Hub Regions Research Articles

Hub vulnerability and short path length to entorhinal cortex are associated with tau binding in Alzheimer’s disease: a combined MEG/PET study

AbstractBackgroundBrain network studies have revealed that highly connected ‘hub’ regions are particularly vulnerable to Alzheimer’s disease (AD) pathology. Additionally, the ‘‘transneuronal spread” hypothesis proposes that a toxic agent (tau) propagates along shortest paths through functionally connected neurons, driven by aberrant neuronal activity. We investigate whether network characteristics as determined using magnetoencephalography (MEG) are correlated to tau pathology in the different stages of AD.MethodWe analysed source‐reconstructed MEG data and dynamic 100‐minutes [18F]flortaucipir PET from 57 subjects positive for amyloid‐beta (Aβ)‐pathology (preclinical AD (n = 16)), mild cognitive impairment (MCI (n = 16)) and AD dementia (n = 25)). Cognitively healthy subjects without Aβ‐pathology were included as controls (n = 25). For each subject, we obtained a network based on the alpha band amplitude envelope correlation (AEC‐c, 8‐13Hz), and theta band phase lag index (PLI, 4‐8Hz), based on the Brainnettome atlas. For each node in the network, we obtained the following measures: weighted degree, degree, betweenness centrality, eccentricity (as measures of hubness); distance to left entorhinal cortex (measure of shortest path/transneuronal spread); hub disruption index for all previous hubness measures (selective hub damage) and [18F]flortaucipir BPND. Pearson’s correlations were calculated between group averages of network measures and tau‐PET binding (FDR‐corrected). Furthermore, we analysed whether network measures of the previous disease stage correlated with [18F]flortaucipir retention in the subsequent disease stage.ResultHub regions were predominantly found in the temporal areas (Fig‐1). Higher ‘hubness’ and shorter neuronal distance to epicentre were associated to higher tau binding in all stages of the AD continuum (Fig‐2a). Disproportional disruption to hub regions in the AEC‐c alpha band was associated with increased tau binding, but the opposite effect was found for the PLI theta band (Fig‐2b). Finally, high weighted degree, degree, and betweenness centrality in the preceding disease stage were correlated with increased tau binding in subsequent disease stages (Fig‐2c).ConclusionHub regions and transneuronal spreading are key mechanisms in the propagation of tau pathology across the AD brain. Furthermore, hubs are particularly vulnerable to tau. The insight that high neuronal activity might play a causal role in Alzheimer’s disease can have implications for early detection and interventional strategies.

Hippocampal Engrams Generate Variable Behavioral Responses and Brain-Wide Network States.

Freezing is a defensive behavior commonly examined during hippocampal-mediated fear engram reactivation. How these cellular populations engage the brain and modulate freezing across varying environmental demands is unclear. To address this, we optogenetically reactivated a fear engram in the dentate gyrus subregion of the hippocampus across three distinct contexts in male mice. We found that there were differential amounts of light-induced freezing depending on the size of the context in which reactivation occurred: mice demonstrated robust light-induced freezing in the most spatially restricted of the three contexts but not in the largest. We then utilized graph theoretical analyses to identify brain-wide alterations in cFos expression during engram reactivation across the smallest and largest contexts. Our manipulations induced positive interregional cFos correlations that were not observed in control conditions. Additionally, regions spanning putative "fear" and "defense" systems were recruited as hub regions in engram reactivation networks. Lastly, we compared the network generated from engram reactivation in the small context with a natural fear memory retrieval network. Here, we found shared characteristics such as modular composition and hub regions. By identifying and manipulating the circuits supporting memory function, as well as their corresponding brain-wide activity patterns, it is thereby possible to resolve systems-level biological mechanisms mediating memory's capacity to modulate behavioral states.

Effects of individual metabolic brain network changes co-affected by T2DM and aging on the probabilities of T2DM: protective and risk factors.

