Neuronal Spiking Responses to Direct Electrical Microstimulation in the Human Cortex.

Microstimulation can modulate the activity of individual neurons 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 heterogeneous. Here we use microelectrode arrays in the human anterior temporal lobe in 6 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 remain poorly understood. This study examines the spiking responses of neurons in the human temporal cortex in response to pulses of microstimulation. This study finds 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.

Characterization of seizures and EEG findings in creatine transporter deficiency due to SLC6A8 mutation.

Seizures occur in up to 59% of boys with creatine transporter deficiency (CTD). While seizure phenotypes have been previously described, electroencephalogram (EEG) findings have only been reported in several case reports. In this prospective observational study, we report seizure characteristics and EEG findings in combination with neurobehavioral and SLC6A8 pathogenic variants in twenty males with CTD. Eighteen study participants (SP) underwent video-EEG, and seven had follow-up EEG recordings. Seizures typically occurred by age of 2 years. Thirteen (65%) had non-febrile seizures, requiring anti-seizure medications in nine. Four had febrile seizures. Seizures were bilateral tonic-clonic in 7 SP and focal impaired awareness in 5 SP; often responding to 1 to 2 antiseizure medications. EEG showed slowing in 5 SP, beta activity in 6 SP, and focal/multifocal, and/or generalized epileptiform activity in 9 SP. Follow-up EEGs in 7 SP showed emergence of epileptiform activity in 1 SP, and increased activity in 2 SP. In conclusion, seizures were frequent in our cohort but tended to respond to antiseizure medications. Longitudinal follow up provided further insight into emergence of seizures and EEG abnormalities soliciting future studies with long term follow up. Biomarkers of epileptogenicity in CTD are needed to predict seizures in this population.

Sleep physiology in patients with epilepsy: Influence of seizures on rapid eye movement (REM) latency and REM duration.

OBJECTIVE: A well-established bidirectional relationship exists between sleep and epilepsy. Patients with epilepsy tend to have less efficient sleep and shorter rapid eye movement (REM) sleep. Seizures are far more likely to arise from sleep transitions and non-REM sleep compared to REM sleep. Delay in REM onset or reduction in REM duration may have reciprocal interactions with seizure occurrence. Greater insight into the relationship between REM sleep and seizure occurrence is essential to our understanding of circadian patterns and predictability of seizure activity. We assessed a cohort of adults undergoing evaluation of drug-resistant epilepsy to examine whether REM sleep prior to or following seizures is delayed in latency or reduced in quantity. METHODS: We used a spectrogram-guided approach to review the video-electroencephalograms of patients' epilepsy monitoring unit admissions for sleep scoring to determine sleep variables. RESULTS: In our cohort of patients, we found group- and individual-level delay of REM latency and reduced REM duration when patients experienced a seizure before the primary sleep period (PSP) of interest or during the PSP of interest. A significant increase in REM latency and decrease in REM quantity were observed on nights where a seizure occurred within 4 h of sleep onset. No change in REM variables was found when investigating seizures that occurred the day after the PSP of interest. Our study is the first to provide insight about a perisleep period, which we defined as 4-h periods before and after the PSP. SIGNIFICANCE: Our results demonstrate a significant relationship between seizures occurring prior to the PSP, during the PSP, and in the 4-h perisleep period and a delay in REM latency. These findings have implications for developing a biomarker of seizure detection as well as longer term seizure risk monitoring.

Interictal discharges in the human brain are travelling waves arising from an epileptogenic source.

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.

Identifying sources of human interictal discharges with travelling wave and white matter propagation.

Interictal epileptiform discharges have been shown to propagate from focal epileptogenic sources as travelling waves or through more rapid white matter conduction. We hypothesize that both modes of propagation are necessary to explain interictal discharge timing delays. We propose a method that, for the first time, incorporates both propagation modes to identify unique potential sources of interictal activity. We retrospectively analysed 38 focal epilepsy patients who underwent intracranial EEG recordings and diffusion-weighted imaging for epilepsy surgery evaluation. Interictal discharges were detected and localized to the most likely source based on relative delays in time of arrival across electrodes, incorporating travelling waves and white matter propagation. We assessed the influence of white matter propagation on distance of spread, timing and clinical interpretation of interictal activity. To evaluate accuracy, we compared our source localization results to earliest spiking regions to predict seizure outcomes. White matter propagation helps to explain the timing delays observed in interictal discharge sequences, underlying rapid and distant propagation. Sources identified based on differences in time of receipt of interictal discharges are often distinct from the leading electrode location. Receipt of activity propagating rapidly via white matter can occur earlier than more local activity propagating via slower cortical travelling waves. In our cohort, our source localization approach was more accurate in predicting seizure outcomes than the leading electrode location. Inclusion of white matter in addition to travelling wave propagation in our model of discharge spread did not improve overall accuracy but allowed for identification of unique and at times distant potential sources of activity, particularly in patients with persistent postoperative seizures. Since distant white matter propagation can occur more rapidly than local travelling wave propagation, combined modes of propagation within an interictal discharge sequence can decouple the commonly assumed relationship between spike timing and distance from the source. Our findings thus highlight the clinical importance of recognizing the presence of dual modes of propagation during interictal discharges, as this may be a cause of clinical mislocalization.

