16 resultados para Brain Dynamics

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Epileptic seizures are due to the pathological collective activity of large cellular assemblies. A better understanding of this collective activity is integral to the development of novel diagnostic and therapeutic procedures. In contrast to reductionist analyses, which focus solely on small-scale characteristics of ictogenesis, here we follow a systems-level approach, which combines both small-scale and larger-scale analyses. Peri-ictal dynamics of epileptic networks are assessed by studying correlation within and between different spatial scales of intracranial electroencephalographic recordings (iEEG) of a heterogeneous group of patients suffering from pharmaco-resistant epilepsy. Epileptiform activity as recorded by a single iEEG electrode is determined objectively by the signal derivative and then subjected to a multivariate analysis of correlation between all iEEG channels. We find that during seizure, synchrony increases on the smallest and largest spatial scales probed by iEEG. In addition, a dynamic reorganization of spatial correlation is observed on intermediate scales, which persists after seizure termination. It is proposed that this reorganization may indicate a balancing mechanism that decreases high local correlation. Our findings are consistent with the hypothesis that during epileptic seizures hypercorrelated and therefore functionally segregated brain areas are re-integrated into more collective brain dynamics. In addition, except for a special sub-group, a highly significant association is found between the location of ictal iEEG activity and the location of areas of relative decrease of localised EEG correlation. The latter could serve as a clinically important quantitative marker of the seizure onset zone (SOZ).

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OBJECTIVE: There are relevant links between resting-state fMRI networks, EEG microstate classes and psychopathological alterations in mental disorders associated with frontal lobe dysfunction. We hypothesized that a certain microstate class, labeled C and correlated with the salience network, was impaired early in frontotemporal dementia (FTD), and that microstate class D, correlated with the frontoparietal network, was impaired in schizophrenia. METHODS: We measured resting EEG microstate parameters in patients with mild FTD (n = 18), schizophrenia (n = 20), mild Alzheimer's disease (AD; n = 19) and age-matched controls (old n = 19, young n = 18) to investigate neuronal dynamics at the whole-brain level. RESULTS: The duration of class C was significantly shorter in FTD than in controls and AD, and the duration of class D was significantly shorter in schizophrenia than in controls, FTD and AD. Transition analysis showed a reversed sequence of activation of classes C and D in FTD and schizophrenia patients compared with that in controls, with controls preferring transitions from C to D, and patients preferring D to C. CONCLUSION: The duration and sequence of EEG microstates reflect specific aberrations of frontal lobe functions in FTD and schizophrenia. SIGNIFICANCE: This study highlights the importance of subsecond brain dynamics for understanding of psychiatric disorders.

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Schizophrenia patients show abnormalities in a broad range of task demands. Therefore, an explanation common to all these abnormalities has to be sought independently of any particular task, ideally in the brain dynamics before a task takes place or during resting state. For the neurobiological investigation of such baseline states, EEG microstate analysis is particularly well suited, because it identifies subsecond global states of stable connectivity patterns directly related to the recruitment of different types of information processing modes (e.g., integration of top-down and bottom-up information). Meanwhile, there is an accumulation of evidence that particular microstate networks are selectively affected in schizophrenia. To obtain an overall estimate of the effect size of these microstate abnormalities, we present a systematic meta-analysis over all studies available to date relating EEG microstates to schizophrenia. Results showed medium size effects for two classes of microstates, namely, a class labeled C that was found to be more frequent in schizophrenia and a class labeled D that was found to be shortened. These abnormalities may correspond to core symptoms of schizophrenia, e.g., insufficient reality testing and self-monitoring as during auditory verbal hallucinations. As interventional studies have shown that these microstate features may be systematically affected using antipsychotic drugs or neurofeedback interventions, these findings may help introducing novel diagnostic and treatment options.

