS) seizure score. We assessed correlations of seizure severity with disease severity (UBDRS capability), adaptive behavior composite score (ABC; Vineland-3), glutamate+glutamine+GABA and N-acetylaspartate+N-acetylaspartyl glutamate (MR spectroscopy), and CSF neurofilament light chain (NEFL) levels. In 20 participants, median age was 10.7 years (IQR = 7.8). Eighteen completed baseline EEG; 12 had a 1-year follow-up. Seizures were reported in 14 (8 1-kb deletion homozygotes), with median age at onset of 10.0 (IQR = 6.8). Epileptiform discharges were noted in 15 (9 homozygotes). Bilateral tonic clonic (n = 11) and nonmotor seizures (n = 7) were most common. UBDRS seizure score correlated with age (rp = 0.50; [0.08,0.77]; P = .02), UBDRS capability (rp = -0.57; [-0.81,-0.17]; P = .009) and ABC (rp = -0.66; [-0.85,-0.31]; P = .001) scores, glutamate+glutamine+GABA (rp = -0.54; [-0.80,-0.11]; P = .02) and N-acetylaspartate+N-acetylaspartyl glutamate (rp = -0.54; [-0.80,-0.11]; P = .02), and CSF NEFL (rp = 0.65; [0.29,0.85]; P = .002) levels. After controlling for age, correlations with ABC and CSF NEFL remained significant. In our CLN3 cohort, seizures and epileptiform discharges were frequent and often started by age 10 years without significant difference between genotypes. ABC and CSF NEFL correlate with UBDRS seizure score, reflecting the role of seizures in the neurodegenerative process. Longitudinal evaluations in a larger cohort are needed to confirm these findings.

The clinical phenotype of Gaucher disease type 3 (GD3), a neuronopathic lysosomal storage disorder, encompasses a wide array of neurological manifestations including neuro-ophthalmological findings, developmental delay, and seizures including progressive myoclonic epilepsy. Electroencephalography (EEG) is a widely available tool used to identify abnormalities in cerebral function, as well as epileptiform abnormalities indicating an increased risk of seizures. We characterized the EEG findings in GD3, reviewing 67 patients with 293 EEGs collected over nearly 50 years. Over 93% of patients had some form of EEG abnormality, most consisting of background slowing (90%), followed by interictal epileptiform discharges (IEDs) (54%), and photoparoxysmal responses (25%). The seven patients without background slowing were all under age 14 (mean 6.7 years). There was a history of seizures in 37% of this cohort; only 30% of these had IEDs on EEG. Conversely, only 56% of patients with IEDs had a history of seizures. These observed EEG abnormalities document an important aspect of the natural history of GD3 and could potentially assist in identifying neurological involvement in a patient with subtle clinical findings. Additionally, this comprehensive description of longitudinal EEG data provides essential baseline data for understanding central nervous system involvement in neuronopathic GD.

Despite large individual differences in memory performance, people remember certain stimuli with overwhelming consistency. This phenomenon is referred to as the memorability of an individual item. However, it remains unknown whether memorability also affects our ability to retrieve associations between items. Here, using a paired-associates verbal memory task, we combine behavioural data, computational modelling and direct recordings from the human brain to examine how memorability influences associative memory retrieval. We find that certain words are correctly retrieved across participants irrespective of the cues used to initiate memory retrieval. These words, which share greater semantic similarity with other words, are more readily available during retrieval and lead to more intrusions when retrieval fails. Successful retrieval of these memorable items, relative to less memorable ones, results in faster reinstatement of neural activity in the anterior temporal lobe. Collectively, our data reveal how the brain prioritizes certain information to facilitate memory retrieval. Xie et al. combine evidence from behavioural data, computational modelling and intracranial electroencephalogram methods to show that the human brain prioritizes certain information to facilitate associative memory retrieval.

