Decision and response monitoring during working memory are sequentially represented in the human insula.

Emerging research supports a role of the insula in human cognition. Here, we used intracranial EEG to investigate the spatiotemporal dynamics in the insula during a verbal working memory (vWM) task. We found robust effects for theta, beta, and high frequency activity (HFA) during probe presentation requiring a decision. Theta band activity showed differential involvement across left and right insulae while sequential HFA modulations were observed along the anteroposterior axis. HFA in anterior insula tracked decision making and subsequent HFA was observed in posterior insula after the behavioral response. Our results provide electrophysiological evidence of engagement of different insula subregions in both decision-making and response monitoring during vWM and expand our knowledge of the role of the insula in complex human behavior.

Inter-site generalizability of EEG based age prediction algorithms in the preterm infant.

Objective. To overcome the effects of site differences in EEG-based brain age prediction in preterm infants.Approach. We used a 'bag of features' with a combination function estimated using support vector regression (SVR) and feature selection (filter then wrapper) to predict post-menstrual age (PMA). The SVR was trained on a dataset containing 138 EEG recordings from 37 preterm infants (site 1). A separate set of 36 EEG recordings from 36 preterm infants was used to validate the age predictor (site 2). The feature distributions were compared between sites and a restricted feature set was constructed using only features that were not significantly different between sites. The mean absolute error between predicted age and PMA was used to define the accuracy of prediction and successful validation was defined as no significant differences in error between site 1 (cross-validation) and site 2.Main results. The age predictor based on all features and trained on site 1 was not validated on site 2 (p< 0.001; MAE site 1 = 1.0 weeks,n= 59 versus MAE site 2 = 2.1 weeks,n= 36). The MAE was improved by training on a restricted features set (MAE site 1 = 1.0 weeks,n= 59 versus MAE site 2 = 1.1 weeks,n= 36), resulting in a validated age predictor when applied to site 2 (p= 0.68). The features selected from the restricted feature set when training on site 1 closely aligned with features selected when trained on a combination of data from site 1 and site 2.Significance. The ability of EEG classifiers, such as brain age prediction, to maintain accuracy on data collected at other sites may be challenged by unexpected, site-dependent differences in EEG signals. Permitting a small amount of data leakage between sites improves generalization, leading towards universal methods of EEG interpretation in preterm infants.

Subspace partitioning in the human prefrontal cortex resolves cognitive interference.

The human prefrontal cortex (PFC) constitutes the structural basis underlying flexible cognitive control, where mixed-selective neural populations encode multiple task features to guide subsequent behavior. The mechanisms by which the brain simultaneously encodes multiple task-relevant variables while minimizing interference from task-irrelevant features remain unknown. Leveraging intracranial recordings from the human PFC, we first demonstrate that competition between coexisting representations of past and present task variables incurs a behavioral switch cost. Our results reveal that this interference between past and present states in the PFC is resolved through coding partitioning into distinct low-dimensional neural states; thereby strongly attenuating behavioral switch costs. In sum, these findings uncover a fundamental coding mechanism that constitutes a central building block of flexible cognitive control.

Whole-exome sequencing in moyamoya patients of Northern-European origin identifies gene variants involved in Nitric Oxide metabolism: A pilot study.

Introduction: Moyamoya disease (MMD) is a chronic cerebrovascular steno-occlusive disease of largely unknown etiology. Variants in the RNF213 gene are strongly associated with MMD in East-Asia. In MMD patients of Northern-European origin, no predominant susceptibility variants have been identified so far. Research question: Are there specific candidate genes associated with MMD of Northern-European origin, including the known RNF213 gene? Can we establish a hypothesis for MMD phenotype and associated genetic variants identified for further research? Material and methods: Adult patients of Northern-European origin, treated surgically for MMD at Oslo University Hospital between October 2018 to January 2019 were asked to participate. WES was performed, with subsequent bioinformatic analysis and variant filtering. The selected candidate genes were either previously reported in MMD or known to be involved in angiogenesis. The variant filtering was based on variant type, location, population frequency, and predicted impact on protein function. Results: Analysis of WES data revealed nine variants of interest in eight genes. Five of those encode proteins involved in nitric oxide (NO) metabolism: NOS3, NR4A3, ITGAV, GRB7 and AGXT2. In the AGXT2 gene, a de novo variant was detected, not previously described in MMD. None harboured the p.R4810K missense variant in the RNF213 gene known to be associated with MMD in East-Asian patients. Discussion and conclusion: Our findings suggest a role for NO regulation pathways in Northern-European MMD and introduce AGXT2 as a new susceptibility gene. This pilot study warrants replication in larger patient cohorts and further functional investigations.

