Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions; however, it is unclear how this mechanism manifests over time. In this ...study, we used time-resolved network analysis of fMRI data to demonstrate that the human brain traverses between functional states that maximize either segregation into tight-knit communities or integration across otherwise disparate neural regions. Integrated states enable faster and more accurate performance on a cognitive task, and are associated with dilations in pupil diameter, suggesting that ascending neuromodulatory systems may govern the transition between these alternative modes of brain function. Together, our results confirm a direct link between cognitive performance and the dynamic reorganization of the network structure of the brain.
•The human brain network traverses segregated and integrated states over time•Integrated states enable fast, effective performance on an N-back task•Integrated states track with fluctuations in pupil diameter•Cognitive performance relates to the dynamic reorganization of brain architecture
Shine et al. use dynamic analyses of fMRI data to demonstrate that the network architecture of the human brain fluctuates between states of high and low global integration that track with effective task performance and may relate to fluctuations in arousal.
Preprocessing of functional magnetic resonance imaging (fMRI) involves numerous steps to clean and standardize the data before statistical analysis. Generally, researchers create ad hoc preprocessing ...workflows for each dataset, building upon a large inventory of available tools. The complexity of these workflows has snowballed with rapid advances in acquisition and processing. We introduce fMRIPrep, an analysis-agnostic tool that addresses the challenge of robust and reproducible preprocessing for fMRI data. fMRIPrep automatically adapts a best-in-breed workflow to the idiosyncrasies of virtually any dataset, ensuring high-quality preprocessing without manual intervention. By introducing visual assessment checkpoints into an iterative integration framework for software testing, we show that fMRIPrep robustly produces high-quality results on a diverse fMRI data collection. Additionally, fMRIPrep introduces less uncontrolled spatial smoothness than observed with commonly used preprocessing tools. fMRIPrep equips neuroscientists with an easy-to-use and transparent preprocessing workflow, which can help ensure the validity of inference and the interpretability of results.
This paper presents an acoustic emission-based method for the condition monitoring of low speed reversible slew bearings. Several acoustic emission (AE) hit parameters as the monitoring parameters ...for the detection of impending failure of slew bearings are reviewed first. The review focuses on: (1) the application of AE in typical rolling element bearings running at different speed classifications, i.e. high speed (>600rpm), low speed (10–600rpm) and very low speed (<10rpm); (2) the commonly used AE hit parameters in rolling element bearings and (3) AE signal processing, feature extraction and pattern recognition methods. In the experiment, impending failure of the slew bearing was detected by the AE hit parameters after the new bearing had run continuously for approximately 15 months. The slew bearing was then dismantled and the evidence of the early defect was analysed. Based on the result, we propose a feature extraction method of the AE waveform signal using the largest Lyapunov exponent (LLE) algorithm and demonstrate that the LLE feature can detect the sign of failure earlier than the AE hit parameters with improved prediction of the progressive trend of the defect.
•This paper presents an AE-based method for the condition monitoring of low speed slew bearing.•The use of AE as the condition monitoring method of rolling element bearings is reviewed.•A feature extraction method of the AE waveform signal using the largest Lyapunov exponent (LLE) algorithm is proposed.
Emotion regulation (ER) is an important skill for well-being. Cognitive reappraisal is a goal-oriented cognitive change strategy. Acceptance involves decentering from immediate habits of reactivity, ...observing moment-to-moment shifts in thoughts, emotions, and sensations. These two regulation strategies are thought to have different effects on emotion; however, no study has examined the differential effects of reappraisal and acceptance on behavioral, autonomic, and brain responses in the context of ideographic personally salient negative self-beliefs. Thirty-five right-handed, healthy adults were presented idiographic negative self-beliefs embedded in autobiographical scripts. We measured negative emotion ratings, autonomic psychophysiology, and functional magnetic resonance imaging blood oxygen-level dependent responses while participants read neutral statements, reacted to their own negative self-beliefs, and implemented reappraisal and acceptance strategies. Compared with react, reappraisal resulted in significantly lesser negative emotion and respiration rate; no differences in heart rate and skin conductance level; greater brain responses implicated in cognitive control, language, and social cognition; and lesser amygdala responses. Compared with react, acceptance resulted in significantly lesser negative emotion, respiration rate, and heart rate; no difference in skin conductance level; and greater brain responses in networks implicated in cognitive control and attention. Compared with acceptance, reappraisal resulted in significantly lesser negative emotion; no difference in respiration rate and skin conductance level; higher heart rate; greater brain responses in brain regions implicated in cognitive control; and lesser brain responses in amygdala. Reappraisal is more effective than acceptance in down-regulating negative emotion, but may require greater recruitment of autonomic, cognitive, and brain resources.
