Connectome - Knowledge (XXG)

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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

844:. 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 27: 979:, serves as an appealing model for exploring the structure and operation of nervous systems. Its central nervous system (CNS) is notably compact, housing approximately 200,000 neurons in adults, yet it exhibits reasonably stereotyped neural connections across individual flies. Despite its small size, this CNS supports a broad spectrum of complex and well-studied behaviors. Obtaining an anatomical dataset of the fly's CNS could be a pivotal step, potentially offering insights into the nervous systems of other organisms. 348:-based regions). While much can be learned from these approaches, it is highly desirable to parcellate the brain into functionally distinct parcels: brain regions with distinct architectonics, connectivity, function, and/or topography (Felleman and Van Essen, 1991). Accurate parcellation allows each node in the macroscale connectome to be more informative by associating it with a distinct connectivity pattern and functional profile. Parcellation of localized areas of cortex have been accomplished using diffusion 4555: 3755: 3197: 3139: 2899: 1869: 1256: 352:(Beckmann et al. 2009) and functional connectivity (Nelson et al. 2010) to non-invasively measure connectivity patterns and define cortical areas based on distinct connectivity patterns. Such analyses may best be done on a whole brain scale and by integrating non-invasive modalities. Accurate whole brain parcellation may lead to more accurate macroscale connectomes for the normal brain, which can then be compared to disease states. 5587: 613:, 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 44: 309: 320:

postulated as indicators for the presence of structural connections. A drawback of the approach is that it provides highly indirect information about cortical connection patterns and requires data from large numbers of individuals to derive a single connection data set across a subject group. Other investigators have attempted to build whole-brain connection matrices from DW-MRI imaging data.

5575: 986:, including 3016 neurons and 548,000 synapses, was published in March 2023. For adults, partial EM connectomes of the brain (~120,000 neurons, ~30,000,000 synapses) or the ventral nerve cord (VNC, the fly's equivalent of the spinal cord, ~14,600 neurons) are also available. A complete adult CNS connectome that includes both the brain and the VNC is currently under construction. 289:(fMRI). The first, when combined with tractography allows reconstruction of the major fiber bundles in the brain. The second allows the researcher to capture the brain's network activity (either at rest or while performing directed tasks), enabling the identification of structurally and anatomically distinct areas of the brain that are functionally connected. 219:, the set of all neuronal connections in the brain is much more than the sum of their individual components. The genome is an entity it-self, as it is from the subtle gene interaction that emerges. In a similar manner, one could consider the brain connectome, set of all neuronal connections, as one single entity, thus emphasizing the fact that the huge brain 258:

from single neurons to populations of neurons to larger systems like cortical areas. Given the methodological uncertainties involved in inferring connectivity from the primary experimental data, and given that there are likely to be large differences in the connectomes of different individuals, any unified map will likely rely on

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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

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is currently 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,

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in brain imaging (Kötter, 2007, Sporns, 2010). These scales can be roughly categorized as macroscale, mesoscale and microscale. Ultimately, it may be possible to join connectomic maps obtained at different scales into a single hierarchical map of the neural organization of a given species that ranges

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Meirovitch, Yaron; Kang, Kai; Draft, Ryan W.; Pavarino, Elisa C.; Henao E., Maria F.; Yang, Fuming; Turney, Stephen G.; Berger, Daniel R.; Peleg, Adi; Schalek, Richard L.; Lu, Ju L.; Tapia, Juan-Carlos; Lichtman, Jeff W. (September 2021). "Neuromuscular connectomes across development reveal synaptic

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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

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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

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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

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To understand the functioning of a network, one must know its elements and their interconnections. The purpose of this article is to discuss research strategies aimed at a comprehensive structural description of the network of elements and connections forming the human brain. We propose to call this

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The significance of the connectome stems from the realization that the structure and function of the human brain are intricately linked, through multiple levels and modes of brain connectivity. There are strong natural constraints on which neurons or neural populations can interact, or how strong or

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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

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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

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in a human genome is 3×10. A few of the main challenges of building a human connectome at the microscale today include: data collection would take years given current technology, machine vision tools to annotate the data remain in their infancy, and are inadequate, and neither theory nor algorithms

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Vogelstein JV, Perlman E, Falk B, Baden A, Gray-Roncal W, Chandrashekhar V, Collman C, Seshamani S, Patsolic JL, Lillaney K, Kazhdan M, Hider R, Pryor D, Matelsky J, Gion T, Manavalan P, Wester B, Chevillet M, Trautman ET, Khairy K, Bridgeford E, Kleissas DM, Tward DJ, Crow AK, Hsueh B, Wright MA,

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Winding, Michael; Pedigo, Benjamin; Barnes, Christopher; Patsolic, Heather; Park, Youngser; Kazimiers, Tom; Fushiki, Akira; Andrade, Ingrid; Khandelwal, Avinash; Valdes-Aleman, Javier; Li, Feng; Randel, Nadine; Barsotti, Elizabeth; Correia, Ana; Fetter, Fetter; Hartenstein, Volker; Priebe, Carey;

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published a pair of articles on micro-connectomes: Bock et al. and Briggman et al. In both articles, the authors first characterized the functional properties of a small subset of cells, and then manually traced a subset of the processes emanating from those cells to obtain a partial subgraph. In

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Throughout the 2000s, several investigators have attempted to map the large-scale structural architecture of the human cerebral cortex. One attempt exploited cross-correlations in cortical thickness or volume across individuals (He et al., 2007). Such gray-matter thickness correlations have been

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resolution) attempts to capture large brain systems that can be parcellated into anatomically distinct modules (areas, parcels or nodes), each having a distinct pattern of connectivity. Connectomic databases at the mesoscale and macroscale may be significantly more compact than those at cellular

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Witvliet, Daniel; Mulcahy, Ben; Mitchell, James K.; Meirovitch, Yaron; Berger, Daniel R.; Wu, Yuelong; Liu, Yufang; Koh, Wan Xian; Parvathala, Rajeev; Holmyard, Douglas; Schalek, Richard L.; Shavit, Nir; Chisholm, Andrew D.; Lichtman, Jeff W.; Samuel, Aravinthan D. T.; Zhen, Mei (August 2021).

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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

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A "mesoscale" connectome corresponds to a spatial resolution of hundreds of micrometers. Rather than attempt to map each individual neuron, a connectome at the mesoscale would attempt to capture anatomically and/or functionally distinct neuronal populations, formed by local circuits (e.g.

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and colleagues were able to mark individual neurons with one of over 100 distinct colors. The labeling of individual neurons with a distinguishable hue then allows the tracing and reconstruction of their cellular structure including long processes within a block of tissue.

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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

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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

199:. The connectome will significantly increase our understanding of how functional brain states emerge from their underlying structural substrate, and will provide new mechanistic insights into how brain function is affected if this structural substrate is disrupted. 4568:

Cook, Steven J.; Jarrell, Travis A.; Brittin, Christopher A.; Wang, Yi; Bloniarz, Adam E.; Yakovlev, Maksim A.; Nguyen, Ken C. Q.; Tang, Leo T.-H.; Bayer, Emily A.; Duerr, Janet S.; Bülow, Hannes E.; Hobert, Oliver; Hall, David H.; Emmons, Scott W. (3 July 2019).

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Recent advances in mapping neural connectivity at the cellular level offer significant new hope for overcoming the limitations of classical techniques and for compiling cellular connectome data sets (Livet et al., 2007; Lichtman et al., 2008). Using

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Azevedo FA, Carvalho LR, Grinberg LT, Farfel JM, Ferretti RE, Leite RE, Jacob Filho W, Lent R, Herculano-Houzel S (April 2009). "Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain".

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resolution) means building a complete map of the neural systems, neuron-by-neuron. The challenge of doing this becomes obvious: the number of neurons comprising the brain easily ranges into the billions in more complex organisms. The human

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Established methods of brain research, such as axonal tracing, provided early avenues for building connectome data sets. However, more recent advances in living subjects has been made by the use of non-invasive imaging technologies such as

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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

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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

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and reconstruction of serially sectioned tissue blocks via electron microscopy (EM). Each of these classical approaches has specific drawbacks when it comes to deployment for connectomics. The staining of single cells, e.g. with the

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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

676:. 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 4026:

Hihara S, Notoya T, Tanaka M, Ichinose S, Ojima H, Obayashi S, Fujii N, Iriki A (2006). "Extension of corticocortical afferents into the anterior bank of the intraparietal sulcus by tool-use training in adult monkeys".

419:) that link hundreds or thousands of individual neurons. This scale still presents a very ambitious technical challenge at this time and can only be probed on a small scale with invasive techniques or very high field 947:

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

570:. Independently, important topologies of functional interactions among several hundred cells are also gradually going to be declared (Shimono and Beggs, 2014). Scaling up ultrastructural circuit mapping to the whole 524:

for detecting long-range pathways across the brain, generally only allows the tracing of fairly large cell populations and single axonal pathways. EM reconstruction was successfully used for the compilation of the

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Wedeen VJ, Wang RP, Schmahmann JD, Benner T, Tseng WY, Dai G, Pandya DN, Hagmann P, D'Arceuil H, de Crespigny AJ (July 2008). "Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers".

