Critical dynamics in spontaneous resting-state oscillations are associated with the attention-related P300 ERP in a go/nogo task

Sustained attention is the ability to continually concentrate on task-relevant information, even in the presence of distraction. Understanding the neural mechanisms underlying this ability is critical for comprehending attentional processes as well as neuropsychiatric disorders characterized by attentional deficits, such as attention deficit hyperactivity disorder (ADHD). In this study, we aimed to investigate how trait-like critical oscillations during rest relate to the P300 evoked potential-a biomarker commonly used to assess attentional deficits. We measured long-range temporal correlations (LRTC) in resting-state EEG oscillations as index for criticality of the signal. In addition, the attentional performance of the subjects was assessed as reaction time variability (RTV) in a continuous performance task following an oddball paradigm. P300 amplitude and latencies were obtained from EEG recordings during this task. We found that, after controlling for individual variability in task performance, LRTC were positively associated with P300 amplitudes but not latencies. In line with previous findings, good performance in the sustained attention task was related to higher P300 amplitudes and earlier peak latencies. Unexpectedly, we observed a positive relationship between LRTC in ongoing oscillations during rest and RTV, indicating that greater criticality in brain oscillations during rest relates to worse task performance. In summary, our results show that resting-state neuronal activity, which operates near a critical state, relates to the generation of higher P300 amplitudes. Brain dynamics close to criticality potentially foster a computationally advantageous state which promotes the ability to generate higher event-related potential (ERP) amplitudes

A comparison of third-generation semi-invasive arterial waveform analysis with thermodilution in patients undergoing coronary surgery

Uncalibrated semi-invasive continous monitoring of cardiac index (CI) has recently gained increasing interest. The aim of the present study was to compare the accuracy of CI determination based on arterial waveform analysis with transpulmonary thermodilution. Fifty patients scheduled for elective coronary surgery were studied after induction of anaesthesia and before and after cardiopulmonary bypass (CPB), respectively. Each patient was monitored with a central venous line, the PiCCO system, and the FloTrac/Vigileo-system. Measurements included CI derived by transpulmonary thermodilution and uncalibrated semi-invasive pulse contour analysis. Percentage changes of CI were calculated. There was a moderate, but significant correlation between pulse contour CI and thermodilution CI both before (r(2) = 0.72, P < 0.0001) and after (r(2) = 0.62, P < 0.0001) CPB, with a percentage error of 31% and 25%, respectively. Changes in pulse contour CI showed a significant correlation with changes in thermodilution CI both before (r(2) = 0.52, P < 0.0001) and after (r(2) = 0.67, P < 0.0001) CPB. Our findings demonstrated that uncalibrated semi-invasive monitoring system was able to reliably measure CI compared with transpulmonary thermodilution in patients undergoing elective coronary surgery. Furthermore, the semi-invasive monitoring device was able to track haemodynamic changes and trends

Assessment of the effect of tricaine (MS-222)-induced anesthesia on brain-wide neuronal activity of zebrafish (Danio rerio) larvae

Fast and effective anesthesia is the key for refining many invasive procedures in fish and gaining reliable data. For fish as for all vertebrates, it is also required by European law to reduce pain, suffering, and distress to the unavoidable minimum in husbandry and experiments. The most often used substance to induce anesthesia in zebrafish is tricaine (MS-222). When properly prepared and dosed, tricaine causes rapid loss of mobility, balance and reaction to touch. These signs are interpreted as a stage of deep anesthesia although its effects on the central nervous system have not convincingly been shown. Therefore, it might be possible that tricaine first acts only on the periphery, resulting in a paralyzed instead of an anesthetized fish. This has severe implications for animals undergoing procedures. To investigate the effects of tricaine on the central nervous system, we used zebrafish larvae [Tg( elavl3 :H2B-GCaMP6s)] at 4 days post fertilization (dpf), expressing a calcium indicator (GCaMP6s) in all neurons, that allows monitoring and quantifying the neuronal activity. After treating larvae with 168 mg/L tricaine, a rapid loss of neuronal activity in the forebrain was observed in confocal microscopy. In contrast, only mild effects were seen in the midbrain and hindbrain. In conclusion, the different larval brain areas showed differences in the sensitivity to tricaine treatment. The effects on the central nervous system are indicative of tricaine’s anesthetic function and are consistent with behavioral observations of inactivity and unresponsiveness to touch

Defining the optimal animal model for translational research using gene set enrichment analysis

The mouse is the main model organism used to study the functions of human genes because most biological processes in the mouse are highly conserved in humans. Recent reports that compared identical transcriptomic datasets of human inflammatory diseases with datasets from mouse models using traditional gene‐to‐gene comparison techniques resulted in contradictory conclusions regarding the relevance of animal models for translational research. To reduce susceptibility to biased interpretation, all genes of interest for the biological question under investigation should be considered. Thus, standardized approaches for systematic data analysis are needed. We analyzed the same datasets using gene set enrichment analysis focusing on pathways assigned to inflammatory processes in either humans or mice. The analyses revealed a moderate overlap between all human and mouse datasets, with average positive and negative predictive values of 48 and 57% significant correlations. Subgroups of the septic mouse models (i.e., Staphylococcus aureus injection) correlated very well with most human studies. These findings support the applicability of targeted strategies to identify the optimal animal model and protocol to improve the success of translational research

Towards Systems Biology of Heterosis: A Hypothesis about Molecular Network Structure Applied for the Arabidopsis Metabolome

We propose a network structure-based model for heterosis, and investigate it relying on metabolite profiles from Arabidopsis. A simple feed-forward two-layer network model (the Steinbuch matrix) is used in our conceptual approach. It allows for directly relating structural network properties with biological function. Interpreting heterosis as increased adaptability, our model predicts that the biological networks involved show increasing connectivity of regulatory interactions. A detailed analysis of metabolite profile data reveals that the increasing-connectivity prediction is true for graphical Gaussian models in our data from early development. This mirrors properties of observed heterotic Arabidopsis phenotypes. Furthermore, the model predicts a limit for increasing hybrid vigor with increasing heterozygosity—a known phenomenon in the literature

Simulation of DNA array hybridization experiments and evaluation of critical parameters during subsequent image and data analysis

BACKGROUND: Gene expression analyses based on complex hybridization measurements have increased rapidly in recent years and have given rise to a huge amount of bioinformatic tools such as image analyses and cluster analyses. However, the amount of work done to integrate and evaluate these tools and the corresponding experimental procedures is not high. Although complex hybridization experiments are based on a data production pipeline that incorporates a significant amount of error parameters, the evaluation of these parameters has not been studied yet in sufficient detail. RESULTS: In this paper we present simulation studies on several error parameters arising in complex hybridization experiments. A general tool was developed that allows the design of exactly defined hybridization data incorporating, for example, variations of spot shapes, spot positions and local and global background noise. The simulation environment was used to judge the influence of these parameters on subsequent data analysis, for example image analysis and the detection of differentially expressed genes. As a guide for simulating expression data real experimental data were used and model parameters were adapted to these data. Our results show how measurement error can be balanced by the analysis tools. CONCLUSIONS: We describe an implemented model for the simulation of DNA-array experiments. This tool was used to judge the influence of critical parameters on the subsequent image analysis and differential expression analysis. Furthermore the tool can be used to guide future experiments and to improve performance by better experimental design. Series of simulated images varying specific parameters can be downloaded from our web-site: http://www.molgen.mpg.de/~lh_bioinf/projects/simulation/biotech