Neuroimaging markers for risk and protective factors related to type 2 diabetes mellitus are critical for clinical prevention and intervention. In this work, the individual metabolic brain networks were constructed with Jensen-Shannon divergence for 4 groups (elderly type 2 diabetes mellitus and healthy controls, and middle-aged type 2 diabetes mellitus and healthy controls). Regional network properties were used to identify hub regions. Rich-club, feeder, and local connections were subsequently obtained, intergroup differences in connections and correlations between them and age (or fasting plasma glucose) were analyzed. Multinomial logistic regression was performed to explore effects of network changes on the probability of type 2 diabetes mellitus. The elderly had increased rich-club and feeder connections, and decreased local connection than the middle-aged among type 2 diabetes mellitus; type 2 diabetes mellitus had decreased rich-club and feeder connections than healthy controls. Protective factors including glucose metabolism in triangle part of inferior frontal gyrus, metabolic connectivity between triangle of the inferior frontal gyrus and anterior cingulate cortex, degree centrality of putamen, and risk factors including metabolic connectivities between triangle of the inferior frontal gyrus and Heschl's gyri were identified for the probability of type 2 diabetes mellitus. Metabolic interactions among critical brain regions increased in type 2 diabetes mellitus with aging. Individual metabolic network changes co-affected by type 2 diabetes mellitus and aging were identified as protective and risk factors for the likelihood of type 2 diabetes mellitus, providing guiding evidence for clinical interventions.

NCOG-07. HUB-RELATED GRAPH METRICS AS MARKER FOR COGNITIVE OUTCOMES IN ADULT GLIOMA SURVIVORS AFTER MULTIMODAL THERAPY

Abstract BACKGROUND Although cognitive impairment is a prevalent long-term side effect in glioma survivors, predictive imaging-based markers remain inconsistent to date. Structural brain network topology could be altered by both the tumor and its’ treatment through reorganization of hubs (i.e. highly interconnected nodes). Here, we explored the role of nodal hub-related graph metrics in cognitive functioning. METHODS 48 WHO grade 2-3 adult glioma survivors ( > 1y post-therapy) and 42 matched controls, underwent a cognitive assessment. Cognitive scores were transformed into w-scores, corrected for age and education. Weighted nodal graph metrics were calculated based on diffusion weighted imaging. Hubs were calculated based on 4 nodal metrics. Significant differences in nodal graph metrics between patients and controls, and hubs versus non-hubs were tested in a repeated measures ANOVA, using Bonferroni correction for multiple testing. Significant group differences in nodal graph metrics were correlated to cognitive scores per domain. RESULTS In controls, 12/78 nodes were defined as hubs. In survivors, the left superior-parietal region and left putamen had a significantly lower likelihood of being a hub (p< .001). These areas showed assortativity to be positively correlated with attention, language and executive function (r(90) > .51,p< .001) and characteristic path length to be negatively correlated with all cognitive domains (r(90) > .51, p< .001). Nodal metrics of clustering coefficient, characteristic path length, local efficiency and assortativity were significantly different between groups in both hub and non-hub regions (p< .001). Except for betweenness centrality, all nodal metrics strongly correlated with cognitive outcomes, occurring more often in hubs (33-50%) than intermediate hubs (10-33%) or non-hubs (4-12%). CONCLUSION Reorganization of hubs is frequently observed in this cohort of glioma survivors. Hub connectivity seems to be important in cognitive functioning, more than for non-hub regions. Therefore, structural nodal hub-related graph metrics might be important in predicting cognitive outcomes.

Investigating altered brain functional hubs and causal connectivity in coronary artery disease with cognitive impairment.