Human brain activity during memory Animal studies suggest that sequence replay of neuronal activity may underlie memory retrieval and consolidation. However, there is no direct evidence that the replay of spiking activity sequences is important for these processes in the human brain. Vaz et al. simultaneously recorded single-unit spikes, local field potential, and intracranial electroencephalography signals in the brain while participants performed a memory task. Sharp wave ripple oscillations in the temporal lobe cortex reflected bursts of neural spiking, and these bursts of spikes organized into sequences during memory formation. These sequences were replayed during successful memory retrieval. The extent of sequence replay during correct recall was related to the extent to which cortical spiking activity was coupled with ripples in the medial temporal lobe. Science , this issue p. 1131

Object repetition commonly leads to long-lasting improvements in identification speed and accuracy, a behavioral facilitation referred to as “repetition priming”. Neuroimaging and non-invasive electromagnetic stimulation studies have most often implicated the involvement of left lateral frontal cortex in repetition priming, although convergent evidence from neuropsychological studies is lacking. In the current study, we examine the impact of surgical resection for the treatment of epilepsy on the magnitude of repetition priming at relatively short-term (30–60 minute delay) and long-term (3 months) delays in 41 patients with varying seizure foci and resection locations. Overall, patients exhibited significant repetition priming at both short-term and long-term delays. However, patients with frontal resections (largely anterior and medial frontal) differed significantly from those with right anterior temporal resections in showing fully intact short-term priming but absent long-term priming. In a comparison set of 10 recovered aphasic patients, patients with left lateral frontal damage exhibited impaired short-term priming relative to other frontal damage locations, suggesting the differential involvement of lateral and anteromedial frontal regions in mediating repetition priming at short-lag and long-lag timescales, respectively.

Microstimulation can modulate the activity of individual neurons in order to affect behavior, but the effects of stimulation on neuronal spiking are complex and remain poorly understood. This is especially challenging in the human brain where the response properties of individual neurons are sparse and heterogenous. Here we use micro- electrode array (MEAs) in the human anterior temporal lobe in six participants (3 female) to examine the spiking responses of individual neurons to microstimulation delivered through multiple distinct stimulation sites. We demonstrate that individual neurons can be driven with excitation or inhibition using different stimulation sites, which suggests an approach for providing direct control of spiking activity at the single neuron level. Spiking responses are inhibitory in neurons that are close to the site of stimulation, while excitatory responses are more spatially distributed. Together, our data demonstrate that spiking responses of individual neurons can be reliably identified and manipulated in the human cortex.SIGNIFICANCE STATEMENT:One of the major limitations in our ability to interface directly with the human brain is that the effects of stimulation on the activity of individual neurons remains poorly understood. Here, Youssef et al. examine the spiking responses of neurons in the human temporal cortex in response to pulses of microstimulation. They find that individual neurons can either be excited or inhibited depending on the site of stimulation. These data suggest an approach for modulating the spiking activity of individual neurons in the human brain.

The sensory cortices of many mammals are often organized into modules in the form of cortical columns, yet whether modular organization at this spatial scale is a general property of the human neocortex is unknown. The strongest evidence for modularity arises when measures of connectivity, structure, and function converge. Here we use microelectrode recordings in humans to examine functional connectivity and neuronal spiking responses in order to assess modularity in submillimeter scale networks. We find that the human temporal lobe consists of temporally persistent spatially compact modules approximately 1.3mm in diameter. Functionally, the information coded by single neurons during an image categorization task is more similar for neurons belonging to the same module than for neurons from different modules. The geometry, connectivity, and spiking responses of these local cortical networks provide converging evidence that the human temporal lobe is organized into functional modules at the micro scale.

Direct brain recordings have provided important insights into how high-frequency activity captured through intracranial EEG (iEEG) supports human memory retrieval. The extent to which such activity is comprised of transient fluctuations that reflect the dynamic coordination of underlying neurons, however, remains unclear. Here, we simultaneously record iEEG, local field potential (LFP), and single unit activity in the human temporal cortex. We demonstrate that fast oscillations within the previously identified 80–120 Hz ripple band contribute to broadband high-frequency activity in the human cortex. These ripple oscillations exhibit a spectrum of amplitudes and durations related to the amount of underlying neuronal spiking. Ripples in the macro-scale iEEG are related to the number and synchrony of ripples in the micro-scale LFP, which in turn are related to the synchrony of neuronal spiking. Our data suggest that neural activity in the human temporal lobe is organized into transient bouts of ripple oscillations that reflect underlying bursts of spiking activity.

