The functions of the resting state networks (RSNs) revealed by functional MRI remain unclear, but it has seemed possible that networks emerge in parallel with the development of related cognitive functions. We tested the alternative hypothesis: that the full repertoire of resting state dynamics emerges during the period of rapid neural growth before the normal time of birth at term (around 40 wk of gestation). We used a series of independent analytical techniques to map in detail the development of different networks in 70 infants born between 29 and 43 wk of postmenstrual age (PMA). We characterized and charted the development of RSNs from recognizable but often fragmentary elements at 30 wk of PMA to full facsimiles of adult patterns at term. Visual, auditory, somatosensory, motor, default mode, frontoparietal, and executive control networks developed at different rates; however, by term, complete networks were present, several of which were integrated with thalamic activity. These results place the emergence of RSNs largely during the period of rapid neural growth in the third trimester of gestation, suggesting that they are formed before the acquisition of cognitive competencies in later childhood.blood oxygen level-dependent | functional MRI | neurodevelopment | intrinsic brain activity | newborn T he detection of spontaneous spatially coherent fluctuations of the blood oxygen level-dependent (BOLD) signal by functional MRI (fMRI) (1) offers potential insights into the largescale organization of neural function at the system levels (comprehensive review presented in 2). These resting state networks (RSNs) replicate the set of functional networks exhibited by the brain over its range of possible tasks (3), encompassing various spatially distinct neural systems, including the medial visual and lateral visual, auditory, somatosensory, motor, cerebellum, executive control, and frontoparietal or dorsal visual stream networks as well as the default mode network (DMN) (2-4). However, although the configurations and consistency of these networks are established, their functions are still not fully understood.Elucidating the ontogeny of RSNs could clarify the role of this large-scale neural organization. Previous studies at the time of normal birth [term, around 40 wk of postmenstrual age (PMA)] have detected RSNs in the primary visual areas, somatosensory and motor cortices, temporal cortex, cerebellum, prefrontal cortex (5, 6), and incomplete DMN (7) but did not find the complete DMN, executive control network, or dorsal visual network. This led to the suggestion that the full architecture emerges during later childhood in parallel with the development of corresponding cognitive functions.Here, we test the alternative hypothesis: that the full adult repertoire of resting state dynamics emerges during the period of rapid neural growth before the normal time of birth at 38-43 postconceptional weeks (term).We used a series of independent analytical techniques to map in detail the development of different networks in ...

White matter disruption is an important determinant of cognitive impairment after brain injury, but conventional neuroimaging underestimates its extent. In contrast, diffusion tensor imaging provides a validated and sensitive way of identifying the impact of axonal injury. The relationship between cognitive impairment after traumatic brain injury and white matter damage is likely to be complex. We applied a flexible technique—tract-based spatial statistics—to explore whether damage to specific white matter tracts is associated with particular patterns of cognitive impairment. The commonly affected domains of memory, executive function and information processing speed were investigated in 28 patients in the post-acute/chronic phase following traumatic brain injury and in 26 age-matched controls. Analysis of fractional anisotropy and diffusivity maps revealed widespread differences in white matter integrity between the groups. Patients showed large areas of reduced fractional anisotropy, as well as increased mean and axial diffusivities, compared with controls, despite the small amounts of cortical and white matter damage visible on standard imaging. A stratified analysis based on the presence or absence of microbleeds (a marker of diffuse axonal injury) revealed diffusion tensor imaging to be more sensitive than gradient-echo imaging to white matter damage. The location of white matter abnormality predicted cognitive function to some extent. The structure of the fornices was correlated with associative learning and memory across both patient and control groups, whilst the structure of frontal lobe connections showed relationships with executive function that differed in the two groups. These results highlight the complexity of the relationships between white matter structure and cognition. Although widespread and, sometimes, chronic abnormalities of white matter are identifiable following traumatic brain injury, the impact of these changes on cognitive function is likely to depend on damage to key pathways that link nodes in the distributed brain networks supporting high-level cognitive functions.

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline * Corresponding author Email address: a.makropoulos11@imperial.ac.uk (Antonios Makropoulos) 1 These authors contributed equally Preprint submitted to NeuroImage January 7, 2018peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/125526 doi: bioRxiv preprint first posted online Apr. 10, 2017; consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity.

