Spatial Mixing Research Articles

Spatio-temporal distribution of rhinovirus types in Kenya: a retrospective analysis, 2014

The epidemiology and circulation patterns of various rhinovirus types within populations remains under-explored. We generated 803 VP4/VP2 gene sequences from rhinovirus-positive samples collected from acute respiratory illness (ARI) patients, including both in-patient and outpatient cases, between 1st January and 31st December 2014 from eleven surveillance sites across Kenya and used phylogenetics to characterise virus introductions and spread. RVs were detected throughout the year, with the highest detection rates observed from January to March and June to July. We detected a total of 114 of the 169 currently classified types. Our analysis revealed numerous virus introductions into Kenya characterized by local expansion and extinction, and extensive spatial mixing of types within the country due to the widespread transmission of the virus after an introduction. This work demonstrates that in a single year, the circulation of rhinovirus in Kenya was characterized by substantial genetic diversity, multiple introductions, and extensive geographical spread.

Numerical Investigation on Enhanced Thermal Performance of Rectangular Microchannels with Triangular Ribs

Effective thermal management becomes crucial with the rising heat produced by electronic devices. Microchannel convection shows excellent potential as a cooling solution. This study employs numerical computational techniques to examine rectangular microchannels’ flow and heat transfer parameters on a semi-octagonal structure, specifically focusing on the Reynolds number (Re) ranging from 100 to 500. An extensive analysis evaluates the heat transfer design and hydraulic performance. Furthermore, the microchannel's diodic performance is assessed by comparing the Nusselt number (Nu) and the pressure drop in both the forward and backward directions. The study demonstrates the excellent performance of the microchannels within the microstructure under low Reynolds number (Re) conditions. Emphasizing the significance of preserving the fundamental geometric characteristics while improving the fluid dynamics within the microchannel. The semi-octagonal structure microchannel design surpasses the conventional design in bidirectional heat transfer by improving spatial fluid mixing. With a Reynolds number of 300, the Nusselt number of this microchannel surpasses that of the traditional rectangular design by a considerable margin. In addition, at this Reynolds number, the thermal diodicity (Dit) and pressure drop diodicity (Dip) showed significant improvements, with values of 1.16 and 1.45, respectively. Therefore, this study comprehensively compares the enhanced heat transfer of microchannel walls under constant heat flux, highlighting the advantages of semi-octagonal structural design in improving heat transfer and hydraulic performance. The results show that this innovative design has great potential to improve the efficiency of microchannel cooling and provides an important reference for the development of efficient thermal management systems.

Phylogenetic evidence of extensive spatial mixing of diverse HIV-1 group M lineages within Cameroon but not between its neighbours.

From the perspective of developing relevant interventions for treating HIV and controlling its spread, it is particularly important to comprehensively understand the underlying diversity of the virus, especially in countries where the virus has been present and evolving since the cross-species transmission event that triggered the global pandemic. Here, we generate and phylogenetically analyse sequences derived from the gag-protease (2010 bp; n = 115), partial integrase (345 bp; n = 36), and nef (719 bp; n = 321) genes of HIV-1 group M (HIV-1M) isolates sampled between 2000 and 2022 from two cosmopolitan cities and 40 remote villages of Cameroon. While 52.4% of all sequenced viruses belonged to circulating recombinant form (CRF) 02_AG (CRF02_AG), the remainder were highly diverse, collectively representing seven subtypes and sub-subtypes, eight CRFs, and 36 highly divergent lineages that fall outside the established HIV-1M classification. Additionally, in 77 samples for which at least two genes were typed, 31% of the studied viruses apparently had fragments from viruses belonging to different clades. Furthermore, we found that the distribution of HIV-1M populations is similar between different regions of Cameroon. In contrast, HIV-1M demographics in Cameroon differ significantly from those in its neighbouring countries in the Congo Basin (CB). In phylogenetic trees, viral sequences cluster according to the countries where they were sampled, suggesting that while there are minimal geographical or social barriers to viral dissemination throughout Cameroon, there is strongly impeded dispersal of HIV-1M lineages between Cameroon and other locations of the CB. This suggests that the apparent stability of highly diverse Cameroonian HIV-1M populations may be attributable to the extensive mixing of human populations within the country and the concomitant trans-national movements of major lineages with very similar degrees of fitness; coupled with the relatively infrequent inter-national transmission of these lineages from neighbouring countries in the CB.

