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Human cortical maturation has been posited to be organized along the sensorimotor-association axis, a hierarchical axis of brain organization that spans from unimodal sensorimotor cortices to transmodal association cortices. Here, we investigate the hypothesis that the development of functional connectivity during childhood through adolescence conforms to the cortical hierarchy defined by the sensorimotor-association axis. We tested this pre-registered hypothesis in four large-scale, independent datasets (totaln = 3355; ages 5–23 years): the Philadelphia Neurodevelopmental Cohort (n = 1207), Nathan Kline Institute-Rockland Sample (n = 397), Human Connectome Project: Development (n = 625), and Healthy Brain Network (n = 1126). Across datasets, the development of functional connectivity systematically varied along the sensorimotor-association axis. Connectivity in sensorimotor regions increased, whereas connectivity in association cortices declined, refining and reinforcing the cortical hierarchy. These consistent and generalizable results establish that the sensorimotor-association axis of cortical organization encodes the dominant pattern of functional connectivity development.

 

Strongly magnetized (B ≥ 1012 G) accreting neutron stars (NSs) are prime targets for studying the launching of jets by objects with a solid surface; while classical jet-launching models predict that such NSs cannot launch jets, recent observations and models argue otherwise. Transient Be/X-ray binaries (BeXRBs) are critical laboratories for probing this poorly explored parameter space for jet formation. Here, we present the coordinated monitoring campaigns of three BeXRBs across four outbursts: giant outbursts of SAX 2103.5+4545, 1A 0535+262, and GRO J1008–57, as well as a Type-I outburst of the latter. We obtain radio detections of 1A 0535+262 during ten out of twenty observations, while the other targets remained undetected at typical limits of 20–50 $\mu$Jy. The radio luminosity of 1A 0535+262 positively correlates with its evolving X-ray luminosity, and inhabits a region of the LX–LR plane continuing the correlation observed previously for the BeXRB Swift J0243.6+6124. We measure a BeXRB LX–LR coupling index of β = 0.86 ± 0.06 ($L_R \propto L_X^\beta$), similar to the indices measured in NS and black hole low-mass X-ray binaries. Strikingly, the coupling’s LR normalization is ∼275 and ∼6.2 × 103 times lower than in those two comparison samples, respectively. We conclude that jet emission likely dominates during the main peak of giant outbursts, but is only detectable for close-by or super-Eddington systems at current radio sensitivities. We discuss these results in the broader context of X-ray binary radio studies, concluding that our results suggest how supergiant X-ray binaries may host a currently unidentified additional radio emission mechanism.

 

We study the problem of sparse signal detection on a spatial domain. We propose a novel approach to model continuous signals that are sparse and piecewise-smooth as the product of independent Gaussian (PING) processes with a smooth covariance kernel. The smoothness of the PING process is ensured by the smoothness of the covariance kernels of the Gaussian components in the product, and sparsity is controlled by the number of components. The bivariate kurtosis of the PING process implies that more components in the product results in the thicker tail and sharper peak at zero. We develop an efficient computation algorithm based on spectral methods. The simulation results demonstrate superior estimation using the PING prior over Gaussian process prior for different image regressions. We apply our method to a longitudinal magnetic resonance imaging dataset to detect the regions that are affected by multiple sclerosis computation in this domain. Supplementary materials for this article are available online. 

Diffusion Spectrum Imaging (DSI) using dense Cartesian sampling ofq‐space has been shown to provide important advantages for modeling complex white matter architecture. However, its adoption has been limited by the lengthy acquisition time required. Sparser sampling ofq‐space combined with compressed sensing (CS) reconstruction techniques has been proposed as a way to reduce the scan time of DSI acquisitions. However prior studies have mainly evaluated CS‐DSI in post‐mortem or non‐human data. At present, the capacity for CS‐DSI to provide accurate and reliable measures of white matter anatomy and microstructure in the living human brain remains unclear. We evaluated the accuracy and inter‐scan reliability of 6 different CS‐DSI schemes that provided up to 80% reductions in scan time compared to a full DSI scheme. We capitalized on a dataset of 26 participants who were scanned over eight independent sessions using a full DSI scheme. From this full DSI scheme, we subsampled images to create a range of CS‐DSI images. This allowed us to compare the accuracy and inter‐scan reliability of derived measures of white matter structure (bundle segmentation, voxel‐wise scalar maps) produced by the CS‐DSI and the full DSI schemes. We found that CS‐DSI estimates of both bundle segmentations and voxel‐wise scalars were nearly as accurate and reliable as those generated by the full DSI scheme. Moreover, we found that the accuracy and reliability of CS‐DSI was higher in white matter bundles that were more reliably segmented by the full DSI scheme. As a final step, we replicated the accuracy of CS‐DSI in a prospectively acquired dataset (n = 20, scanned once). Together, these results illustrate the utility of CS‐DSI for reliably delineating in vivo white matter architecture in a fraction of the scan time, underscoring its promise for both clinical and research applications.

