Functional properties of resting state networks in healthy full-term newborns.

Objective, early, and non-invasive assessment of brain function in high-risk newborns is critical to initiate timely interventions and to minimize long-term neurodevelopmental disabilities. A prerequisite to identifying deviations from normal, however, is the availability of baseline measures of brain function derived from healthy, full-term newborns. Recent advances in functional MRI combined with graph theoretic techniques may provide important, currently unavailable, quantitative markers of normal neurodevelopment. In the current study, we describe important properties of resting state networks in 60 healthy, full-term, unsedated newborns. The neonate brain exhibited an efficient and economical small world topology: densely connected nearby regions, sparse, but well integrated, distant connections, a small world index greater than 1, and global/local efficiency greater than network cost. These networks showed a heavy-tailed degree distribution, suggesting the presence of regions that are more richly connected to others (\u27hubs\u27). These hubs, identified using degree and betweenness centrality measures, show a more mature hub organization than previously reported. Targeted attacks on hubs show that neonate networks are more resilient than simulated scale-free networks. Networks fragmented faster and global efficiency decreased faster when betweenness, as opposed to degree, hubs were attacked suggesting a more influential role of betweenness hub in the neonate network

Human brain development over the early years

Recent studies of the structural and functional development of the human brain over the early years have highlighted the rapid development of brain structures and their interconnectivity. Some regional functional specializations emerge within the first months after birth, while others have a more protracted course of development spanning over the first decade or longer. While some anatomical changes enable the emergence of new functions, evidence also points to the importance of resting state oscillations in sculpting neural architecture during development. In atypical development differences in brain structure, function and task-related activity in infancy often precede the emergence of later diagnostic behavioural symptoms

The anatomical distance of functional connections predicts brain network topology in health and schizophrenia.

The human brain is a topologically complex network embedded in anatomical space. Here, we systematically explored relationships between functional connectivity, complex network topology, and anatomical (Euclidean) distance between connected brain regions, in the resting-state functional magnetic resonance imaging brain networks of 20 healthy volunteers and 19 patients with childhood-onset schizophrenia (COS). Normal between-subject differences in average distance of connected edges in brain graphs were strongly associated with variation in topological properties of functional networks. In addition, a club or subset of connector hubs was identified, in lateral temporal, parietal, dorsal prefrontal, and medial prefrontal/cingulate cortical regions. In COS, there was reduced strength of functional connectivity over short distances especially, and therefore, global mean connection distance of thresholded graphs was significantly greater than normal. As predicted from relationships between spatial and topological properties of normal networks, this disorder-related proportional increase in connection distance was associated with reduced clustering and modularity and increased global efficiency of COS networks. Between-group differences in connection distance were localized specifically to connector hubs of multimodal association cortex. In relation to the neurodevelopmental pathogenesis of schizophrenia, we argue that the data are consistent with the interpretation that spatial and topological disturbances of functional network organization could arise from excessive "pruning" of short-distance functional connections in schizophrenia.PEV is supported by the Medical Research Council (grant number MR/K020706/1). This work was supported by the Neuroscience in Psychiatry Network (NSPN) which is funded by a Wellcome Trust strategy award to the University of Cambridge and University College London. ETB is employed half-time by the University of Cambridge and half-time by GlaxoSmithKline; he holds stock in GSK.This is the final published version. It first appeared at http://onlinelibrary.wiley.com/doi/10.1111/jcpp.12365/full

A Network Neuroscience Approach to Typical and Atypical Brain Development.