Reduction of damage by the exotic invasive conifer seed bug Leptoglossus occidentalis in mixed pine-birch plantations: A case of biotic resistance

The number of invasive non-native pests is increasing rapidly in forests as a result of global change. It is therefore important to prevent their damage in order to preserve the integrity of forest ecosystems and the associated services. According to the biotic resistance hypothesis, species-rich communities are less likely to be invaded. The associational resistance hypothesis states that insect herbivores are more likely to colonise and exploit plants surrounded by conspecific neighbours than heterospecific, non-host plant species. More diverse forests would therefore be less damaged by non-native pests than tree monocultures. We tested these hypotheses by comparing the damage caused to seeds by the western conifer bug Leptoglossus occidentalis, an invasive insect native to North America, in plots of pure maritime pine and mixed plots of maritime pine and birch. These plots were in two tree diversity experiments in Europe. Mixed pine plots differed in terms of pine density (1250 versus 625 pines/ha), proportion of pine and birch (25 %, 50 %, 75 %) and spatial mixing pattern (aggregated versus dispersed). We sampled 635 cones in 37 plots. Overall, the proportion of seeds damaged by the invasive bug was significantly lower in mixed plots than in pure pine plots at both experimental sites. There was no significant effect of pine density or relative proportion in the mixtures on seed damage. Aggregated pines in the mixed plots were significantly more damaged than dispersed pines, suggesting that bugs may have done less damage when they had more difficulty locating their host trees. This is consistent with the hypothesis of lower plant apparency. These results support the view that forest plantations of mixed species, which are known to be less vulnerable to attack by native insects, may also be more resistant to infestation by exotic insects. Row-wise, intimate mixtures of two species represent a promising option for designing tree plantations that are more resistant and easier to manage.

Perfect sampling of $q$-spin systems on $\mathbb{Z}^{2}$ via weak spatial mixing

We present a perfect marginal sampler of the unique Gibbs measure of a spin system on \mathbb{Z}^{2} . The algorithm is an adaptation of a previous “lazy depth-first” approach by the authors, but relaxes the requirement of strong spatial mixing to weak. Our result is a step towards methods of efficient sampling using only weak spatial mixing. The work exploits a classical result in statistical physics relating weak spatial mixing on \mathbb{Z}^{2} to strong spatial mixing on squares. When the spin system exhibits weak spatial mixing, the run-time of our sampler is linear in the size of sample. Applications of note are the ferromagnetic Potts model at supercritical temperatures and the ferromagnetic Ising model with consistent non-zero external field at any non-zero temperature.

Data-driven surrogate modeling and optimization of supercritical jet into supersonic crossflow

For the design and optimization of advanced aero-engines, the prohibitively computational resources required for numerical simulations pose a significant challenge, due to the extensive exploration of design parameters across a vast design space. Surrogate modeling techniques offer a viable alternative for efficiently emulating numerical results within a notably compressed timeframe. This study introduces parametric Reduced-Order Models (ROMs) based on Convolutional AutoEncoders (CAE), Fully Connected AutoEncoders (FCAE), and Proper Orthogonal Decomposition (POD) to fast emulate spatial distributions of physical variables for a supercritical jet into a supersonic crossflow under different operating conditions. To further accelerate the decision-making process, an optimization model is developed to enhance fuel-oxidizer mixing efficiency while minimizing total pressure loss. Results indicate that CAE-based ROMs exhibit superior prediction accuracy while FCAE-based ROMs show inferior predictive accuracy but minimal uncertainty. The latter may be ascribed to the markedly greater number of hyperparameters. POD-based ROMs underperform in regions of strong nonlinear flow dynamics, coupled with higher overall prediction uncertainties. Both AE- and POD-based ROMs achieve online predictions approximately 9 orders of magnitude faster than conventional simulations. The established optimization model enables the attainment of Pareto-optimal frontiers for spatial mixing deficiencies and total pressure recovery coefficient.

Cohesin prevents cross-domain gene coactivation

The contrast between the disruption of genome topology after cohesin loss and the lack of downstream gene expression changes instigates intense debates regarding the structure–function relationship between genome and gene regulation. Here, by analyzing transcriptome and chromatin accessibility at the single-cell level, we discover that, instead of dictating population-wide gene expression levels, cohesin supplies a general function to neutralize stochastic coexpression tendencies of cis-linked genes in single cells. Notably, cohesin loss induces widespread gene coactivation and chromatin co-opening tens of million bases apart in cis. Spatial genome and protein imaging reveals that cohesin prevents gene co-bursting along the chromosome and blocks spatial mixing of transcriptional hubs. Single-molecule imaging shows that cohesin confines the exploration of diverse enhancer and core promoter binding transcriptional regulators. Together, these results support that cohesin arranges nuclear topology to control gene coexpression in single cells.