Genomic analysis, immunomodulation and deep phenotyping of patients with nodding syndrome.

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.

Source-sink connectivity: a novel interictal EEG marker for seizure localization.

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.

Travelling waves reveal a dynamic seizure source in human focal epilepsy.

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.

Seizure phenotype in CLN3 disease and its relation to other neurologic outcome measures.

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.

Language lateralization from task-based and resting state functional MRI in patients with epilepsy.

We compared resting state (RS) functional connectivity and task-based fMRI to lateralize language dominance in 30 epilepsy patients (mean age = 33; SD = 11; 12 female), a measure used for presurgical planning. Language laterality index (LI) was calculated from task fMRI in frontal, temporal, and frontal + temporal regional masks using LI bootstrap method from SPM12. RS language LI was assessed using two novel methods of calculating RS language LI from bilateral Broca's area seed based connectivity maps across regional masks and multiple thresholds (p < .05, p < .01, p < .001, top 10% connections). We compared LI from task and RS fMRI continuous values and dominance classifications. We found significant positive correlations between task LI and RS LI when functional connectivity thresholds were set to the top 10% of connections. Concordance of dominance classifications ranged from 20% to 30% for the intrahemispheric resting state LI method and 50% to 63% for the resting state LI intra- minus interhemispheric difference method. Approximately 40% of patients left dominant on task showed RS bilateral dominance. There was no difference in LI concordance between patients with right-sided and left-sided resections. Early seizure onset (<6 years old) was not associated with atypical language dominance during task-based or RS fMRI. While a relationship between task LI and RS LI exists in patients with epilepsy, language dominance is less lateralized on RS than task fMRI. Concordance of language dominance classifications between task and resting state fMRI depends on brain regions surveyed and RS LI calculation method.

EEG abnormalities in patients with chronic neuronopathic Gaucher disease: A retrospective review.

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.

Signal Complexity of Human Intracranial EEG Tracks Successful Associative-Memory Formation across Individuals.

Memory performance is highly variable among individuals. Most studies examining human memory, however, have largely focused on the neural correlates of successful memory formation within individuals, rather than the differences among them. As such, what gives rise to this variability is poorly understood. Here, we examined intracranial EEG (iEEG) recordings captured from 43 participants (23 male) implanted with subdural electrodes for seizure monitoring as they performed a paired-associates verbal memory task. We identified three separate but related signatures of neural activity that tracked differences in successful memory formation across individuals. High-performing individuals consistently exhibited less broadband power, flatter power spectral density slopes, and greater complexity in their iEEG signals. Furthermore, within individuals across three separate time scales ranging from seconds to days, successful recall was positively associated with these same metrics. Our data therefore suggest that memory ability across individuals can be indexed by increased neural signal complexity.SIGNIFICANCE STATEMENT We show that participants whose intracranial EEG exhibits less low-frequency power, flatter power spectrums, and greater sample entropy overall are better able to memorize associations, and that the same metrics track fluctuations in memory performance across time within individuals. These metrics together signify greater neural signal complexity, which may index the brain's ability to flexibly engage with information and generate separable memory representations. Critically, the current set of results provides a unique window into the neural markers of individual differences in memory performance, which have hitherto been underexplored.

Neuroinflammation in neocortical epilepsy measured by PET imaging of translocator protein.