Combining MRI and Spectral EEG for Assessment of Neurocognitive Outcomes in Preterm Infants.

INTRODUCTION: Predicting impairment in preterm children is challenging. Our aim is to explore the association between MRI at term-equivalent age (TEA) and neurocognitive outcomes in late childhood and to assess whether the addition of EEG improves prognostication. METHODS: This prospective observational study included forty infants with gestational age 24 + 0-30 + 6. Children were monitored with multichannel EEG for 72 h after birth. Total absolute band power for the delta band on day 2 was calculated. Brain MRI was performed at TEA and scored according to the Kidokoro scoring system. At 10-12 years of age, we evaluated neurocognitive outcomes with Wechsler Intelligence Scale for Children 4th edition, Vineland adaptive behavior scales 2nd edition and Behavior Rating Inventory of Executive Function. We performed linear regression analysis to examine the association between outcomes and MRI and EEG, respectively, and multiple regression analysis to explore the combination of MRI and EEG. RESULTS: Forty infants were included. There was a significant association between global brain abnormality score and composite outcomes of WISC and Vineland test, but not the BRIEF test. The adjusted R2 was 0.16 and 0.08, respectively. For EEG, adjusted R2 was 0.34 and 0.15, respectively. When combining MRI and EEG data, adjusted R2 changed to 0.36 for WISC and 0.16 for the Vineland test. CONCLUSION: There was a small association between TEA MRI and neurocognitive outcomes in late childhood. Adding EEG to the model improved the explained variance. Combining EEG and MRI data did not have any additional benefit over EEG alone.

Orbitofrontal cortex governs working memory for temporal order.

How do we think about time? Converging lesion and neuroimaging evidence indicates that orbitofrontal cortex (OFC) supports the encoding and retrieval of temporal context in long-term memory1, which may contribute to confabulation in individuals with OFC damage2. Here, we reveal that OFC damage diminishes working memory for temporal order, that is, the ability to disentangle the relative recency of events as they unfold. OFC lesions reduced working memory for temporal order but not spatial position, and individual deficits were commensurate with lesion size. Comparable effects were absent in patients with lesions restricted to lateral prefrontal cortex (PFC). Based on these findings, we propose that OFC supports understanding of the order of events. Well-documented behavioral changes in individuals with OFC damage2 may relate to impaired temporal-order understanding.

Early spectral EEG in preterm infants correlates with neurocognitive outcomes in late childhood.

BACKGROUND: Evidence regarding the predictive value of early amplitude-integrated electroencephalography (aEEG)/EEG on neurodevelopmental outcomes at school age and beyond is lacking. We  aimed to investigate whether there is an association between early postnatal EEG and neurocognitive outcomes in late childhood. METHODS: This study is an observational prospective cohort study of premature infants with a gestational age <28 weeks. The total absolute band powers (tABP) of the delta, theta, alpha, and beta bands were analyzed from EEG recordings during the first three days of life. At 10-12 years of age, neurocognitive outcomes were assessed using the Wechsler Intelligence Scale for Children 4th edition (WISC-IV), Vineland adaptive behavior scales 2nd edition, and Behavior Rating Inventory of Executive Function (BRIEF). The mean differences in tABP were assessed for individuals with normal versus unfavorable neurocognitive scores. RESULTS: Twenty-two infants were included. tABP values in all four frequency bands were significantly lower in infants with unfavorable results in the main composite scores (full intelligence quotient, adaptive behavior composite score, and global executive composite score) on all three tests (p < 0.05). CONCLUSIONS: Early postnatal EEG has the potential to assist in predicting cognitive outcomes at 10-12 years of age in extremely premature infants <28 weeks' gestation. IMPACT: Evidence regarding the value of early postnatal EEG in long-term prognostication in preterm infants is limited. Our study suggests that early EEG spectral analysis correlates with neurocognitive outcomes in late childhood in extremely preterm infants. Early identification of infants at-risk of later impairment is important to initiate early and targeted follow-up and intervention.

