Association of individual resting state EEG alpha frequency and cerebral blood flow

Cognitive task performance differs considerably between individuals. Besides cognitive capacities, attention might be a source of such differences. The individual's EEG alpha frequency (IAF) is a putative marker of the subject's state of arousal and attention, and was found to be associated with task performance and cognitive capacities. However, little is known about the metabolic substrate (i.e. the network) underlying IAF. Here we aimed to identify this network. Correlation of IAF with regional Cerebral Blood Flow (rCBF) in fifteen young healthy subjects revealed a network of brain areas that are associated with the modulation of attention and preparedness for external input, which are relevant for task execution. We hypothesize that subjects with higher IAF have pre-activated task-relevant networks and thus are both more efficient in the task-execution, and show a reduced fMRI-BOLD response to the stimulus, not because the absolute amount of activation is smaller, but because the additional activation by processing of external input is limited due to the higher baseline.

Topographic electrophysiological signatures of FMRI Resting State Networks

Background: fMRI Resting State Networks (RSNs) have gained importance in the present fMRI literature. Although their functional role is unquestioned and their physiological origin is nowadays widely accepted, little is known about their relationship to neuronal activity. The combined recording of EEG and fMRI allows the temporal correlation between fluctuations of the RSNs and the dynamics of EEG spectral amplitudes. So far, only relationships between several EEG frequency bands and some RSNs could be demonstrated, but no study accounted for the spatial distribution of frequency domain EEG. Methodology/Principal Findings: In the present study we report on the topographic association of EEG spectral fluctuations and RSN dynamics using EEG covariance mapping. All RSNs displayed significant covariance maps across a broad EEG frequency range. Cluster analysis of the found covariance maps revealed the common standard EEG frequency bands. We found significant differences between covariance maps of the different RSNs and these differences depended on the frequency band. Conclusions/Significance: Our data supports the physiological and neuronal origin of the RSNs and substantiates the assumption that the standard EEG frequency bands and their topographies can be seen as electrophysiological signatures of underlying distributed neuronal networks.

Resting state cerebral blood flow and objective motor activity reveal basal ganglia dysfunction in schizophrenia

Reduced motor activity has been reported in schizophrenia and was associated with subtype, psychopathology and medication. Still, little is known about the neurobiology of motor retardation. To identify neural correlates of motor activity, resting state cerebral blood flow (CBF) was correlated with objective motor activity of the same day. Participants comprised 11 schizophrenia patients and 14 controls who underwent magnetic resonance imaging with arterial spin labeling and wrist actigraphy. Patients had reduced activity levels and reduced perfusion of the left parahippocampal gyrus, left middle temporal gyrus, right thalamus, and right prefrontal cortex. In controls, but not in schizophrenia, CBF was correlated with activity in the right thalamic ventral anterior (VA) nucleus, a key module within basal ganglia-cortical motor circuits. In contrast, only in schizophrenia patients positive correlations of CBF and motor activity were found in bilateral prefrontal areas and in the right rostral cingulate motor area (rCMA). Grey matter volume correlated with motor activity only in the left posterior cingulate cortex of the patients. The findings suggest that basal ganglia motor control is impaired in schizophrenia. In addition, CBF of cortical areas critical for motor control was associated with volitional motor behavior, which may be a compensatory mechanism for basal ganglia dysfunction.

Resting-state EEG in schizophrenia: auditory verbal hallucinations are related to shortening of specific microstates

Abnormal perceptions and cognitions in schizophrenia might be related to abnormal resting states of the brain. Previous research found that a specific class (class D) of sub-second electroencephalography (EEG) microstates was shortened in schizophrenia. This shortening correlated with positive symptoms. We questioned if this reflected positive psychotic traits or present psychopathology.

Frontal areas contribute to reduced global coordination of resting-state gamma activities in drug-naïve patients with schizophrenia