Coronary artery disease (CAD) and cognitive impairment (CI) have become significant global disease and medical burdens. There have been several reports documenting the alterations in regional brain function and their correlation with CI in CAD patients. However, there is limited research on the changes in brain network connectivity in CAD patients. To investigate the resting-state connectivity and further understand the effective connectivity strength and directionality in patients with CAD, we utilized degree centrality (DC) and spectral dynamic causal modeling (spDCM) to detect functional hubs in the whole brain network, followed by an analysis of directional connections. Using the aforementioned approaches, it is possible to investigate the hub regions and aberrant connections underlying the altered brain function in CAD patients, providing neuroimaging evidence for the cognitive decline in patients with coronary artery disease. This study was prospectively conducted involving 24 patients diagnosed with CAD and 24 healthy controls (HC) who were matched in terms of age, gender, and education. Functional MRI (fMRI) scans were utilized to investigate brain activity in these individuals. Neuropsychological examinations were performed on all participants. DC analysis and spDCM were employed to investigate abnormal brain networks in patients with CAD. Additionally, the association between effective connectivity strength and cognitive function in patients with CAD was examined based on the aforementioned results. By assessing cognitive functions, we discovered that patients with CAD exhibited notably lower cognitive function compared to the HC group. By utilizing DC analysis and spDCM, we observed significant reductions in DC values within the left parahippocampal cortex (PHC) and the left medial temporal gyrus (MTG) in CAD patients when compared to the control group. In terms of effective connectivity, we observed the absence of positive connectivity between the right superior frontal gyrus (SFG) and PHC in CAD patients. Moreover, there was an increase in negative connectivity from PHC and MTG to SFG, along with a decrease in the strength of positive connectivity between PHC and MTG. Furthermore, we identified a noteworthy positive correlation (r = 0.491, p = 0.015) between the strength of connectivity between the PHC and the MTG and cognitive function in CAD patients. These research findings suggest that alterations in the connectivity of the brain networks involving SFG, PHC, and MTG in CAD patients may mediate changes in cognitive function.

Links among genetic variants and hierarchical brain structural and functional networks for antidepressant treatment: A multivariate study

BackgroundAntidepressant treatment effects are strongly heritable and have substantial effects on brain function and structure, but the underlying mechanisms are still poorly understood. In this research, we aimed to evaluate the factors of single nucleotide polymorphisms (SNPs) and hierarchical brain structural and functional networks that were associated with antidepressant treatment. Moreover, we further explored the correlations and mediation pattern among “brain structure-brain function-gene” in major depressive disorder (MDD). MethodsWe analysed 405 SNPs and rich club/feeder/local connections of hierarchical structural and functional networks with three-way parallel independent component analysis in 179 MDD patients. The group-discriminative independent components of the three modalities between responders and non-responders of antidepressant treatment were identified. Pearson correlations and mediation analysis were further utilized to investigate the associations among SNPs and connections of the structural and functional networks. ResultsNotably, correlations with antidepressant treatment outcomes were found in structural, functional and SNP modalities simultaneously. The features of group-discriminative independent components included the shared feeder connections of hub regions with the inferior frontal orbital gyrus and amygdala in structural and functional modalities and genes enriched in circadian rhythmic processes and dopaminergic synapse pathways. The structural feeder network displayed close correlations with SNPs and the functional feeder network. Furthermore, the structural feeder network could mediate the association between SNPs and the functional feeder network, implying that genetic variants might influence brain function by affecting brain structure in MDD. ConclusionsThese findings provide potential biomarkers for antidepressant therapy and provide a better grasp of the associations among SNPs and hierarchical structural and functional networks in MDD.

Who calls for help? Assessing the reach of the Ohio preschool expulsion prevention partnership

Early childhood expulsions are a systemic issue in early care and education (ECE) that have negative consequences for children, families, ECE programs, and communities. The Ohio Preschool Expulsion Prevention Partnership (OPEPP) represents one state's attempt to reduce the incidence of early childhood expulsions using infant and early mental health consultation distributed statewide in a hub-and-spoke arrangement. The study merges records from the first four years of OPEPP implementation (N = 569 expulsion prevention referrals) with child care licensing data (N = 3408 ECE programs) and data from the American Community Survey to assess OPEPP's reach in both the hub and spoke regions and identify what program and community characteristics were associated with OPEPP uptake. We found that 16.7 % of center-based ECE programs operating in Ohio between April 2016 and December 2019 participated in OPEPP, but distribution of referrals was uneven, with 36 % of ECE programs in the hub participating but just 10 % of programs outside of the hub doing so. ECE programs with higher quality ratings had greater odds of participating in OPEPP, as did ECE programs outside of the hub area that accepted publicly funded child care reimbursements. The differences in participation rates and predictors of participation between the hub and spoke regions suggest a need to explore how the hub-and-spoke arrangement of OPEPP may need to be adjusted to reach ECE programs outside of the hub region more effectively and have implications for other large-scale early childhood expulsion prevention efforts.