Dynamics of elevated dodecane jets in crossflow at supercritical pressure

In advanced aero-engines, kerosene is often transversely injected into the combustor at supercritical pressure, where the shorter jet penetration depth may result in poor mixing and the local hot spots near the combustor wall. Elevating the jet nozzle is proposed to remedy these issues, where the flowfield complexity increases as a result of the intricate interactions among the jet, crossflow, and stack wake. The distinct flow dynamics of elevated dodecane jets in crossflow (EJICF) at supercritical pressure are numerically investigated using large eddy simulation. The effects of various parameters, including ambient pressure, elevation stack thickness, and stack height are studied. The results reveal that, the jet-wake recirculation bubble is prominently evident at low supercritical pressure, attributed to the strong real-fluid effect resulting from significant density stratification in the jet's upstream shear layer. Analysis of streamline patterns and vorticity budgets underscores the role of the real-fluid effect in delaying the shift of the flow pattern from the transitional regime to the jet-dominated regime. Increasing stack thickness mitigates the impact of jet upshear effects and has the potential to eliminate the lock-in phenomena between jet wake and stack wake. A reduction in stack height leads to the diminishment of the stack wake vortex shedding. In contrast to conventional JICF, the EJICF configuration exhibits a heightened tendency for recirculation bubble formation in the jet wake region. An analysis of spatial mixing deficiencies demonstrates that incorporating an elevation stack with proper thickness and height can dramatically improve the jet-crossflow mixing efficiency.

Secured THz communication in photonic microcell networks based on spatial wave mixing of steered beams

Future 6G communication systems are envisioned to expand their carrier frequency to the THz region, where a broad unexplored region of spectrum is available. With this expansion, THz wireless communication has the potential to achieve ultra-high data transmission rates of up to 100Gbit/s. However, as large amounts of data are transmitted in an open wireless environment, there are significant concerns regarding communication security due to the susceptibility to eavesdropping, interception, and jamming. In this work, we proposed a secure approach for THz wireless communication based on spatial wave mixing and flexible beam steering. To achieve this, two frequency-modulated THz waves, which are generated by photonic THz sources and carry encrypted information with true randomness, are mixed at a THz envelope detector with an exclusive-OR logic operation. We analyzed the possible spatial location for the THz detector to ensure a secure microcell network deployment. Our results demonstrate that the size of the decryptable region is directly dependent on the directivity and width of the emitted THz beam. To address this, we have developed an array antenna with integrated uni-traveling-carrier photodiodes (UTC-PDs), which is capable of generating THz waves while also improving the flexibility of beam pointing, allowing for greater control over the location and size of the decodable region. By controlling fiber-optic delay lines, we successfully demonstrated that the directional gain of a 200GHz wave is increased by 8dB through a 1 × 3 UTC-PD-integrated planar bowtie antenna (PBA) array, together with continuous beam steering from -20° to 10°. Additionally, using a 1 × 4 UTC-PD-integrated PBA array to emulate two encryption transmitters and a Femi-level managed barrier diode to detect spatially mixed THz waves, we successfully achieved a feasibility experiment for real-time 200Mbit/s location-based decryption in the 200GHz band. These results indicate that the proposed scheme is feasible for secured THz communication, and would be a powerful candidate to mitigate security risks in 6G microcell networks.

DNA methylation-based high-resolution mapping of long-distance chromosomal interactions in nucleosome-depleted regions.

3C-based methods have significantly advanced our understanding of 3D genome organization. However, it remains a formidable task to precisely capture long-range chromosomal interactions between individual loci, such as those between promoters and distal enhancers. Here, we present Methyltransferase Targeting-based chromosome Architecture Capture (MTAC), a method that maps the contacts between a target site (viewpoint) and the rest of the genome in budding yeast with high resolution and sensitivity. MTAC detects hundreds of intra- and inter-chromosomal interactions within nucleosome-depleted regions (NDRs) that cannot be captured by 4C, Hi-C, or Micro-C. By applying MTAC to various viewpoints, we find that (1) most long-distance chromosomal interactions detected by MTAC reflect tethering by the nuclear pore complexes (NPCs), (2) genes co-regulated by methionine assemble into inter-chromosomal clusters near NPCs upon activation, (3) mediated by condensin, the mating locus forms a highly specific interaction with the recombination enhancer (RE) in a mating-type specific manner, and (4) correlation of MTAC signals among NDRs reveal spatial mixing and segregation of the genome. Overall, these results demonstrate MTAC as a powerful tool to resolve fine-scale long-distance chromosomal interactions and provide insights into the 3D genome organization.