Traumatic brain injury often results in cognitive impairments that limit recovery. The underlying pathophysiology of these impairments is uncertain, which restricts clinical assessment and management. Here, we use magnetic resonance imaging to test the hypotheses that: (i) traumatic brain injury results in abnormalities of functional connectivity within key cognitive networks; (ii) these changes are correlated with cognitive performance; and (iii) functional connectivity within these networks is influenced by underlying changes in structural connectivity produced by diffuse axonal injury. We studied 20 patients in the chronic phase after traumatic brain injury compared with age-matched controls. Network function was investigated in detail using functional magnetic resonance imaging to analyse both regional brain activation, and the interaction of brain regions within a network (functional connectivity). We studied patients during performance of a simple choice-reaction task and at 'rest'. Since functional connectivity reflects underlying structural connectivity, diffusion tensor imaging was used to quantify axonal injury, and test whether structural damage correlated with functional change. The patient group showed typical impairments in information processing and attention, when compared with age-matched controls. Patients were able to perform the task accurately, but showed slow and variable responses. Brain regions activated by the task were similar between the groups, but patients showed greater deactivation within the default mode network, in keeping with an increased cognitive load. A multivariate analysis of 'resting' state functional magnetic resonance imaging was then used to investigate whether changes in network function were present in the absence of explicit task performance. Overall, default mode network functional connectivity was increased in the patient group. Patients with the highest functional connectivity had the least cognitive impairment. In addition, functional connectivity at rest also predicted patterns of brain activation during later performance of the task. As expected, patients showed widespread white matter damage compared with controls. Lower default mode network functional connectivity was seen in those patients with more evidence of diffuse axonal injury within the adjacent corpus callosum. Taken together, our results demonstrate altered patterns of functional connectivity in cognitive networks following injury. The results support a direct relationship between white matter organization within the brain's structural core, functional connectivity within the default mode network and cognitive function following brain injury. They can be explained by two related changes: a compensatory increase in functional connectivity within the default mode network; and a variable degree of structural disconnection that modulates this change in network function.

Combining diffusion magnetic resonance imaging and network analysis in the adult human brain has identified a set of highly connected cortical hubs that form a "rich club"-a high-cost, highcapacity backbone thought to enable efficient network communication. Rich-club architecture appears to be a persistent feature of the mature mammalian brain, but it is not known when this structure emerges during human development. In this longitudinal study we chart the emergence of structural organization in mid to late gestation. We demonstrate that a rich club of interconnected cortical hubs is already present by 30 wk gestation. Subsequently, until the time of normal birth, the principal development is a proliferation of connections between core hubs and the rest of the brain. We also consider the impact of environmental factors on early network development, and compare term-born neonates to preterm infants at term-equivalent age. Though rich-club organization remains intact following premature birth, we reveal significant disruptions in both in cortical-subcortical connectivity and short-distance corticocortical connections. Rich club organization is present well before the normal time of birth and may provide the fundamental structural architecture for the subsequent emergence of complex neurological functions. Premature exposure to the extrauterine environment is associated with altered network architecture and reduced network capacity, which may in part account for the high prevalence of cognitive problems in preterm infants.connectome | brain development | tractography | preterm birth T o understand the functional properties of a complex network it is necessary to examine its structural organization and topological properties. In the human brain this can be achieved at a macroscale by tracing white matter connections between brain regions with diffusion MRI; this enables the interrogation of structural network topology in vivo with millimeter-scale spatial resolution, providing complementary evidence to experimental studies (1, 2).Network analysis of the adult human structural connectome has revealed a set of highly connected cortical "hubs" predominantly located in heteromodal association cortex, that provide a foundation for coherent neuronal activation across distal cortical regions (3-5). Further, some hub regions tend to be densely connected to each other, forming a "rich club" comprised of frontal and parietal cortex, precuneus, cingulate and the insula, as well as the hippocampus, thalamus, and putamen (6). Rich-club organization has been identified in a number of complex networks (7) and represents an attractive feature for investigation in the brain because rich-club connections tend to dominate network topology (8). Rich-club architecture appears to be a fundamental feature of the mature mammalian brain with similar organization identified in animal models (9, 10).It has been suggested that the emergence of complex neurological function is associated with the integration of major hubs across the cortex (11,...