Brain monitoring in hospitals needs to be strengthened. / Hjerneovervåking i sykehusene må styrkes.

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

Equity theory and fair inequality: a neuroeconomic study.

The present paper reports results from, to our knowledge, the first study designed to examine the neuronal responses to income inequality in situations in which individuals have made different contributions in terms of work effort. We conducted an experiment that included a prescanning phase in which the participants earned money by working, and a neuronal scanning phase in which we examined how the brain responded when the participants evaluated different distributions of their earnings. We provide causal evidence for the relative contribution of work effort being crucial for understanding the hemodynamic response in the brain to inequality. We found a significant hemodynamic response in the striatum to deviations from the distribution of income that was proportional to work effort, but found no effect of deviations from the equal distribution of income. We also observed a striking correlation between the hemodynamic response in the striatum and the self-reported evaluation of the income distributions. Our results provide, to our knowledge, the first set of neuronal evidence for equity theory and suggest that people distinguish between fair and unfair inequalities.

Understanding the Epilepsy in POLG Related Disease.

Epilepsy is common in polymerase gamma (POLG) related disease and is associated with high morbidity and mortality. Epileptiform discharges typically affect the occipital regions initially and focal seizures, commonly evolving to bilateral convulsive seizures which are the most common seizure types in both adults and children. Our work has shown that mtDNA depletion-i.e., the quantitative loss of mtDNA-in neurones is the earliest and most important factor of the subsequent development of cellular dysfunction. Loss of mtDNA leads to loss of mitochondrial respiratory chain (MRC) components that, in turn, progressively disables energy metabolism. This critically balanced neuronal energy metabolism leads to both a chronic and continuous attrition (i.e., neurodegeneration) and it leaves the neurone unable to cope with increased demand that can trigger a potentially catastrophic cycle that results in acute focal necrosis. We believe that it is the onset of epilepsy that triggers the cascade of damage. These events can be identified in the stepwise evolution that characterizes the clinical, Electroencephalography (EEG), neuro-imaging, and neuropathology findings. Early recognition with prompt and aggressive seizure management is vital and may play a role in modifying the epileptogenic process and improving survival.

Reduced error signalling in medication-naive children with ADHD: associations with behavioural variability and post-error adaptations.

BACKGROUND: We examined the blood-oxygen level-dependent (BOLD) activation in brain regions that signal errors and their association with intraindividual behavioural variability and adaptation to errors in children with attention-deficit/hyperactivity disorder (ADHD). METHODS: We acquired functional MRI data during a Flanker task in medication-naive children with ADHD and healthy controls aged 8-12 years and analyzed the data using independent component analysis. For components corresponding to performance monitoring networks, we compared activations across groups and conditions and correlated them with reaction times (RT). Additionally, we analyzed post-error adaptations in behaviour and motor component activations. RESULTS: We included 25 children with ADHD and 29 controls in our analysis. Children with ADHD displayed reduced activation to errors in cingulo-opercular regions and higher RT variability, but no differences of interference control. Larger BOLD amplitude to error trials significantly predicted reduced RT variability across all participants. Neither group showed evidence of post-error response slowing; however, post-error adaptation in motor networks was significantly reduced in children with ADHD. This adaptation was inversely related to activation of the right-lateralized ventral attention network (VAN) on error trials and to task-driven connectivity between the cingulo-opercular system and the VAN. LIMITATIONS: Our study was limited by the modest sample size and imperfect matching across groups. CONCLUSION: Our findings show a deficit in cingulo-opercular activation in children with ADHD that could relate to reduced signalling for errors. Moreover, the reduced orienting of the VAN signal may mediate deficient post-error motor adaptions. Pinpointing general performance monitoring problems to specific brain regions and operations in error processing may help to guide the targets of future treatments for ADHD.

Tracking whole-brain connectivity dynamics in the resting state.

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.

Working memory networks and activation patterns in schizophrenia and bipolar disorder: comparison with healthy controls.

BACKGROUND: Schizophrenia and bipolar disorder are severe mental disorders with overlapping genetic and clinical characteristics, including cognitive impairments. An important question is whether these disorders also have overlapping neuronal deficits. AIMS: To determine whether large-scale brain networks associated with working memory, as measured with functional magnetic resonance imaging (fMRI), are the same in both schizophrenia and bipolar disorder, and how they differ from those in healthy individuals. METHOD: Patients with schizophrenia (n = 100) and bipolar disorder (n = 100) and a healthy control group (n = 100) performed a 2-back working memory task while fMRI data were acquired. The imaging data were analysed using independent component analysis to extract large-scale networks of task-related activations. RESULTS: Similar working memory networks were activated in all groups. However, in three out of nine networks related to the experimental task there was a graded response difference in fMRI signal amplitudes, where patients with schizophrenia showed greater activation than those with bipolar disorder, who in turn showed more activation than healthy controls. Secondary analysis of the patient groups showed that these activation patterns were associated with history of psychosis and current elevated mood in bipolar disorder. CONCLUSIONS: The same brain networks were related to working memory in schizophrenia, bipolar disorder and controls. However, some key networks showed a graded hyperactivation in the two patient groups, in line with a continuum of neuronal abnormalities across psychotic disorders.

