Variability in the analysis of a single neuroimaging dataset by many teams.

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

The significance and limited influence of cerebrovascular reactivity on age and sex effects in task- and resting-state brain activity.

Functional MRI measures the blood-oxygen-level dependent signals, which provide an indirect measure of neural activity mediated by neurovascular responses. Cerebrovascular reactivity affects both task-induced and resting-state blood-oxygen-level dependent activity and may confound inter-individual effects, such as those related to aging and biological sex. We examined a large dataset containing breath-holding, checkerboard, and resting-state tasks. We used the breath-holding task to measure cerebrovascular reactivity, used the checkerboard task to obtain task-based activations, and quantified resting-state activity with amplitude of low-frequency fluctuations and regional homogeneity. We hypothesized that cerebrovascular reactivity would be correlated with blood-oxygen-level dependent measures and that accounting for these correlations would result in better estimates of age and sex effects. We found that cerebrovascular reactivity was correlated with checkerboard task activations in the visual cortex and with amplitude of low-frequency fluctuations and regional homogeneity in widespread fronto-parietal regions, as well as regions with large vessels. We also found significant age and sex effects in cerebrovascular reactivity, some of which overlapped with those observed in amplitude of low-frequency fluctuations and regional homogeneity. However, correcting for the effects of cerebrovascular reactivity had very limited influence on the estimates of age and sex. Our results highlight the limitations of accounting for cerebrovascular reactivity with the current breath-holding task.

Network-wise analysis of movie-specific information in dynamic functional connectivity using COBE.

Movie watching during functional magnetic resonance imaging has emerged as a promising tool to measure the complex behavior of the brain in response to a stimulus similar to real-life situations. It has been observed that presenting a movie (sequence of events) as a stimulus will lead to a unique time course of dynamic functional connectivity related to movie stimuli that can be compared across the participants. We assume that the observed dynamic functional connectivity across subjects can be divided into following 2 components: (i) specific to a movie stimulus (depicting group-level behavior in functional connectivity) and (ii) individual-specific behavior (not necessarily common across the subjects). In this work, using the dynamic time warping distance measure, we have shown the extent of similarity between the temporal sequences of functional connectivity while the underlying movie stimuli were same and different. Further, the temporal sequence of functional connectivity patterns related to a movie is enhanced by suppressing the subject-specific components of dynamic functional connectivity using common and orthogonal basis extraction. Quantitative analysis using the F-ratio measure reveals significant differences in dynamic functional connectivity within the somatomotor network and default mode network, as well as between the occipital network and somatomotor networks.

Altered white matter functional pathways in Alzheimer's disease.

Alzheimer's disease (AD) is associated with functional disruption in gray matter (GM) and structural damage to white matter (WM), but the relationship to functional signal in WM is unknown. We performed the functional connectivity (FC) and graph theory analysis to investigate abnormalities of WM and GM functional networks and corpus callosum among different stages of AD from a publicly available dataset. Compared to the controls, AD group showed significantly decreased FC between the deep WM functional network (WM-FN) and the splenium of corpus callosum, between the sensorimotor/occipital WM-FN and GM visual network, but increased FC between the deep WM-FN and the GM sensorimotor network. In the clinical groups, the global assortativity, modular interaction between occipital WM-FN and visual network, nodal betweenness centrality, degree centrality, and nodal clustering coefficient in WM- and GM-FNs were reduced. However, modular interaction between deep WM-FN and sensorimotor network, and participation coefficients of deep WM-FN and splenium of corpus callosum were increased. These findings revealed the abnormal integration of functional networks in different stages of AD from a novel WM-FNs perspective. The abnormalities of WM functional pathways connect downward to the corpus callosum and upward to the GM are correlated with AD.

Boosting interpersonal emotion regulation through facial imitation: functional neuroimaging foundations.