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Brian electric activity is viewed as sequences of momentary maps of potential distribution. Frequency-domain source modeling, estimation of the complexity of the trajectory of the mapped brain field distributions in state space, and microstate parsing were used as analysis tools. Input-presentation as well as task-free (spontaneous thought) data collection paradigms were employed. We found: Alpha EEG field strength is more affected by visualizing mentation than by abstract mentation, both input-driven as well as self-generated. There are different neuronal populations and brain locations of the electric generators for different temporal frequencies of the brain field. Different alpha frequencies execute different brain functions as revealed by canonical correlations with mentation profiles. Different modes of mentation engage the same temporal frequencies at different brain locations. The basic structure of alpha electric fields implies inhomogeneity over time — alpha consists of concatenated global microstates in the sub-second range, characterized by quasi-stable field topographies, and rapid transitions between the microstates. In general, brain activity is strongly discontinuous, indicating that parsing into field landscape-defined microstates is appropriate. Different modes of spontaneous and induced mentation are associated with different brain electric microstates; these are proposed as candidates for psychophysiological ``atoms of thought''.

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The temporal dynamics of the neural activity that implements the dimensions valence and arousal during processing of emotional stimuli were studied in two multi-channel ERP experiments that used visually presented emotional words (experiment 1) and emotional pictures (experiment 2) as stimulus material. Thirty-two healthy subjects participated (mean age 26.8 +/- 6.4 years, 24 women). The stimuli in both experiments were selected on the basis of verbal reports in such a way that we were able to map the temporal dynamics of one dimension while controlling for the other one. Words (pictures) were centrally presented for 450 (600) ms with interstimulus intervals of 1,550 (1,400) ms. ERP microstate analysis of the entire epochs of stimulus presentations parsed the data into sequential steps of information processing. The results revealed that in several microstates of both experiments, processing of pleasant and unpleasant valence (experiment 1, microstate #3: 118-162 ms, #6: 218-238 ms, #7: 238-266 ms, #8: 266-294 ms; experiment 2, microstate #5: 142-178 ms, #6: 178-226 ms, #7: 226-246 ms, #9: 262-302 ms, #10: 302-330 ms) as well as of low and high arousal (experiment 1, microstate #8: 266-294 ms, #9: 294-346 ms; experiment 2, microstate #10: 302-330 ms, #15: 562-600 ms) involved different neural assemblies. The results revealed also that in both experiments, information about valence was extracted before information about arousal. The last microstate of valence extraction was identical with the first microstate of arousal extraction.

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To assess (1) how large-scale correlation of intracranial EEG signals in the high-frequency range (80-200Hz) evolves from the pre-ictal, through the ictal into the postictal state and (2) whether the contribution of local neuronal activity to large-scale EEG correlation differentiates epileptogenic from non-epileptogenic brain tissue.

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Epileptic seizures typically reveal a high degree of stereotypy, that is, for an individual patient they are characterized by an ordered and predictable sequence of symptoms and signs with typically little variability. Stereotypy implies that ictal neuronal dynamics might have deterministic characteristics, presumably most pronounced in the ictogenic parts of the brain, which may provide diagnostically and therapeutically important information. Therefore the goal of our study was to search for indications of determinism in periictal intracranial electroencephalography (EEG) studies recorded from patients with pharmacoresistent epilepsy.

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Homeostasis within the central nervous system (CNS) is a prerequisite to elicit proper neuronal function. The CNS is tightly sealed from the changeable milieu of the blood stream by the blood-brain barrier (BBB) and the blood-cerebrospinal fluid (CSF) barrier (BCSFB). Whereas the BBB is established by specialized endothelial cells of CNS microvessels, the BCSFB is formed by the epithelial cells of the choroid plexus. Both constitute physical barriers by a complex network of tight junctions (TJs) between adjacent cells. During many CNS inflammatory disorders, such as multiple sclerosis, human immunodeficiency virus infection, or Alzheimer's disease, production of pro-inflammatory cytokines, matrix metalloproteases, and reactive oxygen species are responsible for alterations of CNS barriers. Barrier dysfunction can contribute to neurological disorders in a passive way by vascular leakage of blood-borne molecules into the CNS and in an active way by guiding the migration of inflammatory cells into the CNS. Both ways may directly be linked to alterations in molecular composition, function, and dynamics of the TJ proteins. This review summarizes current knowledge on the cellular and molecular aspects of the functional and dysfunctional TJ complexes at the BBB and the BCSFB, with a particular emphasis on CNS inflammation and the role of reactive oxygen species.