Driving factors for developing integrated farming: Multi-criteria decision-making analysis

Integrated farming (IF) by temporal and spatial mixing of crops, livestock, fishery, and allied activities in a single farm, is considered a critical multifunctional option for smallholder farmers, who form the backbone of Indian agriculture, to ensure sustainable livelihoods, the productivity of agricultural enterprises, stability of farm income, food and nutritional security. However, the adoption of IF still remains low. To explore the critical factors of IF systems and prioritize them for stakeholders’ decision-making and development of strategies, the current research was undertaken to integrate SWOT (Strengths, Weaknesses, Opportunities, and Threats) - AHP (Analytic Hierarchy Process) analysis. We used a multi-stage sampling to select 60 practicing IF adopters in West Bengal state of eastern India for the collection of pair-wise comparison data on 32 SWOT factors using a close-ended questionnaire and subjected to AHP analysis to understand the quantitative importance of each factor of SWOT. Results of the multi- criteria analysis showed the total priority weight of the opportunity component (0.450) was the highest, followed by strength (0.341), weakness (0.114), and threat components (0.095). Based on the global priority weight of all 32 SWOT factors, sustainable livelihood security” was the key driving factor (0.081) followed by promotion of organic farming (0.072), better risk management (0.063) and incorporation of high-value crops (0.063) of opportunity component. Increased farm production and productivity (0.058) and enhancement in income (0.055) of strength component also played as vital driving factors. There was no factor of weakness and threat components within the first 10 important factors. The insights of this study may help improve extension services to smallholder farmers for prioritizing strategies in the adoption process of IF. Additionally, it can also help policymakers to design targeted policies, remove barriers, foster innovation, and promote sustainable practices, contributing to food security and environmental sustainability.

An interphase actin wave promotes mitochondrial content mixing and organelle homeostasis

Across the cell cycle, mitochondrial dynamics are regulated by a cycling wave of actin polymerization/depolymerization. In metaphase, this wave induces actin comet tails on mitochondria that propel these organelles to drive spatial mixing, resulting in their equitable inheritance by daughter cells. In contrast, during interphase the cycling actin wave promotes localized mitochondrial fission. Here, we identify the F-actin nucleator/elongator FMNL1 as a positive regulator of the wave. FMNL1-depleted cells exhibit decreased mitochondrial polarization, decreased mitochondrial oxygen consumption, and increased production of reactive oxygen species. Accompanying these changes is a loss of hetero-fusion of wave-fragmented mitochondria. Thus, we propose that the interphase actin wave maintains mitochondrial homeostasis by promoting mitochondrial content mixing. Finally, we investigate the mechanistic basis for the observation that the wave drives mitochondrial motility in metaphase but mitochondrial fission in interphase. Our data indicate that when the force of actin polymerization is resisted by mitochondrial tethering to microtubules, as in interphase, fission results.

EEG source imaging of hand movement-related areas: an evaluation of the reconstruction and classification accuracy with optimized channels

The hand motor activity can be identified and converted into commands for controlling machines through a brain-computer interface (BCI) system. Electroencephalography (EEG) based BCI systems employ electrodes to measure the electrical brain activity projected at the scalp and discern patterns. However, the volume conduction problem attenuates the electric potential from the brain to the scalp and introduces spatial mixing to the signals. EEG source imaging (ESI) techniques can be applied to alleviate these issues and enhance the spatial segregation of information. Despite this potential solution, the use of ESI has not been extensively applied in BCI systems, largely due to accuracy concerns over reconstruction accuracy when using low-density EEG (ldEEG), which is commonly used in BCIs. To overcome these accuracy issues in low channel counts, recent studies have proposed reducing the number of EEG channels based on optimized channel selection. This work presents an evaluation of the spatial and temporal accuracy of ESI when applying optimized channel selection towards ldEEG number of channels. For this, a simulation study of source activity related to hand movement has been performed using as a starting point an EEG system with 339 channels. The results obtained after optimization show that the activity in the concerned areas can be retrieved with a spatial accuracy of 3.99, 10.69, and 14.29 mm (localization error) when using 32, 16, and 8 channel counts respectively. In addition, the use of optimally selected electrodes has been validated in a motor imagery classification task, obtaining a higher classification performance when using 16 optimally selected channels than 32 typical electrode distributions under 10–10 system, and obtaining higher classification performance when combining ESI methods with the optimal selected channels.