Functional brain connectivity in young adults with post-stroke epilepsy.

Approximately 1 in 10 young stroke patients (18-50 years) will develop post-stroke epilepsy, which is associated with cognitive impairment. While previous studies have shown altered brain connectivity in patients with epilepsy, little is however known about the changes in functional brain connectivity in young stroke patients with post-stroke epilepsy and their relationship with cognitive impairment. Therefore, we aimed to investigate whether young ischaemic stroke patients have altered functional networks and whether this alteration is related to cognitive impairment. We included 164 participants with a first-ever cerebral infarction at young age (18-50 years), along with 77 age- and sex-matched controls, from the Follow-Up of Transient Ischemic Attack and Stroke patients and Unelucidated Risk Factor Evaluation study. All participants underwent neuropsychological testing and resting-state functional MRI to generate functional connectivity networks. At follow-up (10.5 years after the index event), 23 participants developed post-stroke epilepsy. Graph theoretical analysis revealed functional network reorganization in participants with post-stroke epilepsy, in whom a weaker (i.e. network strength), less-integrated (i.e. global efficiency) and less-segregated (i.e. clustering coefficient and local efficiency) functional network was observed compared with the participants without post-stroke epilepsy group and the controls (P < 0.05). Regional analysis showed a trend towards decreased clustering coefficient, local efficiency and nodal efficiency in contralesional brain regions, including the caudal anterior cingulate cortex, posterior cingulate cortex, precuneus, superior frontal gyrus and insula in participants with post-stroke epilepsy compared with those without post-stroke epilepsy. Furthermore, participants with post-stroke epilepsy more often had impairment in the processing speed domain than the group without post-stroke epilepsy, in whom the network properties of the precuneus were positively associated with processing speed performance. Our findings suggest that post-stroke epilepsy is associated with functional reorganization of the brain network after stroke that is characterized by a weaker, less-integrated and less-segregated brain network in young ischaemic stroke patients compared with patients without post-stroke epilepsy. The contralesional brain regions, which are mostly considered as hub regions, might be particularly involved in the altered functional network and may contribute to cognitive impairment in post-stroke epilepsy patients. Overall, our findings provide additional evidence for a potential role of disrupted functional network as underlying pathophysiological mechanism for cognitive impairment in patients with post-stroke epilepsy.

Using multi-modal neuroimaging to characterise social brain specialisation in infants.

The specialised regional functionality of the mature human cortex partly emerges through experience-dependent specialisation during early development. Our existing understanding of functional specialisation in the infant brain is based on evidence from unitary imaging modalities and has thus focused on isolated estimates of spatial or temporal selectivity of neural or haemodynamic activation, giving an incomplete picture. We speculate that functional specialisation will be underpinned by better coordinated haemodynamic and metabolic changes in a broadly orchestrated physiological response. To enable researchers to track this process through development, we develop new tools that allow the simultaneous measurement of coordinated neural activity (EEG), metabolic rate, and oxygenated blood supply (broadband near-infrared spectroscopy) in the awake infant. In 4- to 7-month-old infants, we use these new tools to show that social processing is accompanied by spatially and temporally specific increases in coupled activation in the temporal-parietal junction, a core hub region of the adult social brain. During non-social processing, coupled activation decreased in the same region, indicating specificity to social processing. Coupling was strongest with high-frequency brain activity (beta and gamma), consistent with the greater energetic requirements and more localised action of high-frequency brain activity. The development of simultaneous multimodal neural measures will enable future researchers to open new vistas in understanding functional specialisation of the brain.