Over 15 million epilepsy patients worldwide have drug-resistant epilepsy. Successful surgery is a standard of care treatment but can only be achieved through complete resection or disconnection of the epileptogenic zone, the brain region(s) where seizures originate. Surgical success rates vary between 20% and 80%, because no clinically validated biological markers of the epileptogenic zone exist. Localizing the epileptogenic zone is a costly and time-consuming process, which often requires days to weeks of intracranial EEG (iEEG) monitoring. Clinicians visually inspect iEEG data to identify abnormal activity on individual channels occurring immediately before seizures or spikes that occur interictally (i.e. between seizures). In the end, the clinical standard mainly relies on a small proportion of the iEEG data captured to assist in epileptogenic zone localization (minutes of seizure data versus days of recordings), missing opportunities to leverage these largely ignored interictal data to better diagnose and treat patients. IEEG offers a unique opportunity to observe epileptic cortical network dynamics but waiting for seizures increases patient risks associated with invasive monitoring. In this study, we aimed to leverage interictal iEEG data by developing a new network-based interictal iEEG marker of the epileptogenic zone. We hypothesized that when a patient is not clinically seizing, it is because the epileptogenic zone is inhibited by other regions. We developed an algorithm that identifies two groups of nodes from the interictal iEEG network: those that are continuously inhibiting a set of neighbouring nodes (‘sources’) and the inhibited nodes themselves (‘sinks’). Specifically, patient-specific dynamical network models were estimated from minutes of iEEG and their connectivity properties revealed top sources and sinks in the network, with each node being quantified by source-sink metrics. We validated the algorithm in a retrospective analysis of 65 patients. The source-sink metrics identified epileptogenic regions with 73% accuracy and clinicians agreed with the algorithm in 93% of seizure-free patients. The algorithm was further validated by using the metrics of the annotated epileptogenic zone to predict surgical outcomes. The source-sink metrics predicted outcomes with an accuracy of 79% compared to an accuracy of 43% for clinicians’ predictions (surgical success rate of this dataset). In failed outcomes, we identified brain regions with high metrics that were untreated. When compared with high frequency oscillations, the most commonly proposed interictal iEEG feature for epileptogenic zone localization, source-sink metrics outperformed in predictive power (by a factor of 1.2), suggesting they may be an interictal iEEG fingerprint of the epileptogenic zone.

Objective Due to variability in the patterns of propagation of interictal epileptiform discharges (IEDs), qualitative definition of the irritative zone has been challenging. Here, we introduce a quantitative approach toward exploration of the dynamics of IED propagation within the irritative zone. Methods We examined intracranial EEG (iEEG) in nine participants undergoing invasive monitoring for seizure localization. We used an automated IED detector and a community detection algorithm to identify populations of electrodes exhibiting IED activity that co-occur in time, and to group these electrodes into communities. Results Within our algorithmically-identified communities, IED activity in the seizure onset zone (SOZ) tended to lead IED activity in other functionally coupled brain regions. The tendency of pathological activity to arise in the SOZ, and to spread to non-SOZ tissues, was greater in the asleep state. Conclusions IED activity, and, by extension, the variability observed between the asleep and awake states, is propagated from a core seizure focus to nearby less pathological brain regions. Significance Using an unsupervised, computational approach, we show that the spread of IED activity through the epilepsy network varies with physiologic state.

