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Careful brain monitoring saves lives and is beneficial to patients' health. Nevertheless, Norway lacks guidelines for brain monitoring in hospitals.

Careful brain monitoring saves lives and is beneficial to patients' health. Nevertheless, Norway lacks guidelines for brain monitoring in hospitals.

Highlights • There is concern that the SCORE reporting standard for EEG takes too long. • This study shows that a normal EEG can typically be reported in SCORE EEG in 8 min. • Reviewing time is higher for abnormal recordings, and declined by 25% in this study., Objective Visual EEG analysis is the gold standard for clinical EEG interpretation and analysis, but there is no published data on how long it takes to review and report an EEG in clinical routine. Estimates of reporting times may inform workforce planning and automation initiatives for EEG. The SCORE standard has recently been adopted to standardize clinical EEG reporting, but concern has been expressed about the time spent reporting. Methods Elapsed times were extracted from 5889 standard and sleep-deprived EEGs reported between 2015 and 2017 reported using the SCORE EEG software. Results The median review time for standard EEG was 12.5 min, and for sleep deprived EEG 20.9 min. A normal standard EEG had a median review time of 8.3 min. Abnormal EEGs took longer than normal EEGs to review, and had more variable review times. 99% of EEGs were reported within 24 h of end of recording. Review times declined by 25% during the study period. Conclusion Standard and sleep-deprived EEG review and reporting times with SCORE EEG are reasonable, increasing with increasing EEG complexity and decreasing with experience. EEG reports can be provided within 24 h. Significance Clinical standard and sleep-deprived EEG reporting with SCORE EEG has acceptable reporting times.

Background Hyperactive performance monitoring, as measured by the error-related negativity (ERN) in the event-related potential, is a reliable finding in obsessive-compulsive disorder (OCD) research and may be an endophenotype of the disorder. Imaging studies revealed inconsistent results as to which brain regions are involved in altered performance monitoring in OCD. We investigated performance monitoring in OCD with simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) signals to determine the neural source of the enhanced ERN. Methods Concurrent EEG and fMRI data were collected from 20 patients with OCD and 22 healthy control subjects during a flanker task. Independent component analysis was used separately on EEG and fMRI to segment the data functionally and focus on processes of interest. The ERN, hemodynamic responses following errors, and intraindividual correlation of the ERN and blood oxygen level–dependent activity were compared between groups. Results Patients with OCD showed significantly increased ERN amplitudes. Blood oxygen level–dependent activity in midcingulate cortex was not significantly different between groups. Increased activation of the right amygdala and the subgenual anterior cingulate cortex following errors was observed in patients with OCD. Increased intraindividual correlation of the ERN and activity of the presupplementary motor area was found in patients with OCD compared with healthy controls. Conclusions Higher error-related activity was found in the amygdala and subgenual anterior cingulate cortex, suggesting a stronger affective response toward errors in patients with OCD. Additionally, increased correlation of the ERN and presupplementary motor area may indicate stronger recruitment of proactive control in OCD.

We report a 15-year-old female with POLG-related mitochondrial disease who developed severe multifocal epilepsia partialis continua, unresponsive to standard anti seizure drug treatment and general anesthesia. Based on an earlier case report, we treated her focal seizures that affected her right upper limb with 20-min sessions of transcranial direct current stimulation (tDCS) at an intensity of 2 mA on each of five consecutive days. The cathode was placed over the left primary motor cortex, the anode over the contralateral orbitofrontal cortex. Surface electromyography (EMG) were recorded 20 min before, 20 min during, and 20 min after four of five tDCS sessions to measure its effect on the muscle jerks. The electroencephalography (EEG) was recorded before and after tDCS to measure the frequency of spikes. Our results showed no statistically or clinically significant reduction of seizures or epileptiform activity using EEG and EMG, with this treatment protocol. To our knowledge, this is only the second time that adjunct tDCS treatment of epileptic seizures has been tried in POLG-related mitochondrial disease. Taken together with the positive findings from the earlier case report, the present study highlights that more data are needed to determine if, and under which parameters, the treatment is effective., Highlights • Case report of multifocal epilepsy in POLG disease with upper limp myoclonus. • Epileptic activity resulting in myoclonus was treated with 5 days of 20 minutes cathodal 2 mA tDCS over left motor cortex. • tDCS treatment did not yield significant reduction of myoclonus activity.