A data-driven flow loss prediction model for the blade hub region of a boundary layer ingestion fan rotor

PurposeIn a boundary layer ingestion (BLI) propulsion system, the fan operates continuously under distorted inflow conditions, leading to an increment of aerodynamic loss and in turn impacting the potential fuel burn reduction of the aircraft. Usually, in the preliminary design stage of a BLI propulsion system, it is essential to assess the impact of fuselage boundary layer fluids on fan aerodynamic performances under various flight conditions. However, the hub region flow loss is one of the major loss sources in a fan and would greatly influence the fan performances. Moreover, the inflow distortion also results in a complex and highly nonlinear mapping relation between loss and local physical parameters. It will diminish the prediction accuracy of the commonly used low-fidelity computational approaches which often incorporate traditional physics-based loss models, reducing the reliability of these approaches in evaluating fan performances. Meanwhile, the high-fidelity full-annulus unsteady Reynolds-averaged Navier–Stokes (URANS) approach, even though it can give rather accurate loss predictions, is extremely time-consuming. This study aims to develop a fast and accurate hub loss prediction method for a BLI fan under distorted inflow conditions.Design/methodology/approachThis paper develops a data-driven hub loss prediction method for a BLI fan under distorted inflows. To improve the prediction accuracy and applicability, physical understandings of hub flow features are integrated into the modeling process. Then, the key physical parameters related to flow loss are screened by conducting a sensitivity analysis of influencing parameters. Next, a quasi-steady assumption of flow is made to generate a training sample database, reducing the computational time by acquiring one single sample from the highly time-consuming full-annulus URANS approach to a cost-efficient single-blade-passage approach. Finally, a radial basis function neural network is used to establish a surrogate model that correlates the input parameters and the output loss.FindingsThe data-driven hub loss model shows higher prediction accuracy than the traditional physics-based loss models. It can accurately capture the circumferentially and radially nonuniform variation trends of the losses and the associated absolute magnitudes in a BLI fan under different blade load, inlet distortion intensity and rotating speed conditions. Compared with the high-fidelity full-annulus URANS results, the averaged relative prediction errors of the data-driven hub loss model are kept less than 10%.Originality/valueThe originality of this paper lies in developing a new method for predicting flow loss in a BLI fan rotor blade hub region. This method offers higher prediction accuracy than the traditional loss models and lower computational time cost than the full-annulus URANS approach, which could realize fast evaluations of fan aerodynamic performances and provide technical support for designing high-performance BLI fans.

The role of the cerebellum in fluid intelligence: An fMRI study

Traditionally, neuroimaging studies of fluid intelligence have focused on brain activation in frontal-parietal regions. In the past decade there has been accumulating evidence regarding the involvement of the cerebellum in higher cognitive function. In the current study we aimed to further investigate the role of the cerebellum in processing of fluid intelligence. We therefore scanned thirty-nine healthy participants (13 females and 26 males), recruited from the general population. Participant performed a novel abstract reasoning functional Magnetic Resonance Imaging task, modeled after stimuli from the advanced Raven's Progressive Matrices test. Analyses of both brain function and network architecture focusing on hubness were performed. We demonstrate activation in frontal and parietal well-known regions, together with an extensive activation in several cerebellar sub-regions. Moreover, four cerebellar regions served as crucial hub regions. Therefore, we provide evidence of the role of the cerebellum in fluid intelligence both by means of task brain activation and graph theory topology. Future studies should further assess in-depth the cerebellar contribution to cognitive processing in different brain disorders involving neural network alterations, allowing a better understanding of cognitive deficits.

Sex differences in the structural rich-club connectivity in patients with Alzheimer's disease.

Alzheimer's disease (AD) is more prevalent in women than in men; however, there is a discrepancy in research on sex differences in AD. The human brain is a large-scale network with hub regions forming a central core, the rich-club, which is vital to cognitive functions. However, it is unknown whether alterations in the rich-clubs in AD differ between men and women. We aimed to investigate sex differences in the rich-club organization in the brains of patients with AD. In total, 260 cognitively unimpaired individuals with negative amyloid positron emission tomography (PET) scans, 281 with prodromal AD (mild cognitive impairment due to AD) and 285 with AD dementia who confirmed with positive amyloid PET scans participated in the study. We obtained high-resolution T1-weighted and diffusion tensor images and performed network analysis. We observed sex differences in the rich-club and feeder connections in patients with AD, suggesting lower structural connectivity strength in women than in men. We observed a significant group-by-sex interaction in the feeder connections, particularly in the thalamus. In addition, the connectivity strength of the thalamus in the feeder connections was significantly correlated with general cognitive function in only men with prodromal AD and women with AD dementia. Our findings provide important evidence for sex-specific alterations in the structural brain network related to AD.