Intracranial Recordings Demonstrate Both Cortical and Medial Temporal Lobe Engagement in Visual Search in Humans.

Visual search is a fundamental human behavior, providing a gateway to understanding other sensory domains as well as the role of search in higher-order cognition. Search has been proposed to include two component processes: inefficient search (Search) and efficient search (Pop-out). According to extant research, these two processes map onto two separable neural systems located in the frontal and parietal association cortices. In this study, we use intracranial recordings from 23 participants to delineate the neural correlates of Search and Pop-out with an unprecedented combination of spatiotemporal resolution and coverage across cortical and subcortical structures. First, we demonstrate a role for the medial temporal lobe in visual search, on par with engagement in frontal and parietal association cortex. Second, we show a gradient of increasing engagement over anatomical space from dorsal to ventral lateral frontal cortex. Third, we confirm previous intracranial work demonstrating nearly complete overlap in neural engagement across cortical regions in Search and Pop-out. We further demonstrate Pop-out selectivity, manifesting as activity increase in Pop-out as compared to Search, in a distributed set of sites including frontal cortex. This result is at odds with the view that Pop-out is implemented in low-level visual cortex or parietal cortex alone. Finally, we affirm a central role for the right lateral frontal cortex in Search.

Validation of a new approach for distinguishing anesthetized from awake state in patients using directed transfer function applied to raw EEG.

We test whether a measure based on the directed transfer function (DTF) calculated from short segments of electroencephalography (EEG) time-series can be used to monitor the state of the patients also during sevoflurane anesthesia as it can for patients undergoing propofol anesthesia. We collected and analyzed 25-channel EEG from 7 patients (3 females, ages 41-56 years) undergoing surgical anesthesia with sevoflurane, and quantified the sensor space directed connectivity for every 1-s epoch using DTF. The resulting connectivity parameters were compared to corresponding parameters from our previous study (n = 8, patients anesthetized with propofol and remifentanil, but otherwise using a similar protocol). Statistical comparisons between and within studies were done using permutation statistics, a data driven algorithm based on the DTF-parameters was employed to classify the epochs as coming from awake or anesthetized state. According to results of the permutation tests, DTF-parameter topographies were significantly different between the awake and anesthesia state at the group level. However, the topographies were not significantly different when comparing results computed from sevoflurane and propofol data, neither in the awake nor in anesthetized state. Optimizing the algorithm for simultaneously having high sensitivity and specificity in classification yielded an accuracy of 95.1% (SE = 0.96%), with sensitivity of 98.4% (SE = 0.80%) and specificity of 94.8% (SE = 0.10%). These findings indicate that the DTF changes in a similar manner when humans undergo general anesthesia caused by two distinct anesthetic agents with different molecular mechanisms of action.

Top-Down Attentional Modulation in Human Frontal Cortex: Differential Engagement during External and Internal Attention.

Decades of electrophysiological research on top-down control converge on the role of the lateral frontal cortex in facilitating attention to behaviorally relevant external inputs. However, the involvement of frontal cortex in the top-down control of attention directed to the external versus internal environment remains poorly understood. To address this, we recorded intracranial electrocorticography while subjects directed their attention externally to tones and responded to infrequent target tones, or internally to their own thoughts while ignoring the tones. Our analyses focused on frontal and temporal cortices. We first computed the target effect, as indexed by the difference in high frequency activity (70-150 Hz) between target and standard tones. Importantly, we then compared the target effect between external and internal attention, reflecting a top-down attentional effect elicited by task demands, in each region of interest. Both frontal and temporal cortices showed target effects during external and internal attention, suggesting this effect is present irrespective of attention states. However, only the frontal cortex showed an enhanced target effect during external relative to internal attention. These findings provide electrophysiological evidence for top-down attentional modulation in the lateral frontal cortex, revealing preferential engagement with external attention.

An electrophysiological marker of arousal level in humans.