Coupled ripples in memory Short-lived, high-frequency oscillations in the brain called ripples have been implicated as substrates for memory formation. There is, however, little evidence linking ripple activity with awake memory retrieval in humans. Vaz et al. analyzed intracranial recordings in human subjects (see the Perspective by Gelinas). They found that ripple oscillations in the brain's medial temporal lobe were coupled with ripple oscillations in the temporal cortex. This coupling was enhanced just before successful memory retrieval. During successful retrievals with ripples, patterns of oscillations were recapitulated across multiple electrodes, consistent with the initial encoding. The observation that ripple oscillations occur before successful memory retrieval suggests that they may play a mechanistic role in the retrieval process. Science , this issue p. 975 ; see also p. 927

Epilepsy is a global epidemic and 30% of the 60 million patients do not respond to medication treatment. The only treatment options for patients with medically refractory epilepsy are surgical removal or electrical stimulation of the epileptogenic zone (EZ) i.e. the source of their seizures. Despite extensive evaluations with neuroimaging, visual EEG analysis and clinical testing, surgical success rates vary between 30-70%. Currently, no computational methods have been translated into the clinic to assist in localizing the EZ. Here, we applied a dynamical network model that quantifies the fragility of nodes within a patient9s intracranial EEG (iEEG) brain network. Fragility is quantified as the minimal amount of perturbation that must to be applied to a node9s influence on a "balanced" network to cause imbalance. Here, a balanced network is one in which the connectivity between excitatory and inhibitory nodes render a stable system, and an imbalanced network is unstable and hence can generate seizures. Using iEEG data from 91 patients treated across 5 epilepsy centers (44 successes, 47 failures), we demonstrated that nodal fragility is greater in electrodes within the EZ. In addition, we compared fragility of iEEG nodes to 7 frequency-based and 14 graph theoretic features of the EZ in both seizure (n=91) and non-seizure data (n=54). We calculated a confidence statistic, defined as the ratio of the value of a given feature averaged across electrodes in the clinically annotated seizure onset zone to its average across all other electrodes. Fragility has a significantly greater effect size difference between surgical outcomes when compared to other features. This novel feature, outperformed the most popular iEEG features when comparing across surgical outcomes, possibly defining a superior network-based EEG fingerprint for the EZ.

We examined safety, tolerability, and efficacy of SGS-742, a γ-aminobutyric acid B (GABA-B) receptor antagonist, in patients with succinic semialdehyde dehydrogenase deficiency. This was a single-center randomized, double-blind crossover phase II clinical trial of SGS-742 versus placebo in patients with succinic semialdehyde dehydrogenase deficiency. Procedures included transcranial magnetic stimulation and the Adaptive Behavior Assessment Scale. Nineteen subjects were consented and enrolled; the mean age was 14.0 ± 7.5 years and 11 (58%) were female. We did not find a significant effect of SGS-742 on the Adaptive Behavior Assessment Scale score, motor threshold, and paired-pulse stimulation. The difference in recruitment curve slopes between treatment groups was 0.003 ( P = .09). There was no significant difference in incidence of adverse effects between drug and placebo arms. SGS-742 failed to produce improved cognition and normalization of cortical excitability as measured by the Adaptive Behavior Assessment Scale and transcranial magnetic stimulation. Our data do not support the current use of SGS-742 in succinic semialdehyde dehydrogenase deficiency. Trial registry number NCT02019667. Phase 2 Clinical Trial of SGS-742 Therapy in Succinic Semialdehyde Dehydrogenase Deficiency. https://clinicaltrials.gov/ct2/show/NCT02019667

Direct brain recordings have provided important insights into how persistent oscillatory activity support human memory retrieval, but the extent to which transient fluctuations in intracranial EEG (iEEG) captures the dynamic coordination of underlying neurons involved in memory processing remains unclear. Here, we simultaneously record iEEG, local field potential (LFP), and single unit activity in the human temporal cortex. We demonstrate that cortical ripples contribute to broadband high frequency activity and exhibit a spectrum of amplitudes and durations related to the amount of underlying neuronal spiking. Ripples in the macro-scale iEEG are related to the number and synchrony of ripples in the micro-scale LFP, which in turn are related to the synchrony of neuronal spiking. Our data suggest that neural activity in the human cortex is organized into dynamic, discrete packets of information.

