underway (mikula, 2012). an alternative approach to mapping connectivity was recently proposed by zador and colleagues (zador et al., 2012). zador's technique, called boinc (barcoding of individual neuronal connections) uses high-throughput dna sequencing to map neural circuits. briefly, the approach consists of labelling each neuron with a unique dna barcode, transferring barcodes between synaptically coupled neurons (for example using suid herpesvirus 1, suhv1), and fusion of barcodes to represent a synaptic pair. this approach has the potential to be cheap, fast, and extremely high-throughput. in 2016, the intelligence advanced research projects activity of the united states government launched microns, a five-year, multi-institute project to map one cubic millimeter of rodent visual cortex, as part of the brain initiative. though only a small volume of biological tissue, this project will yield one of the largest micro-scale connectomics datasets currently in existence. mapping functional connectivity using fmri in the resting state and during tasks, functions of the connectome circuits are being studied. just as detailed road maps of the earth's surface do not tell us much about the kind of vehicles that travel those roads or what cargo they are hauling, to understand how neural structures result in specific functional behavior such as consciousness, it is necessary to build theories that relate functions to anatomical connectivity. however, the bond between structural and functional connectivity is not straightforward. computational models of whole-brain network dynamics are valuable tools to investigate the role of the anatomical network in shaping functional connectivity. in particular, computational models can be used to predict the dynamic effect of lesions in the connectome. as a network or graph the connectome can be studied as a network by means of network science and graph theory. in case of a micro-scale connectome, the nodes of this network (or graph) are the neurons, and the edges correspond to the synapses between those neurons. for the macro-scale connectome, the nodes correspond to the rois (regions of interest), while the edges of the graph are derived from the axons interconnecting those areas. thus connectomes are sometimes referred to as brain graphs, as they are indeed graphs in a mathematical sense which describe the connections in the brain (or, in a broader sense, the whole nervous system). one group of researchers (iturria-medina et al., 2008) has constructed connectome data sets using diffusion tensor imaging (dti) followed by the derivation of average connection probabilities between 70–90 cortical and basal brain gray matter areas. all networks were found to have small-world attributes and "broad-scale" degree distributions. an analysis of betweenness centrality in these networks demonstrated high centrality for the precuneus, the insula, the superior parietal and the superior frontal cortex. another group (gong et al. 2008) has applied dti to map a network of anatomical connections between 78 cortical regions. this study also identified several hub regions in the human brain, including the precuneus and the superior frontal gyrus. hagmann et al. (2007) constructed a connection matrix from fiber densities measured between homogeneously distributed and equal-sized rois numbering between 500 and 4000. a quantitative analysis of connection matrices obtained for approximately 1,000 rois and approximately 50,000 fiber pathways from two subjects demonstrated an exponential (one-scale) degree distribution as well as robust small-world attributes for the network. the data sets were derived from diffusion spectrum imaging (dsi) (wedeen, 2005), a variant of diffusion-weighted imaging that is sensitive to intra-voxel heterogeneities in diffusion directions caused by crossing fiber tracts and thus allows more accurate mapping of axonal trajectories than other diffusion imaging approaches (wedeen, 2008). the combination of whole-head dsi datasets acquired and processed according to the approach developed by hagmann et al. (2007) with the graph analysis tools conceived initially for animal tracing studies (sporns, 2006; sporns, 2007) allow a detailed study of the network structure of human cortical connectivity (hagmann et al., 2008). the human brain network was characterized using a broad array of network analysis methods including core decomposition, modularity analysis, hub classification and centrality. hagmann et al. presented evidence for the existence of a structural core of highly and mutually interconnected brain regions, located primarily in posterior medial and parietal cortex. the core comprises portions of the posterior cingulate cortex, the precuneus, the cuneus, the paracentral lobule, the isthmus of the cingulate, the banks of the superior temporal sulcus, and the inferior and superior parietal cortex, all located in both cerebral hemispheres. a subfield of connectomics deals with the comparison of the brain graphs of multiple subjects. it is possible to build a consensus graph such the budapest reference connectome by allowing only edges that are present in at least k connectomes, for a selectable k parameter. the budapest reference connectome has led the researchers to the discovery of the consensus connectome dynamics of the human brain graphs. the edges appeared in all of the brain graphs form a connected subgraph around the brainstem. by allowing gradually less frequent edges, this core subgraph grows continuously, as a shrub. the growth dynamics may reflect the individual brain development and provide an opportunity to direct some edges of the human consensus brain graph. alternatively, local difference which are statistically significantly different among groups have attracted more attention as they highlight specific connections and therefore shed more light on specific brain traits or pathology. hence, algorithms to find local difference between graph populations have also been introduced (e.g. to compare case versus control groups). those can be found by using either an adjusted t-test, or a sparsity model, with the aim of finding statistically significant connections which are different among those groups. the possible causes of the difference between individual connectomes were also investigated. indeed, it has been found that the macro-scale connectomes of women