Human connectomics
Highlights
► Structural and functional connectivity can be non-invasively measured across the whole human brain. ► Connectivity patterns of brain regions can aid parcellation and are related to their functional specialisation. ► Structural connectivity partially predicts functional interactions among brain regions. ► Network analysis of connectome maps reveals high clustering, modules and hubs as major features of brain organisation.
Introduction
The principal goal of connectomics is the comprehensive mapping and analysis of brain connectivity, across all scales, from the micro-scale of individual synaptic connections between neurons to the macro-scale of brain regions and interregional pathways [1]. The nascent field of macro-connectomics, at first glance, shares little but a name with its microscopic cousin. Instead of building maps of neural circuits that are detailed enough to include every synaptic connection, macro-connectomics attempts to map brain connections at the largest scale. In doing so, it bridges two influential ideas in systems neuroscience [2]. Functional specialisation considers large regions of the brain's grey matter as individual units that become engaged in different functional contexts; and functional integration considers how such brain regions interact and influence one-another to produce coherent experiences and behaviour (e.g. [3, 4]). It is this systems-level understanding of neural processing that has most to benefit from macro-connectomics, which aims to provide systematic approaches both for identifying functional subunits, and for mapping the connections between them.
Invasive techniques for localising brain regions and tracing anatomical connections have existed for many decades. Tracers are injected into a candidate brain region, taken up inside cells and transported along the axon. Post-mortem histological staining then reveals the distribution of the labelled axons and their connections with distant cells. Tracer techniques are exquisitely precise and accurate. Using different tracers, experimenters may specifically map connections travelling in different pathways or emerging from different cell types or layers. Using viral tracers, monosynaptic or multi-synaptic connections may be selectively labelled. Recent advances have been directed at detailed and accurate quantification of the density of regional brain connections [5, 6••].
By comparison, currently available techniques for measuring brain connections non-invasively are based on a process of inference – their estimation is indirect; they can be difficult to interpret quantitatively; and they continue to be error-prone. However, their non-invasive nature and ease of measurement permit us to address scientific questions that cannot be answered by any other means. In particular, brain connections can be measured in living human subjects, and measurements can be made simultaneously across the entire brain, thus permitting the creation of a comprehensive whole-brain connection map, the connectome. Hence, areal connections may be compared in humans across individuals and across many cortical and subcortical sites, allowing detailed studies of connectional organisation and individual differences. Furthermore, these techniques enable direct investigation of the common rationale that underlies the study of brain circuitry at any scale – the assumed importance of connectional architecture for functional processing and thence behaviour. Using in vivo techniques, this dependence may be tested directly, by comparing structural connectivity to measurements of regional activations and interregional correlations (functional connectivity). Furthermore, variations in anatomical or functional connectivity across the population may be related to variations in behavioural abilities [7•].
In this review, we survey the current state-of-the-art in human connectomics, including a comparison of techniques for mapping brain connectivity, the use of connectivity data to discern functionally specialised regions, the relation of structural to functional connections, and the use of network analysis measures to quantitatively characterise the architecture of the human connectome.
Section snippets
Measuring regional brain connections in the living human brain
There are two common approaches for mapping interregional connections in vivo. They both use magnetic resonance imaging (MRI), but rely on very different principles. Diffusion tractography aims to infer the tracks of axon bundles millimetre-by-millimetre as they traverse the brain's white matter. By contrast, resting-state functional MRI measures spontaneous fluctuations in the blood-oxygenation-level-dependent (BOLD) signal in grey matter regions and estimates statistical dependencies between
Connectional anatomy and functional specialisation
Despite these limitations, it is clear that both anatomical and functional connectivity, measured either invasively or by MRI, place strong constraints on regional brain function. When the results of many invasive tracer studies are considered simultaneously [37], it is possible to build ‘connectional fingerprints’ for brain regions that differ in their cellular cytoarchitecture, which is assumed to reflect functional divisions. These fingerprints show the pattern of afferent and efferent
Relating structural to functional connections
The central rationale for human connectomics builds on the premise that structural brain connectivity can serve as a basis for understanding brain dynamics and behaviour. As discussed earlier the two main techniques for measuring regional brain connections are strikingly different both in what they attempt to measure (structural vs functional connections) and in how they measure it. Can the two ways of mapping brain connectivity be interrelated?
A series of convergent studies have reported that
Network analysis and modelling
Brain networks generated by human connectomics studies can be described and modelled with a broad range of network analysis tools [64•, 65] (Figure 4), many of which have also been profitably applied in other biological systems. In general, all networks, including those generated from brain data, consist of collections of nodes and edges, usually aggregated in matrix form. In structural brain networks, nodes correspond to neural elements (typically brain regions), and edges define their
Conclusion
Comprehensive maps of the structural and functional connectivity of the human brain have provided important insights into how anatomical connections shape and constrain brain dynamics, and how this relation varies across individuals. New approaches from network analysis and modelling have begun to reveal some fundamental motifs of human brain architecture and their relation to brain function is a focus of ongoing research. The commencement of several concerted efforts to map the human
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as:
• of special interest
•• of outstanding interest
Acknowledgements
T.B. was supported by The Wellcome Trust, UK Medical Research Council and the EU CONNECT project.1 O.S. was supported by the J.S. McDonnell Foundation. Both authors were funded in part by the Human Connectome Project (1U54MH091657-01) from the 16 NIH Institutes
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