Empathic function, which is primarily manifested by facial imitation, is believed to play a pivotal role in interpersonal emotion regulation for mood reinstatement. To explore this association and its neural substrates, we performed a questionnaire survey (study l) to identify the relationship between empathy and interpersonal emotion regulation; and a task-mode fMRI study (study 2) to explore how facial imitation, as a fundamental component of empathic processes, promotes the interpersonal emotion regulation effect. Study 1 showed that affective empathy was positively correlated with interpersonal emotion regulation. Study 2 showed smaller negative emotions in facial imitation interpersonal emotion regulation (subjects imitated experimenter's smile while followed the interpersonal emotion regulation guidance) than in normal interpersonal emotion regulation (subjects followed the interpersonal emotion regulation guidance) and Watch conditions. Mirror neural system (e.g. inferior frontal gyrus and inferior parietal lobe) and empathy network exhibited greater activations in facial imitation interpersonal emotion regulation compared with normal interpersonal emotion regulation condition. Moreover, facial imitation interpersonal emotion regulation compared with normal interpersonal emotion regulation exhibited increased functional coupling from mirror neural system to empathic and affective networks during interpersonal emotion regulation. Furthermore, the connectivity of the right orbital inferior frontal gyrus-rolandic operculum lobe mediated the association between the accuracy of facial imitation and the interpersonal emotion regulation effect. These results show that the interpersonal emotion regulation effect can be enhanced by the target's facial imitation through increased functional coupling from mirror neural system to empathic and affective neural networks.

The critical mediating roles of the middle temporal gyrus and ventrolateral prefrontal cortex in the dynamic processing of interpersonal emotion regulation.

Interpersonal emotion regulation (IER) is a crucial ability for effectively recovering from negative emotions through social interaction. It has been emphasized that the empathy network, cognitive control network, and affective generation network sustain the deployment of IER. However, the temporal dynamics of functional connectivity among these networks of IER remains unclear. This study utilized IER task-fMRI and sliding window approach to examine both the stationary and dynamic functional connectivity (dFC) of IER. Fifty-five healthy participants were recruited for the present study. Through clustering analysis, four distinct brain states were identified in dFC. State 1 demonstrated situation modification stage of IER, with strong connectivity between affective generation and visual networks. State 2 exhibited pronounced connectivity between empathy network and both cognitive control and affective generation networks, reflecting the empathy stage of IER. Next, a 'top-down' pattern is observed between the connectivity of cognitive control and affective generation networks during the cognitive control stage of state 3. The affective response modulation stage of state 4 mainly involved connections between empathy and affective generation networks. Specifically, the degree centrality of the left middle temporal gyrus (MTG) mediated the association between one's IER tendency and the regulatory effects in state 2. The betweenness centrality of the left ventrolateral prefrontal cortex (VLPFC) mediated the association between one's IER efficiency and the regulatory effects in state 3. Altogether, these findings revealed that dynamic connectivity transitions among empathy, cognitive control, and affective generation networks, with the left VLPFC and MTG playing dominant roles, evident across the IER processing.

Estimation of static and dynamic functional connectivity in resting-state fMRI using zero-frequency resonator.

Resting-state functional magnetic resonance imaging (rs-fMRI) is increasingly being used to infer the functional organization of the brain. Blood oxygen level-dependent (BOLD) features related to spontaneous neuronal activity, are yet to be clearly understood. Prior studies have hypothesized that rs-fMRI is spontaneous event-related and these events convey crucial information about the neuronal activity in estimating resting state functional connectivity (FC). Attempts have been made to extract these temporal events using a predetermined threshold. However, the thresholding methods in addition to being very sensitive to noise, may consider redundant events or exclude the low-valued inflection points. Here, we extract the event-related temporal onsets from the rs-fMRI time courses using a zero-frequency resonator (ZFR). The ZFR reflects the transient behavior of the BOLD events at its output. The conditional rate (CR) of the BOLD events occurring in a time course with respect to a seed time course is used to derive static FC. The temporal activity around the estimated events called high signal-to-noise ratio (SNR) segments are also obtained in the rs-fMRI time course and are then used to compute static and dynamic FCs during rest. Coactivation pattern (CAP) is the dynamic FC obtained using the high SNR segments driven by the ZFR. The static FC demonstrates that the ZFR-based CR distinguishes the coactivation and non-coactivation scores well in the distribution. CAP analysis demonstrated the stable and longer dwell time dominant resting state functional networks with high SNR segments driven by the ZFR. Static and dynamic FC analysis underpins that the ZFR-driven temporal onsets of BOLD events derive reliable and consistent FCs in the resting brain using a subset of the time points.

