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The Human Connectome: a Structural Description of the Human Brain Olaf Sporns*, Giulio Tononi, Rolf Ko¨ Tter

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The Human Connectome: a Structural Description of the Human Brain Olaf Sporns*, Giulio Tononi, Rolf Ko¨ Tter Review The Human Connectome: A Structural Description of the Human Brain Olaf Sporns*, Giulio Tononi, Rolf Ko¨ tter ABSTRACT Experimental approaches to human cognition have been significantly enhanced by the arrival of functional he connection matrix of the human brain (the human neuroimaging [5], a set of techniques that can be applied to ‘‘connectome’’) represents an indispensable study a broad range of cognitive functions, with ever- T foundation for basic and applied neurobiological increasing spatial and temporal resolution. But the research. However, the network of anatomical connections mechanistic interpretation of neuroimaging data is limited, linking the neuronal elements of the human brain is still in part due to a severe lack of information on the structure largely unknown. While some databases or collations of large- and dynamics of the networks that generate the observed scale anatomical connection patterns exist for other activation patterns. A potential theoretical framework for mammalian species, there is currently no connection matrix conceptualizing cognition as a network phenomenon is based of the human brain, nor is there a coordinated research effort on two main organizational principles found in the cerebral to collect, archive, and disseminate this important cortex, functional segregation, and functional integration information. We propose a research strategy to achieve this [6,7]. Emerging network theories of cognition emphasize the goal, and discuss its potential impact. contextual [8], distributed [9], dynamic [10], and degenerate [11,12] nature of structure–function mappings in the brain. Introduction To successfully map structure to function in the human brain, To understand the functioning of a network, one must we urgently need a comprehensive, detailed structural model know its elements and their interconnections. The purpose of of neuronal units and their connections. Connectional this article is to discuss research strategies aimed at a models of the human brain are scarce and poorly defined comprehensive structural description of the network of [13], and they are largely based on extrapolating anatomical elements and connections forming the human brain. We information from other primate species such as the macaque propose to call this dataset the human ‘‘connectome,’’ and we monkey, an approach that is problematic [14], in part, argue that it is fundamentally important in cognitive because of our incomplete understanding of evolutionary neuroscience and neuropsychology. The connectome will changes. significantly increase our understanding of how functional Our proposal to assemble the human connectome has brain states emerge from their underlying structural several components. First, we attempt to define a level of substrate, and will provide new mechanistic insights into how scale at which a first draft of the human connectome might be brain function is affected if this structural substrate is assembled. We consider several potential experimental and disrupted. It will provide a unified, time-invariant, and neuroinformatics approaches for creating this first draft. We readily available neuroinformatics resource that could be then discuss potential problems and limitations of the used in virtually all areas of experimental and theoretical connectome, including the central issues of individual variability and development. Finally, we sketch out the neuroscience. potential impact of the connectome in computational and Recent research in neuroscience has resulted in a rapid cognitive neuroscience. proliferation of neuroscience datasets and in the arrival of a new discipline, neuroinformatics [1–4]. Despite considerable advances in experimental techniques and computational paradigms, we still have an incomplete understanding of how human cognitive function emerges from neuronal structure and dynamics. Here, we focus on the relative lack of Citation: Sporns O, Tononi G, Ko¨tter R (2005) The human connectome: A structural information about the different types of neural elements and description of the human brain. PLoS Comput Biol 1(4): e42. their neural connections in the human brain. While a larger Copyright: Ó 2005 Sporns et al. This is an open-access article distributed under the number of anatomical studies of the human brain have been terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author carried out at the macroscopic (cerebral lobes, surface and source are credited. landmarks, and white matter tracts) or microscopic Abbreviation: DTI, diffusion tensor imaging (cytoarchitectonics, myeloarchitectonics, chemoarchitectonics, etc.) anatomical level, there is virtually Olaf Sporns is in the Department of Psychology and Programs in Neuroscience and Cognitive Science, Indiana University, Bloomington, Indiana, United States of no information on the finer connectivity patterns, including America. Giulio Tononi is in the Department of Psychiatry, University of Wisconsin, neuronal connection densities or laminar projection patterns Madison, Wisconsin, United States of America. Rolf Ko¨tter is at C. and O. Vogt Brain in relation to anatomically segregated cortical areas or Research Institute and Institute of Anatomy II, Heinrich Heine University, Du¨sseldorf, Germany. intraregional differentiation. Furthermore, none of the available information is deposited in a single standardized *To whom correspondence should be addressed. E-mail: [email protected] data format, nor can it be accessed through a public database. DOI: 10.1371/journal.pcbi.0010042 PLoS Computational Biology | www.ploscompbiol.org0245 September 2005 | Volume 1 | Issue 4 | e42 Scales and Levels of Structural Description (approximately 1010 neurons and 1013 connections in the cortex alone) [18,19]. Recording or tracing 1015 connections The human genome is composed of approximately 3 3 109 is not only technically impossible, it may also be unnecessary. base pairs, containing around 20,000–30,000 genes [15]. The While a genomic mutation in a single base pair can have compilation of the genome was aided by the fact that base dramatic consequences, alterations of single synapses or cells pairs and genes are relatively straightforward choices as basic have not been shown to have similar macroscopic effects. structural elements. The connectome will consist of two main Instead, there is overwhelming evidence that human cognitive descriptors defining its network architecture: neural elements functions depend on the activity and coactivity of large and neural connections. Data fields for these elements specify populations of neurons in distributed networks, including the superordinate or subordinate structures, a normalized corticothalamic system [20]. Furthermore, individual neurons position within a standard coordinate system, and additional and connections are subject to rapid plastic changes. These parameters such as physiological/biophysical metadata that changes include synaptic weights as well as structural are crucial for specifying neural dynamics. The set of all N remodeling of dendritic spines and presynaptic boutons [21], elements constitutes the columns (targets) and rows (sources) possibly switching synaptic connections between large of an N2–N connection matrix A, whose a entries represent ij numbers of potential synaptic sites [22,23]. We suggest that connections between individual elements i and j. In keeping the vast number, high variability, and fast dynamics of with conventions adopted by other authors [16,17], confirmed individual neurons and synapses render them inappropriate ¼ absence of a connection is denoted by aij 0, while confirmed as basic elements for an initial draft of the connectome. presence of a connection (irrespective of its strength or physiological characteristics) results in aij ¼ 1. Once a Macroscale: Brain Regions and Pathways connection is confirmed to be present, its nonzero matrix An advantage of single neurons is that the elements element receives additional data entries cataloguing a range themselves are relatively easily demarcated and well defined. of structural and physiological parameters, such as fiber In contrast, brain areas and neuronal populations are more direction, connection density, strength, sign (excitatory/ difficult to delineate. No single universally accepted inhibitory), conduction delay, potential modulatory effects parcellation scheme currently exists for human brain regions (voltage dependence), etc. The union of the binary (e.g., areas of the cerebral cortex), posing a significant connection matrix and connection-specific physiological data obstacle to creating a unified resource such as the then results in a structural description that combines connectome. In the human cerebral cortex, neurons are connection topology and biophysics. arranged in an unknown number of anatomically distinct Compiling the connectome faces two significant challenges regions and areas, perhaps on the order of 100 [24] or more. not shared by other natural or technological networks. First, Different subdivisions of the human brain (e.g., brain stem, the human brain is a highly complex organ with a great thalamus, cerebellum, or cortex) may require different number of structurally distinct, heterogeneous, yet criteria for parcellation. interconnected components. Because a primary application Nonetheless, anatomically distinct brain regions and inter- of the connectome will likely be a structural substrate for regional
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