Highlights • Multiscale image filters provide a good representation of local cortical appearance. • Most FCD lesions and some normal cortical regions appear as outliers in our model. • FCDs appear similar to the anterior insula and some paralimbic cortical regions. • Our constrained outlier detection approach allows for automated FCD detection., Objective Focal cortical dysplasias (FCDs) are a common cause of apparently non-lesional drug-resistant focal epilepsy. Visual detection of subtle FCDs on MRI is clinically important and often challenging. In this study, we implement a set of 3D local image filters adapted from computer vision applications to characterize the appearance of normal cortex surrounding the gray-white junction. We create a normative model to serve as the basis for a novel multivariate constrained outlier approach to automated FCD detection. Methods Standardized MPRAGE, T2 and FLAIR MR images were obtained in 15 patients with radiologically or histologically diagnosed FCDs and 30 healthy volunteers. Multiscale 3D local image filters were computed for each MR contrast then sampled onto the gray-white junction surface. Using an iterative Gaussianization procedure, we created a normative model of cortical variability in healthy volunteers, allowing for identification of outlier regions and estimates of similarity in normal cortex and FCD lesions. We used a constrained outlier approach following local normalization to automatically detect FCD lesions based on projection onto the mean FCD feature vector. Results FCDs as well as some normal cortical regions such as primary sensorimotor and paralimbic regions appear as outliers. Regions such as the paralimbic regions and the anterior insula have similar features to FCDs. Our constrained outlier approach allows for automated FCD detection with 80% sensitivity and 70% specificity. Significance A normative model using multiscale local image filters can be used to describe the normal cortical variability. Although FCDs appear similar to some cortical regions such as the anterior insula and paralimbic cortices, they can be identified using a constrained outlier detection approach. Our method for detecting outliers and estimating similarity is generic and could be extended to identification of other types of lesions or atypical cortical areas.

Our memories enable us to form expectations for our future experiences, yet the precise neural mechanisms underlying how we compare any experience to our memory remain unknown. Here, using intracranial EEG recordings, we show that episodic memories formed after a single visual experience establish expectations for future experience within neocortical-medial temporal lobe circuits. When subsequent experiences violate these expectations, we find a 80–120 Hz prediction error signal that emerges in both visual association areas and the medial temporal lobe. Critically, this error signal emerges in visual association areas first and then propagates to the medial temporal lobe. This error signal is accompanied by alpha coherence between the two regions. Our data therefore suggest that internal models formed from episodic memories are generated throughout the visual hierarchy after just a single exposure, and that these internal models are then used for comparison with future experiences., Haque et al. demonstrate that the episodic memory of a single visual scene is sufficient for humans to recognize if a visual scene has subsequently changed. A prediction error signal first arises in the visual association cortex when individuals recognize these changes.

Carefully selected patients with drug-resistant epilepsy may be candidates for resective surgery. Neuroimaging, including positron emission tomography (PET), magnetic resonance imaging (MRI), and ictal single-photon emission computed tomography (SPECT), are important clinical tools for presurgical seizure focus localization. MRI is an essential part of evaluation for patients with epilepsy. Structural studies may show focal abnormalities such as mesial temporal sclerosis or focal cortical dysplasia, which are the pathological substrates of seizure initiation. Functional localization data from arterial spin labeling for cerebral blood flow and spike-triggered or resting-state signal acquisition are potentially valuable as well. PET and SPECT usually only are performed for patients being considered for surgery. PET may show decreased interictal glucose metabolism in the epileptogenic zone. PET may also contribute to understanding the pathophysiology of epilepsy through the use of ligands for neurotransmitter receptors and neuroinflammation. Reduced benzodiazepine receptor binding may have occasional clinical relevance. Ictal SPECT may show increased blood flow if the tracer is injected soon after seizure onset, particularly if an interictal scan is subtracted and the image co-registered with structural MRI. When interpreting imaging in epilepsy, it is important to consider the clinical context, ictal semiology, and electrographic studies.