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The initial explorations in macroscale human connectomics were done using either equally sized regions or anatomical regions with unclear relationship to the underlying functional organization of the brain (e.g.

239:, which discusses the high-level goals of mapping the human connectome, as well as ongoing efforts to build a three-dimensional neural map of brain tissue at the microscale. In 2012, Seung published the book 692:. 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 516:, to trace cellular processes and connectivity suffers from the limited resolution of light-microscopy as well as difficulties in capturing long-range projections. Tract tracing, often described as the " 168:

independently and simultaneously suggested the term "connectome" to refer to a map of the neural connections within the brain. This term was directly inspired by the ongoing effort to sequence the human

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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.

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Le Bihan D, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M (November 1986). "MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders".

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About 43% of all connections and 16% of all synapses were not conserved between animals. This degree of variability contrasts with the widely held view that the C. elegans connectome is hardwired.

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Livet J, Weissman TA, Kang H, Draft RW, Lu J, Bennis RA, Sanes JR, Lichtman JW (November 2007). "Transgenic strategies for combinatorial expression of fluorescent proteins in the nervous system".

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databases for anatomical connectivity allow for continual updating and refinement of such anatomical connection maps. The online macaque cortex connectivity tool CoCoMac (Kötter, 2004) and the

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resolution, but they require effective strategies for accurate anatomical or functional parcellation of the neural volume into network nodes (for complexities see, e.g., Wallace et al., 2004).

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Iturria-Medina Y, Sotero RC, Canales-Rodríguez EJ, Alemán-Gómez Y, Melie-García L (April 2008). "Studying the human brain anatomical network via diffusion-weighted MRI and Graph Theory".

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connectome (White et al., 1986). However, applications to larger tissue blocks of entire nervous systems have traditionally had difficulty with projections that span longer distances.

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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).

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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

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Despite such complex and variable structure-function mappings, the connectome is an indispensable basis for the mechanistic interpretation of dynamic brain data, from

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Le Bihan D, Breton E (1985). "Imagerie de diffusion in vivo par résonance magnétique nucléaire" [Imagery of diffusion in vivo by nuclear magnetic resonance].

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Witvliet, Daniel; Mulcahy, Ben; Mitchell, James K.; Meirovitch, Yaron; Berger, Daniel R.; Wu, Yuelong; Liu, Yufang; Koh, Wan Xian; Parvathala, Rajeev (2020-04-30),

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Yamamoto, William S.; Achacoso, Theodore B. (1992-06-01). "Scaling up the nervous system of Caenorhabditis elegans: Is one ape equal to 33 million worms?".

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Szalkai B, Varga B, Grolmusz V (April 2017). "Brain size bias compensated graph-theoretical parameters are also better in women's structural connectomes".

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currently requires post-mortem (after death) microscopic analysis of limited portions of brain tissue. Non-optical techniques that rely on high-throughput

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Cabral J, Hugues E, Kringelbach ML, Deco G (September 2012). "Modeling the outcome of structural disconnection on resting-state functional connectivity".

566:, the authors of Bock et al. (2011) have released their data for public access. The full resolution 12 terabyte dataset from Bock et al. is available at 480:

Current non-invasive imaging techniques cannot capture the brain's activity on a neuron-by-neuron level. Mapping the connectome at the cellular level in

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learning. However, it is not likely that long-distance neural connections undergo extensive rewiring in adults. Small changes in an already established

596:. Though only a small volume of biological tissue, this project will yield one of the largest micro-scale connectomics datasets currently in existence. 575:

the approach consists of labelling each neuron with a unique DNA barcode, transferring barcodes between synaptically coupled neurons (for example using

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Horn A, Ostwald D, Reisert M, Blankenburg F (November 2014). "The structural-functional connectome and the default mode network of the human brain".

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The first full connectome of a mammalian circuit was constructed in 2021. This construction included the development of all connections between the

645:, 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). 4231:

Knott GW, Holtmaat A, Wilbrecht L, Welker E, Svoboda K (September 2006). "Spine growth precedes synapse formation in the adult neocortex in vivo".

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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

581:, SuHV1), and fusion of barcodes to represent a synaptic pair. This approach has the potential to be cheap, fast, and extremely high-throughput. 4401: 5547: 3212:"How to Direct the Edges of the Connectomes: Dynamics of the Consensus Connectomes and the Development of the Connections in the Human Brain" 1336: 1311: 286: 1885:

White JG, Southgate E, Thomson JN, Brenner S (November 1986). "The structure of the nervous system of the nematode Caenorhabditis elegans".

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Nelson SM, Cohen AL, Power JD, Wig GS, Miezin FM, Wheeler ME, Velanova K, Donaldson DI, Phillips JS, Schlaggar BL, Petersen SE (July 2010).

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connectome was later revised and expanded to show changes during the animal's development. Despite having an invariant cell lineage, the

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and strength of the connection. Such graphs have even been used to analyze the damage done to the famous traumatic brain injury patient

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brain gray matter areas. All networks were found to have small-world attributes and "broad-scale" degree distributions. An analysis of

5232: 641:), while the edges of the graph are derived from the axons interconnecting those areas. Thus connectomes are sometimes referred to as 26: 3382:

Ingalhalikar M, Smith A, Parker D, Satterthwaite TD, Elliott MA, Ruparel K, Hakonarson H, Gur RE, Gur RC, Verma R (January 2014).

129:. A connectome is constructed by tracing the neuron in a nervous system and mapping where neurons are connected through synapses. 3651:

Irimia A, Chambers MC, Torgerson CM, Filippou M, Hovda DA, Alger JR, Gerig G, Toga AW, Vespa PM, Kikinis R, Van Horn JD (2012).

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Zalesky, Andrew; Fornito, Alex; Bullmore, Edward (2010). "Network-based statistic: identifying differences in brain networks".

792:, or a sparsity model, with the aim of finding statistically significant connections which are different among those groups. 705: 2140:

Briggman KL, Helmstaedter M, Denk W (March 2011). "Wiring specificity in the direction-selectivity circuit of the retina".

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Kötter R (2004). "Online retrieval, processing, and visualization of primate connectivity data from the CoCoMac database".

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can be shown forming within days following sensory experience and learning. Changes can even be seen within five hours on

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Greenough WT, Bailey CH (January 1988). "The anatomy of a memory: convergence of results across a diversity of tests".

2796:"Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography" 1129: 788:

have also been introduced (e.g. to compare case versus control groups). Those can be found by using either an adjusted

5469: 2311: 374:. Axonal tracing methods form the primary basis for the systematic charting of long-distance pathways into extensive, 3051:

Sporns O (July 2006). "Small-world connectivity, motif composition, and complexity of fractal neuronal connections".

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Mikula S, Binding J, Denk W (December 2012). "Staining and embedding the whole mouse brain for electron microscopy".

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of the healthy human brain at the macro scale, using a combination of multiple imaging technologies and resolutions.

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capacity and computational power critically relies on this subtle and incredibly complex connectivity architecture.

3653:"Patient-tailored connectomics visualization for the assessment of white matter atrophy in traumatic brain injury" 2080:

Bock DD, Lee WC, Kerlin AM, Andermann ML, Hood G, Wetzel AW, Yurgenson S, Soucy ER, Kim HS, Reid RC (March 2011).

5559: 4177: 102: 4942: 5515: 5360: 5292: 5110:"Reconstruction of motor control circuits in adult Drosophila using automated transmission electron microscopy" 4361: 3604:"Circular representation of human cortical networks for subject and population-level connectomic visualization" 1059: 1039: 913: 717: 713: 709: 669: 649: 313: 293: 186:

In their 2005 paper, "The Human Connectome, a structural description of the human brain", Sporns et al. wrote:

183:(Hagmann, 2005) has been defined as the science concerned with assembling and analyzing connectome data sets. 51:

architecture of the human brain are visualized color-coded by traversing direction (xyz-directions mapping to

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in the visual cortex. Additionally, the number of local connections between pyramidal neurons in the primary

5500: 5372: 220: 145: 4554: 3754: 3196: 3138: 2898: 1868: 1255: 592:, a five-year, multi-institute project to map one cubic millimeter of rodent visual cortex, as part of the 5541: 5457: 5260: 5225: 2339:"Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization" 1069: 1006: 942: 677: 657: 526: 192: 1498:"Connectivity-based parcellation of human cingulate cortex and its relation to functional specialization" 5520: 5474: 3152:

Hagmann P, Cammoun L, Gigandet X, Meuli R, Honey CJ, Wedeen VJ, Sporns O (July 2008). Friston KJ (ed.).

1034: 999: 970: 813: 345: 141: 4335: 4072:"Axonal sprouting and formation of terminals in the adult cerebellum during associative motor learning" 2846:

Hagmann P, Kurant M, Gigandet X, Thiran P, Wedeen VJ, Meuli R, Thiran JP (July 2007). Sporns O (ed.).