The effects of domain division types on the performance prediction of a rim-driven thruster

The rim-driven thruster (RDT) is an innovative propulsion thruster. The rotating subdomain can contain different assemblies with different domain division types (DDT). This paper tried to figure out the effects of DDT on the performance of RDT. This paper uses the Delayed Detached Eddy Simulation (DDES) turbulence model to conduct the simulations. Three DDTs are carefully analyzed to understand their effects on predictive performance. The convergence analysis is performed by taking a typical method: Grid Convergence Index (GCI). Some theoretical results and the experimental hydrodynamics of a popular combination of Ka 4–70 and MARIN 19 A are used to validate the numerical method. The numerical results demonstrate that the computational efficiency is influenced by the cell number on the interfaces between two subdomains and an inherent characteristic of DDT. Moreover, the torques acting on rim surfaces are closely accounting for the gap flow. Moreover, regarding the morphology and variables of the vortex system, the third type of DDT enhances vortices presenting in the hub region and vortex-instability region. Although the present analysis is performed for an RDT, the findings should be generally applicable for other RDT designs with similar structures and operational conditions.

P01.07.A HUB-RELATED GRAPH METRICS AS MARKER FOR COGNITIVE OUTCOMES IN ADULT GLIOMA SURVIVORS AFTER MULTIMODAL THERAPY

Abstract BACKGROUND Although cognitive impairment is a serious and prevalent long-term side effect in adult glioma survivors after therapy, predictive imaging-based markers remain inconsistent to date. Structural brain network topology could be altered by both the tumor and its’ treatment through reorganization of hubs (i.e. highly interconnected nodes). Here, we explored the role of nodal hub-related graph metrics in higher cognitive functioning. MATERIAL AND METHODS 48 WHO grade 2-3 adult glioma survivors (&amp;gt;1 year post-therapy) and 42 matched controls, underwent a cognitive assessment, covering five cognitive domains. Cognitive scores were transformed into w-scores, corrected for age and education. In addition, weighted nodal graph metrics were calculated based on diffusion weighted imaging, using multi-shell multi-tissue constrained spherical deconvolution and anatomically-constrained tractography. Hubs (hub score≥2) were calculated based on 4 nodal metrics, in which the 20% nodes with highest nodal strength and betweenness centrality, and lowest clustering coefficient and characteristic path length received 1 point (score 0-4). Significant differences in nodal graph metrics between patients and controls, and hubs versus non-hubs were tested in a repeated measures ANOVA, using Bonferroni correction for multiple testing. Significant group differences in nodal graph metrics were correlated to cognitive scores per domain. RESULTS In healthy controls 12/78 nodes were defined as hubs, i.e. the bilateral postcentral, precentral, superior frontal, parietofrontal, superior parietal gyri, thalamus and putamen. In glioma survivors, the left superior-parietal region and left putamen had a significantly lower likelihood of being a hub (p&amp;lt;.001). These specific areas showed assortativity to be positively correlated with attention, language and executive function (r(90)&amp;gt;.51, p&amp;lt;.001) and characteristic path length to be negatively correlated with all cognitive domains (r(90)&amp;gt;.51, p&amp;lt;.001). Nodal metrics of clustering coefficient, characteristic path length, local efficiency and assortativity were significantly different between groups in both hub and non-hub regions (both p&amp;lt;.001). Except for betweenness centrality, all nodal metrics strongly correlated with cognitive outcomes, occurring more often in hubs (33-50%) than intermediate hubs (10-33%) or non-hubs (4-12%). CONCLUSION Reorganization of hubs in the brain network is frequently observed in this cohort of glioma survivors compared to healthy controls. Hub connectivity seems to be important in cognitive functioning, more than for non-hub regions. Therefore, structural nodal hub-related graph metrics might be important to consider in predicting cognitive outcomes in glioma survivors.