OBJECTIVES: Neuroinflammation, implicated in epilepsy, can be imaged in humans with positron emission tomography (PET) ligands for translocator protein 18 kDa (TSPO). Previous studies in patients with temporal lobe epilepsy and mesial temporal sclerosis found increased [11C]PBR28 uptake ipsilateral to seizure foci. Neocortical foci present more difficult localization problems and more variable underlying pathology. METHODS: We studied 11 patients with neocortical seizure foci using [11C]PBR28 or [11C] N,N-diethyl-2-(4-methoxyphenyl)-5,7-dimethylpyrazolo[1,5-a]pyrimidine-3-acetamide (DPA) 713, and 31 healthy volunteers. Seizure foci were identified with structural magnetic resonance imaging (MRI) and ictal video-electroencephalography (EEG) monitoring. Six patients had surgical resections; five had focal cortical dysplasia type 2A or B and one microdysgenesis. Brain regions were delineated using FreeSurfer and T1-weighted MRI. We measured brain radioligand uptake (standardized uptake values [SUVs]) in ipsilateral and contralateral regions, to compare calculated asymmetry indices [AIs; 200% *(ipsilateral - contralateral)/(ipsilateral + contralateral)] between epilepsy patients and controls, as well as absolute [11C]PBR28 binding as the ratio of distribution volume to free fraction (VT /fP ) in 9 patients (5 high affinity and 4 medium affinity binders) and 11 age-matched volunteers (5 high-affinity and 6 medium affinity) who had metabolite-corrected arterial input functions measured. RESULTS: Nine of 11 patients had AIs exceeding control mean 95% confidence intervals in at least one region consistent with the seizure focus. Three of the nine had normal MRI. There was a nonsignificant trend for patients to have higher binding than volunteers both ipsilateral and contralateral to the focus in the group that had absolute binding measured. SIGNIFICANCE: Our study demonstrates the presence of focal and distributed inflammation in neocortical epilepsy. There may be a role for TSPO PET for evaluation of patients with suspected neocortical seizure foci, particularly when other imaging modalities are unrevealing. However, a complex method, inherent variability, and increased binding in regions outside seizure foci will limit applicability.

Functional MRI and direct cortical stimulation: Prediction of postoperative language decline.

OBJECTIVE: To assess the ability of functional MRI (fMRI) to predict postoperative language decline compared to direct cortical stimulation (DCS) in epilepsy surgery patients. METHODS: In this prospective case series, 17 patients with drug-resistant epilepsy had intracranial monitoring and resection from 2012 to 2016 with 1-year follow-up. All patients completed preoperative language fMRI, mapping with DCS of subdural electrodes, pre- and postoperative neuropsychological testing for language function, and resection. Changes in language function before and after surgery were assessed. fMRI activation and DCS electrodes in the resection were evaluated as potential predictors of language decline. RESULTS: Four of 17 patients (12 female; median [range] age, 43 [23-59] years) experienced postoperative language decline 1 year after surgery. Two of 4 patients had overlap of fMRI activation, language-positive electrodes in basal temporal regions (within 1 cm), and resection. Two had overlap between resection volume and fMRI activation, but not DCS. fMRI demonstrated 100% sensitivity and 46% specificity for outcome compared to DCS (50% and 85%, respectively). When fMRI and DCS language findings were concordant, the combined tests showed 100% sensitivity and 75% specificity for language outcome. Seizure-onset age, resection side, type, volume, or 1 year seizure outcome did not predict language decline. SIGNIFICANCE: Language localization overlap of fMRI and direct cortical stimulation in the resection influences postoperative language performance. Our preliminary study suggests that fMRI may be more sensitive and less specific than direct cortical stimulation. Together they may predict outcome better than either test alone.

fMRI prediction of naming change after adult temporal lobe epilepsy surgery: Activation matters.

OBJECTIVE: We aimed to predict language deficits after epilepsy surgery. In addition to evaluating surgical factors examined previously, we determined the impact of the extent of functional magnetic resonance imaging (fMRI) activation that was resected on naming ability. METHOD: Thirty-five adults (mean age 37.5 ± 10.9 years, 13 male) with temporal lobe epilepsy completed a preoperative fMRI auditory description decision task, which reliably activates frontal and temporal language networks. Patients underwent temporal lobe resections (20 left resection). The Boston Naming Test (BNT) was used to determine language functioning before and after surgery. Language dominance was determined for Broca and Wernicke area (WA) by calculating a laterality index following statistical parametric mapping processing. We used an innovative method to generate anatomic resection masks automatically from pre- and postoperative MRI tissue map comparison. This mask provided the following: (a) resection volume; (b) overlap between resection and preoperative activation; and (c) overlap between resection and WA. We examined postoperative language change predictors using stepwise linear regression. Predictors included parameters described above as well as age at seizure onset (ASO), preoperative BNT score, and resection side and its relationship to language dominance. RESULTS: Seven of 35 adults had significant naming decline (6 dominant-side resections). The final regression model predicted 38% of the naming score change variance (adjusted r2  = 0.28, P = 0.012). The percentage of top 10% fMRI activation resected (P = 0.017) was the most significant contributor. Other factors in the model included WA LI, ASO, volume of WA resected, and WA LI absolute value (extent of laterality). SIGNIFICANCE: Resection of fMRI activation during a word-definition decision task is an important factor for postoperative change in naming ability, along with other previously reported predictors. Currently, many centers establish language dominance using fMRI. Our results suggest that the amount of the top 10% of language fMRI activation in the intended resection area provides additional predictive power and should be considered when planning surgical resection.