Photosensitive epilepsy is the most common subset of reflex epilepsy in humans. It is characterized by an abnormal electroencephalogram trait known as photoparoxysmal response (PPR) corresponding to ictal symptomology in response to intermittent photic stimulation. Increased exposure to photic stimulation through technological and societal advance has had a significant impact on the incidence and interest in photosensitive epilepsy. Paralleled scientific developments have deepened our understanding of the neurophysiology underlying photosensitivity, especially in the context of deep genomic sequencing and neuroimaging. Furthermore, given the relatively predictable nature of photosensitive epilepsy, there is substantial interest in translating advancements in this field to epilepsy as a whole. Herein, we comprehensively review the epidemiology, clinical features and novel insights into the mechanism behind photosensitive epilepsy with a focus on the clinical implications of new advancements.

Traveling waves of oscillatory activity are thought to influence neuronal spiking, providing a spatiotemporal frame-work for neural communication. However, no direct link has been established between traveling waves and neuronal spiking in humans. We examined traveling waves in the human lateral temporal lobe by using recordings from intracranial electrodes implanted in twenty participants for seizure monitoring as they performed a paired-associates verbal memory task. We observed ubiquitous low frequency traveling waves across the temporal lobe. While wave occurrence in a broad low frequency range did not differ between successful and unsuccessful memory conditions, in a subset of participants with microelectrode recordings, we found that macro-scale waves co-occurred with micro-scale waves, which in turn were temporally locked to single unit spiking. This temporal coordination between traveling waves at different spatial scales and between waves and neuronal spiking in the human brain suggests a role for traveling waves in neural communication.

Summary The epilepsy surgery database from 1984 to 2012 at the National Institutes of Health (NIH) was reviewed to determine the association of postoperative electroencephalography (EEG) with seizure recurrence. Eighty‐three patients were analyzed, with 41 having at least 5 years of follow‐up. The relationship between epileptiform postoperative EEG findings and seizure recurrence at 1, 2, and 5 years was not significant, despite a significant decrease in abnormal EEG recordings after surgery. Clinicians use a variety of tools to predict seizure recurrence following epilepsy surgery to guide medication management and to modulate patient expectations. EEG is but one tool for assessing the likelihood of seizure recurrence following epilepsy surgery.

Objective Presurgical language assessment can help minimize damage to eloquent cortex during resective epilepsy surgery. Two methods for presurgical language mapping are functional MRI (fMRI) and direct cortical stimulation (DCS) of implanted subdural electrodes. We compared fMRI results to DCS to help optimize noninvasive language localization and assess its validity. Methods We studied 19 patients referred for presurgical evaluation of drug-resistant epilepsy. Patients completed four language tasks during preoperative fMRI. After subdural electrode implantation, we used DCS to localize language areas. For each stimulation site, we determined whether language positive electrode pairs intersected with significant fMRI activity clusters for language tasks. Results Sensitivity and specificity depended on electrode region of interest radii and statistical thresholding. For patients with at least one language positive stimulation site, an auditory description decision task provided the best trade-off between sensitivity and specificity. For patients with no language positive stimulation sites, fMRI was a dependable method of excluding eloquent language processing. Interpretation Language fMRI is an effective tool for determining language lateralization before electrode implantation and is especially useful for excluding unexpected critical language areas. It can help guide subdural electrode implantation and narrow the search for eloquent cortical areas by DCS. Ann Neurol 2017;81:526-537.

Electrical brain stimulation is used clinically to target pathological regions of the brain for treatment of diseases, such as Parkinson’s disease, epilepsy and depression. Conventional treatments involve chronic implants that disrupt activity through a fixed periodic train of pulses or bursts of pulses applied to the affected region. However, stimulating one region of the brain necessarily affects other structurally and/or functionally connected areas. Understanding how connected regions of the brain are affected by stimulation at the implant site could improve treatment efficacy by informing optimal placement and stimulation patterns. In this study, we build predictive input-output models from intracranial recordings obtained from 10 epilepsy patients implanted with electrodes. Specific contacts within each subject were electrically stimulated (inputs), and evoked responses were simultaneously captured from all contacts (outputs). From these data, we constructed and compared four different dynamical models that contain causal linear and nonlinear components. All model architectures successfully predicted evoked responses to stimulation with single pulses and sequences of pulses. Results suggest that a linear time-invariant model in series with a quadratic non-linearity best captures the relationship between stimulation amplitudes and evoked responses.