Refractory and super-refractory status epilepticus in children and adolescents: A population-based study.

PURPOSE: Refractory (RSE) and super-refractory status epilepticus (SRSE) are serious medical emergencies whose long-term outcomes depend on the timeliness of their management. Population-based clinical and epidemiological data on these conditions are sparse. We aimed to provide a detailed description of the epidemiology and clinical course of RSE and SRSE in children and adolescents and identify potential prognostic biomarkers. METHODS: In this retrospective population-based study, patients aged one month to 18 years who fulfilled the RSE/SRSE diagnostic criteria and were admitted to the intensive care unit of Haukeland University Hospital from 2012 to 2021 were considered eligible. Detailed clinical and laboratory findings along with information on management and outcomes were systematically analyzed. RESULTS: Forty-three patients with 52 episodes of RSE/SRSE were identified. The incidence rate was 3.13 per 100,000 per year. The median time from SE onset to the administration of the first rescue drug was 13 min, and from the first rescue drug to second- and third-line treatments, 83 and 66 min, respectively. All patients were alive at discharge. CONCLUSION: Delays in treatment were observed in various stages of the clinical course of RSE/SRSE. Improvement measures targeting the prompt administration of recuse mediation and subsequent treatment escalation are needed.

Methods for simultaneous EEG-fMRI: an introductory review.

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.

The spatiospectral characterization of brain networks: fusing concurrent EEG spectra and fMRI maps.

Different imaging modalities capture different aspects of brain activity. Functional magnetic resonance imaging (fMRI) reveals intrinsic networks whose BOLD signals have periods from 100 s (0.01 Hz) to about 10s (0.1 Hz). Electroencephalographic (EEG) recordings, in contrast, commonly reflect cortical electrical fluctuations with periods up to 20 ms (50 Hz) or above. We examined the correspondence between intrinsic fMRI and EEG network activity at rest in order to characterize brain networks both spatially (with fMRI) and spectrally (with EEG). Brain networks were separately identified within the concurrently recorded fMRI and EEG at the aggregate group level with group independent component analysis and the association between spatial fMRI and frequency by spatial EEG sources was examined by deconvolving their component time courses. The two modalities are considered linked if the estimated impulse response function (IRF) is significantly non-zero at biologically plausible delays. We found that negative associations were primarily present within two of five alpha components, which highlights the importance of considering multiple alpha sources in EEG-fMRI. Positive associations were primarily present within the lower (e.g. delta and theta) and higher (e.g. upper beta and lower gamma) spectral regions, sometimes within the same fMRI components. Collectively, the results demonstrate a promising approach to characterize brain networks spatially and spectrally, and reveal that positive and negative associations appear within partially distinct regions of the EEG spectrum.

Functional parcellation of the inferior frontal and midcingulate cortices in a flanker-stop-change paradigm.

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.

Visual activation of auditory cortex reflects maladaptive plasticity in cochlear implant users.

Cross-modal reorganization in the auditory cortex has been reported in deaf individuals. However, it is not well understood whether this compensatory reorganization induced by auditory deprivation recedes once the sensation of hearing is partially restored through a cochlear implant. The current study used electroencephalography source localization to examine cross-modal reorganization in the auditory cortex of post-lingually deafened cochlear implant users. We analysed visual-evoked potentials to parametrically modulated reversing chequerboard images between cochlear implant users (n = 11) and normal-hearing listeners (n = 11). The results revealed smaller P100 amplitudes and reduced visual cortex activation in cochlear implant users compared with normal-hearing listeners. At the P100 latency, cochlear implant users also showed activation in the right auditory cortex, which was inversely related to speech recognition ability with the cochlear implant. These results confirm a visual take-over in the auditory cortex of cochlear implant users. Incomplete reversal of this deafness-induced cortical reorganization might limit clinical benefit from a cochlear implant and help explain the high inter-subject variability in auditory speech comprehension.

Posterior medial frontal cortex activity predicts post-error adaptations in task-related visual and motor areas.

As Seneca the Younger put it, "To err is human, but to persist is diabolical." To prevent repetition of errors, human performance monitoring often triggers adaptations such as general slowing and/or attentional focusing. The posterior medial frontal cortex (pMFC) is assumed to monitor performance problems and to interact with other brain areas that implement the necessary adaptations. Whereas previous research showed interactions between pMFC and lateral-prefrontal regions, here we demonstrate that upon the occurrence of errors the pMFC selectively interacts with perceptual and motor regions and thereby drives attentional focusing toward task-relevant information and induces motor adaptation observed as post-error slowing. Functional magnetic resonance imaging data from an interference task reveal that error-related pMFC activity predicts the following: (1) subsequent activity enhancement in perceptual areas encoding task-relevant stimulus features; (2) activity suppression in perceptual areas encoding distracting stimulus features; and (3) post-error slowing-related activity decrease in the motor system. Additionally, diffusion-weighted imaging revealed a correlation of individual post-error slowing and white matter integrity beneath pMFC regions that are connected to the motor inhibition system, encompassing right inferior frontal gyrus and subthalamic nucleus. Thus, disturbances in task performance are remedied by functional interactions of the pMFC with multiple task-related brain regions beyond prefrontal cortex that result in a broad repertoire of adaptive processes at perceptual as well as motor levels.