ZusammenfassungEine 2013 von der „International Federation of Clinical Neurophysiology“ gegründete Taskforce hat eine international konsensfähige EEG-Terminologie entwickelt. Im Folgenden soll das Resultat – die 2. Version des Standardized Computer-based Organized Reporting of EEG (SCORE) - vorgestellt werden. Die Terminologie wurde im Rahmen eines Softwarepaketes (SCORE-EEG) in der klinischen Praxis an über 12.000 EEGs getestet. Die Auswahl der Begriffe ist kontextabhängig: die initiale Auswahl bestimmt, welche weiteren Auswahlmöglichkeiten zur Verfügung stehen. Im Verlauf wird automatisch ein Befund erstellt und dessen Einzelmerkmale in eine Datenbank eingespeist. SCORE verfügt über Module spezifisch für die Befundung epileptischer Anfälle, sowie charakteristischer neonataler und intensivmedizinische EEG-Merkmale. SCORE ist nicht nur ein nützliches Werkzeug im ambulanten, klinischen und wissenschaftlichen Setting, es erleichtert auch Qualitätssicherung, Datenaustausch und die EEG-Aus und Weiterbildung.

Contains fulltext : 14156.pdf (Publisher’s version ) (Closed access) Humans often commit errors when they are distracted by irrelevant information and no longer focus on what is relevant to the task at hand. Adjustments following errors are essential for optimizing goal achievement. The posterior medial frontal cortex (pMFC), a key area for monitoring errors, has been shown to trigger such post-error adjustments by modulating activity in visual cortical areas. However, the mechanisms by which pMFC controls sensory cortices are unknown. We provide evidence for a mechanism based on pMFC-induced recruitment of cholinergic projections to task-relevant sensory areas. Using fMRI in healthy volunteers, we found that error-related pMFC activity predicted subsequent adjustments in task-relevant visual brain areas. In particular, following an error, activity increased in those visual cortical areas involved in processing task-relevant stimulus features, whereas activity decreased in areas representing irrelevant, distracting features. Following treatment with the muscarinic acetylcholine receptor antagonist biperiden, activity in visual areas was no longer under control of error-related pMFC activity. This was paralleled by abolished post-error behavioral adjustments under biperiden. Our results reveal a prominent role of acetylcholine in cognitive control that has not been recognized thus far. Regaining optimal performance after errors critically depends on top-down control of perception driven by the pMFC and mediated by acetylcholine. This may explain the lack of adaptivity in conditions with reduced availability of cortical acetylcholine, such as Alzheimer's disease. 8 p.

Standardized terminology for computer-based assessment and reporting of EEG has been previously developed in Europe. The International Federation of Clinical Neurophysiology established a taskforce in 2013 to develop this further, and to reach international consensus. This work resulted in the second, revised version of SCORE (Standardized Computer-based Organized Reporting of EEG), which is presented in this paper. The revised terminology was implemented in a software package (SCORE EEG), which was tested in clinical practice on 12,160 EEG recordings. Standardized terms implemented in SCORE are used to report the features of clinical relevance, extracted while assessing the EEGs. Selection of the terms is context sensitive: initial choices determine the subsequently presented sets of additional choices. This process automatically generates a report and feeds these features into a database. In the end, the diagnostic significance is scored, using a standardized list of terms. SCORE has specific modules for scoring seizures (including seizure semiology and ictal EEG patterns), neonatal recordings (including features specific for this age group), and for Critical Care EEG Terminology. SCORE is a useful clinical tool, with potential impact on clinical care, quality assurance, data-sharing, research and education.