Schizophrenia has been postulated to involve impaired neuronal cooperation in large-scale neural networks, including cortico-cortical circuitry. Alterations in gamma band oscillations have attracted a great deal of interest as they appear to represent a pathophysiological process of cortical dysfunction in schizophrenia. Gamma band oscillations reflect local cortical activities, and the synchronization of these activities among spatially distributed cortical areas has been suggested to play a central role in the formation of networks. To assess global coordination across spatially distributed brain regions, Omega complexity (OC) in multichannel EEG was proposed. Using OC, we investigated global coordination of resting-state EEG activities in both gamma (30–50 Hz) and below-gamma (1.5–30 Hz) bands in drug-naïve patients with schizophrenia and investigated the effects of neuroleptic treatment. We found that gamma band OC was significantly higher in drug-naïve patients with schizophrenia compared to control subjects and that a right frontal electrode (F3) contributed significantly to the higher OC. After neuroleptic treatment, reductions in the contribution of frontal electrodes to global OC in both bands correlated with the improvement of schizophrenia symptomatology. The present study suggests that frontal brain processes in schizophrenia were less coordinated with activity in the remaining brain. In addition, beneficial effects of neuroleptic treatment were accompanied by improvement of brain coordination predominantly due to changes in frontal regions. Our study provides new evidence of improper intrinsic brain integration in schizophrenia by investigating the resting-state gamma band activity.

Structural and resting state functional connectivity of the subthalamic nucleus: identification of motor STN parts and the hyperdirect pathway

Deep brain stimulation (DBS) for Parkinson's disease often alleviates the motor symptoms, but causes cognitive and emotional side effects in a substantial number of cases. Identification of the motor part of the subthalamic nucleus (STN) as part of the presurgical workup could minimize these adverse effects. In this study, we assessed the STN's connectivity to motor, associative, and limbic brain areas, based on structural and functional connectivity analysis of volunteer data. For the structural connectivity, we used streamline counts derived from HARDI fiber tracking. The resulting tracks supported the existence of the so-called "hyperdirect" pathway in humans. Furthermore, we determined the connectivity of each STN voxel with the motor cortical areas. Functional connectivity was calculated based on functional MRI, as the correlation of the signal within a given brain voxel with the signal in the STN. Also, the signal per STN voxel was explained in terms of the correlation with motor or limbic brain seed ROI areas. Both right and left STN ROIs appeared to be structurally and functionally connected to brain areas that are part of the motor, associative, and limbic circuit. Furthermore, this study enabled us to assess the level of segregation of the STN motor part, which is relevant for the planning of STN DBS procedures.

Time course based artifact identification for independent components of resting-state FMRI

In functional magnetic resonance imaging (fMRI) coherent oscillations of the blood oxygen level-dependent (BOLD) signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting-state networks (RSN). Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA) and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting-state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82, and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting-state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting-state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

Shifted Coupling of EEG Driving Frequencies and fMRI Resting State Networks in Schizophrenia Spectrum Disorders

INTRODUCTION: The cerebral resting state in schizophrenia is altered, as has been demonstrated separately by electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) resting state networks (RSNs). Previous simultaneous EEG/fMRI findings in healthy controls suggest that a consistent spatiotemporal coupling between neural oscillations (EEG frequency correlates) and RSN activity is necessary to organize cognitive processes optimally. We hypothesized that this coupling is disorganized in schizophrenia and related psychotic disorders, in particular regarding higher cognitive RSNs such as the default-mode (DMN) and left-working-memory network (LWMN). METHODS: Resting state was investigated in eleven patients with a schizophrenia spectrum disorder (n = 11) and matched healthy controls (n = 11) using simultaneous EEG/fMRI. The temporal association of each RSN to topographic spectral changes in the EEG was assessed by creating Covariance Maps. Group differences within, and group similarities across frequencies were estimated for the Covariance Maps. RESULTS: The coupling of EEG frequency bands to the DMN and the LWMN respectively, displayed significant similarities that were shifted towards lower EEG frequencies in patients compared to healthy controls. CONCLUSIONS: By combining EEG and fMRI, each measuring different properties of the same pathophysiology, an aberrant relationship between EEG frequencies and altered RSNs was observed in patients. RSNs of patients were related to lower EEG frequencies, indicating functional alterations of the spatiotemporal coupling. SIGNIFICANCE: The finding of a deviant and shifted coupling between RSNs and related EEG frequencies in patients with a schizophrenia spectrum disorder is significant, as it might indicate how failures in the processing of internal and external stimuli, as commonly seen during this symptomatology (i.e. thought disorders, hallucinations), arise.