Altered Brain Connectivity and Network Topological Organization in a Non-ordinary State of Consciousness Induced by Hypnosis.

Hypnosis has been shown to be of clinical utility; however, its underlying neural mechanisms remain unclear. This study aims to investigate altered brain dynamics during the non-ordinary state of consciousness induced by hypnosis. We studied high-density EEG in 9 healthy participants during eyes-closed wakefulness and during hypnosis, induced by a muscle relaxation and eyes fixation procedure. Using hypotheses based on internal and external awareness brain networks, we assessed region-wise brain connectivity between six ROIs (right and left frontal, right and left parietal, upper and lower midline regions) at the scalp level and compared across conditions. Data-driven, graph-theory analyses were also carried out to characterize brain network topology in terms of brain network segregation and integration. During hypnosis, we observed (1) increased delta connectivity between left and right frontal, as well as between right frontal and parietal regions; (2) decreased connectivity for alpha (between right frontal and parietal and between upper and lower midline regions) and beta-2 bands (between upper midline and right frontal, frontal and parietal, also between upper and lower midline regions); and (3) increased network segregation (short-range connections) in delta and alpha bands, and increased integration (long-range connections) in beta-2 band. This higher network integration and segregation was measured bilaterally in frontal and right parietal electrodes, which were identified as central hub regions during hypnosis. This modified connectivity and increased network integration-segregation properties suggest a modification of the internal and external awareness brain networks that may reflect efficient cognitive-processing and lower incidences of mind-wandering during hypnosis.

Simulation of Head-on Collisions between Filamentary Molecular Clouds Threaded by a Lateral Magnetic Field and Subsequent Evolution

Filamentary molecular clouds are regarded as the place where newborn stars form. In particular, a hub region, a place where it appears as if several filaments are colliding, often indicates active star formation. To understand the star formation in filament structures, we investigate the collisions between two filaments using two-dimensional magnetohydrodynamical simulations. As a model of filaments, we assume that the filaments are in magnetohydrostatic equilibrium under a global magnetic field perpendicular to the filament axis. We set two identical filaments with an infinite length and make them collide with a zero-impact parameter (head-on). When the two filaments collide while sharing the same magnetic flux, we found two types of evolution after a merged filament is formed: runaway radial collapse and stable oscillation with a finite amplitude. The condition for the radial collapse is independent of the collision velocity and is given by the total line mass of the two filaments exceeding the magnetically critical line mass for which no magnetohydrostatic solution exists. The radial collapse proceeds in a self-similar manner, resulting in a unique distribution irrespective of the various initial line masses of the filament, as the collapse progresses. When the total line mass is less massive than the magnetically critical line mass, the merged filament oscillates, and the density distribution is well-fitted by a magnetohydrostatic equilibrium solution. The condition necessary for the radial collapse is also applicable to the collision whose direction is perpendicular to the global magnetic field.

Daily heart rate variability biofeedback training decreases locus coeruleus MRI contrast in younger adults in a randomized clinical trial

As an arousal hub region in the brain, the locus coeruleus (LC) has bidirectional connections with the autonomic nervous system. Magnetic resonance imaging (MRI)-based measures of LC structural integrity have been linked to cognition and arousal, but less is known about factors that influence LC structure and function across time. Here, we tested the effects of heart rate variability (HRV) biofeedback, an intervention targeting the autonomic nervous system, on LC MRI contrast and sympathetic activity. Younger and older participants completed daily HRV biofeedback training for five weeks. Those assigned to an experimental condition performed biofeedback involving slow, paced breathing designed to increase heart rate oscillations, whereas those assigned to a control condition performed biofeedback to decrease heart rate oscillations. At the pre- and post-training timepoints, LC contrast was assessed using turbo spin echo MRI scans, and RNA sequencing was used to assess cAMP-responsive element binding protein (CREB)-regulated gene expression in circulating blood cells, an index of sympathetic nervous system signaling. We found that left LC contrast decreased in younger participants in the experimental group, and across younger participants, decreases in left LC contrast were related to the extent to which participants increased their heart rate oscillations during training. Furthermore, decreases in left LC contrast were associated with decreased expression of CREB-associated gene transcripts. On the contrary, there were no effects of biofeedback on LC contrast among older participants in the experimental group. These findings provide novel evidence that in younger adults, HRV biofeedback involving slow, paced breathing can decrease both LC contrast and sympathetic nervous system signaling.