The human brain operates by dynamically modulating different neural populations to enable goal directed behavior. The synchrony or lack thereof between different brain regions is thought to correspond to observed functional connectivity dynamics in resting state brain imaging data. In a large sample of healthy human adult subjects and utilizing a sliding windowed correlation method on functional imaging data, earlier we demonstrated the presence of seven distinct functional connectivity states/patterns between different brain networks that reliably occur across time and subjects. Whether these connectivity states correspond to meaningful electrophysiological signatures was not clear. In this study, using a dataset with concurrent EEG and resting state functional imaging data acquired during eyes open and eyes closed states, we demonstrate the replicability of previous findings in an independent sample, and identify EEG spectral signatures associated with these functional network connectivity changes. Eyes open and eyes closed conditions show common and different connectivity patterns that are associated with distinct EEG spectral signatures. Certain connectivity states are more prevalent in the eyes open case and some occur only in eyes closed state. Both conditions exhibit a state of increased thalamocortical anticorrelation associated with reduced EEG spectral alpha power and increased delta and theta power possibly reflecting drowsiness. This state occurs more frequently in the eyes closed state. In summary, we find a link between dynamic connectivity in fMRI data and concurrently collected EEG data, including a large effect of vigilance on functional connectivity. As demonstrated with EEG and fMRI, the stationarity of connectivity cannot be assumed, even for relatively short periods.

Reading epilepsy is a form of reflex-induced seizures. Two entities are postulated as part of a clinical spectrum; one anterior variant with jaw jerks and orofacial myoclonia and another posterior variant with visual symptoms and alexia or dyslexia. We present a case with suggestible evidence of both conditions coexisting within the same patient, a finding that, to our knowledge, has not been previously reported. The diagnosis in this specific case was contributed to by the patient searching the internet. publishedVersion

Contains fulltext : 116726.pdf (Publisher’s version ) (Closed access) OBJECTIVE: In a previous article reporting group data, we presented event-related potentials (ERPs), which were evoked by randomly presented target stimuli in a 'learning-oddball' task. These ERPs contained a large N2-P3 complex that decreased and a Contingent Negative Variation (CNV) that increased when the targets were presented in a regular fashion. Using the learning-oddball paradigm, the aim of the present paper was to determine ERP effects of introducing regularity in individual participants. METHODS: The data from the previous study were re-analyzed at the level of the individual participant, extracting individual sigmoid curves by means of wavelet-denoising and focusing on RTs, and CNV, N2, and P3 ERP components. RESULTS: Most participants displayed significant sigmoid curves with respect to the P3 component (22 of the 24 participants - 22/24), the N2 component (20/24), and/or the CNV (19/24) component. In contrast, reaction times (RTs) appeared less sensitive to incidental learning (15/24). Modest correlations were observed between RTs and N2 component amplitudes. CONCLUSIONS: It is possible to extract significant ERP changes to introducing regularity in individual participants. SIGNIFICANCE: Tracking ERP changes within the learning-oddball paradigm might be a useful tool to assess pattern detection capacities in individual patients. 8 p.

