Development of segregation and integration of functional connectomes during the first 1,000 days.

The first 1,000 days of human life lay the foundation for brain development and later cognitive growth. However, the developmental rules of the functional connectome during this critical period remain unclear. Using high-resolution, longitudinal, task-free functional magnetic resonance imaging data from 930 scans of 665 infants aged 28 postmenstrual weeks to 3 years, we report the early maturational process of connectome segregation and integration. We show the dominant development of local connections alongside a few global connections, the shift of brain hubs from primary regions to high-order association cortices, the developmental divergence of network segregation and integration along the anterior-posterior axis, the prediction of neurocognitive outcomes, and their associations with gene expression signatures of microstructural development and neuronal metabolic pathways. These findings advance our understanding of the principles of connectome remodeling during early life and its neurobiological underpinnings and have implications for studying typical and atypical development.

Structural connectome architecture shapes the maturation of cortical morphology from childhood to adolescence.

Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear. Here, we show cortical thinning patterns primarily located in the lateral frontal and parietal heteromodal nodes during childhood and adolescence, which are structurally constrained by white matter network architecture and are particularly represented using a network-based diffusion model. Furthermore, connectome-based constraints are regionally heterogeneous, with the largest constraints residing in frontoparietal nodes, and are associated with gene expression signatures of microstructural neurodevelopmental events. These results are highly reproducible in another independent dataset. These findings advance our understanding of network-level mechanisms and the associated genetic basis that underlies the maturational process of cortical morphology during childhood and adolescence.

Frequency-resolved connectome alterations in major depressive disorder: A multisite resting fMRI study.

BACKGROUND: Functional connectome studies have revealed widespread connectivity alterations in major depressive disorder (MDD). However, the low frequency bandpass filtering (0.01-0.08 Hz or 0.01-0.1 Hz) in most studies have impeded our understanding on whether and how these alterations are affected by frequency of interest. METHODS: Here, we performed frequency-resolved (0.01-0.06 Hz, 0.06-0.16 Hz and 0.16-0.24 Hz) connectome analyses using a large-sample resting-state functional MRI dataset of 1002 MDD patients and 924 healthy controls from seven independent centers. RESULTS: We reported significant frequency-dependent connectome alterations in MDD in left inferior parietal, inferior temporal, precentral, and fusiform cortices and bilateral precuneus. These frequency-dependent connectome alterations are mainly derived by abnormalities of medium- and long-distance connections and are brain network-dependent. Moreover, the connectome alteration of left precuneus in high frequency band (0.16-0.24 Hz) is significantly associated with illness duration. LIMITATIONS: Multisite harmonization model only removed linear site effects. Neurobiological underpinning of alterations in higher frequency (0.16-0.24 Hz) should be further examined by combining fMRI data with respiration, heartbeat and blood flow recordings in future studies. CONCLUSIONS: These results highlight the frequency-dependency of connectome alterations in MDD and the benefit of examining connectome alteration in MDD under a wider frequency band.

Meta-connectomic analysis maps consistent, reproducible, and transcriptionally relevant functional connectome hubs in the human brain.

Human brain connectomes include sets of densely connected hub regions. However, the consistency and reproducibility of functional connectome hubs have not been established to date and the genetic signatures underlying robust hubs remain unknown. Here, we conduct a worldwide harmonized meta-connectomic analysis by pooling resting-state functional MRI data of 5212 healthy young adults across 61 independent cohorts. We identify highly consistent and reproducible connectome hubs in heteromodal and unimodal regions both across cohorts and across individuals, with the greatest effects observed in lateral parietal cortex. These hubs show heterogeneous connectivity profiles and are critical for both intra- and inter-network communications. Using post-mortem transcriptome datasets, we show that as compared to non-hubs, connectome hubs have a spatiotemporally distinctive transcriptomic pattern dominated by genes involved in the neuropeptide signaling pathway, neurodevelopmental processes, and metabolic processes. These results highlight the robustness of macroscopic connectome hubs and their potential cellular and molecular underpinnings, which markedly furthers our understanding of how connectome hubs emerge in development, support complex cognition in health, and are involved in disease.