On the space-time decomposition and reconstruction of the pump-jet propulsor flow field

In this numerical study, a modal approach based on the stress blend eddy simulation (SBES) was employed to investigated the morphology and development regime of the vortices in a pump-jet propulsor (PJP). Modal analysis was conducted on the corresponding surfaces to gain insights into the evaluation of the flow field, with a focus on spectral proper orthogonal decomposition (SPOD) and dynamic mode decomposition (DMD). These methods consider both temporal and spatial domain decomposition. By comparing the modes obtained from SOPD and DMD, it was observed that the coherent structure morphology exhibited similarities with only minor differences. The results indicated that the flow field could be effectively reconstructed using a few low-order modes. Both SPOD and DMD accurately captured the flow field, expect in the downstream hub region where chaotic flow was present. This study provides valuable insights into wake flow field of the PJP and sheds light on the understanding of vortex dynamics.

Direct Observational Evidence of the Multi-scale, Dynamical Mass Accretion Toward a High-mass Star-forming Hub-filament System

There is growing evidence that high-mass star formation and hub-filament systems (HFS) are intricately linked. The gas kinematics along the filaments and the forming high-mass star(s) in the central hub are in excellent agreement with the new generation of global hierarchical high-mass star formation models. In this paper, we present an observational investigation of a typical HFS cloud, G310.142+0.758 (G310 hereafter), which reveals unambiguous evidence of mass inflow from the cloud scale via the filaments onto the forming protostar(s) at the hub conforming with the model predictions. Continuum and molecular line data from the ATOMS and MALT90 surveys that cover different spatial scales are used. Three filaments (with a total mass of 5.7 ± 1.1 × 103 M ⊙) are identified converging toward the central hub region where several signposts of high-mass star formation have been observed. The hub region contains a massive clump (1280 ± 260 M ⊙) harboring a central massive core. Additionally, five outflow lobes are associated with the central massive core implying a forming cluster. The observed large-scale, smooth, and coherent velocity gradients from the cloud down to the core scale, and the signatures of infall motion seen in the central massive clump and core, clearly unveil a nearly continuous, multi-scale mass accretion/transfer process at a similar mass infall rate of ∼10−3 M ⊙ yr−1 over all scales, feeding the central forming high-mass protostar(s) in the G310 HFS cloud.

SIRT1 in the BNST modulates chronic stress-induced anxiety of male mice via FKBP5 and corticotropin-releasing factor signaling.

Although clinical reports have highlighted association of the deacetylase sirtuin 1 (SIRT1) gene with anxiety, its exact role in the pathogenesis of anxiety disorders remains unclear. The present study was designed to explore whether and how SIRT1 in the mouse bed nucleus of the stria terminalis (BNST), a key limbic hub region, regulates anxiety. In a chronic stress model to induce anxiety in male mice, we used site- and cell-type-specific in vivo and in vitro manipulations, protein analysis, electrophysiological and behavioral analysis, in vivo MiniScope calcium imaging and mass spectroscopy, to characterize possible mechanism underlying a novel anxiolytic role for SIRT1 in the BNST. Specifically, decreased SIRT1 in parallel with increased corticotropin-releasing factor (CRF) expression was found in the BNST of anxiety model mice, whereas pharmacological activation or local overexpression of SIRT1 in the BNST reversed chronic stress-induced anxiety-like behaviors, downregulated CRF upregulation, and normalized CRF neuronal hyperactivity. Mechanistically, SIRT1 enhanced glucocorticoid receptor (GR)-mediated CRF transcriptional repression through directly interacting with and deacetylating the GR co-chaperone FKBP5 to induce its dissociation from the GR, ultimately downregulating CRF. Together, this study unravels an important cellular and molecular mechanism highlighting an anxiolytic role for SIRT1 in the mouse BNST, which may open up new therapeutic avenues for treating stress-related anxiety disorders.