Human brain networks based on neuroimaging data have already proven useful in characterizing both normal and abnormal brain structure and function. However, many brain disorders are neurodevelopmental in origin, highlighting the need to go beyond characterizing brain organization in terms of static networks. Here, we review the fast-growing literature shedding light on developmental changes in network phenotypes. We begin with an overview of recent large-scale efforts to map healthy brain development, and we describe the key role played by longitudinal data including repeated measurements over a long period of follow-up. We also discuss the subtle ways in which healthy brain network development can inform our understanding of disorders, including work bridging the gap between macroscopic neuroimaging results and the microscopic level. Finally, we turn to studies of three specific neurodevelopmental disorders that first manifest primarily in childhood and adolescence/early adulthood, namely psychotic disorders, attention-deficit/hyperactivity disorder, and autism spectrum disorder. In each case we discuss recent progress in understanding the atypical features of brain network development associated with the disorder, and we conclude the review with some suggestions for future directions

THE MODULAR BRAIN: SPATIOTEMPORAL EVOLUTION IN THE EARLY BRAIN FUNCTIONAL DEVELOPMENT

Characterizing functional development of the human brain is of critical importance. With an improved understanding of the functional maturation processes, assessing and monitoring the normal and abnormal brain development are feasible. The ultimate goal of this dissertation was to provide novel insights into early brain functional development. Three major achievements have been accomplished. First, we found that brain functional development could be separated into three distinct stages in the first two years of life. Specifically, from stages 1 to 2, the connection density increases by almost two-fold, local efficiency is significantly improved, and there is no change in global efficiency. From stages 2 to 3, connection density increases slightly, local efficiency shows no change, and a significant increase in global efficiency is observed. In addition, 27 core regions are identified which yield clustering results that resemble those obtained using all brain regions. Second, we delineated the development of brain functional integration by computing participation coefficients. Improved functional integration was uncovered after 12 months of age. The spatiotemporal distribution of the brain diverse clubs was also revealed. Comparing with the adult result, low spatial overlapping ratios (~25%) were observed in infant groups. Nevertheless, posterior cingulate cortex, amygdala, hippocampus, and fusiform area have been consistently observed in infants and adults, suggesting the critical role of these regions for functional integration starting from birth. Finally, we delineated the emergency of a functionally flexible brain during early infancy. Continually increased flexibility was found in whole brain, high-order brain functional networks and motor network, while a temporally stable pattern was observed in visual networks. Moreover, visual network functional flexibility at 3 months of age was significantly associated with the behavioral performance measured at 5/6 years of age. We further termed the brain regions with the highest 10% flexibility as the “flexible club,” and compared these regions with hubs and diverse clubs to uncover their unique functional roles. In conclusion, our results provide important brain developmental patterns during the first two years of life. These findings fill the gaps on brain functional development, and may shed new light on the underlying processes of brain maturation.Doctor of Philosoph

Towards Quantitative Assessment of Human Functional Brain Development in the First Years of Life

Characterizing the developmental process of human brain function is of critical importance not only in gaining insight into its maturing architecture but also in providing essential age-specific information for assessment and monitoring of both normal and abnormal neurodevelopment. The recent development of non-invasive neuroimaging techniques, particularly resting-state functional connectivity magnetic resonance imaging (rfcMRI) has opened a window into very early functional brain development. Together with diffusion tensor imaging (DTI), rfcMRI offers the unique opportunity to tackle a largely unknown area - early functional brain development as well as its structural underpinnings. In this dissertation, both rfcMRI and DTI were utilized to delineate early brain development. Structurally, we found that white matter fiber tracts experience most rapid axonal development as well as myelination in the first year, followed by a much slower but steady growth thereafter. Spatially, the central white matter tracts develop earlier than the peripheral ones. Functionally, by focusing on one of the most salient high-order cognitive networks during the resting condition (absence of any goal-directed tasks) - the default-mode network, our results showed early emergence of this network in neonates, followed by dramatic synchronization during the first year of life and an adult-like architecture in 2yr olds regarding the core regions. Moreover, we found the anti-correlation (competing functions) between the default network and the task positive network is largely mediated by the frontal-parietal control system using both regional and newly designed network-level approaches, shedding light on brain's functional interaction patterns at a network level. Finally, focusing on the whole brain architecture, our results showed interesting patterns of brain's functional organization development. Specifically, the brain's functional architecture develops from more anatomically sensible to more functionally sensible; for the functional hubs, they gradually shift from sensory-related cortices to higher-order cognitive function related cortices. In conclusion, by focusing on neural circuit development at regional, network as well as whole brain levels and coupling with structural elements, our results delineated interesting and important functional circuits growth patterns and may shed light on the potential principles guiding normal early brain functional development