The minimum regret path problem on stochastic fuzzy time-varying networks.

In this paper, we introduce a stochastic fuzzy time-varying minimum regret path problem (SFTMRP), which combines the characteristics of the min-max regret path and maximum probability path as a variant of the stochastic fuzzy time-varying shortest path problem, and its purpose is to find a path with the minimum regret degree in a given stochastic fuzzy time-varying network. To address this problem, we propose a random fuzzy delay neural network (RFDNN) based on novel random fuzzy delay neurons and without any training requirements. The random fuzzy delay neuron consists of six layers: an input layer, receiving layer, status layer, generation layer, sending layer, and output layer. Among them, the input and output layers are the ports of communication between neurons, and the receiving layer, status layer, generate layer, and sending layer are the information processing units of neurons. The information exchange between neurons is characterized by two kinds of signals: the shortest path signal and the maximum probability solution signal. The theoretical analysis of the proposed algorithm is carried out with respect to time-complexity and correctness. The numerical example and experimental results on 25 randomly generated stochastic fuzzy time-varying road networks with different numbers of 1000-5000 nodes show that the performance of the proposed algorithm is significantly better than that of existing algorithms.

The Simons Observatory: A large-diameter truss for a refracting telescope cooled to 1 K.

We present the design and measured performance of a new carbon fiber strut design that is used in a cryogenically cooled truss for the Simons Observatory small aperture telescope. The truss consists of two aluminum 6061 rings separated by 24 struts. Each strut consists of a central carbon fiber tube fitted with two aluminum end caps. We tested the performance of the strut and truss by (i) cryogenically cycling and destructively pull-testing strut samples, (ii) non-destructively pull-testing the final truss, and (iii) measuring the thermal conductivity of the carbon fiber tubes. We found that the strut strength is limited by the mounting fasteners and the strut end caps, not the epoxy adhesive or the carbon fiber tube. This result is consistent with our numerical predictions. Our thermal measurements suggest that the conductive heat load through the struts (from 4 to 1 K) will be less than 1 mW. This strut design may be a promising candidate for use in other cryogenic support structures.

Alterations in Connectome Dynamics in Autism Spectrum Disorder: A Harmonized Mega- and Meta-analysis Study Using the Autism Brain Imaging Data Exchange Dataset.

BACKGROUND: Neuroimaging studies have reported functional connectome aberrancies in autism spectrum disorder (ASD). However, the time-varying patterns of connectome topology in individuals with ASD and the connection between these patterns and gene expression profiles remain unknown. METHODS: To investigate case-control differences in dynamic connectome topology, we conducted mega- and meta-analyses of resting-state functional magnetic resonance imaging data of 939 participants (440 patients with ASD and 499 healthy control subjects, all males) from 18 independent sites, selected from the Autism Brain Imaging Data Exchange (ABIDE) dataset. Functional data were preprocessed and analyzed using harmonized protocols, and brain module dynamics was assessed using a multilayer network model. We further leveraged postmortem brain-wide gene expression data to identify transcriptomic signatures associated with ASD-related alterations in brain dynamics. RESULTS: Compared with healthy control participants, individuals with ASD exhibited a higher global mean and lower standard deviation of whole-brain module dynamics, indicating an unstable and less regionally differentiated pattern. More specifically, individuals with ASD showed higher module switching, primarily in the medial prefrontal cortex, posterior cingulate gyrus, and angular gyrus, and lower switching in the visual regions. These alterations in brain dynamics were predictive of social impairments in individuals with ASD and were linked with expression profiles of genes primarily involved in the regulation of neurotransmitter transport and secretion as well as with previously identified autism-related genes. CONCLUSIONS: This study is the first to identify consistent alterations in brain network dynamics in ASD and the transcriptomic signatures related to those alterations, furthering insights into the biological basis behind this disorder.

Simons Observatory: characterizing the Large Aperture Telescope Receiver with radio holography.

