Early human brain development:insights into macroscale connectome wiring

BACKGROUND: Early brain development is closely dictated by distinct neurobiological principles. Here, we aimed to map early trajectories of structural brain wiring in the neonatal brain. METHODS: We investigated structural connectome development in 44 newborns, including 23 preterm infants and 21 full-term neonates scanned between 29 and 45 postmenstrual weeks. Diffusion-weighted imaging data were combined with cortical segmentations derived from T2 data to construct neonatal connectome maps. RESULTS: Projection fibers interconnecting primary cortices and deep gray matter structures were noted to mature faster than connections between higher-order association cortices (fractional anisotropy (FA) F = 58.9, p < 0.001, radial diffusivity (RD) F = 28.8, p < 0.001). Neonatal FA-values resembled adult FA-values more than RD, while RD approximated the adult brain faster (F = 358.4, p < 0.001). Maturational trajectories of RD in neonatal white matter pathways revealed substantial overlap with what is known about the sequence of subcortical white matter myelination from histopathological mappings as recorded by early neuroanatomists (mean RD 68 regions r = 0.45, p = 0.008). CONCLUSION: Employing postnatal neuroimaging we reveal that early maturational trajectories of white matter pathways display discriminative developmental features of the neonatal brain network. These findings provide valuable insight into the early stages of structural connectome development

Значение мотивации персонала на предприятии

Основная цель – систематизировать сведения о мотивации персонала и его значении на предприятии

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

The emergence of functional architecture during early brain development

Early human brain development constitutes a sequence of intricate processes resulting in the ontogeny of functionally operative neural circuits. Developmental trajectories of early brain network formation are genetically programmed and can be modified by epigenetic and environmental influences. Such alterations may exert profound effects on neurodevelopment, potentially persisting throughout the lifespan. This review focuses on the critical period of fetal and early postnatal brain development. Here we collate findings from neuroimaging studies, with a particular focus on functional MRI research that interrogated early brain network development in both health and high-risk or disease states. First, we will provide an overview of the developmental processes that take place from the embryonic period through early infancy in order to contextualize brain network formation. Second, functional brain network development in the typically developing brain will be discussed. Third, we will touch on prenatal and perinatal risk factors that may interfere with the trajectories of functional brain wiring, including prenatal substance exposure, maternal mental illness and preterm birth. Collectively, studies have revealed the blueprint of adult human brain organization to be present in the neonatal brain. Distinct attributes of human brain architecture have even been detected in the developing fetal brain from as early as 24 postconceptional weeks. During postnatal brain development, the brain's wiring pattern is further sculpted and modulated to become the full facsimile of the adult human brain, with functional brain network refinement being more rigorous than structural brain network maturation. Advances in neuroimaging techniques have paved the way towards a comprehensive understanding of the maturational pathways of brain network development and of how early developmental adversity may affect these trajectories. Such insights are fundamental for our understanding of human brain functioning, for early identification of infants at risk, as well as for future neuroprotective strategies

The emergence of functional architecture during early brain development

Early human brain development constitutes a sequence of intricate processes resulting in the ontogeny of functionally operative neural circuits. Developmental trajectories of early brain network formation are genetically programmed and can be modified by epigenetic and environmental influences. Such alterations may exert profound effects on neurodevelopment, potentially persisting throughout the lifespan. This review focuses on the critical period of fetal and early postnatal brain development. Here we collate findings from neuroimaging studies, with a particular focus on functional MRI research that interrogated early brain network development in both health and high-risk or disease states. First, we will provide an overview of the developmental processes that take place from the embryonic period through early infancy in order to contextualize brain network formation. Second, functional brain network development in the typically developing brain will be discussed. Third, we will touch on prenatal and perinatal risk factors that may interfere with the trajectories of functional brain wiring, including prenatal substance exposure, maternal mental illness and preterm birth. Collectively, studies have revealed the blueprint of adult human brain organization to be present in the neonatal brain. Distinct attributes of human brain architecture have even been detected in the developing fetal brain from as early as 24 postconceptional weeks. During postnatal brain development, the brain's wiring pattern is further sculpted and modulated to become the full facsimile of the adult human brain, with functional brain network refinement being more rigorous than structural brain network maturation. Advances in neuroimaging techniques have paved the way towards a comprehensive understanding of the maturational pathways of brain network development and of how early developmental adversity may affect these trajectories. Such insights are fundamental for our understanding of human brain functioning, for early identification of infants at risk, as well as for future neuroprotective strategies

Impact of surgery and anesthesia during early brain development: A perfect storm

Neonatal surgery and concomitant anesthesia coincide with a timeframe of rapid brain development. The speed and complexity of early brain development superimposed on immature regulatory mechanisms that include incomplete cerebral autoregulation, insufficient free radical scavenging and an immature immune response puts the brain at risk. Brain injury may have long-term consequences for multiple functional domains including cognition, learning skills, and behavior. Neurodevelopmental follow-up studies have noted mild-to-moderate deficits in children who underwent major neonatal surgery and related anesthesia. The present review evaluates neonatal surgery against the background of neurobiological processes that unfold at a pace unparalleled by any other period of human brain development. First, a structured summary of early brain development is provided in order to establish theoretical groundwork. Next, literature on brain injury and neurodevelopmental outcome after neonatal surgery is discussed. Special attention is given to recent findings of structural brain damage reported after neonatal surgery. Notably, high-quality imaging data acquired before surgery are currently lacking. Third, mechanisms of injury are interrogated taking the perspective of early brain development into account. We propose a novel disease model that constitutes a triad of inflammation, vascular immaturity, and neurotoxicity of prolonged exposure to anesthetic drugs. With each of these components exacerbating the other, this amalgam incites the perfect storm, resulting in brain injury. When examining the brain, it seems intuitive to distinguish between neonates (i.e., <60 postconceptional weeks) and more mature infants, multiple and/or prolonged anesthesia exposure and single, short surgery. This review culminates in an outline of anesthetic considerations and future directions that we believe will help move the field forward