Cued Memory Retrieval Exhibits Reinstatement of High Gamma Power on a Faster Timescale in the Left Temporal Lobe and Prefrontal Cortex.

Converging evidence suggests that reinstatement of neural activity underlies our ability to successfully retrieve memories. However, the temporal dynamics of reinstatement in the human cortex remain poorly understood. One possibility is that neural activity during memory retrieval, like replay of spiking neurons in the hippocampus, occurs at a faster timescale than during encoding. We tested this hypothesis in 34 participants who performed a verbal episodic memory task while we recorded high gamma (62-100 Hz) activity from subdural electrodes implanted for seizure monitoring. We show that reinstatement of distributed patterns of high gamma activity occurs faster than during encoding. Using a time-warping algorithm, we quantify the timescale of the reinstatement and identify brain regions that show significant timescale differences between encoding and retrieval. Our data suggest that temporally compressed reinstatement of cortical activity is a feature of cued memory retrieval.SIGNIFICANCE STATEMENT We show that cued memory retrieval reinstates neural activity on a faster timescale than was present during encoding. Our data therefore provide a link between reinstatement of neural activity in the cortex and spontaneous replay of cortical and hippocampal spiking activity, which also exhibits temporal compression, and suggest that temporal compression may be a universal feature of memory retrieval.

Surface based electrode localization and standardized regions of interest for intracranial EEG.

Intracranial recordings captured from subdural electrodes in patients with drug resistant epilepsy offer clinicians and researchers a powerful tool for examining neural activity in the human brain with high spatial and temporal precision. There are two major challenges, however, to interpreting these signals both within and across individuals. Anatomical distortions following implantation make accurately identifying the electrode locations difficult. In addition, because each implant involves a unique configuration, comparing neural activity across individuals in a standardized manner has been limited to broad anatomical regions such as cortical lobes or gyri. We address these challenges here by introducing a semi-automated method for localizing subdural electrode contacts to the unique surface anatomy of each individual, and by using a surface-based grid of regions of interest (ROIs) to aggregate electrode data from similar anatomical locations across individuals. Our localization algorithm, which uses only a postoperative CT and preoperative MRI, builds upon previous spring-based optimization approaches by introducing manually identified anchor points directly on the brain surface to constrain the final electrode locations. This algorithm yields an accuracy of 2 mm. Our surface-based ROI approach involves choosing a flexible number of ROIs with different spatial resolutions. ROIs are registered across individuals to represent identical anatomical locations while accounting for the unique curvature of each brain surface. This ROI based approach therefore enables group level statistical testing from spatially precise anatomical regions.

Language functional MRI and direct cortical stimulation in epilepsy preoperative planning.

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.

Stable functional networks exhibit consistent timing in the human brain.

Despite many advances in the study of large-scale human functional networks, the question of timing, stability, and direction of communication between cortical regions has not been fully addressed. At the cellular level, neuronal communication occurs through axons and dendrites, and the time required for such communication is well defined and preserved. At larger spatial scales, however, the relationship between timing, direction, and communication between brain regions is less clear. Here, we use a measure of effective connectivity to identify connections between brain regions that exhibit communication with consistent timing. We hypothesized that if two brain regions are communicating, then knowledge of the activity in one region should allow an external observer to better predict activity in the other region, and that such communication involves a consistent time delay. We examine this question using intracranial electroencephalography captured from nine human participants with medically refractory epilepsy. We use a coupling measure based on time-lagged mutual information to identify effective connections between brain regions that exhibit a statistically significant increase in average mutual information at a consistent time delay. These identified connections result in sparse, directed functional networks that are stable over minutes, hours, and days. Notably, the time delays associated with these connections are also highly preserved over multiple time scales. We characterize the anatomic locations of these connections, and find that the propagation of activity exhibits a preferred posterior to anterior temporal lobe direction, consistent across participants. Moreover, networks constructed from connections that reliably exhibit consistent timing between anatomic regions demonstrate features of a small-world architecture, with many reliable connections between anatomically neighbouring regions and few long range connections. Together, our results demonstrate that cortical regions exhibit functional relationships with well-defined and consistent timing, and the stability of these relationships over multiple time scales suggests that these stable pathways may be reliably and repeatedly used for large-scale cortical communication.