Static and dynamic characteristics of cerebral blood flow during the resting state in schizophrenia

Background: The cerebral network that is active during rest and is deactivated during goal-oriented activity is called the default mode network (DMN). It appears to be involved in self-referential mental activity. Atypical functional connectivity in the DMN has been observed in schizophrenia. One hypothesis suggests that pathologically increased DMN connectivity in schizophrenia is linked with a main symptom of psychosis, namely, misattribution of thoughts. Methods: A resting-state pseudocontinuous arterial spin labeling (ASL) study was conducted to measure absolute cerebral blood flow (CBF) in 34 schizophrenia patients and 27 healthy controls. Using independent component analysis (ICA), the DMN was extracted from ASL data. Mean CBF and DMN connectivity were compared between groups using a 2-sample t test. Results: Schizophrenia patients showed decreased mean CBF in the frontal and temporal regions (P < .001). ICA demonstrated significantly increased DMN connectivity in the precuneus (x/y/z = -16/-64/38) in patients than in controls (P < .001). CBF was not elevated in the respective regions. DMN connectivity in the precuneus was significantly correlated with the Positive and Negative Syndrome Scale scores (P < .01). Conclusions: In schizophrenia patients, the posterior hub-which is considered the strongest part of the DMN-showed increased DMN connectivity. We hypothesize that this increase hinders the deactivation of the DMN and, thus, the translation of cognitive processes from an internal to an external focus. This might explain symptoms related to defective self-monitoring, such as auditory verbal hallucinations or ego disturbances.

When the systems fail to communicate. Cerebral resting state networks in schizophrenia spectrum disorders.

There have been numerous attempts to reveal the neurobiological basis of schizophrenia spectrum disorders. Results however, remain as heterogeneous as the schizophrenia spectrum disorders itself. Therefore, one aim of this thesis was to divide patients affected by this disorder into subgroups in order to homogenize the results of future studies. In a first study it is suggested that psychopathological rating scales should focus on symptoms-clusters that may have a common neurophysiological background. The here presented Bern Psychopathology Scale (BPS) proposes that alterations in three wellknown brain systems (motor, language, and affective) are largely leading to the communication failures observable on a behavioral level, but also - as repeatedly hypothesized - to dysconnectivity within and between brain systems in schizophrenia spectrum disorders. The external validity of the motor domain in the BPS was tested against the objective measure of 24 hours wrist actigraphy, in a second study. The subjective, the quantitative, as well as the global rating of the degree of motor disorders in this patient group showed significant correlations to the acquired motor activity. This result confirmed in a first step the practicability of the motor domain of the BPS, but needs further validation regarding pathological brain alterations. Finally, in a third study (independent from the two other studies), two cerebral Resting State Networks frequently altered in schizophrenia were investigated for the first time using simultaneous EEG/fMRI: The well-known default mode network and the left working memory network. Besides the changes in these fMRI-based networks, there are well-documented findings that patients exhibit alterations in EEG spectra compared to healthy controls. However, only through the multimodal approach it was possible to discover that patients with schizophrenia spectrum disorders have a slower driving frequency of the Resting State Networks compared to the matched healthy controls. Such a dysfunctional coupling between neuronal frequency and functional brain organization could explain in a uni- or multifactorial way (dysfunctional cross-frequency coupling, maturational effects, vigilance fluctuations, task-related suppression), how the typical psychotic symptoms might occur. To conclude, the major contributions presented in this thesis were on one hand the development of a psychopathology rating scale that is based on the assumption of dysfunctional brain networks, as well as the new evidence of a dysfunctional triggering frequency of Resting State Networks from the simultaneous EEG/fMRI study in patients affected by a schizophrenia spectrum disorder.

Remote Effects Modulating the Spin Equilibrium of the Resting State of Cytochrome P450cam –An Investigation Using Active Site Analogues

The crystal structure of the resting state of cytochrome P450cam (CYP101), a heme thiolate protein, shows a cluster of six water molecules in the substrate binding pocket, one of which is coordinating to iron(III) as sixth ligand. The resting state is low-spin and changes to high-spin when substrate camphor binds and H2O is removed. In contrast to the protein, previously synthesised enzyme models such as H2O[BOND]FeIII(porph)(ArS−) were shown to be purely high-spin. Iron(S−)porphyrins with different distal sites mimicking proposed remote effects have been prepared and studied by cw-EPR. The results indicate that the low-spin of the resting state of P450cam is due to the fact that the water molecule coordinating to iron has an OH−-like character because of hydrogen bonding and polarisation of the water cluster, respectively.

The origin of the low-spin character of the resting state of cytochrome P450cam investigated by means of active site analogues

Crown-capped iron(S−) porphyrins 1·H2O and 2·H2O and their corresponding Ba2+ complexes have been prepared as active site analogues of the resting state of cytochrome P450cam. cw-EPR studies and electronic structure calculations at the density functional theory (DFT) level of model systems suggest a functional role of the water cluster of P450cam.