Connectomics

How does human brain structure mature during adolescence? We used MRI to measure cortical thickness and intracortical myelination in 297 population volunteers aged 14-24 y old. We found and replicated that association cortical areas were thicker and less myelinated than primary cortical areas at 14 y. However, association cortex had faster rates of shrinkage and myelination over the course of adolescence. Age-related increases in cortical myelination were maximized approximately at the internal layer of projection neurons...

Increasingly detailed data on the network topology of neural circuits create a need for theoretical principles that explain how these networks shape neural communication. Here we use a model of cascade spreading to reveal architectural features of human brain networks that facilitate spreading. Using an anatomical brain network derived from high-resolution diffusion spectrum imaging (DSI), we investigate scenarios where perturbations initiated at seed nodes result in global cascades that interact either cooperatively or competitively...

The brain's default mode network consists of discrete, bilateral and symmetrical cortical areas, in the medial and lateral parietal, medial prefrontal, and medial and lateral temporal cortices of the human, nonhuman primate, cat, and rodent brains. Its discovery was an unexpected consequence of brain-imaging studies first performed with positron emission tomography in which various novel, attention-demanding, and non-self-referential tasks were compared with quiet repose either with eyes closed or with simple visual fixation...

Network science provides theoretical, computational, and empirical tools that can be used to understand the structure and function of the human brain in novel ways using simple concepts and mathematical representations. Network neuroscience is a rapidly growing field that is providing considerable insight into human structural connectivity, functional connectivity while at rest, changes in functional networks over time (dynamics), and how these properties differ in clinical populations. In addition, a number of studies have begun to quantify network characteristics in a variety of cognitive processes and provide a context for understanding cognition from a network perspective...

Recently, there has been considerable interest in understanding brain networks in major depressive disorder (MDD). Neural pathways can be tracked in the living brain using diffusion-weighted imaging (DWI); graph theory can then be used to study properties of the resulting fiber networks. To date, global abnormalities have not been reported in tractography-based graph metrics in MDD, so we used a machine learning approach based on "support vector machines" to differentiate depressed from healthy individuals based on multiple brain network properties...

Communication across the brain networks is dependent on neuronal oscillations. Detection of the synchronous activation of neurons can be used to determine the well-being of the connectivity in the human brain networks. Well-connected highly synchronous activity can be measured by MEG, EEG, fMRI, and PET and then analyzed with several types of mathematical algorithms. Coherence is one mathematical method that can detect how well 2 or more sensors or brain regions have similar oscillatory activity with each other...

PURPOSE OF REVIEW: The neural connections, interconnections and organized networks of the central nervous system (CNS), which represent the human connectome, are critical for intact brain function. Consequently, disturbances at any level or juncture of these networks may alter behaviour and/or lead to brain dysfunction. In this review, we focus on highlighting recent work using advanced imaging methods to address alterations in the structural and functional connectome in patients with schizophrenia...

Pathological perturbations of the brain are rarely confined to a single locus; instead, they often spread via axonal pathways to influence other regions. Patterns of such disease propagation are constrained by the extraordinarily complex, yet highly organized, topology of the underlying neural architecture; the so-called connectome. Thus, network organization fundamentally influences brain disease, and a connectomic approach grounded in network science is integral to understanding neuropathology. Here, we consider how brain-network topology shapes neural responses to damage, highlighting key maladaptive processes (such as diaschisis, transneuronal degeneration and dedifferentiation), and the resources (including degeneracy and reserve) and processes (such as compensation) that enable adaptation...

MOTIVATION: In neuroscience, as in many other scientific domains, the primary form of knowledge dissemination is through published articles. One challenge for modern neuroinformatics is finding methods to make the knowledge from the tremendous backlog of publications accessible for search, analysis and the integration of such data into computational models. A key example of this is metascale brain connectivity, where results are not reported in a normalized repository. Instead, these experimental results are published in natural language, scattered among individual scientific publications...

Functional and structural connectivity measures, as assessed by means of functional and diffusion MRI, are emerging as potential intermediate biomarkers for Alzheimer disease (AD) and other disorders. This Review aims to summarize current evidence that connectivity biomarkers are associated with upstream and downstream disease processes (molecular pathology and clinical symptoms, respectively) in the major neurodegenerative diseases. The vast majority of studies have addressed functional and structural connectivity correlates of clinical phenotypes, confirming the predictable correlation with topography and disease severity in AD and frontotemporal dementia...

Brain structure varies between people in a markedly organized fashion. Communities of brain regions co-vary in their morphological properties. For example, cortical thickness in one region influences the thickness of structurally and functionally connected regions. Such networks of structural co-variance partially recapitulate the functional networks of healthy individuals and the foci of grey matter loss in neurodegenerative disease. This architecture is genetically heritable, is associated with behavioural and cognitive abilities and is changed systematically across the lifespan...