Neural correlates of trial-to-trial fluctuations in response caution.

Trial-to-trial variability in decision making can be caused by variability in information processing as well as by variability in response caution. In this paper, we study which neural components code for trial-to-trial adjustments in response caution using a new computational approach that quantifies response caution on a single-trial level. We found that the frontostriatal network updates the amount of response caution. In particular, when human participants were required to respond quickly, we found a positive correlation between trial-to-trial fluctuations in response caution and the hemodynamic response in the presupplementary motor area and dorsal anterior cingulate. In contrast, on trials that required a change from a speeded response mode to a more accurate response mode or vice versa, we found a positive correlation between response caution and hemodynamic response in the anterior cingulate proper. These results indicate that for each decision, response caution is set through corticobasal ganglia functioning, but that individual choices differ according to the mechanisms that trigger changes in response caution.

Modulations of functional connectivity in the healthy and schizophrenia groups during task and rest.

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.

SimTB, a simulation toolbox for fMRI data under a model of spatiotemporal separability.

We introduce SimTB, a MATLAB toolbox designed to simulate functional magnetic resonance imaging (fMRI) datasets under a model of spatiotemporal separability. The toolbox meets the increasing need of the fMRI community to more comprehensively understand the effects of complex processing strategies by providing a ground truth that estimation methods may be compared against. SimTB captures the fundamental structure of real data, but data generation is fully parameterized and fully controlled by the user, allowing for accurate and precise comparisons. The toolbox offers a wealth of options regarding the number and configuration of spatial sources, implementation of experimental paradigms, inclusion of tissue-specific properties, addition of noise and head movement, and much more. A straightforward data generation method and short computation time (3-10 seconds for each dataset) allow a practitioner to simulate and analyze many datasets to potentially understand a problem from many angles. Beginning MATLAB users can use the SimTB graphical user interface (GUI) to design and execute simulations while experienced users can write batch scripts to automate and customize this process. The toolbox is freely available at http://mialab.mrn.org/software together with sample scripts and tutorials.

Capturing inter-subject variability with group independent component analysis of fMRI data: a simulation study.

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 intersubject 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.

Multimodal imaging of incidental retrieval: the low route to memory.

Memories of past episodes frequently come to mind incidentally, without directed search. It has remained unclear how incidental retrieval processes are initiated in the brain. Here we used fMRI and ERP recordings to find brain activity that specifically correlates with incidental retrieval, as compared to intentional retrieval. Intentional retrieval was associated with increased activation in dorsolateral prefrontal cortex. By contrast, incidental retrieval was associated with a reduced fMRI signal in posterior brain regions, including extrastriate and parahippocampal cortex, and a modulation of a posterior ERP component 170 msec after the onset of visual retrieval cues. Successful retrieval under both intentional and incidental conditions was associated with increased activation in the hippocampus, precuneus, and ventrolateral prefrontal cortex, as well as increased amplitude of the P600 ERP component. These results demonstrate how early bottom-up signals from posterior cortex can lead to reactivation of episodic memories in the absence of strategic retrieval attempts.

Cortico-striatal connectivity and cognition in normal aging: a combined DTI and resting state fMRI study.

Resting state fMRI studies have found that cognitive decline in aging is associated with alterations in functional connectivity of distributed neural systems in the brain. While functional connections have been shown to rely on the underlying structural connectivity, direct structural connections have been studied in only a few distributed cortical systems so far. It is well known that subcortical nuclei have structural connections to the entire cortex. We hypothesized that structural subcortico-cortical connections may provide integral routes for communication between cortical resting state networks, and that changes in the integrity of these connections have a role in cognitive aging. We combined anatomical MRI, diffusion tensor MRI, and resting state fMRI in 100 healthy elderly to identify fiber bundles connecting cortical resting state networks to subcortical nuclei. In identified tracts, white matter fiber bundle integrity measures were compared to composite cognitive measures on executive function, processing speed, and memory performance. The integrity (FA values) in selected fiber bundles correlated strongly with cognitive measures on executive function and processing speed. Correlation was most pronounced between executive function and fiber bundles connecting the putamen to the dorsal attention network (r=0.73, p<0.001). Our findings show that unique cortico-subcortical fiber bundles can be identified for a range of cortical resting state networks, and indicate that these connections play an important role in cortical resting state network communication and cognition.