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Bovine herpesvirus 1 (BoHV-1) and BoHV-5 are closely related pathogens of cattle, but only BoHV-5 is considered a neuropathogen. We engineered intertypic gD exchange mutants with BoHV-1 and BoHV-5 backbones in order to address their in vitro and in vivo host ranges, with particular interest in invasion of the brain. The new viruses replicated in cell culture with similar dynamics and to titers comparable to those of their wild-type parents. However, gD of BoHV-5 (gD5) was able to interact with a surprisingly broad range of nectins. In vivo, gD5 provided a virulent phenotype to BoHV-1 in AR129 mice, featuring a high incidence of neurological symptoms and early onset of disease. However, only virus with the BoHV-5 backbone, independent of the gD type, was detected in the brain by immunohistology. Thus, gD of BoHV-5 confers an extended cellular host range to BoHV-1 and may be considered a virulence factor but does not contribute to the invasion of the brain.

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Differential cyp19 aromatase expression during development leads to sexual dimorphisms in the mammalian brain. Whether this is also true for fish is unknown. The aim of the current study has been to follow the expression of the brain-specific aromatase cyp19a2 in the brains of sexually differentiating zebrafish. To assess the role of cyp19a2 in the zebrafish brain during gonadal differentiation, we used quantitative reverse transcriptase-polymerase chain reaction and immunohistochemistry to detect differences in the transcript or protein levels and/or expression pattern in juvenile fish, histology to monitor the gonadal status, and double immunofluorescence with neuronal or radial glial markers to characterize aromatase-positive cells. Our data show that cyp19a2 expression levels during zebrafish sexual differentiation cannot be assigned to a particular sex; the expression pattern in the brain is similar in both sexes and aromatase-positive cells appear to be mostly of radial glial nature.

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The mechanisms causing brain damage after acute subdural hematoma (SDH) are poorly understood. A decrease in cerebral blood flow develops immediately after the hematoma forms, thus reducing cerebral oxygenation. This in turn may activate mitochondrial failure and tissue damage leading to ionic imbalance and possibly to cellular breakdown. The purpose of this study was to test whether a simple therapeutic measure, namely increased fraction of inspired oxygen (FiO2 100), and hence increased arterial and brain tissue oxygen tension, can influence brain glucose and lactate dynamics acutely after subdural hematoma in the rat. Twenty-five male Sprague-Dawley anesthetized rats were studied before, during and after induction of the SDH in two separate groups. The Oxygen group (n = 10) was ventilated with 100% oxygen immediately after induction of the SDH. The Air group (n = 10) was ventilated during the entire study with 21% oxygen. Brain microdialysate samples were analyzed for glucose and lactate. All rats were monitored with femoral arterial blood pressure catheters, arterial blood gas analysis, arterial glucose, lactate and end tidal CO2 (EtCO2). Five male Sprague-Dawley rats were sham operated to measure the effect of oxygen challenge on glucose-lactate dynamics without injury. Arterial oxygen tension in the Oxygen group was 371 +/- 30 mmHg and was associated with significantly greater increase in dialysate lactate in the first 30 min after induction of SDH. Dialysate glucose initially dropped in both groups, after SDH, but then reverted significantly faster to values above baseline in the Oxygen group. Changes in ventilatory parameters had no significant effect on dialysate glucose and lactate parameters in the sham group. Extracellular dialysate lactate and glucose are influenced by administration of 100% O2 after SDH. Dialysate glucose normalizes significantly quicker upon 100% oxygen ventilation. We hypothesize that increased neural tissue oxygen tension, in presence of reduced regional CBF, and possibly compromised mitochondrial function, after acute SDH results in upregulation of rate-limiting enzyme systems responsible for both glycolytic and aerobic metabolism. Similar changes have been seen in severe human head injury, and suggest that a simple therapeutic measure, such as early ventilation with 100% O2, may improve cerebral energy metabolism, early after SDH. Further studies to measure the generation of adenosine triphosphate (ATP) are needed to validate the hypothesis.