Flow Dynamics of a Dodecane Jet in Oxygen Crossflow at Supercritical Pressures

In advanced aeropropulsion engines, liquid fuel is often injected into the combustor at supercritical pressures, where flow dynamics are distinct from the subcritical counterpart. Large-eddy simulation, combined with real-fluid thermodynamics and transport processes of a liquid N-dodecane jet in oxygen crossflow, is presented at different supercritical pressures and jet-to-crossflow momentum flux ratios (J). Various vortical structures are discussed in detail. The results show that, with the same velocity ratio of 0.75, the upstream shear layer (USL) is absolutely unstable at high supercritical pressure (J=7.1) and convectively unstable at low supercritical pressure (J=13.2), consistent with the empirical criterion at subcritical pressures (Jcr≈10). While decreasing J to 7.1 at low supercritical pressure, however, the USL remains convectively unstable, manifested by the variable dominant Strouhal number of the USL along the upstream jet trajectory. Such abnormal behavior can be attributed to the real-fluid effect induced by strong density stratification at low supercritical pressure, under which an inflection point in the upstream mixing layer renders a large density gradient and tends to stabilize the USL. Linear stability analysis further verifies these findings. The analysis of spatial mixing deficiencies reveals that the mixing efficiency is enhanced at a higher J.

Parametric study of blind-label acoustic subwavelength imaging

There is a long-existing tradeoff between the imaging resolution and the penetration depth in imaging systems caused by the diffraction limit. We developed a “blind label” approach to tackle this problem, which significantly improves the practicality of acoustic subwavelength imaging in biomedical ultrasound imaging, non-destructive testing, and other acoustic sensing and communication applications. The “blind labels” in our system refer to randomly distributed acoustic scatterers with deep-subwavelength sizes whose exact locations and trajectories are not necessary information in image reconstruction. Our imaging framework is composed of two parts: (1) spatial mixing: a physical process that converts the originally evanescent components in the scattered waves from the object to propagating components that can reach the far-field detector and (2) computational reconstruction. In this talk, we will mainly report our quantitative investigation of the system parameters’ impact on the performance of the blind-label subwavelength imaging system, providing guidance to future system setups in various applications.

Counter‐Propagating Evanescent Illumination Super‐Resolution Chip

Super‐resolution chip (SRC) made of fluorescent polymer film and polygon film waveguide can realize subdiffraction imaging. However, the propagation losses of evanescent waves impose a serious restriction on imaging performance. Meanwhile, the required redundant raw images hinder the imaging speed. Multiple‐azimuths evanescent illumination at the same time can efficiently increase the illumination intensity and uniformity, and reduce the number of required raw images. But, the experimental realization is impeded by the complex spatial frequency mixing problem. Herein, an SRC microscopy method with counter‐propagating evanescent illumination is demonstrated, which circumvents the influence of complex spatial frequency mixing, and efficiently enhances the reconstructed results. Meanwhile, the proposed method reduces the number of required raw images by half and saves the image acquisition time, which benefits the imaging speed enhancement of the SRC microscopy system and promotes its future practical application.

Mosaic-PICASSO: accurate crosstalk removal for multiplex fluorescence imaging.

Ultra-multiplexed fluorescence imaging has revolutionized our understanding of biological systems, enabling the simultaneous visualization and quantification of multiple targets within biological specimens. A recent breakthrough in this field is PICASSO, a mutual-information-based technique capable of demixing up to 15 fluorophores without their spectra, thereby significantly simplifying the application of ultra-multiplexed fluorescence imaging. However, this study has identified a limitation of mutual information (MI)-based techniques. They do not differentiate between spatial colocalization and spectral mixing. Consequently, MI-based demixing may incorrectly interpret spatially co-localized targets as non-colocalized, leading to overcorrection. We found that selecting regions within a multiplex image with low-spatial similarity for measuring spectroscopic mixing results in more accurate demixing. This method effectively minimizes overcorrections and promises to accelerate the broader adoption of ultra-multiplex imaging. The codes are available at https://github.com/xing-lab-pitt/mosaic-picasso.

