Uncovering intrinsic connectional architecture of functional networks in awake rat brain

Intrinsic connectional architecture of the brain is a crucial element in understanding the governing principle of brain organization. To date, enormous effort has been focused on addressing this issue in humans by combining resting-state functional magnetic resonance imaging (rsfMRI) with other techniques. However, this research area is significantly underexplored in animals, perhaps because of confounding effects of anesthetic agents used in most animal experiments on functional connectivity. To bridge this gap, we have systematically investigated the intrinsic connectional architecture in the rodent brain by using a previously established awake-animal imaging model. First, group independent component analysis was applied to the rsfMRI data to extract elementary functional clusters of the brain. The connectional relationships between these clusters, as evaluated by partial correlation analysis, were then used to construct a graph of whole-brain neural network. This network exhibited the typical features of small-worldness and strong community structures seen in the human brain. Finally, the whole-brain network was segregated into community structures using a graph-based analysis. The results of this work provided a functional atlas of intrinsic connectional architecture of the rat brain at both intraregion and interregion levels. More importantly, the current work revealed that functional networks in rats are organized in a nontrivial manner and conserve fundamental topological properties that are also seen in the human brain. Given the high psychopathological relevance of network organization of the brain, this study demonstrated the feasibility of studying mechanisms and therapies of multiple neurological and psychiatric diseases through translational research

Typical and atypical development of the brain’s functional network architecture

The human brain is a complex organ that gives rise to many behaviors. Specialized neural regions cooperate as functional networks that form an intricate functional architecture. Development provides a unique window into how brain functioning and human thinking are affected if the necessary neural features and connections are not fully formed. Similarly, developmental disorders can shed light on atypical trajectories of neural systems that may lead to or be a consequence of symptomatic behavior. A description of the typical and atypical development of functional networks is essential to identify the features of brain organization critical for mature human thinking and to provide better diagnosis, treatment, and prognosis in neurodevelopmental disorders. Recently, resting state functional MRI has been found to illuminate functionally related regions, giving access to functional networks and the organization of brain’s functional architecture. This thesis aims to harness resting-state functional connectivity to explore how functional networks coordinate over the course of development. First, I present our work investigating the organizing principles of typical developmental patterns in functional networks (Chapter 2). Then, I apply these approaches to the atypical development of functional networks in Tourette syndrome (TS), a developmental disorder characterized by motor and vocal tics. In this work, we tested whether the patterns in functional networks that distinguish individuals with TS from controls differ between children and adults and alter the typical developmental pattern of functional networks (Chapter 3). Lastly, I present our work to identify and describe the coordination of specific functional networks that develop atypically in TS (Chapter 4)

Module hierarchy and centralisation in the anatomy and dynamics of human cortex

Systems neuroscience has recently unveiled numerous fundamental features of the macroscopic architecture of the human brain, the connectome, and we are beginning to understand how characteristics of brain dynamics emerge from the underlying anatomical connectivity. The current work utilises complex network analysis on a high-resolution structural connectivity of the human cortex to identify generic organisation principles, such as centralised, modular and hierarchical properties, as well as specific areas that are pivotal in shaping cortical dynamics and function. After confirming its small-world and modular architecture, we characterise the cortex’ multilevel modular hierarchy, which appears to be reasonably centralised towards the brain’s strong global structural core. The potential functional importance of the core and hub regions is assessed by various complex network metrics, such as integration measures, network vulnerability and motif spectrum analysis. Dynamics facilitated by the large-scale cortical topology is explored by simulating coupled oscillators on the anatomical connectivity. The results indicate that cortical connectivity appears to favour high dynamical complexity over high synchronizability. Taking the ability to entrain other brain regions as a proxy for the threat posed by a potential epileptic focus in a given region, we also show that epileptic foci in topologically more central areas should pose a higher epileptic threat than foci in more peripheral areas. To assess the influence of macroscopic brain anatomy in shaping global resting state dynamics on slower time scales, we compare empirically obtained functional connectivity data with data from simulating dynamics on the structural connectivity. Despite considerable micro-scale variability between the two functional connectivities, our simulations are able to approximate the profile of the empirical functional connectivity. Our results outline the combined characteristics a hierarchically modular and reasonably centralised macroscopic architecture of the human cerebral cortex, which, through these topological attributes, appears to facilitate highly complex dynamics and fundamentally shape brain function

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

Functional Geometry of Human Connectomes

Mapping the brain imaging data to networks, where nodes represent anatomical brain regions and edges indicate the occurrence of fiber tracts between them, has enabled an objective graph-theoretic analysis of human connectomes. However, the latent structure on higher-order interactions remains unexplored, where many brain regions act in synergy to perform complex functions. Here we use the simplicial complexes description of human connectome, where the shared simplexes encode higher-order relationships between groups of nodes. We study consensus connectome of 100 female (F-connectome) and of 100 male (M-connectome) subjects that we generated from the Budapest Reference Connectome Server v3.0 based on data from the Human Connectome Project. Our analysis reveals that the functional geometry of the common F&M-connectome coincides with the M-connectome and is characterized by a complex architecture of simplexes to the 14th order, which is built in six anatomical communities, and linked by short cycles. The F-connectome has additional edges that involve different brain regions, thereby increasing the size of simplexes and introducing new cycles. Both connectomes contain characteristic subjacent graphs that make them 3/2-hyperbolic. These results shed new light on the functional architecture of the brain, suggesting that insightful differences among connectomes are hidden in their higher-order connectivity