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MITK Diffusion: Free software for the processing of diffusion-weighted MR data including connectomics

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Database of hundreds of braingraphs with different resolutions and weight functions at braingraph.org

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character, with overall cortical connectivity decreasing with age. The aim of the as of 2015 ongoing

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of layer five pyramidal neurons in the primary motor cortex after a seed reaching task in primates.

652:(DTI) followed by the derivation of average connection probabilities between 70 and 90 cortical and 5490: 5464: 5322: 5309: 5270: 876: 804:

is to identify connectome differences between 6 age groups (4–6, 8–9, 14–15, 25–35, 45–55, 65–75).

797: 721: 544: 504: 474: 465:. 2011). To address the machine-vision and image-processing issues, the Open Connectome Project is 458: 648:

One group of researchers (Iturria-Medina et al., 2008) has constructed connectome data sets using

5444: 5255: 4899: 4719: 4640: 4256: 4213: 4052: 4008: 3842: 3535: 3454: 3364: 3223: 3033: 2672: 2580: 2478: 2265: 2173: 1961: 1751: 1707: 1660: 1110: 701: 638: 605: 540: 324: 254: 161: 920:(NIH), was created with the goal of mapping the 86 billion neurons (and their connections) in a 2388:"Consciousness, plasticity, and connectomics: the role of intersubjectivity in human cognition" 961:

connectome shows variability between individuals, both at the level of synapse and connection.

5623: 5495: 5304: 5218: 5139: 5090: 5045: 4994: 4891: 4831: 4777: 4769: 4695: 4676: 4608: 4543: 4474: 4447: 4439: 4316: 4248: 4205: 4158: 4101: 4044: 3973: 3955: 3894: 3807: 3743: 3684: 3633: 3584: 3527: 3492: 3423: 3356: 3321: 3261: 3185: 3127: 3068: 3025: 2989: 2935: 2887: 2825: 2776: 2729: 2664: 2629: 2572: 2537: 2470: 2419: 2368: 2257: 2222: 2165: 2119: 2059: 2010: 1953: 1910: 1857: 1803: 1743: 1699: 1652: 1617: 1576: 1527: 1478: 1434: 1393: 1332: 1307: 1244: 1102: 892: 781: 20: 4465:

Achacoso, Theodore B.; Fernandez, Victor; Nguyen, Duc C.; Yamamoto, William S. (1989-11-08).

2498:"Network structure of cerebral cortex shapes functional connectivity on multiple time scales" 5419: 5414: 5192: 5162: 5129: 5121: 5080: 5072: 5035: 5025: 4984: 4976: 4881: 4873: 4821: 4811: 4759: 4709: 4701: 4666: 4658: 4598: 4590: 4533: 4523: 4482: 4431: 4369: 4306: 4298: 4240: 4197: 4148: 4140: 4091: 4083: 4036: 4000: 3963: 3947: 3884: 3876: 3834: 3797: 3789: 3733: 3723: 3674: 3664: 3623: 3615: 3574: 3566: 3519: 3482: 3472: 3413: 3403: 3348: 3311: 3303: 3251: 3241: 3175: 3165: 3117: 3107: 3060: 3017: 2981: 2925: 2877: 2867: 2815: 2807: 2768: 2719: 2711: 2656: 2619: 2611: 2564: 2527: 2517: 2460: 2450: 2409: 2399: 2358: 2350: 2249: 2212: 2204: 2157: 2109: 2101: 2049: 2041: 2000: 1992: 1945: 1902: 1847: 1837: 1793: 1785: 1735: 1691: 1644: 1607: 1566: 1558: 1517: 1509: 1468: 1424: 1413:"Small-world anatomical networks in the human brain revealed by cortical thickness from MRI" 1383: 1373: 1299: 1234: 1224: 1174: 1137: 1094: 593: 557: 548: 496: 457:. To address the data collection issues, several groups are building high-throughput serial 395: 66: 47:

Rendering of a group connectome based on 20 subjects. Anatomical fibers that constitute the

4040: 1680:"The anatomy of memory: an interactive overview of the parahippocampal-hippocampal network" 5434: 5424: 5409: 5345: 5196: 5157:

Takemura, Shin-ya (2023-06-06). "A Connectome of the Male Drosophila Ventral Nerve Cord".

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Varshney LR, Chen BL, Paniagua E, Hall DH, Chklovskii DB (February 2011). Sporns O (ed.).

4180:(June 2006). "Experience-dependent and cell-type-specific spine growth in the neocortex". 4119:

Ko H, Cossell L, Baragli C, Antolik J, Clopath C, Hofer SB, Mrsic-Flogel TD (April 2013).

896: 841: 626: 437: 416: 228: 196: 52: 776:. By allowing gradually less frequent edges, this core subgraph grows continuously, as a 637:

between those neurons. For the macro-scale connectome, the nodes correspond to the ROIs (

5085: 5064: 4654: 4586: 4519: 4294: 4193: 4136: 3933: 3785: 3719: 3468: 3399: 3299: 3237: 3103: 2914:"Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging" 2863: 2764: 2707: 2513: 2153: 2097: 1941: 1898: 1887:

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences

1369: 1220: 5591: 5429: 5332: 5275: 5134: 5109: 5040: 5013: 4989: 4968: 4886: 4851: 4826: 4799: 4671: 4628: 4603: 4570: 4538: 4503: 4487: 4466: 4311: 4278: 4153: 4120: 4096: 4071: 3968: 3917: 3889: 3864: 3802: 3769: 3738: 3703: 3679: 3652: 3628: 3603: 3579: 3554: 3487: 3442: 3418: 3383: 3316: 3283: 3256: 3211: 3180: 3153: 3122: 3087: 2882: 2847: 2820: 2795: 2724: 2691: 2624: 2599: 2532: 2497: 2414: 2387: 2363: 2338: 2217: 2192: 2114: 2081: 2054: 2029: 2005: 1980: 1852: 1825: 1798: 1773: 1571: 1546: 1522: 1497: 1239: 1204: 827: 754: 734: 673: 665: 485: 371: 253:

Brain networks can be defined at different levels of scale, corresponding to levels of

236: 118: 110: 4277:

Xu T, Yu X, Perlik AJ, Tobin WF, Zweig JA, Tennant K, Jones T, Zuo Y (December 2009).

3770:"Topological impact of negative links on the stability of resting-state brain network" 2715: 2337:

Van Dijk KR, Hedden T, Venkataraman A, Evans KC, Lazar SW, Buckner RL (January 2010).

1388: 1353: 5607: 5404: 5350: 5314: 4969:"A complete electron microscopy volume of the brain of adult Drosophila melanogaster" 4903: 4723: 4435: 4279:"Rapid formation and selective stabilization of synapses for enduring motor memories" 4012: 3838: 3619: 3352: 3064: 3021: 2660: 2568: 2269: 1789: 1098: 1054: 653: 629:

and graph theory. In case of a micro-scale connectome, the nodes of this network (or

610: 500: 489: 399: 383: 328: 282: 260: 206: 4260: 4056: 3880: 3846: 3443:"Graph Theoretical Analysis Reveals: Women's Brains Are Better Connected than Men's" 3368: 2985: 2584: 2455: 2438: 1711: 1664: 784:

and provide an opportunity to direct some edges of the human consensus brain graph.

43: 5394: 5355: 5287: 4217: 4087: 3570: 3539: 3037: 2676: 2482: 2177: 1965: 1755: 1513: 1114: 1029: 817: 808: 614: 576: 563: 521: 470: 356: 349: 308: 215:

It is clear that, like the genome, which is much more than just a juxtaposition of

191:

dataset the human "connectome," and we argue that it is fundamentally important in

170: 48: 37: 4786:

C. elegans neurons show inter-individual variability in adjacency and connectivity

4697:

Connectomes across development reveal principles of brain maturation in C. elegans

1772:

Van Essen DC, Smith SM, Barch DM, Behrens TE, Yacoub E, Ugurbil K (October 2013).

4528: 3728: 3477: 3246: 3170: 3112: 2872: 1842: 1562: 1229: 5367: 5299: 4868: 4467:"Computer Representation of the Synaptic Connectivity of Caenorhabditis Elegans" 1303: 1270: 1044: 1019: 921: 863: 571: 513: 495:

Traditional histological circuit-mapping approaches rely on imaging and include

379: 331:

sharpened to an atomic edge, and electron microscopy for imaging tissue slices.

157: 30: 5125: 4980: 3951: 3793: 3388:

Proceedings of the National Academy of Sciences of the United States of America

3307: 3284:"MultiLink analysis: brain network comparison via sparse connectivity analysis" 2502:

Proceedings of the National Academy of Sciences of the United States of America

1996: 1358:

Proceedings of the National Academy of Sciences of the United States of America

5452: 5399: 5389: 5384: 5200: 5166: 5076: 4764: 4747: 4705: 4662: 4629:"A community-developed open-source computational ecosystem for big neuro data" 4594: 4374: 4004: 3942: 3523: 2794:

Gong G, He Y, Concha L, Lebel C, Gross DW, Evans AC, Beaulieu C (March 2009).