CMAT: Integrating Convolution Mixer and Self-Attention for Visual Tracking

Convolutional Neural Networks (CNNs) and Transformer are two powerful representation learning techniques for visual tracking. Although CNNs can effectively reduce local redundancy via small-neighborhood convolution operations, their limited receptive fields make it difficult to capture global dependency. Self-attention in Transformer uses patches as the input representation, which can effectively capture long-range dependency. However, blind similarity comparisons between all patches can lead to high redundancy. Is there then a technique that combines well the advantages of both paradigms for visual tracking? In this work, we design a novel backbone network for feature extraction. First, we choose Depthwise Convolution and Pointwise Convolution to build a Convolution Mixer, which effectively separates spatial mixing from channel-wise mixing of information. The Convolution Mixer reduces redundancy in spatial and channel features while increasing receptive field. Then, to exploit the global modeling ability of self-attention, we construct a module by aggregating Convolution Mixer and self-attention. The module shares dominant computational complexity (the square of the channel size) in the first stage. In the second stage, the shift and summation operations are lightweight. Finally, to alleviate the overfitting of the backbone network during training, a dropout layer is added at the end of the module to improve the generalization ability of the network model. Stronger image features are provided for subsequent feature fusion and prediction. The proposed tracker (named CMAT) achieves satisfying tracking performance on ten challenging datasets. In particular, CMAT achieves a 64.1% AUC on LaSOT and a 68.9% AUC on UAV123 while running at 23 frames per second (FPS).

Vocal signatures affected by population identity and environmental sound levels.

Passive acoustic monitoring has improved our understanding of vocalizing organisms in remote habitats and during all weather conditions. Many vocally active species are highly mobile, and their populations overlap. However, distinct vocalizations allow the tracking and discrimination of individuals or populations. Using signature whistles, the individually distinct calls of bottlenose dolphins, we calculated a minimum abundance of individuals, characterized and compared signature whistles from five locations, and determined reoccurrences of individuals throughout the Mid-Atlantic Bight and Chesapeake Bay, USA. We identified 1,888 signature whistles in which the duration, number of extrema, start, end, and minimum frequencies of signature whistles varied significantly by site. All characteristics of signature whistles were deemed important for determining from which site the whistle originated and due to the distinct signature whistle characteristics and lack of spatial mixing of the dolphins detected at the Offshore site, we suspect that these dolphins are of a different population than those at the Coastal and Bay sites. Signature whistles were also found to be shorter when sound levels were higher. Using only the passively recorded vocalizations of this marine top predator, we obtained information about its population and how it is affected by ambient sound levels, which will increase as offshore wind energy is developed. In this rapidly developing area, these calls offer critical management insights for this protected species.

Evaluating functional brain organization in individuals and identifying contributions to network overlap

Abstract Individual differences in the spatial organization of resting-state networks have received increased attention in recent years. Measures of individual-specific spatial organization of brain networks and overlapping network organization have been linked to important behavioral and clinical traits and are therefore potential biomarker targets for personalized psychiatry approaches. To better understand individual-specific spatial brain organization, this paper addressed three key goals. First, we determined whether it is possible to reliably estimate weighted (non-binarized) resting-state network maps using data from only a single individual, while also maintaining maximum spatial correspondence across individuals. Second, we determined the degree of spatial overlap between distinct networks, using test-retest and twin data. Third, we systematically tested multiple hypotheses (spatial mixing, temporal switching, and coupling) as candidate explanations for why networks overlap spatially. To estimate weighted network organization, we adopt the Probabilistic Functional Modes (PROFUMO) algorithm, which implements a Bayesian framework with hemodynamic and connectivity priors to supplement optimization for spatial sparsity/independence. Our findings showed that replicable individual-specific estimates of weighted resting-state networks can be derived using high-quality fMRI data within individual subjects. Network organization estimates using only data from each individual subject closely resembled group-informed network estimates (which was not explicitly modeled in our individual-specific analyses), suggesting that cross-subject correspondence was largely maintained. Furthermore, our results confirmed the presence of spatial overlap in network organization, which was replicable across sessions within individuals and in monozygotic twin pairs. Intriguingly, our findings provide evidence that overlap between 2-network pairs is indicative of coupling. These results suggest that regions of network overlap concurrently process information from both contributing networks, potentially pointing to the role of overlapping network organization in the integration of information across multiple brain systems.