 

Multiple behavioral and biomechanical analyses have demonstrated that capuchin monkeys (CebusandSapajus) are specialized for breaking down hard‐object foods as compared to other cebid monkeys. In addition to a complex suite of craniodental adaptations, it has specifically been demonstrated that capuchins possess highly complex dental enamel, with extensive Hunter–Schreger banding and other decussation, that likely serve as an adaptation to resist crack propagation during hard‐object feeding. Furthermore, it has been demonstrated that robust capuchins (Sapajusspp., formerlyCebus apella) demonstrate further adaptation for hard‐object feeding than other capuchins, routinely breaking down extremely mechanically challenging foods. However, there has been no comparison of dental enamel complexity in robust versus gracile capuchins, to assess whether the dental enamel inSapajusfollows this same pattern of further specialization. Therefore, this study compares dental enamel complexity in images of dental thin sections from a sample of robust versus gracile capuchins using image compression ratio (ICR) analysis. ICR is a variable that correlates with enamel complexity, such that higher ICR values are indicative of increased complexity in the form of enamel decussation. We found no significant difference between robust and gracile capuchins when assessing all teeth in our sample together, however, we did find that robust capuchins have significantly higher ICR values than gracile capuchins for canine teeth, specifically. Our results support prior studies suggesting that robust capuchins are specialized to generate increased masticatory loads with their anterior dentition, specifically, as compared to gracile species.

 

Abstract A diverse set of white matter connections supports seamless transitions between cognitive states. However, it remains unclear how these connections guide the temporal progression of large-scale brain activity patterns in different cognitive states. Here, we analyze the brain’s trajectories across a set of single time point activity patterns from functional magnetic resonance imaging data acquired during the resting state and an n-back working memory task. We find that specific temporal sequences of brain activity are modulated by cognitive load, associated with age, and related to task performance. Using diffusion-weighted imaging acquired from the same subjects, we apply tools from network control theory to show that linear spread of activity along white matter connections constrains the probabilities of these sequences at rest, while stimulus-driven visual inputs explain the sequences observed during the n-back task. Overall, these results elucidate the structural underpinnings of cognitively and developmentally relevant spatiotemporal brain dynamics. 

Chemical defense against predators is widespread in natural ecosystems. Occasionally, taxonomically distant organisms share the same defense chemical. Here, we describe an unusual tripartite marine symbiosis, in which an intracellular bacterial symbiont (“ Candidatus Endobryopsis kahalalidefaciens”) uses a diverse array of biosynthetic enzymes to convert simple substrates into a library of complex molecules (the kahalalides) for chemical defense of the host, the alga Bryopsis sp., against predation. The kahalalides are subsequently hijacked by a third partner, the herbivorous mollusk Elysia rufescens , and employed similarly for defense. “ Ca . E. kahalalidefaciens” has lost many essential traits for free living and acts as a factory for kahalalide production. This interaction between a bacterium, an alga, and an animal highlights the importance of chemical defense in the evolution of complex symbioses. 

Abstract We present a broadband radio study of the transient jets ejected from the black hole candidate X-ray binary MAXI J1535–571, which underwent a prolonged outburst beginning on 2017 September 2. We monitored MAXI J1535–571 with the Murchison Widefield Array (MWA) at frequencies from 119 to 186 MHz over six epochs from 2017 September 20 to 2017 October 14. The source was quasi-simultaneously observed over the frequency range 0.84–19 GHz by UTMOST (the Upgraded Molonglo Observatory Synthesis Telescope) the Australian Square Kilometre Array Pathfinder (ASKAP), the Australia Telescope Compact Array (ATCA), and the Australian Long Baseline Array (LBA). Using the LBA observations from 2017 September 23, we measured the source size to be $34\pm1$ mas. During the brightest radio flare on 2017 September 21, the source was detected down to 119 MHz by the MWA, and the radio spectrum indicates a turnover between 250 and 500 MHz, which is most likely due to synchrotron self-absorption (SSA). By fitting the radio spectrum with a SSA model and using the LBA size measurement, we determined various physical parameters of the jet knot (identified in ATCA data), including the jet opening angle ( $\phi_{\rm op} = 4.5\pm1.2^{\circ}$ ) and the magnetic field strength ( $B_{\rm s} = 104^{+80}_{-78}$ mG). Our fitted magnetic field strength agrees reasonably well with that inferred from the standard equipartition approach, suggesting the jet knot to be close to equipartition. Our study highlights the capabilities of the Australian suite of radio telescopes to jointly probe radio jets in black hole X-ray binaries via simultaneous observations over a broad frequency range, and with differing angular resolutions. This suite allows us to determine the physical properties of X-ray binary jets. Finally, our study emphasises the potential contributions that can be made by the low-frequency part of the Square Kilometre Array (SKA-Low) in the study of black hole X-ray binaries. 

Adolescents are known for taking risks, from driving too fast to experimenting with drugs and alcohol. Such behaviors tend to decrease as individuals move into adulthood. Most people in their mid-twenties have greater self-control than they did as teenagers. They are also often better at planning, sustaining attention, and inhibiting impulsive behaviors. These skills, which are known as executive functions, develop over the course of adolescence. Executive functions rely upon a series of brain regions distributed across the frontal lobe and the lobe that sits just behind it, the parietal lobe. Fiber tracts connect these regions to form a fronto-parietal network. These fiber tracts are also referred to as white matter due to the whitish fatty material that surrounds and insulates them. Cui et al. now show that changes in white matter networks have implications for teen behavior. Almost 950 healthy young people aged between 8 and 23 years underwent a type of brain scan called diffusion-weighted imaging that visualizes white matter. The scans revealed that white matter networks in the frontal and parietal lobes mature over adolescence. This makes it easier for individuals to activate their fronto-parietal networks by decreasing the amount of energy required. Cui et al. show that a computer model can predict the maturity of a person's brain based on the energy needed to activate their fronto-parietal networks. These changes help explain why executive functions improve during adolescence. This in turn explains why behaviors such as risk-taking tend to decrease with age. That said, adults with various psychiatric disorders, such as ADHD and psychosis, often show impaired executive functions. In the future, it may be possible to reduce these impairments by applying magnetic fields to the scalp to reduce the activity of specific brain regions. The techniques used in the current study could help reveal which brain regions to target with this approach.