1142: 685: 481: 432: 363: 273: 4773: 4478: 4443: 3959: 3702:

Van Horn JD, Irimia A, Torgerson CM, Chambers MC, Kikinis R, Toga AW (2012).

3669: 2404: 1648: 1612: 1595: 1473: 1456: 1178: 5511:

Matrix-assisted laser desorption ionization-time of flight mass spectrometer

5379: 4877: 4800:"Information flow, cell types and stereotypy in a full olfactory connectome" 3408: 2811: 2522: 2285:"The U.S. Government Launches a $ 100-Million "Apollo Project of the Brain"" 2208: 2193:"Functional Clusters, Hubs, and Communities in the Cortical Microconnectome" 1429: 1412: 1378: 773: 661: 449: 360: 134: 5143: 5094: 5049: 4998: 4895: 4835: 4781: 4680: 4612: 4547: 4471:

Proceedings of the Annual Symposium on Computer Application in Medical Care

4320: 4252: 4209: 4162: 4105: 4048: 3977: 3898: 3811: 3747: 3688: 3637: 3588: 3553:

Gong G, Rosa-Neto P, Carbonell F, Chen ZJ, He Y, Evans AC (December 2009).

3531: 3496: 3427: 3360: 3325: 3265: 3189: 3131: 3072: 3029: 2939: 2891: 2829: 2772: 2668: 2633: 2576: 2541: 2474: 2423: 2372: 2261: 2226: 2169: 2123: 2063: 2014: 1957: 1914: 1906: 1861: 1807: 1747: 1703: 1656: 1621: 1580: 1531: 1438: 1397: 1248: 1106: 477:

and inference tools to parse these brain-graphs (Goldenberg et al., 2009).

4627:

Miller MI, Smith SJ, Vogelstein JR, Deisseroth K, Burns R (October 2018).

4451: 3282:

Crimi, Alessandro; Giancardo, Luca; Sambataro, Fabio; Diego, Sona (2019).

2993: 2780: 2749:"Estimation of the effective self-diffusion tensor from the NMR spin echo" 2733: 2354: 1482: 1168: 937:

The first (and so far only) fully reconstructed connectome belongs to the

5241: 4714: 1596:"The connectional organization of the cortico-thalamic system of the cat" 1274: 938: 536: 508: 382:

regions. Landmark studies have included the areas and connections of the

367: 114: 5187: 5030: 4816: 4302: 4201: 4144: 3555:"Age- and gender-related differences in the cortical anatomical network" 2912:

Wedeen VJ, Hagmann P, Tseng WY, Reese TG, Weisskoff RM (December 2005).

2161: 2105: 1949: 55:

respectively). Visualization of fibers was done using TrackVis software.

5340: 5205: 3768:

Saberi M, Khosrowabadi R, Khatibi A, Misic B, Jafari G (January 2021).

2465: 2253: 801: 634: 589: 445: 387: 375: 126: 4504:"Structural properties of the Caenorhabditis elegans neuronal network" 3918:"Connectomes across development reveal principles of brain maturation" 2930: 2913: 2615: 2439:"Exploring the network dynamics underlying brain activity during rest" 1739: 137:

lies in the pattern of dynamic interactions shaped by the connectome.

4746:

Cook, Steven J.; Kalinski, Cristine A.; Hobert, Oliver (2023-06-05).

995: 789: 697: 441: 174: 122: 2748: 2045: 1695: 1679: 1457:"Distributed hierarchical processing in the primate cerebral cortex" 4645: 4244: 3459: 3228: 2082:"Network anatomy and in vivo physiology of visual cortical neurons" 1205:"The human connectome: A structural description of the human brain" 883:

increases following altered whisker sensory experience in rodents.

4850:

Vogelstein, Joshua; Cardona, Albert; Zlatic, Marta (10 Mar 2023).

2848:"Mapping human whole-brain structural networks with diffusion MRI" 1981:"Ome sweet ome: what can the genome tell us about the connectome?" 982:

A full electron microscopy (EM) connectome of the larval brain of

777: 341: 106: 42: 25: 5014:"A connectome and analysis of the adult Drosophila central brain" 3384:"Sex differences in the structural connectome of the human brain" 327:

is attempting to reconstruct the entire mouse connectome using a

4748:"Neuronal contact predicts connectivity in the C. elegans brain" 4070:

Boele HJ, Koekkoek SK, De Zeeuw CI, Ruigrok TJ (November 2013).

1594:

Scannell JW, Burns GA, Hilgetag CC, O'Neil MA, Young MP (1999).

394:

in the feline brain (Scannell et al., 1999). The development of

216: 5214: 4571:"Whole-animal connectomes of both Caenorhabditis elegans sexes" 3602:

Irimia A, Chambers MC, Torgerson CM, Van Horn JD (April 2012).

1824:

Zador AM, Dubnau J, Oyibo HK, Zhan H, Cao G, Peikon ID (2012).

133:

direct their interactions are. Indeed, the foundation of human

1547:"A parcellation scheme for human left lateral parietal cortex" 1294:

Kötter R (2007). "Anatomical Concepts of Brain Connectivity".

403: 34: 5182: 3088:"Identification and classification of hubs in brain networks" 3086:

Sporns O, Honey CJ, Kötter R (October 2007). Kaiser M (ed.).

4121:"The emergence of functional microcircuits in visual cortex" 473:

is an emerging discipline which is developing sophisticated

264:

representations of connectivity data (Sporns et al., 2005).

5210: 90: 81: 72: 1496:

Beckmann M, Johansen-Berg H, Rushworth MF (January 2009).

796:

hemispheres. In addition, connectomes generally exhibit a

469:(algorithm outsourcing) this hurdle. Finally, statistical 3704:"Mapping connectivity damage in the case of Phineas Gage" 2600:"Dynamical consequences of lesions in cortical networks" 2496:

Honey CJ, Kötter R, Breakspear M, Sporns O (June 2007).

453:

are readily available for the analysis of the resulting

1880: 1878: 660:

in these networks demonstrated high centrality for the

625:

The connectome can be studied as a network by means of

312:

Tractographic reconstruction of neural connections via

227:

The term "connectome" was more recently popularized by

3154:"Mapping the structural core of human cerebral cortex" 1352:

Wallace MT, Ramachandran R, Stein BE (February 2004).

242:

Connectome: How the Brain's Wiring Makes Us Who We Are

1767: 1765: 757: 737: 539:, a combinatorial color labeling method based on the 84: 78: 69: 1678:

van Strien NM, Cappaert NL, Witter MP (April 2009).

866:

are likely what is observed in macroscale rewiring.

731:

by allowing only edges that are present in at least

87: 16:

Comprehensive map of neural connections in the brain

5534: 5483: 5443: 5331: 5248: 3210:Kerepesi C, Szalkai B, Varga B, Grolmusz V (2016). 1774:"The WU-Minn Human Connectome Project: an overview" 633:) are the neurons, and the edges correspond to the 93: 75: 4919:"Scientists complete first map of an insect brain" 2690:Basser PJ, Mattiello J, LeBihan D (January 1994). 1298:. Understanding Complex Systems. pp. 149–67. 763: 743: 3989: 3987: 1354:"A revised view of sensory cortical parcellation" 780:. The growth dynamics may reflect the individual 378:-specific anatomical connection matrices between 2747:Basser PJ, Mattiello J, LeBihan D (March 1994). 586:Intelligence Advanced Research Projects Activity 3910: 3908: 3865:"Rewiring the connectome: Evidence and effects" 2437:Cabral J, Kringelbach ML, Deco G (March 2014). 1450: 1448: 1203:Sporns O, Tononi G, Kötter R (September 2005). 296:, led by the WU-Minn consortium, is to build a 3863:Bennett SH, Kirby AJ, Finnerty GT (May 2018). 2692:"MR diffusion tensor spectroscopy and imaging" 1162: 1160: 5226: 4176:Holtmaat A, Wilbrecht L, Knott GW, Welker E, 2841: 2839: 1009:and a single muscle from birth to adulthood. 283:diffusion-weighted magnetic resonance imaging 8: 4336:"Will We Ever Be Able to Upload Our Brains?" 3277: 3275: 2312:"Mapping the Brain to Build Better Machines" 2028:Lichtman JW, Livet J, Sanes JR (June 2008). 1819: 1817: 1198: 1196: 1194: 431:Mapping the connectome at the "microscale" ( 5506:Matrix-assisted laser desorption ionization 5188:The NIH Blueprint for Neuroscience Research 5065:"Neuronal wiring diagram of an adult brain" 4943:"First wiring map of insect brain complete" 2030:"A technicolour approach to the connectome" 406:are prominent examples of such a database. 5574: 5233: 5219: 5211: 4362:"Mapping the brain to understand the mind" 448:connections. By comparison, the number of 5133: 5084: 5039: 5029: 4988: 4885: 4867: 4825: 4815: 4763: 4713: 4670: 4644: 4602: 4537: 4527: 4486: 4373: 4310: 4152: 4095: 3967: 3941: 3888: 3801: 3737: 3727: 3678: 3668: 3627: 3578: 3486: 3476: 3458: 3417: 3407: 3315: 3255: 3245: 3227: 3179: 3169: 3121: 3111: 2955:Comptes Rendus de l'Académie des Sciences 2929: 2881: 2871: 2819: 2723: 2623: 2531: 2521: 2464: 2454: 2413: 2403: 2362: 2216: 2113: 2053: 2004: 1851: 1841: 1797: 1611: 1570: 1521: 1472: 1428: 1387: 1377: 1238: 1228: 1141: 756: 736: 588:of the United States government launched 1411:He Y, Chen ZJ, Evans AC (October 2007). 1170:From diffusion MRI to brain connectomics 307: 3441:Szalkai B, Varga B, Grolmusz V (2015). 2753:Journal of Magnetic Resonance, Series B 2135: 2133: 2075: 2073: 1081: 826:Recent research studied the brain as a 390:(Felleman and Van Essen, 1991) and the 304:Recent advances in connectivity mapping 33:within a human brain, as visualized by 4360:Brouillette, Monique (21 April 2022). 4041:10.1016/j.neuropsychologia.2005.11.020 3869:Neuroscience and Biobehavioral Reviews 5548:European Molecular Biology Laboratory 4272: 4270: 3858: 3856: 2283:Cepelewicz, Jordana (March 8, 2016). 1271:"Sebastian Seung: I am my connectome" 335:Challenge for macroscale connectomics 287:functional magnetic resonance imaging 7: 2191:Shimono M, Beggs JM (October 2015). 1728:The Journal of Comparative Neurology 1050:List of animals by number of neurons 4852:"The connectome of an insect brain" 1979:Lichtman JW, Sanes JR (June 2008). 503:, injection of labeling agents for 4366:Knowable Magazine | Annual Reviews 1455:Felleman DJ, Van Essen DC (1991). 507:, or chemical brain preservation, 440:alone contains on the order of 10 370:, by degeneration methods, and by 14: 4424:Computers and Biomedical Research 562:alignment with the principles of 5586: 5585: 5573: 4798:Schlegel, Philipp (2021-05-25). 4553: 3753: 3620:10.1016/j.neuroimage.2012.01.107 3353:10.1016/j.neuroimage.2010.06.041 3195: 3137: 3065:10.1016/j.biosystems.2006.02.008 3022:10.1016/j.neuroimage.2008.03.036 2897: 2661:10.1016/j.neuroimage.2007.10.060 2598:Honey CJ, Sporns O (July 2008). 2569:10.1016/j.neuroimage.2012.06.007 1867: 1790:10.1016/j.neuroimage.2013.05.041 1254: 1128:Mackenzie, Dana (6 March 2023). 1099:10.1016/j.neuroimage.2013.09.069 272:A connectome at the macroscale ( 109:, and may be thought of as its " 65: 5526:Chromosome conformation capture 5063:Dorkenwald, Sven (2023-06-29). 3881:10.1016/j.neubiorev.2018.03.001 2986:10.1148/radiology.161.2.3763909 2456:10.1016/j.pneurobio.2013.12.005 2310:Emily, Singer (April 6, 2016). 1985:Current Opinion in Neurobiology 1331:. Cambridge, Mass.: MIT Press. 1130:"How animals follow their nose" 994:Partial connectomes of a mouse 877:experience-dependent plasticity 600:Mapping functional connectivity 488:have been proposed recently by 4334:Jensen, K. Thor (8 May 2020). 4088:10.1523/JNEUROSCI.0511-13.2013 3571:10.1523/JNEUROSCI.2308-09.2009 2918:Magnetic Resonance in Medicine 1514:10.1523/JNEUROSCI.3328-08.2009 1296:Handbook of Brain Connectivity 751:connectomes, for a selectable 1: 5554:National Institutes of Health 5108:Phelps, Jasper (2021-02-04). 2716:10.1016/S0006-3495(94)80775-1 1025:Brain connectivity estimators 918:National Institutes of Health 729:Budapest Reference Connectome 461:(Kasthuri et al., 2009; Bock 298:structural and functional map 4967:Zheng, Zhihao (2018-07-19). 4529:10.1371/journal.pcbi.1001066 4436:10.1016/0010-4809(92)90043-A 3839:10.1016/0166-2236(88)90139-7 3729:10.1371/journal.pone.0037454 3478:10.1371/journal.pone.0130045 3247:10.1371/journal.pone.0158680 3171:10.1371/journal.pbio.0060159 3113:10.1371/journal.pone.0001049 2873:10.1371/journal.pone.0000597 2386:Allen M, Williams G (2011). 2034:Nature Reviews. Neuroscience 1843:10.1371/journal.pbio.1001411 1684:Nature Reviews. Neuroscience 1563:10.1016/j.neuron.2010.05.025 1230:10.1371/journal.pcbi.0010042 835:Plasticity of the connectome 166:Lausanne University Hospital 152:Origin and usage of the term 101:) is a comprehensive map of 5470:Structure-based drug design 4869:10.1101/2022.11.28.516756v1 4076:The Journal of Neuroscience 3559:The Journal of Neuroscience 1826:"Sequencing the connectome" 1502:The Journal of Neuroscience 1304:10.1007/978-3-540-71512-2_5 1269:Seung S (September 2010) . 555:In March 2011, the journal 5640: 5619:Computational neuroscience 5126:10.1016/j.cell.2020.12.013 4981:10.1016/j.cell.2018.06.019 4917:Rosen, Jill (2023-03-09). 