contain significantly more edges than those of men, and a larger portion of the edges in the connectomes of women run between the two hemispheres. in addition, connectomes generally exhibit a small-world character, with overall cortical connectivity decreasing with age. the aim of the as of 2015 ongoing hcp lifespan pilot project is to identify connectome differences between 6 age groups (4–6, 8–9, 14–15, 25–35, 45–55, 65–75). more recently, connectograms have been used to visualize full-brain data by placing cortical areas around a circle, organized by lobe. inner circles then depict cortical metrics on a color scale. white matter fiber connections in dti data are then drawn between these cortical regions and weighted by fractional anisotropy and strength of the connection. such graphs have even been used to analyze the damage done to the famous traumatic brain injury patient phineas gage. statistical graph theory is an emerging discipline which is developing sophisticated pattern recognition and inference tools to parse these brain graphs (goldenberg et al., 2009). recent research studied the brain as a signed network and indicated that hubness in positive and negative subnetworks increases the stability of the brain network. it highlighted the role of negative functional connections that are paid less attention to. plasticity of the connectome at the beginning of the connectome project, it was thought that the connections between neurons were unchangeable once established and that only individual synapses could be altered. however, recent evidence suggests that connectivity is also subject to change, termed neuroplasticity. there are two ways that the brain can rewire: formation and removal of synapses in an established connection or formation or removal of entire connections between neurons. both mechanisms of rewiring are useful for learning completely novel tasks that may require entirely new connections between regions of the brain. however, the ability of the brain to gain or lose entire connections poses an issue for mapping a universal species connectome. although rewiring happens on different scales, from microscale to macroscale, each scale does not occur in isolation. for example, in the c. elegans connectome, the total number of synapses increases 5-fold from birth to adulthood, changing both local and global network properties. other developmental connectomes, such as the muscle connectome, retain some global network properties even though the number of synapses decreases by 10-fold in early postnatal life. macroscale rewiring evidence for macroscale rewiring mostly comes from research on grey and white matter density, which could indicate new connections or changes in axon density. direct evidence for this level of rewiring comes from primate studies, using viral tracing to map the formation of connections. primates that were taught to use novel tools developed new connections between the interparietal cortex and higher visual areas of the brain. further viral tracing studies have provided evidence that macroscale rewiring occurs in adult animals during associative learning. however, it is not likely that long-distance neural connections undergo extensive rewiring in adults. small changes in an already established nerve tract are likely what is observed in macroscale rewiring. mesoscale rewiring rewiring at the mesoscale involves studying the presence or absence of entire connections between neurons. evidence for this level of rewiring comes from observations that local circuits form new connections as a result of experience-dependent plasticity in the visual cortex. additionally, the number of local connections between pyramidal neurons in the primary somatosensory cortex increases following altered whisker sensory experience in rodents. microscale rewiring microscale rewiring is the formation or removal of synaptic connections between two neurons and can be studied with longitudinal two-photon imaging. dendritic spines on pyramidal neurons can be shown forming within days following sensory experience and learning. changes can even be seen within five hours on apical tufts of layer five pyramidal neurons in the primary motor cortex after a seed reaching task in primates. datasets humans the human connectome project, sponsored by the national institutes of health (nih), was created with the goal of mapping the 86 billion neurons (and their connections) in a human brain. roundworm the first (and so far only) fully reconstructed connectome belongs to the roundworm caenorhabditis elegans. the major effort began with the first electron micrographs published by white, brenner et al., 1986. based on this seminal work, the first ever connectome (then called "neural circuitry database" by the authors) for c. elegans was published in book form with accompanying floppy disks by achacoso and yamamoto in 1992. the very first paper on the computer representation of its connectome was presented and published three years earlier in 1989 by achacoso at the symposium on computer application in medical care (scamc). the c. elegans connectome was later revised and expanded to show changes during the animal's development. fruit fly a full connectome of the larval brain of drosophila melanogaster, including 3016 neurons and 548,000 synapses, was published in march 2023. the fruit fly connectome was used to identify an area of the fruit fly brain that is involved in odor detection and tracking. flies choose a direction in turbulent conditions by combining information about the direction of air flow and the movement of odor packets. based on the fly connectome, processing must occur in the “fan-shaped body” where wind-sensing neurons and olfactory direction-sensing neurons cross. mouse partial connectomes of a mouse retina and mouse primary visual cortex are available. the first full connectome of a mammalian circuit was constructed in 2021. this construction included the development of all connections between the central nervous system and a single muscle from birth to adulthood. eyewire game these paragraphs are an excerpt from eyewire. eyewire is a citizen science game from sebastian seung's lab at princeton university. it is a human-based computation game that uses players to map retinal neurons. eyewire launched on december 10, 2012. the game utilizes data generated by the max planck institute for medical research.