We present near-field radio holography measurements of the Simons Observatory Large Aperture Telescope Receiver optics. These measurements demonstrate that radio holography of complex millimeter-wave optical systems comprising cryogenic lenses, filters, and feed horns can provide detailed characterization of wave propagation before deployment. We used the measured amplitude and phase, at 4 K, of the receiver near-field beam pattern to predict two key performance parameters: 1) the amount of scattered light that will spill past the telescope to 300 K and 2) the beam pattern expected from the receiver when fielded on the telescope. These cryogenic measurements informed the removal of a filter, which led to improved optical efficiency and reduced sidelobes at the exit of the receiver. Holography measurements of this system suggest that the spilled power past the telescope mirrors will be less than 1%, and the main beam with its near sidelobes are consistent with the nominal telescope design. This is the first time such parameters have been confirmed in the lab prior to deployment of a new receiver. This approach is broadly applicable to millimeter and submillimeter instruments.

Simons Observatory HoloSim-ML: machine learning applied to the efficient analysis of radio holography measurements of complex optical systems.

Near-field radio holography is a common method for measuring and aligning mirror surfaces for millimeter and sub-millimeter telescopes. In instruments with more than a single mirror, degeneracies arise in the holography measurement, requiring multiple measurements and new fitting methods. We present HoloSim-ML, a Python code for beam simulation and analysis of radio holography data from complex optical systems. This code uses machine learning to efficiently determine the position of hundreds of mirror adjusters on multiple mirrors with few micrometer accuracy. We apply this approach to the example of the Simons Observatory 6 m telescope.

Individual Uniqueness in the Neonatal Functional Connectome.

The functional connectome is highly distinctive in adults and adolescents, underlying individual differences in cognition and behavior. However, it remains unknown whether the individual uniqueness of the functional connectome is present in neonates, who are far from mature. Here, we utilized the multiband resting-state functional magnetic resonance imaging data of 40 healthy neonates from the Developing Human Connectome Project and a split-half analysis approach to characterize the uniqueness of the functional connectome in the neonatal brain. Through functional connectome-based individual identification analysis, we found that all the neonates were correctly identified, with the most discriminative regions predominantly confined to the higher-order cortices (e.g., prefrontal and parietal regions). The connectivities with the highest contributions to individual uniqueness were primarily located between different functional systems, and the short- (0-30 mm) and middle-range (30-60 mm) connectivities were more distinctive than the long-range (>60 mm) connectivities. Interestingly, we found that functional data with a scanning length longer than 3.5 min were able to capture the individual uniqueness in the functional connectome. Our results highlight that individual uniqueness is present in the functional connectome of neonates and provide insights into the brain mechanisms underlying individual differences in cognition and behavior later in life.

The Simons Observatory: modeling optical systematics in the Large Aperture Telescope.

We present geometrical and physical optics simulation results for the Simons Observatory Large Aperture Telescope. This work was developed as part of the general design process for the telescope, allowing us to evaluate the impact of various design choices on performance metrics and potential systematic effects. The primary goal of the simulations was to evaluate the final design of the reflectors and the cold optics that are now being built. We describe nonsequential ray tracing used to inform the design of the cold optics, including absorbers internal to each optics tube. We discuss ray tracing simulations of the telescope structure that allow us to determine geometries that minimize detector loading and mitigate spurious near-field effects that have not been resolved by the internal baffling. We also describe physical optics simulations, performed over a range of frequencies and field locations, that produce estimates of monochromatic far-field beam patterns, which in turn are used to gauge general optical performance. Finally, we describe simulations that shed light on beam sidelobes from panel gap diffraction.

The Simons Observatory: metamaterial microwave absorber and its cryogenic applications.