ClinicalTrials.gov
identifier: NCT02036658
Functional magnetic resonance imaging (fMRI) is a standard tool to investigate the neural correlates of cognition. fMRI noninvasively measures brain activity, allowing identification of patterns ...evoked by tasks performed during scanning. Despite the long history of this technique, the idiosyncrasies of each dataset have led to the use of ad-hoc preprocessing protocols customized for nearly every different study. This approach is time consuming, error prone and unsuitable for combining datasets from many sources. Here we showcase fMRIPrep (http://fmriprep.org), a robust tool to prepare human fMRI data for statistical analysis. This software instrument addresses the reproducibility concerns of the established protocols for fMRI preprocessing. By leveraging the Brain Imaging Data Structure to standardize both the input datasets (MRI data as stored by the scanner) and the outputs (data ready for modeling and analysis), fMRIPrep is capable of preprocessing a diversity of datasets without manual intervention. In support of the growing popularity of fMRIPrep, this protocol describes how to integrate the tool in a task-based fMRI investigation workflow.
This paper presents a new application of the largest Lyapunov exponent (LLE) algorithm for feature extraction method in low speed slew bearing condition monitoring. The LLE algorithm is employed to ...measure the degree of non-linearity of the vibration signal which is not easily monitored by existing methods. The method is able to detect changes in the condition of the bearing and demonstrates better tracking of the progressive deterioration of the bearing during the 139 measurement days than comparable methods such as the time domain feature methods based on root mean square (RMS), skewness and kurtosis extraction from the raw vibration signal and also better than extracting similar features from selected intrinsic mode functions (IMFs) of the empirical mode decomposition (EMD) result. The application of the method is demonstrated with laboratory slew bearing vibration data and industrial bearing data from a coal bridge reclaimer used in a local steel mill.
•This paper presents a new application of the largest Lyapunov exponent (LLE) algorithm for feature extraction.•The increase deterioration level of slew bearing is detected.•The comparison between LLE feature and time-domain features and EMD is reported.•The most important LLE parameters namely reconstruction delay J is selected based on the FFT.
When confronted with unwanted negative emotions, individuals use a variety of cognitive strategies for regulating these emotions. The brain mechanisms underlying these emotion regulation strategies ...have not been fully characterized, and it is not yet clear whether these mechanisms vary as a function of emotion intensity. To address these issues, 30 community participants (17 females, 13 males, M
age
= 24.3 years) completed a picture-viewing emotion regulation task with neutral viewing, reacting to negative stimuli, cognitive reappraisal, attentional deployment, and self-distancing conditions. Brain and behavioral data were simultaneously collected in a 3T GE MRI scanner. Findings indicated that prefrontal regions were engaged by all three regulation strategies, but reappraisal showed the least amount of increase in activity as a function of intensity. Overall, these results suggest that there are both brain and behavioral effects of intensity and that intensity is useful for probing strategy-specific effects and the relationships between the strategies. Furthermore, while these three strategies showed significant overlap, there also were specific strategy-intensity interactions, such as frontoparietal control regions being preferentially activated by reappraisal and self-distancing. Conversely, self-referential and attentional regions were preferentially recruited by self-distancing and distraction as intensity increased. Overall, these findings are consistent with the notion that there is a continuum of cognitive emotion regulation along which all three of these strategies lie.
Social anxiety disorder (SAD) is characterized by negative self-referential processing, which triggers excessive emotional reactivity. In healthy individuals, positive self-views typically ...predominate and are supported by regions of the default mode network (DMN) that represent self-related information and regions of the frontoparietal control network (FPCN) that contribute to metacognitive awareness and emotion regulation. The current study used functional magnetic resonance imaging (fMRI) to examine patterns of DMN and FPCN activation during positive and negative self-referential judgments in SAD patients (
N
= 97) and controls (
N
= 34). As expected, SAD patients demonstrated a striking difference in self-beliefs compared with non-anxious healthy controls, endorsing fewer positive traits and more negative traits. However, SAD patients and controls demonstrated largely similar patterns of DMN and FPCN recruitment during self-referential judgements. No significant group differences were observed. However, equivalence testing identified numerous regions demonstrating effect sizes that were not small enough to conclude that they were practically equivalent to zero, despite the nonsignificant null hypothesis test. These regions may be key targets to investigate in future studies using larger samples.
The aim of this study was to characterize neural activation during the processing of negative facial expressions in a non-clinical group of individuals characterized by two factors: the levels of ...stress experienced in early life and in adulthood. Two models of stress consequences were investigated: the match/mismatch and cumulative stress models. The match/mismatch model assumes that early adversities may promote optimal coping with similar events in the future through fostering the development of coping strategies. The cumulative stress model assumes that effects of stress are additive, regardless of the timing of the stressors. Previous studies suggested that stress can have both cumulative and match/mismatch effects on brain structure and functioning and, consequently, we hypothesized that effects on brain circuitry would be found for both models. We anticipated effects on the neural circuitry of structures engaged in face perception and emotional processing. Hence, the amygdala, fusiform face area, occipital face area, and posterior superior temporal sulcus were selected as seeds for seed-based functional connectivity analyses. The interaction between early and recent stress was related to alterations during the processing of emotional expressions mainly in to the cerebellum, middle temporal gyrus, and supramarginal gyrus. For cumulative stress levels, such alterations were observed in functional connectivity to the middle temporal gyrus, lateral occipital cortex, precuneus, precentral and postcentral gyri, anterior and posterior cingulate gyri, and Heschl’s gyrus. This study adds to the growing body of literature suggesting that both the cumulative and the match/mismatch hypotheses are useful in explaining the effects of stress.
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