4508:PLOS Computational Biology 3952:10.1038/s41586-021-03778-8 3794:10.1038/s41598-021-81767-7 3512:Brain Imaging and Behavior 3308:10.1038/s41598-018-37300-4 2343:Journal of Neurophysiology 1997:10.1016/j.conb.2008.08.010 1209:PLOS Computational Biology 1173:(Thesis). Lausanne: EPFL. 1065:Outline of the human brain 968: 802:HCP Lifespan Pilot Project 694:posterior cingulate cortex 421:magnetic resonance imaging 355:Pathways through cerebral 203:In his 2005 Ph.D. thesis, 164:and Dr. Patric Hagmann at 125:which communicate through 18: 5569: 5560:Wellcome Sanger Institute 5167:10.1101/2023.06.05.543757 5077:10.1101/2023.06.27.546656 4975:. 174.3 (2018): 730–743. 4765:10.1016/j.cub.2023.04.071 4706:10.1101/2020.04.30.066209 4663:10.1038/s41592-018-0181-1 4595:10.1038/s41586-019-1352-7 4375:10.1146/knowable-042122-1 4005:10.1101/2021.09.20.460480 3943:10.1101/2020.04.30.066209 3524:10.1007/s11682-017-9720-0 2291:. Springer Nature America 1143:10.1146/knowable-030623-4 292:Notably, the goal of the 235:speech given at the 2010 5516:Microfluidic-based tools 5361:Human Connectome Project 5293:Human Microbiome Project 5012:Scheffer, Louis (2020). 3670:10.3389/fneur.2012.00010 2443:Progress in Neurobiology 2405:10.3389/fpsyg.2011.00020 1179:10.5075/epfl-thesis-3230 1167:Hagmann, Patric (2005). 1060:Outline of brain mapping 1040:Human Connectome Project 914:Human Connectome Project 718:superior parietal cortex 710:superior temporal sulcus 706:isthmus of the cingulate 650:diffusion tensor imaging 423:(MRI) on a local scale. 294:Human Connectome Project 5501:Electrospray ionization 5373:Human Epigenome Project 4947:University of Cambridge 4878:10.1126/science.add9330 3827:Trends in Neurosciences 3409:10.1073/pnas.1316909110 2523:10.1073/pnas.0701519104 2392:Frontiers in Psychology 1379:10.1073/pnas.0305697101 977:Drosophila melanogaster 146:functional neuroimaging 19:For the 2012 book, see 5614:Cognitive neuroscience 5542:DNA Data Bank of Japan 5458:Human proteome project 5261:Computational genomics 4390:"Ay's Neuroanatomy of 3657:Frontiers in Neurology 2773:10.1006/jmrb.1994.1037 1907:10.1098/rstb.1986.0056 1613:10.1093/cercor/9.3.277 1474:10.1093/cercor/1.1.1-a 1070:Lesion network mapping 1007:central nervous system 943:Caenorhabditis elegans 765: 745: 720:, all located in both 678:superior frontal gyrus 658:betweenness centrality 543:expression of several 392:thalamocortical system 316: 225: 221:neuronal communication 201: 193:cognitive neuroscience 142:single-cell recordings 56: 40: 5521:Isotope affinity tags 5475:Expression proteomics 2812:10.1093/cercor/bhn102 2355:10.1152/jn.00783.2009 2209:10.1093/cercor/bhu252 1430:10.1093/cercor/bhl149 1329:Networks of the Brain 1035:Drosophila connectome 1000:primary visual cortex 971:Drosophila connectome 814:fractional anisotropy 766: 746: 696:, the precuneus, the 621:As a network or graph 311: 213: 209:to brain connectomics 188: 46: 29: 5281:Human Genome Project 5266:Comparative genomics 4758:(11): 2315–2320.e2. 1093:. 102 Pt 1: 142–51. 881:somatosensory cortex 755: 735: 722:cerebral hemispheres 545:fluorescent proteins 459:electron microscopes 5491:2-D electrophoresis 5465:Call-map proteomics 5323:Structural genomics 5310:Population genomics 5271:Functional genomics 5031:10.7554/eLife.57443 4817:10.7554/eLife.66018 4655:2018arXiv180402835B 4587:2019Natur.571...63C 4520:2011PLSCB...7E1066V 4303:10.1038/nature08389 4295:2009Natur.462..915X 4233:Nature Neuroscience 4202:10.1038/nature04783 4194:2006Natur.441..979H 4145:10.1038/nature12015 4137:2013Natur.496...96K 3934:2021Natur.596..257W 3786:2021NatSR..11.2176S 3720:2012PLoSO...737454V 3469:2015PLoSO..1030045S 3400:2014PNAS..111..823I 3300:2019NatSR...9...65C 3238:2016PLoSO..1158680K 3104:2007PLoSO...2.1049S 2864:2007PLoSO...2..597H 2765:1994JMRB..103..247B 2708:1994BpJ....66..259B 2696:Biophysical Journal 2604:Human Brain Mapping 2514:2007PNAS..10410240H 2318:. Simons Foundation 2289:Scientific American 2162:10.1038/nature09818 2154:2011Natur.471..183B 2106:10.1038/nature09802 2098:2011Natur.471..177B 1950:10.1038/nature06293 1942:2007Natur.450...56L 1899:1986RSPTB.314....1W 1370:2004PNAS..101.2167W 1221:2005PLSCB...1...42S 916:, sponsored by the 887:Microscale rewiring 853:Macroscale rewiring 708:, the banks of the 639:regions of interest 617:in the connectome. 475:pattern recognition 31:White matter tracts 5445:Structural biology 5256:Cognitive genomics 5201:I am my connectome 4862:(6636): eadd9330. 3774:Scientific Reports 3288:Scientific Reports 2254:10.1038/nmeth.2213 1649:10.1385/NI:2:2:127 1136:. Annual Reviews. 870:Mesoscale rewiring 761: 741: 702:paracentral lobule 604:Using fMRI in the 578:Suid herpesvirus 1 402:connectome of the 359:can be charted by 325:Blue Brain Project 317: 255:spatial resolution 233:I am my Connectome 162:Indiana University 103:neural connections 57: 41: 5601: 5600: 5496:Mass spectrometer 5305:Personal genomics 5120:(2021): 759–774. 4082:(45): 17897–907. 3995:ordering rules". 3928:(7871): 257–261. 2931:10.1002/mrm.20642 2616:10.1002/hbm.20579 1740:10.1002/cne.21974 1338:978-0-262-01469-4 1327:Sporns O (2011). 1313:978-3-540-71462-0 1134:Knowable Magazine 893:pyramidal neurons 782:brain development 764:{\displaystyle k} 744:{\displaystyle k} 672:and the superior 670:superior parietal 497:light-microscopic 211:, Hagmann wrote: 21:Connectome (book) 5631: 5589: 5588: 5577: 5576: 5420:Pharmacogenomics 5415:Pharmacogenetics 5235: 5228: 5221: 5212: 5171: 5170: 5154: 5148: 5147: 5137: 5105: 5099: 5098: 5088: 5060: 5054: 5053: 5043: 5033: 5009: 5003: 5002: 4992: 4964: 4958: 4957: 4955: 4954: 4939: 4933: 4932: 4930: 4929: 4914: 4908: 4907: 4889: 4871: 4846: 4840: 4839: 4829: 4819: 4795: 4789: 4788: 4767: 4743: 4737: 4736: 4731: 4730: 4717: 4691: 4685: 4684: 4674: 4648: 4623: 4617: 4616: 4606: 4565: 4559: 4558: 4557: 4551: 4541: 4531: 4499: 4493: 4492: 4490: 4462: 4456: 4455: 4419: 4413: 4412: 4410: 4409: 4400:. Archived from 4394:for Computation" 4386: 4380: 4379: 4377: 4357: 4351: 4350: 4348: 4346: 4331: 4325: 4324: 4314: 4274: 4265: 4264: 4228: 4222: 4221: 4188:(7096): 979–83. 4173: 4167: 4166: 4156: 4131:(7443): 96–100. 4116: 4110: 4109: 4099: 4067: 4061: 4060: 4029:Neuropsychologia 4023: 4017: 4016: 3991: 3982: 3981: 3971: 3945: 3912: 3903: 3902: 3892: 3860: 3851: 3850: 3822: 3816: 3815: 3805: 3765: 3759: 3758: 3757: 3751: 3741: 3731: 3699: 3693: 3692: 3682: 3672: 3648: 3642: 3641: 3631: 3599: 3593: 3592: 3582: 3565:(50): 15684–93. 3550: 3544: 3543: 3507: 3501: 3500: 3490: 3480: 3462: 3438: 3432: 3431: 3421: 3411: 3379: 3373: 3372: 3347:(4): 1197–1207. 