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Both deepening sleep and evolving epileptic seizures are associated with increasing slow-wave activity. Larger-scale functional networks derived from electroencephalogram indicate that in both transitions dramatic changes of communication between brain areas occur. During seizures these changes seem to be 'condensed', because they evolve more rapidly than during deepening sleep. Here we set out to assess quantitatively functional network dynamics derived from electroencephalogram signals during seizures and normal sleep. Functional networks were derived from electroencephalogram signals from wakefulness, light and deep sleep of 12 volunteers, and from pre-seizure, seizure and post-seizure time periods of 10 patients suffering from focal onset pharmaco-resistant epilepsy. Nodes of the functional network represented electrical signals recorded by single electrodes and were linked if there was non-random cross-correlation between the two corresponding electroencephalogram signals. Network dynamics were then characterized by the evolution of global efficiency, which measures ease of information transmission. Global efficiency was compared with relative delta power. Global efficiency significantly decreased both between light and deep sleep, and between pre-seizure, seizure and post-seizure time periods. The decrease of global efficiency was due to a loss of functional links. While global efficiency decreased significantly, relative delta power increased except between the time periods wakefulness and light sleep, and pre-seizure and seizure. Our results demonstrate that both epileptic seizures and deepening sleep are characterized by dramatic fragmentation of larger-scale functional networks, and further support the similarities between sleep and seizures.

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During the generalization of epileptic seizures, pathological activity in one brain area recruits distant brain structures into joint synchronous discharges. However, it remains unknown whether specific changes in local circuit activity are related to the aberrant recruitment of anatomically distant structures into epileptiform discharges. Further, it is not known whether aberrant areas recruit or entrain healthy ones into pathological activity. Here we study the dynamics of local circuit activity during the spread of epileptiform discharges in the zero-magnesium in vitro model of epilepsy. We employ high-speed multi-photon imaging in combination with dual whole-cell recordings in acute thalamocortical (TC) slices of the juvenile mouse to characterize the generalization of epileptic activity between neocortex and thalamus. We find that, although both structures are exposed to zero-magnesium, the initial onset of focal epileptiform discharge occurs in cortex. This suggests that local recurrent connectivity that is particularly prevalent in cortex is important for the initiation of seizure activity. Subsequent recruitment of thalamus into joint, generalized discharges is coincident with an increase in the coherence of local cortical circuit activity that itself does not depend on thalamus. Finally, the intensity of population discharges is positively correlated between both brain areas. This suggests that during and after seizure generalization not only the timing but also the amplitude of epileptiform discharges in thalamus is entrained by cortex. Together these results suggest a central role of neocortical activity for the onset and the structure of pathological recruitment of thalamus into joint synchronous epileptiform discharges.

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Recent functional magnetic resonance imaging (fMRI) studies consistently revealed contributions of fronto-parietal and related networks to the execution of a visuospatial judgment task, the so-called "Clock Task". However, due to the low temporal resolution of fMRI, the exact cortical dynamics and timing of processing during task performance could not be resolved until now. In order to clarify the detailed cortical activity and temporal dynamics, 14 healthy subjects performed an established version of the "Clock Task", which comprises a visuospatial task (angle discrimination) and a control task (color discrimination) with the same stimulus material, in an electroencephalography (EEG) experiment. Based on the time-resolved analysis of network activations (microstate analysis), differences in timing between the angle compared to the color discrimination task were found after sensory processing in a time window starting around 200ms. Significant differences between the two tasks were observed in an analysis window from 192ms to 776ms. We divided this window in two parts: an early phase - from 192ms to ∼440ms, and a late phase - from ∼440ms to 776ms. For both tasks, the order of network activations and the types of networks were the same, but, in each phase, activations for the two conditions were dominated by differing network states with divergent temporal dynamics. Our results provide an important basis for the assessment of deviations in processing dynamics during visuospatial tasks in clinical populations.