It has been suggested that intra-individual variability (IIV) in performance on attention and other cognitive tasks might be a cognitive endophenotype in individuals with ADHD. Despite robust IIV findings in behavioral data, only sparse data exist on how what type of brain dysfunction underlies variable response times. In this study, we asked whether ADHD IIV in reaction time on a commonly-used test of attention might be related to variation in hemodynamic responses (HRs) observed trial-to-trial. Based on previous studies linking IIV to regions within the “default mode” network (DMN), we predicted that adolescents with ADHD would have higher HR variability in the DMN compared with controls, and this in turn would be related to behavioral IIV. We also explored the influence of social anxiety on HR variability in ADHD as means to test whether higher arousal associated with high trait anxiety would affect the neural abnormalities. We assessed single-trial variability of HRs, estimated from fMRI event-related responses elicited during an auditory oddball paradigm in adolescents with ADHD and healthy controls (11–18 years old; N = 46). Adolescents with ADHD had higher HR variability compared with controls in anterior regions of the DMN. This effect was specific to ADHD and not associated with traits of age, IQ and anxiety. However, an ADHD effect of higher HR variability also appeared in a basal ganglia network, but for these brain regions the relationships of HR variability and social anxiety levels were more complex. Performance IIV correlated significantly with variability of HRs in both networks. These results suggest that assessment of trial-to-trial HR variability in ADHD provides information beyond that detectable through analysis of behavioral data and average brain activation levels, revealing specific neural correlates of a possible ADHD IIV endophenotype., Highlights • We studied if the behavioral variability in ADHD is also found on a neuronal level. • Independent component analysis was combined with BOLD amplitude variability. • Adolescents with ADHD had higher amplitude variability than healthy controls. • Higher amplitude variability was shown in an anterior default mode network. • Social anxiety in ADHD associated with high amplitude variability in the striatum

Background: Tourette syndrome (TS) is a childhood-onset neurodevelopmental disorder and its impact on cognitive development needs further study. Evidence from neuropsychological, neuroimaging and electrophysiological studies suggests that the decline in tic severity and the ability to suppress tics relate to the development of self-regulatory functions in late childhood and adolescence. Hence, tasks measuring performance monitoring might provide insight into the regulation of tics in children with TS. Method: Twenty-five children with TS, including 14 with comorbid Attention-deficit/ hyperactivity disorder (ADHD), 39 children with ADHD and 35 typically developing children aged 8–12 years were tested with a modified Eriksen-Flanker task during a 34-channel electroencephalography (EEG) recording. Task performance, as well as stimulus-locked and response-locked event-related potentials (ERP) were analyzed and compared across groups. Results: Participants did not differ in their behavioral performance. Children with TS showed higher amplitudes of an early P3 component of the stimulus-locked ERPs in ensemble averages and in separate trial outcomes, suggesting heightened orienting and/or attention during stimulus evaluation. In response-locked averages, children with TS had a slightly higher positive complex before the motor response, likely also reflecting a late P3. Groups did not differ in post-response components, particularly in the error-related negativity (ERN) and error-related positivity (Pe). Conclusions: These findings suggest that children with TS may employ additional attentional resources as a compensatory mechanism to maintain equal behavioral performance. publishedVersion

Spontaneous fluctuations are a hallmark of recordings of neural signals, emergent over time scales spanning milliseconds and tens of minutes. However, investigations of intrinsic brain organization based on resting-state functional magnetic resonance imaging have largely not taken into account the presence and potential of temporal variability, as most current approaches to examine functional connectivity (FC) implicitly assume that relationships are constant throughout the length of the recording. In this work, we describe an approach to assess whole-brain FC dynamics based on spatial independent component analysis, sliding time window correlation, and k-means clustering of windowed correlation matrices. The method is applied to resting-state data from a large sample (n = 405) of young adults. Our analysis of FC variability highlights particularly flexible connections between regions in lateral parietal and cingulate cortex, and argues against a labeling scheme where such regions are treated as separate and antagonistic entities. Additionally, clustering analysis reveals unanticipated FC states that in part diverge strongly from stationary connectivity patterns and challenge current descriptions of interactions between large-scale networks. Temporal trends in the occurrence of different FC states motivate theories regarding their functional roles and relationships with vigilance/arousal. Overall, we suggest that the study of time-varying aspects of FC can unveil flexibility in the functional coordination between different neural systems, and that the exploitation of these dynamics in further investigations may improve our understanding of behavioral shifts and adaptive processes.