3336: 3330: 3329: 3319: 3279: 3270: 3269: 3259: 3249: 3231: 3207: 3201: 3200: 3199: 3193: 3183: 3173: 3149: 3143: 3142: 3141: 3135: 3125: 3115: 3083: 3077: 3076: 3048: 3042: 3041: 3004: 2998: 2997: 2969: 2963: 2962: 2950: 2944: 2943: 2933: 2909: 2903: 2902: 2901: 2895: 2885: 2875: 2843: 2834: 2833: 2823: 2791: 2785: 2784: 2744: 2738: 2737: 2727: 2687: 2681: 2680: 2644: 2638: 2637: 2627: 2595: 2589: 2588: 2552: 2546: 2545: 2535: 2525: 2493: 2487: 2486: 2468: 2458: 2434: 2428: 2427: 2417: 2407: 2383: 2377: 2376: 2366: 2334: 2328: 2327: 2325: 2323: 2307: 2301: 2300: 2298: 2296: 2280: 2274: 2273: 2248:(12): 1198–201. 2237: 2231: 2230: 2220: 2188: 2182: 2181: 2137: 2128: 2127: 2117: 2092:(7337): 177–82. 2077: 2068: 2067: 2057: 2025: 2019: 2018: 2008: 1976: 1970: 1969: 1925: 1919: 1918: 1882: 1873: 1872: 1871: 1865: 1855: 1845: 1836:(10): e1001411. 1821: 1812: 1811: 1801: 1769: 1760: 1759: 1722: 1716: 1715: 1675: 1669: 1668: 1637:Neuroinformatics 1632: 1626: 1625: 1615: 1591: 1585: 1584: 1574: 1542: 1536: 1535: 1525: 1493: 1487: 1486: 1476: 1452: 1443: 1442: 1432: 1408: 1402: 1401: 1391: 1381: 1349: 1343: 1342: 1324: 1318: 1317: 1291: 1285: 1284: 1282: 1281: 1266: 1260: 1259: 1258: 1252: 1242: 1232: 1200: 1189: 1188: 1186: 1185: 1164: 1155: 1154: 1152: 1150: 1145: 1125: 1119: 1118: 1086: 849:postnatal life. 770: 768: 767: 762: 750: 748: 747: 742: 594:BRAIN Initiative 549:Jeff W. Lichtman 417:cortical columns 396:neuroinformatics 100: 99: 96: 95: 92: 89: 86: 83: 80: 77: 74: 71: 5639: 5638: 5634: 5633: 5632: 5630: 5629: 5628: 5604: 5603: 5602: 5597: 5565: 5530: 5479: 5439: 5435:Transcriptomics 5425:Systems biology 5410:Paleopolyploidy 5346:Cheminformatics 5327: 5244: 5239: 5197:Sebastian Seung 5179: 5174: 5156: 5155: 5151: 5107: 5106: 5102: 5062: 5061: 5057: 5011: 5010: 5006: 4966: 4965: 4961: 4952: 4950: 4941: 4940: 4936: 4927: 4925: 4916: 4915: 4911: 4848: 4847: 4843: 4797: 4796: 4792: 4752:Current Biology 4745: 4744: 4740: 4728: 4726: 4693: 4692: 4688: 4639:(11): 846–847. 4625: 4624: 4620: 4581:(7763): 63–71. 4567: 4566: 4562: 4552: 4514:(2): e1001066. 4501: 4500: 4496: 4464: 4463: 4459: 4421: 4420: 4416: 4407: 4405: 4388: 4387: 4383: 4359: 4358: 4354: 4344: 4342: 4333: 4332: 4328: 4289:(7275): 915–9. 4276: 4275: 4268: 4230: 4229: 4225: 4175: 4174: 4170: 4118: 4117: 4113: 4069: 4068: 4064: 4035:(13): 2636–46. 4025: 4024: 4020: 3993: 3992: 3985: 3914: 3913: 3906: 3862: 3861: 3854: 3824: 3823: 3819: 3767: 3766: 3762: 3752: 3701: 3700: 3696: 3650: 3649: 3645: 3601: 3600: 3596: 3552: 3551: 3547: 3509: 3508: 3504: 3453:(7): e0130045. 3440: 3439: 3435: 3381: 3380: 3376: 3338: 3337: 3333: 3281: 3280: 3273: 3222:(6): e0158680. 3209: 3208: 3204: 3194: 3151: 3150: 3146: 3136: 3085: 3084: 3080: 3050: 3049: 3045: 3006: 3005: 3001: 2971: 2970: 2966: 2952: 2951: 2947: 2911: 2910: 2906: 2896: 2845: 2844: 2837: 2800:Cerebral Cortex 2793: 2792: 2788: 2746: 2745: 2741: 2689: 2688: 2684: 2646: 2645: 2641: 2597: 2596: 2592: 2554: 2553: 2549: 2508:(24): 10240–5. 2495: 2494: 2490: 2436: 2435: 2431: 2385: 2384: 2380: 2336: 2335: 2331: 2321: 2319: 2316:Quanta Magazine 2309: 2308: 2304: 2294: 2292: 2282: 2281: 2277: 2239: 2238: 2234: 2203:(10): 3743–57. 2197:Cerebral Cortex 2190: 2189: 2185: 2148:(7337): 183–8. 2139: 2138: 2131: 2079: 2078: 2071: 2046:10.1038/nrn2391 2027: 2026: 2022: 1978: 1977: 1973: 1936:(7166): 56–62. 1927: 1926: 1922: 1893:(1165): 1–340. 1884: 1883: 1876: 1866: 1823: 1822: 1815: 1771: 1770: 1763: 1724: 1723: 1719: 1696:10.1038/nrn2614 1677: 1676: 1672: 1634: 1633: 1629: 1600:Cerebral Cortex 1593: 1592: 1588: 1544: 1543: 1539: 1495: 1494: 1490: 1461:Cerebral Cortex 1454: 1453: 1446: 1423:(10): 2407–19. 1417:Cerebral Cortex 1410: 1409: 1405: 1351: 1350: 1346: 1339: 1326: 1325: 1321: 1314: 1293: 1292: 1288: 1279: 1277: 1268: 1267: 1263: 1253: 1202: 1201: 1192: 1183: 1181: 1166: 1165: 1158: 1148: 1146: 1127: 1126: 1122: 1088: 1087: 1083: 1079: 1074: 1015: 1002:are available. 992: 984:D. melanogaster 975:The fruit fly, 973: 967: 935: 930: 928:Model organisms 910: 905: 889: 872: 855: 842:neuroplasticity 837: 807:More recently, 753: 752: 733: 732: 627:network science 623: 602: 499:techniques for 438:cerebral cortex 429: 412: 337: 306: 270: 251: 229:Sebastian Seung 197:neuropsychology 154: 68: 64: 24: 17: 12: 11: 5: 5637: 5635: 5627: 5626: 5621: 5616: 5606: 5605: 5599: 5598: 5596: 5595: 5583: 5570: 5567: 5566: 5564: 5563: 5557: 5551: 5545: 5538: 5536: 5532: 5531: 5529: 5528: 5523: 5518: 5513: 5508: 5503: 5498: 5493: 5487: 5485: 5484:Research tools 5481: 5480: 5478: 5477: 5472: 5467: 5462: 5461: 5460: 5449: 5447: 5441: 5440: 5438: 5437: 5432: 5430:Toxicogenomics 5427: 5422: 5417: 5412: 5407: 5402: 5397: 5392: 5387: 5382: 5377: 5376: 5375: 5365: 5364: 5363: 5353: 5348: 5343: 5337: 5335: 5333:Bioinformatics 5329: 5328: 5326: 5325: 5320: 5312: 5307: 5302: 5297: 5296: 5295: 5285: 5284: 5283: 5276:Genome project 5273: 5268: 5263: 5258: 5252: 5250: 5246: 5245: 5240: 5238: 5237: 5230: 5223: 5215: 5209: 5208: 5203: 5190: 5185: 5178: 5177:External links 5175: 5173: 5172: 5149: 5100: 5055: 5004: 4959: 4934: 4909: 4841: 4790: 4738: 4686: 4633:Nature Methods 4618: 4560: 4494: 4457: 4430:(3): 279–291. 4414: 4381: 4352: 4326: 4266: 4245:10.1038/nn1747 4239:(9): 1117–24. 4223: 4168: 4111: 4062: 4018: 3983: 3904: 3852: 3833:(4): 142–147. 3817: 3760: 3694: 3643: 3614:(2): 1340–51. 3594: 3545: 3518:(3): 663–673. 3502: 3433: 3374: 3331: 3271: 3202: 3144: 3078: 3043: 3016:(4): 1267–77. 2999: 2964: 2945: 2924:(6): 1377–86. 2904: 2835: 2786: 2739: 2682: 2655:(3): 1064–76. 2639: 2590: 2563:(3): 1342–53. 2547: 2488: 2429: 2378: 2349:(1): 297–321. 2329: 2302: 2275: 2242:Nature Methods 2232: 2183: 2129: 2069: 2020: 1971: 1920: 1874: 1813: 1761: 1717: 1670: 1627: 1586: 1537: 1508:(4): 1175–90. 1488: 1444: 1403: 1364:(7): 2167–72. 1344: 1337: 1319: 1312: 1286: 1261: 1190: 1156: 1120: 1080: 1078: 1075: 1073: 1072: 1067: 1062: 1057: 1052: 1047: 1042: 1037: 1032: 1027: 1022: 1016: 1014: 1011: 991: 988: 969:Main article: 966: 963: 934: 931: 929: 926: 909: 906: 904: 901: 888: 885: 871: 868: 854: 851: 836: 833: 828:signed network 760: 740: 674:frontal cortex 622: 619: 601: 598: 486:DNA sequencing 428: 425: 411: 408: 372:axonal tracing 336: 333: 305: 302: 269: 266: 250: 247: 237:TED conference 181:"Connectomics" 153: 150: 121:is made up of 119:nervous system 111:wiring diagram 15: 13: 10: 9: 6: 4: 3: 2: 5636: 5625: 5622: 5620: 5617: 5615: 5612: 5611: 5609: 5594: 5593: 5584: 5582: 5581: 5572: 5571: 5568: 5561: 5558: 5555: 5552: 5549: 5546: 5543: 5540: 5539: 5537: 5535:Organizations 5533: 5527: 5524: 5522: 5519: 5517: 5514: 5512: 5509: 5507: 5504: 5502: 5499: 5497: 5494: 5492: 5489: 5488: 5486: 5482: 5476: 5473: 5471: 5468: 5466: 5463: 5459: 5456: 5455: 5454: 5451: 5450: 5448: 5446: 5442: 5436: 5433: 5431: 5428: 5426: 5423: 5421: 5418: 5416: 5413: 