Cerebrovascular reactivity increases across development in multiple networks as revealed by a breath-holding task: A longitudinal fMRI study.

Functional magnetic resonance imaging (fMRI) has been widely used to understand the neurodevelopmental changes that occur in cognition and behavior across childhood. The blood-oxygen-level-dependent (BOLD) signal obtained from fMRI is understood to be comprised of both neuronal and vascular information. However, it is unclear whether the vascular response is altered across age in studies investigating development in children. Since the breath-hold (BH) task is commonly used to understand cerebrovascular reactivity (CVR) in fMRI studies, it can be used to account for developmental differences in vascular response. This study examines how the cerebrovascular response changes over age in a longitudinal children's BH data set from the Nathan Kline Institute (NKI) Rockland Sample (aged 6-18 years old at enrollment). A general linear model approach was applied to derive CVR from BH data. To model both the longitudinal and cross-sectional effects of age on BH response, we used mixed-effects modeling with the following terms: linear, quadratic, logarithmic, and quadratic-logarithmic, to find the best-fitting model. We observed increased BH BOLD signals in multiple networks across age, in which linear and logarithmic mixed-effects models provided the best fit with the lowest Akaike information criterion scores. This shows that the cerebrovascular response increases across development in a brain network-specific manner. Therefore, fMRI studies investigating the developmental period should account for cerebrovascular changes that occur with age.

Compressed cerebro-cerebellar functional gradients in children and adolescents with attention-deficit/hyperactivity disorder.

Both cortical and cerebellar developmental differences have been implicated in attention-deficit/hyperactivity disorder (ADHD). Recently accumulating neuroimaging studies have highlighted hierarchies as a fundamental principle of brain organization, suggesting the importance of assessing hierarchy abnormalities in ADHD. A novel gradient-based resting-state functional connectivity analysis was applied to investigate the cerebro-cerebellar disturbed hierarchy in children and adolescents with ADHD. We found that the interaction of functional gradient between diagnosis and age was concentrated in default mode network (DMN) and visual network (VN). At the same time, we also found that the opposite gradient changes of DMN and VN caused the compression of the cortical main gradient in ADHD patients, implicating the co-occurrence of both low- (visual processing) and high-order (self-related thought) cognitive dysfunction manifesting in abnormal cerebro-cerebellar organizational hierarchy in ADHD. Our study provides a neurobiological framework to better understand the co-occurrence and interaction of both low-level and high-level functional abnormalities in the cortex and cerebellum in ADHD.

Frequency-dependent alterations of global signal topography in patients with major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is associated not only with disorders in multiple brain networks but also with frequency-specific brain activities. The abnormality of spatiotemporal networks in patients with MDD remains largely unclear. METHODS: We investigated the alterations of the global spatiotemporal network in MDD patients using a large-sample multicenter resting-state functional magnetic resonance imaging dataset. The spatiotemporal characteristics were measured by the variability of global signal (GS) and its correlation with local signals (GSCORR) at multiple frequency bands. The association between these indicators and clinical scores was further assessed. RESULTS: The GS fluctuations were reduced in patients with MDD across the full frequency range (0-0.1852 Hz). The GSCORR was also reduced in the MDD group, especially in the relatively higher frequency range (0.0728-0.1852 Hz). Interestingly, these indicators showed positive correlations with depressive scores in the MDD group and relative negative correlations in the control group. CONCLUSION: The GS and its spatiotemporal effects on local signals were weakened in patients with MDD, which may impair inter-regional synchronization and related functions. Patients with severe depression may use the compensatory mechanism to make up for the functional impairments.