Deep non-rapid eye movement sleep (NREM) and general anesthesia with propofol are prominent states of reduced arousal linked to the occurrence of synchronized oscillations in the electroencephalogram (EEG). Although rapid eye movement (REM) sleep is also associated with diminished arousal levels, it is characterized by a desynchronized, 'wake-like' EEG. This observation implies that reduced arousal states are not necessarily only defined by synchronous oscillatory activity. Using intracranial and surface EEG recordings in four independent data sets, we demonstrate that the 1/f spectral slope of the electrophysiological power spectrum, which reflects the non-oscillatory, scale-free component of neural activity, delineates wakefulness from propofol anesthesia, NREM and REM sleep. Critically, the spectral slope discriminates wakefulness from REM sleep solely based on the neurophysiological brain state. Taken together, our findings describe a common electrophysiological marker that tracks states of reduced arousal, including different sleep stages as well as anesthesia in humans.

Electroencephalogram (EEG for short) is a widespread technique that helps to monitor the electrical activity of the brain. In particular, it can be used to examine, recognize and compare different states of brain consciousness such as sleep, wakefulness or general anesthesia. Yet, during rapid eye movement sleep (the sleep phase in which dreaming occurs), the electrical activity of the brain is similar to the one recorded during wakefulness, making it difficult to distinguish these states based on EEG alone. EEG records brain activity in the shape of rhythmic waves whose frequency, shape and amplitude vary depending on the state of consciousness. In the EEG signal from the human brain, the higher frequency waves are weaker than the low-frequency waves: a measure known as spectral slope reflects the degree of this difference in the signal strength. Previous research suggests that spectral slope can be used to distinguish wakefulness from anesthesia and non-REM sleep. Here, Lendner et al. explored whether certain elements of the spectral slope could also discern wakefulness from all states of reduced arousal. EEG readings were taken from patients and volunteers who were awake, asleep or under anesthesia, using electrodes placed either on the scalp or into the brain. Lendner et al. found that the spectral slope could distinguish wakefulness from anesthesia, deep non-REM and REM sleep. The changes in the spectral slope during sleep could accurately track the degree of arousal with great temporal precision and across a wide range of time scales. This method means that states of consciousness can be spotted just from a scalp EEG. In the future, this approach could be embedded into the techniques used for monitoring sleep or anesthesia during operations; it could also be harnessed to monitor other low-response states, such as comas.

Optimized set of criteria for defining interictal epileptiform EEG discharges.

OBJECTIVE: To find and validate the optimal combination of criteria that define interictal epileptiform EEG discharges (IEDs). Our target was a specificity over 95%, to avoid over-reading in clinical EEG. METHODS: We constructed 63 combinations of the six criteria from the operational definition of IEDs, recently issued in the EEG-glossary of the International Federation of Clinical Neurophysiology (IFCN). The diagnostic gold standard was derived from video-EEG recordings. In a testing EEG dataset from 100 patients, we selected the best performing combinations of criteria and then we validated them in an independent dataset from 70 patients. We compared their performance with subjective, expert-scorings and we determined inter-rater agreement (IRA). RESULTS: Without using criteria, the specificity of expert-scorings was lower than the pre-defined threshold (86%). The best performing combination of criteria was the following: waves with spiky morphology, followed by a slow-afterwave and voltage map suggesting a source in the brain. In the validation dataset this achieved a specificity of 97% and a sensitivity of 89%. IRA was substantial. CONCLUSIONS: The optimized set of criteria for defining IEDs has high accuracy and IRA. SIGNIFICANCE: Using these criteria will contribute to decreasing over-reading of EEG and avoid misdiagnosis of epilepsy.

Criteria for defining interictal epileptiform discharges in EEG: A clinical validation study.

OBJECTIVE: To define and validate criteria for accurate identification of EEG interictal epileptiform discharges (IEDs) using (1) the 6 sensor space criteria proposed by the International Federation of Clinical Neurophysiology (IFCN) and (2) a novel source space method. Criteria yielding high specificity are needed because EEG over-reading is a common cause of epilepsy misdiagnosis. METHODS: Seven raters reviewed EEG sharp transients from 100 patients with and without epilepsy (diagnosed definitively by video-EEG recording of habitual events). Raters reviewed the transients, randomized, and classified them as epileptiform or nonepileptiform in 3 separate rounds: in 2, EEG was reviewed in sensor space (scoring the presence/absence of each IFCN criterion for each transient or classifying unrestricted by criteria [expert scoring]); in the other, review and classification were performed in source space. RESULTS: Cutoff values of 4 and 5 criteria in sensor space and analysis in source space provided high accuracy (91%, 88%, and 90%, respectively), similar to expert scoring (92%). Two methods had specificity exceeding the desired threshold of 95%: using 5 IFCN criteria as cutoff and analysis in source space (both 95.65%); the sensitivity of these methods was 81.48% and 85.19%, respectively. CONCLUSIONS: The presence of 5 IFCN criteria in sensor space and analysis in source space are optimal for clinical implementation. By extracting these objective features, diagnostic accuracy similar to expert scorings is achieved. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that IFCN criteria in sensor space and analysis in source space have high specificity (>95%) and sensitivity (81%-85%) for identification of IEDs.