Controlling stray light at millimeter wavelengths requires special optical design and selection of absorptive materials that should be compatible with cryogenic operating environments. While a wide selection of absorptive materials exists, these typically exhibit high indices of refraction and reflect/scatter a significant fraction of light before absorption. For many lower index materials such as commercial microwave absorbers, their applications in cryogenic environments are challenging. In this paper, we present a new tool to control stray light: metamaterial microwave absorber tiles. These tiles comprise an outer metamaterial layer that approximates a lossy gradient index anti-reflection coating. They are fabricated via injection molding commercially available carbon-loaded polyurethane (25% by mass). The injection molding technology enables mass production at low cost. The design of these tiles is presented, along with thermal tests to 1 K. Room temperature optical measurements verify their control of reflectance to less than 1% up to 65∘ angles of incidence, and control of wide angle scattering below 0.01%. The dielectric properties of the bulk carbon-loaded material used in the tiles is also measured at different temperatures, confirming that the material maintains similar dielectric properties down to 3 K.

Atypical meningioma: a retrospective analysis of six cases and literature review.

BACKGROUND: Atypical meningiomas (AM) are WHO grade II tumors with high heterogeneity and invasiveness, which are unique in their clinical presentation, imaging, pathology, treatment, and prognosis. In 2016, the diagnosis of AM remodified by the classification of central nervous system tumors of World Health Organization (WHO). In order to further analyze the diagnosis and treatment characteristics of AM, the clinical diagnosis, surgery treatment and follow-up data of 6 patients with AM in our hospital from January 2016 to December 2019 were analyzed retrospectively. METHODS: The clinical diagnosis, treatment and follow-up data of six patients with AM admitted to our hospital between January 2016 and December 2019 were analyzed retrospectively, and related literature was reviewed. RESULTS: The main clinical symptoms of the patients were increased intracranial pressure and functional area symptoms. MRI showed obvious enhancement, an unclear boundary with adjacent brain tissue, a large edema signal shadow in the white matter of peripheral brain tissue, and rapid enlargement in some cases. Pathological manifestations showed local necrosis and increased nuclear division activity. The results of immunocytochemistry showed that vimentin and epithelial membrane antigen (EMA) were positive, S-100 protein (S-100) and glial fibrillary acidic protein (GFAP) were negative, and the Ki-67 proliferation index was increased. Simpson's grade I-II resection was performed in five cases and no recurrence found after 4 to 46 months of follow-up. Simpson's grade IV resection was performed in one case and no follow-up was performed after discharge. CONCLUSIONS: AMs are highly heterogeneous and invasive. Histologic diagnosis is the gold standard for diagnosis and surgical resection is the first treatment choice. Total resection (Simpson I-II) helps to reduce recurrence.

Disrupted Intersubject Variability Architecture in Functional Connectomes in Schizophrenia.

Schizophrenia (SCZ) is a highly heterogeneous disorder with remarkable intersubject variability in clinical presentations. Previous neuroimaging studies in SCZ have primarily focused on identifying group-averaged differences in the brain connectome between patients and healthy controls (HCs), largely neglecting the intersubject differences among patients. We acquired whole-brain resting-state functional MRI data from 121 SCZ patients and 183 HCs and examined the intersubject variability of the functional connectome (IVFC) in SCZ patients and HCs. Between-group differences were determined using permutation analysis. Then, we evaluated the relationship between IVFC and clinical variables in SCZ. Finally, we used datasets of patients with bipolar disorder (BD) and major depressive disorder (MDD) to assess the specificity of IVFC alteration in SCZ. The whole-brain IVFC pattern in the SCZ group was generally similar to that in HCs. Compared with the HC group, the SCZ group exhibited higher IVFC in the bilateral sensorimotor, visual, auditory, and subcortical regions. Moreover, altered IVFC was negatively correlated with age of onset, illness duration, and Brief Psychiatric Rating Scale scores and positively correlated with clinical heterogeneity. Although the SCZ shared altered IVFC in the visual cortex with BD and MDD, the alterations of IVFC in the sensorimotor, auditory, and subcortical cortices were specific to SCZ. The alterations of whole-brain IVFC in SCZ have potential implications for the understanding of the high clinical heterogeneity of SCZ and the future individualized clinical diagnosis and treatment of this disease.