Properties of a random attachment growing network

In this study we introduce and analyze the statistical structural properties of a model of growing networks which may be relevant to social networks. At each step a new node is added which selects 'k' possible partners from the existing network and joins them with probability delta by undirected edges. The 'activity' of the node ends here; it will get new partners only if it is selected by a newcomer. The model produces an infinite-order phase transition when a giant component appears at a specific value of delta, which depends on k. The average component size is discontinuous at the transition. In contrast, the network behaves significantly different for k=1. There is no giant component formed for any delta and thus in this sense there is no phase transition. However, the average component size diverges for delta greater or equal than one half.Comment: LaTeX, 19 pages, 6 figures. Discussion section, comments, a new figure and a new reference are added. Equations simplifie

Prediction of emerging technologies based on analysis of the US patent citation network

Abstract The network of patents connected by citations is an evolving graph, which provides a representation of the innovation process. A patent citing another implies that the cited patent reflects a piece of previously existing knowledge that the citing patent builds upon. A methodology presented here (1) identifies actual clusters of patents: i.e., technological branches, an

Prediction of Emerging Technologies Based on Analysis of the U.S. Patent Citation Network

The network of patents connected by citations is an evolving graph, which provides a representation of the innovation process. A patent citing another implies that the cited patent reflects a piece of previously existing knowledge that the citing patent builds upon. A methodology presented here (i) identifies actual clusters of patents: i.e. technological branches, and (ii) gives predictions about the temporal changes of the structure of the clusters. A predictor, called the {citation vector}, is defined for characterizing technological development to show how a patent cited by other patents belongs to various industrial fields. The clustering technique adopted is able to detect the new emerging recombinations, and predicts emerging new technology clusters. The predictive ability of our new method is illustrated on the example of USPTO subcategory 11, Agriculture, Food, Textiles. A cluster of patents is determined based on citation data up to 1991, which shows significant overlap of the class 442 formed at the beginning of 1997. These new tools of predictive analytics could support policy decision making processes in science and technology, and help formulate recommendations for action

Connectivity of neuronal populations within and between areas of primate somatosensory cortex

Functions of the cerebral cortex emerge via interactions of horizontally distributed neuronal populations within and across areas. However, the connectional underpinning of these interactions is not well understood. The present study explores the circuitry of column-size cortical domains within the hierarchically organized somatosensory cortical areas 3b and 1 using tract tracing and optical intrinsic signal imaging (OIS). The anatomical findings reveal that feedforward connections exhibit high topographic specificity, while intrinsic and feedback connections have a more widespread distribution. Both intrinsic and inter-areal connections are topographically oriented across the finger representations. Compared to area 3b, the low clustering of connections and small cortical magnification factor supports that the circuitry of area 1 scaffolds a sparse functional representation that integrates peripheral information from a large area that is fed back to area 3b. Fast information exchange between areas is ensured by thick axons forming a topographically organized, reciprocal pathway. Moreover, the highest density of projecting neurons and groups of axon arborization patches corresponds well with the size and locations of the functional population response reported by OIS. The findings establish connectional motifs at the mesoscopic level that underpin the functional organization of the cerebral cortex

Connectivity of neuronal populations within and between areas of primate somatosensory cortex

Functions of the cerebral cortex emerge via interactions of horizontally distributed neuronal populations within and across areas. However, the connectional underpinning of these interactions is not well understood. The present study explores the circuitry of column-size cortical domains within the hierarchically organized somatosensory cortical areas 3b and 1 using tract tracing and optical intrinsic signal imaging (OIS). The anatomical findings reveal that feedforward connections exhibit high topographic specificity, while intrinsic and feedback connections have a more widespread distribution. Both intrinsic and inter-areal connections are topographically oriented across the finger representations. Compared to area 3b, the low clustering of connections and small cortical magnification factor supports that the circuitry of area 1 scaffolds a sparse functional representation that integrates peripheral information from a large area that is fed back to area 3b. Fast information exchange between areas is ensured by thick axons forming a topographically organized, reciprocal pathway. Moreover, the highest density of projecting neurons and groups of axon arborization patches corresponds well with the size and locations of the functional population response reported by OIS. The findings establish connectional motifs at the mesoscopic level that underpin the functional organization of the cerebral cortex

Synaptic organization of cortico-cortical communication in primates

In cortical circuitry synaptic communication across areas is based on two types of axon terminals, small and large, with modulatory and driving roles, respectively. In contrast, it is not known whether similar synaptic specializations exist for intra‐areal projections. Using anterograde tracing and three‐dimensional reconstruction by electron microscopy (3D‐EM) we asked if large boutons form synapses in the circuit of somatosensory cortical areas 3b and 1. In contrast to observations in macaque visual cortex, light microscopy showed both small and large boutons not only in inter‐areal pathways, but also in long‐distance intrinsic connections. 3D‐EM showed that correlation of surface and volume provides a powerful tool for classifying cortical endings. Principal component analysis supported this observation and highlighted the significance of the size of mitochondria as a distinguishing feature of bouton type. The larger mitochondrion and higher degree of perforated postsynaptic density associated with large rather than to small boutons support the driver‐like function of large boutons. In contrast to bouton size and complexity, the size of the postsynaptic density appeared invariant across the bouton types. Comparative studies in human supported that size is a major distinguishing factor of bouton type in the cerebral cortex. In conclusion, the driver‐like function of the large endings could facilitate fast dissemination of tactile information within the intrinsic and inter‐areal circuitry of areas 3b and 1

Synaptic organization of cortico-cortical communication in primates

In cortical circuitry synaptic communication across areas is based on two types of axon terminals, small and large, with modulatory and driving roles, respectively. In contrast, it is not known whether similar synaptic specializations exist for intra‐areal projections. Using anterograde tracing and three‐dimensional reconstruction by electron microscopy (3D‐EM) we asked if large boutons form synapses in the circuit of somatosensory cortical areas 3b and 1. In contrast to observations in macaque visual cortex, light microscopy showed both small and large boutons not only in inter‐areal pathways, but also in long‐distance intrinsic connections. 3D‐EM showed that correlation of surface and volume provides a powerful tool for classifying cortical endings. Principal component analysis supported this observation and highlighted the significance of the size of mitochondria as a distinguishing feature of bouton type. The larger mitochondrion and higher degree of perforated postsynaptic density associated with large rather than to small boutons support the driver‐like function of large boutons. In contrast to bouton size and complexity, the size of the postsynaptic density appeared invariant across the bouton types. Comparative studies in human supported that size is a major distinguishing factor of bouton type in the cerebral cortex. In conclusion, the driver‐like function of the large endings could facilitate fast dissemination of tactile information within the intrinsic and inter‐areal circuitry of areas 3b and 1