Auditory deviance detection in the human insula: An intracranial EEG study.

The human insula is known to be involved in auditory processing, but knowledge about its precise functional role and the underlying electrophysiology is limited. To assess its role in automatic auditory deviance detection we analyzed the EEG high frequency activity (HFA; 75-145 Hz) and ERPs from 90 intracranial insular channels across 16 patients undergoing pre-surgical intracranial monitoring for epilepsy treatment. Subjects passively listened to a stream of standard and deviant tones differing in four physical dimensions: intensity, frequency, location or time. HFA responses to auditory stimuli were found in the short and long gyri, and the anterior, superior, and inferior segments of the circular sulcus of the insular cortex. Only a subset of channels in the inferior segment of the circular sulcus of the insula showed HFA deviance detection responses, i.e., a greater and longer latency response to specific deviants relative to standards. Auditory deviancy processing was also later in the insula when compared with the superior temporal cortex. ERP results were more widespread and supported the HFA insular findings. These results provide evidence that the human insula is engaged during auditory deviance detection.

Default network and frontoparietal control network theta connectivity supports internal attention.

Attending to our inner world is a fundamental cognitive phenomenon1-3, yet its neural underpinnings remain largely unknown. Neuroimaging evidence implicates the default network (DN) and frontoparietal control network (FPCN)4; however, the electrophysiological basis for the interaction between these networks is unclear. Here we recorded intracranial electroencephalogram from DN and FPCN electrodes implanted in individuals undergoing presurgical monitoring for refractory epilepsy. Subjects performed an attention task during which they attended to tones (that is, externally directed attention) or ignored the tones and thought about whatever came to mind (that is, internally directed attention). Given the emerging role of theta band connectivity in attentional processes5,6, we examined the theta power correlation between DN and two subsystems of the FPCN as a function of attention states. We found increased connectivity between DN and FPCNA during internally directed attention compared to externally directed attention, which positively correlated with attention ratings. There was no statistically significant difference between attention states in the connectivity between DN and FPCNB. Our results indicate that enhanced theta band connectivity between the DN and FPCNA is a core electrophysiological mechanism that underlies internally directed attention.

EEG features in Encephalopathy related to Status Epilepticus during slow Sleep.

Encephalopathy related to Status Epilepticus during slow Sleep (ESES) is a peculiar electro-clinical condition, with variable etiologies, characterized by an age-dependent phenomenon of extreme activation of epileptic activity during sleep, i.e. "status epilepticus during sleep", that is strictly associated with the appearance of cognitive and behavioral disturbances. Even though the peculiar EEG picture is fundamental for the diagnosis of ESES, clear-cut and shared diagnostic criteria for defining the EEG boundaries of this syndrome are still lacking. The diagnosis of ESES can be further complicated by the variability of the EEG findings, that during the course of the disease can change from diffuse to more or less focal and viceversa, depending both on the spontaneous clinical evolution of this condition and/or on the effects of medications. Given the complexity and the heterogeneity of EEG parameters during the ESES course, it is important to correlate the EEG findings with the concomitant cognitive and behavioral status, possibly taking into account not only the spike-wave index, but also other parameters, such as for instance the topography of the epileptic abnormalities, their patterns of spread, and their fluctuations over time. Moreover, the epileptiform activity not only during sleep, but also during wakefulness, the presence of focal slowing, the organization of the EEG background and a derangement of the sleep architecture may play a role in determining the clinical picture.

Quantitative EEG analysis in Encephalopathy related to Status Epilepticus during slow Sleep.