Relationship between large-scale structural and functional brain connectivity in the human lifespan

The relationship between the anatomical structure of the brain and its functional organization is not straightforward and has not been elucidated yet, despite the growing interest this topic has received in the last decade. In particular, a new area of research has been defined in these years, called \u2019connectomics\u2019: this is the study of the different kinds of \u2019connections\u2019 existing among micro- and macro-areas of the brain, from structural connectivity \u2014 described by white matter fibre tracts physically linking cortical areas \u2014 to functional connectivity \u2014 defined as temporal correlation between electrical activity of different brain regions \u2014 to effective connectivity\u2014defining causal relationships between functional activity of different brain areas. Cortical areas of the brain physically linked by tracts of white matter fibres are known to exhibit a more coherent functional synchronization than areas which are not anatomically linked, but the absence of physical links between two areas does not imply a similar absence of functional correspondence. Development and ageing, but also structural modifications brought on by malformations or pathology, can modify the relation between structure and function. The aim of my PhD work has been to further investigate the existing relationship between structural and functional connectivity in the human brain at different ages of the human lifespan, in particular in healthy adults and both healthy and pathological neonates and children. These two \u2019categories\u2019 of subjects are very different in terms of the analysis techniques which can be applied for their study, due to the different characteristics of the data obtainable from them: in particular, while healthy adult data can be studied with the most advanced state-of-the-art methods, paediatric and neonatal subjects pose hard constraints to the acquisition methods applicable, and thus to the quality of the data which can be analysed. During this PhD I have studied this relation in healthy adult subjects by comparing structural connectivity from DWI data with functional connectivity from stereo-EEG recordings of epileptic patients implanted with intra-cerebral electrodes. I have then focused on the paediatric age, and in particular on the challenges posed by the paediatric clinical environment to the analysis of structural connectivity. In collaboration with the Neuroradiology Unit of the Giannina Gaslini Hospital in Genova, I have adapted and tested advanced DWI analysis methods for neonatal and paediatric data, which is commonly studied with less effective methods. We applied the same methods to the study of the effects of a specific brain malformation on the structural connectivity in 5 paediatric patients. While diffusion weighted imaging (DWI) is recognised as the best method to compute structural connectivity in the human brain, the most common methods for estimating functional connectivity data \u2014 functional MRI (fMRI) and electroencephalography (EEG) \u2014 suffer from different limitations: fMRI has good spatial resolution but low temporal resolution, while EEG has a better temporal resolution but the localisation of each signal\u2019s originating area is difficult and not always precise. Stereo-EEG (SEEG) combines strong spatial and temporal resolution with a high signal-to-noise ratio and allows to identify the source of each signal with precision, but is not used for studies on healthy subjects because of its invasiveness. Functional connectivity in children can be computed with either fMRI, EEG or SEEG, as in adult subjects. On the other hand, the study of structural connectivity in the paediatric age is met with obstacles posed by the specificity of this data, especially for the application of the advanced DWI analysis techniques commonly used in the adult age. Moreover, the clinical environment introduces even more constraints on the quality of the available data, both in children and adults, further limiting the possibility of applying advanced analysis methods for the investigation of connectivity in the paediatric age. Our results on adult subjects showed a positive correlation between structural and functional connectivity at different granularity levels, from global networks to community structures to single nodes, suggesting a correspondence between structural and functional organization which is maintained at different aggregation levels of brain units. In neonatal and paediatric subjects, we successfully adapted and applied the same advanced DWI analysis method used for the investigation in adults, obtaining white matter reconstructions more precise and anatomically plausible than with methods commonly used in paediatric clinical environments, and we were able to study the effects of a specific type of brain malformation on structural connectivity, explaining the different physical and functional manifestation of this malformation with respect to similar pathologies. This work further elucidates the relationship between structural and functional connectivity in the adult subject, and poses the basis for a corresponding work in the neonatal and paediatric subject in the clinical environment, allowing to study structural connectivity in the healthy and pathological child with clinical data