Connectivity analysis using functional magnetic resonance imaging (fMRI) data is an important area, useful for the identification of biomarkers for various mental disorders, including schizophrenia. Most studies to date have focused on resting data, while the study of functional connectivity during task and the differences between task and rest are of great interest as well. In this work, we examine the graph-theoretical properties of the connectivity maps constructed using spatial components derived from independent component analysis (ICA) for healthy controls and patients with schizophrenia during an auditory oddball task (AOD) and at extended rest. We estimate functional connectivity using the higher-order statistical dependence, i.e., mutual information among the ICA spatial components, instead of the typically used temporal correlation. We also define three novel topological metrics based on the modules of brain networks obtained using a clustering approach. Our experimental results show that although the schizophrenia patients preserve the small-world property, they present a significantly lower small-worldness during both AOD task and rest when compared to the healthy controls, indicating a consistent tendency towards a more random organization of brain networks. In addition, the task-induced modulations to topological measures of several components involving motor, cerebellum and parietal regions are altered in patients relative to controls, providing further evidence for the aberrant connectivity in schizophrenia.

The simultaneous recording and analysis of electroencephalography (EEG) and fMRI data in human systems, cognitive and clinical neurosciences is rapidly evolving and has received substantial attention. The significance of multimodal brain imaging is documented by a steadily increasing number of laboratories now using simultaneous EEG-fMRI aiming to achieve both high temporal and spatial resolution of human brain function. Due to recent developments in technical and algorithmic instrumentation, the rate-limiting step in multimodal studies has shifted from data acquisition to analytic aspects. Here, we introduce and compare different methods for data integration and identify the benefits that come with each approach, guiding the reader toward an understanding and informed selection of the integration approach most suitable for addressing a particular research question.

Conflict monitoring and motor inhibition are engaged in the performance of complex tasks. The midcingulate cortex (MCC) has been suggested to detect conflicts, whereas the right inferior frontal cortex (IFC) seems to be of relevance for the inhibition process. The current experiment investigates the neural underpinnings of their interplay via a modified flanker paradigm. Conflict was manipulated by the congruency of flanking stimuli relative to a target (congruent vs. incongruent) and motor inhibition by a within‐trial response change of the initiated response (keep response vs. stop‐change). We used event‐related functional magnetic resonance imaging, decomposition with high model order ICA, and single trial analysis to derive a functional parcellation of the whole‐brain data. Results demonstrate the segmentation of the MCC into anterior and posterior subregions, and of the IFC into the pars opercularis, pars triangularis, and pars orbitalis. The pars opercularis and pars triangularis of the right IFC constituted the foundation of inhibition‐related networks. With high conflict on incongruent trials, activity in the posterior MCC network, as well as in one right IFC network was observed. Stop‐change trials modulated both the MCC as well as networks covering extended parts of the IFC. Whereas conflict processing and inhibition most often are studied separately, this study provides a synopsis of functionally coupled brain regions acting in concert to enable an optimal performance in situations involving interference and inhibition. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.

A key challenge in functional neuroimaging is the meaningful combination of results across subjects. Even in a sample of healthy participants, brain morphology and functional organization exhibit considerable variability, such that no two individuals have the same neural activation at the same location in response to the same stimulus. This inter-subject variability limits inferences at the group-level as average activation patterns may fail to represent the patterns seen in individuals. A promising approach to multi-subject analysis is group independent component analysis (GICA), which identifies group components and reconstructs activations at the individual level. GICA has gained considerable popularity, particularly in studies where temporal response models cannot be specified. However, a comprehensive understanding of the performance of GICA under realistic conditions of inter-subject variability is lacking. In this study we use simulated functional magnetic resonance imaging (fMRI) data to determine the capabilities and limitations of GICA under conditions of spatial, temporal, and amplitude variability. Simulations, generated with the SimTB toolbox, address questions that commonly arise in GICA studies, such as: (1) How well can individual subject activations be estimated and when will spatial variability preclude estimation? (2) Why does component splitting occur and how is it affected by model order? (3) How should we analyze component features to maximize sensitivity to inter-subject differences? Overall, our results indicate an excellent capability of GICA to capture between-subject differences and we make a number of recommendations regarding analytic choices for application to functional imaging data.