Since its first description, quantifying the burden of epileptiform abnormalities in sleep EEG has played a fundamental role in the diagnosis of Encephalopathy related to Status Epilepticus during slow Sleep (ESES). In fact, in the 1971 seminal paper by Tassinari's group and in the following studies on this syndrome, the amount of epileptiform discharges (EDs) was calculated as the percentage of slow sleep occupied by spike-and-waves and referred to as "spike and wave index" (SWI). However, nowadays it is becoming increasingly clear that the SWI alone does not explain the whole clinical course of patients affected by ESES. In this paper, we aim to provide a state-of-the-art summary of the quantitative EEG methods currently used in the ESES/CSWS literature, highlighting the possible pitfalls and discrepancies explaining the unsatisfactory correlation between SWI and clinical course. Furthermore; we illustrate a number of methodological refinements - taking into account inter-individual, intra-individual, and temporal variability of EDs - alongside "new" quantitative variables -including ED-related and sleep-related features - potentially useful to reach a reliable electro-clinical correlation in patients with ESES.

Safety aspects of antiepileptic drugs-a population-based study of adverse effects relative to changes in utilisation.

PURPOSE: Antiepileptic drugs (AEDs) are increasingly used, and knowledge about adverse effects is scarce based on clinical studies. The purpose of the present study was to characterise adverse effects reports of AEDs in Norway relative to changes in utilisation in various indications from population-based data to elucidate important safety aspects of use of AEDs. METHODS: Aggregated data of adverse effects reported for AEDs in Norway from the EudraVigilance-database (2004-2013) in addition to indication-specific use of AEDs during 2004-2015 from the Norwegian Prescription Database were used. RESULTS: The use of AEDs increased twofold the last decade due to use in psychiatry and neuropathic pain: lamotrigine, pregabalin, gabapentin, valproate, and carbamazepine. There were 1593 adverse effects reported (403 Individual Case Safety Reports, 2/3 women), 0-95 years (mean 46). Most adverse effects were reported for pregabalin (593), carbamazepine (265), lamotrigine (206), gabapentin (144), and valproate (119), where pregabalin had by far the highest reports in relation to the number of users. The most frequently reported adverse drug effects included rash, dizziness, cross-sensitivity reactions, and pyrexia. Overall, nervous system disorders constitute the largest organ class with the majority of the reports. Reporting of fatal outcomes is mandatory, and sudden unexplained death in epilepsy (SUDEP) was reported in 34 occasions. CONCLUSIONS: This study demonstrates that most adverse effects reported concerned AEDs increasingly used in non-epilepsy indications: neuropathic pain (pregabalin, gabapentin, carbamazepine) and psychiatry (lamotrigine, valproate, carbamazepine). Pregabalin had the highest prevalence of adverse effects reported in relation to number of users. This elucidates an important part of pharmacovigilance for improved safety and considerations in clinical practice.

Diagnostic accuracy of interictal source imaging in presurgical epilepsy evaluation: A systematic review from the E-PILEPSY consortium.

OBJECTIVE: Interictal high resolution (HR-) electric source imaging (ESI) and magnetic source imaging (MSI) are non-invasive tools to aid epileptogenic zone localization in epilepsy surgery candidates. We carried out a systematic review on the diagnostic accuracy and quality of evidence of these modalities. METHODS: Embase, Pubmed and the Cochrane database were searched on 13 February 2017. Diagnostic accuracy studies taking post-surgical seizure outcome as reference standard were selected. Quality appraisal was based on the QUADAS-2 framework. RESULTS: Eleven studies were included: eight MSI (n = 267), three HR-ESI (n = 127) studies. None was free from bias. This mostly involved: selection of operated patients only, interference of source imaging with surgical decision, and exclusion of indeterminate results. Summary sensitivity and specificity estimates were 82% (95% CI: 75-88%) and 53% (95% CI: 37-68%) for overall source imaging, with no statistical difference between MSI and HR-ESI. Specificity is higher when partially concordant results were included as non-concordant (p < 0.05). Inclusion of indeterminate test results as non-concordant lowered sensitivity (p < 0.05). CONCLUSIONS: Source imaging has a relatively high sensitivity but low specificity for identification of the epileptogenic zone. SIGNIFICANCE: We need higher quality studies allowing unbiased test evaluation to determine the added value and diagnostic accuracy of source imaging in the presurgical workup of refractory focal epilepsy.