5411: 5408: 5406: 5405:Nutrigenomics 5403: 5401: 5398: 5396: 5393: 5391: 5388: 5386: 5383: 5381: 5378: 5374: 5371: 5370: 5369: 5366: 5362: 5359: 5358: 5357: 5354: 5352: 5351:Chemogenomics 5349: 5347: 5344: 5342: 5339: 5338: 5336: 5334: 5330: 5324: 5321: 5319: 5317: 5313: 5311: 5308: 5306: 5303: 5301: 5298: 5294: 5291: 5290: 5289: 5286: 5282: 5279: 5278: 5277: 5274: 5272: 5269: 5267: 5264: 5262: 5259: 5257: 5254: 5253: 5251: 5247: 5243: 5236: 5231: 5229: 5224: 5222: 5217: 5216: 5213: 5207: 5204: 5202: 5198: 5194: 5191: 5189: 5186: 5184: 5181: 5180: 5176: 5168: 5164: 5160: 5153: 5150: 5145: 5141: 5136: 5131: 5127: 5123: 5119: 5115: 5111: 5104: 5101: 5096: 5092: 5087: 5082: 5078: 5074: 5070: 5066: 5059: 5056: 5051: 5047: 5042: 5037: 5032: 5027: 5023: 5019: 5015: 5008: 5005: 5000: 4996: 4991: 4986: 4982: 4978: 4974: 4970: 4963: 4960: 4948: 4944: 4938: 4935: 4924: 4920: 4913: 4910: 4905: 4901: 4897: 4893: 4888: 4883: 4879: 4875: 4870: 4865: 4861: 4857: 4853: 4845: 4842: 4837: 4833: 4828: 4823: 4818: 4813: 4809: 4805: 4801: 4794: 4791: 4787: 4783: 4779: 4775: 4771: 4766: 4761: 4757: 4753: 4749: 4742: 4739: 4735: 4725: 4721: 4716: 4715:1721.1/143880 4711: 4707: 4703: 4699: 4698: 4690: 4687: 4682: 4678: 4673: 4668: 4664: 4660: 4656: 4652: 4647: 4642: 4638: 4634: 4630: 4622: 4619: 4614: 4610: 4605: 4600: 4596: 4592: 4588: 4584: 4580: 4576: 4572: 4564: 4561: 4556: 4549: 4545: 4540: 4535: 4530: 4525: 4521: 4517: 4513: 4509: 4505: 4498: 4495: 4489: 4484: 4480: 4476: 4472: 4468: 4461: 4458: 4453: 4449: 4445: 4441: 4437: 4433: 4429: 4425: 4418: 4415: 4404:on 2019-10-15 4403: 4399: 4395: 4393: 4385: 4382: 4376: 4371: 4367: 4363: 4356: 4353: 4341: 4337: 4330: 4327: 4322: 4318: 4313: 4308: 4304: 4300: 4296: 4292: 4288: 4284: 4280: 4273: 4271: 4267: 4262: 4258: 4254: 4250: 4246: 4242: 4238: 4234: 4227: 4224: 4219: 4215: 4211: 4207: 4203: 4199: 4195: 4191: 4187: 4183: 4179: 4172: 4169: 4164: 4160: 4155: 4150: 4146: 4142: 4138: 4134: 4130: 4126: 4122: 4115: 4112: 4107: 4103: 4098: 4093: 4089: 4085: 4081: 4077: 4073: 4066: 4063: 4058: 4054: 4050: 4046: 4042: 4038: 4034: 4030: 4022: 4019: 4014: 4010: 4006: 4002: 3998: 3990: 3988: 3984: 3979: 3975: 3970: 3965: 3961: 3957: 3953: 3949: 3944: 3939: 3935: 3931: 3927: 3923: 3919: 3911: 3909: 3905: 3900: 3896: 3891: 3886: 3882: 3878: 3874: 3870: 3866: 3859: 3857: 3853: 3848: 3844: 3840: 3836: 3832: 3828: 3821: 3818: 3813: 3809: 3804: 3799: 3795: 3791: 3787: 3783: 3779: 3775: 3771: 3764: 3761: 3756: 3749: 3745: 3740: 3735: 3730: 3725: 3721: 3717: 3714:(5): e37454. 3713: 3709: 3705: 3698: 3695: 3690: 3686: 3681: 3676: 3671: 3666: 3662: 3658: 3654: 3647: 3644: 3639: 3635: 3630: 3625: 3621: 3617: 3613: 3609: 3605: 3598: 3595: 3590: 3586: 3581: 3576: 3572: 3568: 3564: 3560: 3556: 3549: 3546: 3541: 3537: 3533: 3529: 3525: 3521: 3517: 3513: 3506: 3503: 3498: 3494: 3489: 3484: 3479: 3474: 3470: 3466: 3461: 3456: 3452: 3448: 3444: 3437: 3434: 3429: 3425: 3420: 3415: 3410: 3405: 3401: 3397: 3393: 3389: 3385: 3378: 3375: 3370: 3366: 3362: 3358: 3354: 3350: 3346: 3342: 3335: 3332: 3327: 3323: 3318: 3313: 3309: 3305: 3301: 3297: 3293: 3289: 3285: 3278: 3276: 3272: 3267: 3263: 3258: 3253: 3248: 3243: 3239: 3235: 3230: 3225: 3221: 3217: 3213: 3206: 3203: 3198: 3191: 3187: 3182: 3177: 3172: 3167: 3163: 3159: 3155: 3148: 3145: 3140: 3133: 3129: 3124: 3119: 3114: 3109: 3105: 3101: 3098:(10): e1049. 3097: 3093: 3089: 3082: 3079: 3074: 3070: 3066: 3062: 3058: 3054: 3047: 3044: 3039: 3035: 3031: 3027: 3023: 3019: 3015: 3011: 3003: 3000: 2995: 2991: 2987: 2983: 2979: 2975: 2968: 2965: 2960: 2957:(in French). 2956: 2949: 2946: 2941: 2937: 2932: 2927: 2923: 2919: 2915: 2908: 2905: 2900: 2893: 2889: 2884: 2879: 2874: 2869: 2865: 2861: 2857: 2853: 2849: 2842: 2840: 2836: 2831: 2827: 2822: 2817: 2813: 2809: 2806:(3): 524–36. 2805: 2801: 2797: 2790: 2787: 2782: 2778: 2774: 2770: 2766: 2762: 2759:(3): 247–54. 2758: 2754: 2750: 2743: 2740: 2735: 2731: 2726: 2721: 2717: 2713: 2709: 2705: 2702:(1): 259–67. 2701: 2697: 2693: 2686: 2683: 2678: 2674: 2670: 2666: 2662: 2658: 2654: 2650: 2643: 2640: 2635: 2631: 2626: 2621: 2617: 2613: 2609: 2605: 2601: 2594: 2591: 2586: 2582: 2578: 2574: 2570: 2566: 2562: 2558: 2551: 2548: 2543: 2539: 2534: 2529: 2524: 2519: 2515: 2511: 2507: 2503: 2499: 2492: 2489: 2484: 2480: 2476: 2472: 2467: 2462: 2457: 2452: 2448: 2444: 2440: 2433: 2430: 2425: 2421: 2416: 2411: 2406: 2401: 2397: 2393: 2389: 2382: 2379: 2374: 2370: 2365: 2360: 2356: 2352: 2348: 2344: 2340: 2333: 2330: 2317: 2313: 2306: 2303: 2290: 2286: 2279: 2276: 2271: 2267: 2263: 2259: 2255: 2251: 2247: 2243: 2236: 2233: 2228: 2224: 2219: 2214: 2210: 2206: 2202: 2198: 2194: 2187: 2184: 2179: 2175: 2171: 2167: 2163: 2159: 2155: 2151: 2147: 2143: 2136: 2134: 2130: 2125: 2121: 2116: 2111: 2107: 2103: 2099: 2095: 2091: 2087: 2083: 2076: 2074: 2070: 2065: 2061: 2056: 2051: 2047: 2043: 2040:(6): 417–22. 2039: 2035: 2031: 2024: 2021: 2016: 2012: 2007: 2002: 1998: 1994: 1991:(3): 346–53. 1990: 1986: 1982: 1975: 1972: 1967: 1963: 1959: 1955: 1951: 1947: 1943: 1939: 1935: 1931: 1924: 1921: 1916: 1912: 1908: 1904: 1900: 1896: 1892: 1888: 1881: 1879: 1875: 1870: 1863: 1859: 1854: 1849: 1844: 1839: 1835: 1831: 1827: 1820: 1818: 1814: 1809: 1805: 1800: 1795: 1791: 1787: 1783: 1779: 1775: 1768: 1766: 1762: 1757: 1753: 1749: 1745: 1741: 1737: 1734:(5): 532–41. 1733: 1729: 1721: 1718: 1713: 1709: 1705: 1701: 1697: 1693: 1690:(4): 272–82. 1689: 1685: 1681: 1674: 1671: 1666: 1662: 1658: 1654: 1650: 1646: 1643:(2): 127–44. 1642: 1638: 1631: 1628: 1623: 1619: 1614: 1609: 1606:(3): 277–99. 1605: 1601: 1597: 1590: 1587: 1582: 1578: 1573: 1568: 1564: 1560: 1557:(1): 156–70. 1556: 1552: 1548: 1541: 1538: 1533: 1529: 1524: 1519: 1515: 1511: 1507: 1503: 1499: 1492: 1489: 1484: 1480: 1475: 1470: 1466: 1462: 1458: 1451: 1449: 1445: 1440: 1436: 1431: 1426: 1422: 1418: 1414: 1407: 1404: 1399: 1395: 1390: 1385: 1380: 1375: 1371: 1367: 1363: 1359: 1355: 1348: 1345: 1340: 1334: 1330: 1323: 1320: 1315: 1309: 1305: 1301: 1297: 1290: 1287: 1276: 1272: 1265: 1262: 1257: 1250: 1246: 1241: 1236: 1231: 1226: 1222: 1218: 1214: 1210: 1206: 1199: 1197: 1195: 1191: 1180: 1176: 1172: 1171: 1163: 1161: 1157: 1144: 1139: 1135: 1131: 1124: 1121: 1116: 1112: 1108: 1104: 1100: 1096: 1092: 1085: 1082: 1076: 1071: 1068: 1066: 1063: 1061: 1058: 1056: 1055:Neural coding 1053: 1051: 1048: 1046: 1043: 1041: 1038: 1036: 1033: 1031: 1028: 1026: 1023: 1021: 1018: 1017: 1012: 1010: 1008: 1003: 1001: 997: 989: 987: 985: 980: 978: 972: 964: 962: 960: 956: 951: 946: 944: 940: 932: 927: 925: 923: 919: 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