• We train a model to generate connectomes based on individual measures. • Generated networks preserve individuals’ unique neural fingerprint and connectome topology. • Individual measures exhibit different importance to connectome generation. • Generated networks aid machine learning model training as augmented data. An individual’s connectome is unique. Interindividual variation in connectome architecture associates with disease status, cognition, lifestyle factors, and other personal attributes. While models to predict personal attributes from a person’s connectome are abundant, the inverse task—inferring connectome architecture from an individual’s personal profile—has not been widely studied. Here, we introduce a deep model to generate a person’s entire connectome exclusively based on their age, sex, body phenotypes, cognition, and lifestyle factors. Using the richly phenotyped UK Biobank connectome cohort (N=8,086), we demonstrate that our model can generate network architectures that closely recapitulate connectomes mapped empirically using diffusion MRI and tractography. We find that age, sex, and body phenotypes exert the strongest influence on the connectome generation process, with an impact approximately four times greater than that of cognition and lifestyle factors. Regional differences in the importance of measures were observed, including an increased importance of cognition in the association cortex relative to the visual system. We further show that generated connectomes can improve the training of machine learning models and reduce their predictive errors. Our work demonstrates the feasibility of inferring brain connectivity from an individual’s personal data and enables future applications of connectome generation such as data augmentation and anonymous data sharing.

To compute link blocking rates in an optical burst/packet switched network, it has been shown that the Engset formula should be used with a reduced packet arrival rate to account for packet dumping. This reduction is realized by lengthening the off-time during which a source remains idle, which is referred to as the lengthened off-time approximation (LOA). It is known that if the blocking probability is small or the number of sources (input links) is large, the LOA is redundant. We show here that the LOA is also redundant for certain state independent approximations and prove that they are equivalent to the Engset formula if the blocking probability is evaluated as a function of utilization. We consider a new LOA whereby the interval by which the off-time is lengthened depends on the number of busy channels. We demonstrate that this new state-dependent LOA (sdLOA) yields higher accuracy irrespective of whether blocking probability is evaluated as a function of either utilization which is a system-dependent measure, or system independent measures such as the intended arrival rate.

We arm researchers with a simple method to chart a macroscopic cortico-cortical connectivity network in living human subjects. The researcher provides a diffusion-magnetic resonance imaging (MRI) data set and N cortical regions of interest. In return, we provide an N xN structural adjacency matrix (SAM) quantifying the relative connectivity between all cortical region pairs. We also return a connectivity map for each pair to enable visualization of interconnecting fiber bundles. The measure of connectivity we devise is: 1) free of length bias, 2) proportional to fiber bundle cross-sectional area, and 3) invariant to an exchange of seed and target. We construct a 3-D lattice scaffolding (graph) for white-matter by drawing a link between each pair of voxels in a 26-voxel neighborhood for which their two respective principal eigenvectors form a sufficiently small angle. The connectivity between a cortical region pair is then measured as the maximum number of link-disjoint paths that can be established between them in the white-matter graph. We devise an efficient Edmonds-Karp-like algorithm to compute a conservative bound on the maximum number of link-disjoint paths. Using both simulated and authentic diffusion-tensor imaging data, we demonstrate that the number of link-disjoint paths as a measure of connectivity satisfies properties 1)-3), unlike the fraction of intersecting streamlines-the measure intrinsic to most existing probabilistic tracking algorithms. Finally, we present connectivity maps of some notoriously difficult to track longitudinal and contralateral fasciculi.

We derive a new fiber tracking algorithm for DT-MRI that parts with the locally "greedy" paradigm intrinsic to conventional tracking algorithms. We demonstrate the ability to precisely reconstruct a diverse range of fiber trajectories in authentic and computer-generated DT-MRI data, for which well-known conventional tracking algorithms are shown to fail. Our approach is to pose fiber tracking as a problem in computing shortest paths in a weighted digraph. Voxels serve as vertices, and edges are included between neighboring voxels. We assign probabilities (weights) to edges using a Bayesian framework. Higher probabilities are assigned to edges that are aligned with fiber trajectories in their close proximity. We compute optimal paths of maximum probability using computationally scalable shortest path algorithms. The salient features of our approach are: global optimality--unlike conventional tracking algorithms, local errors do not accumulate and one "wrong-turn" does not spell disaster; a target point is specified a priori; precise reconstruction is demonstrated for extremely low signal-to-noise ratio; impartiality to which of two endpoints is used as a seed; and, faster computation times than conventional all-paths tracking. We can use our new tracking algorithm in either a single-path tracking mode (deterministic tracking) or an all-paths tracking mode (probabilistic tracking).

We consider a telecommunication competition model involving an incumbent and one or more new entrants who only choose to serve the most profitable traffic. The contribution of this paper is a new analysis that studies the effect of traffic shifts, which are common in the Internet era, on the distribution of market share. Introducing and using a new concept of a shifting network process, we analyze an incumbent network provider adapting its network to this shifting network process with a mixed integer linear program (MILP). In addition, a second MILP is developed to determine the maximum market share obtainable by a single competitor, engaging in so-called "cream-skimming". Further, we investigate the situation wherein multiple competitors compete on specific parts of the network. Numerical results are provided to demonstrate the various market share effects that may occur.

In this paper, we consider the problem of estimating steady-state blocking probability for circuit-switched networks with alternate routing. In particular, we focus on networks protected by trunk reservation. A new blocking probability estimate, the so-called overflow priority classification approximation (OPCA), is considered as an alternative to the currently used the Erlang fixed-point approximation (EFPA). OPCA is applied to the case of arbitrary circuit-switched networks with trunk reservation. We show through empirical results that OPCA yields a superior estimate for blocking probability compared to EFPA for circuit-switched networks with alternate routing that are reasonably protected against instability by trunk reservation.

This paper studies the blocking performance of optical burst switching (OBS) networks using a sequential office control (SOC) state-independent deflection routing policy. We show that unprotected deflection routing may destabilize OBS resulting in higher blocking probabilities than if bursts were not deflected but simply blocked. This study was motivated by the well-known destabilizing effect that alternative routing has on circuit switching in classical telephony networks. We propose two forms of protection to guard against destabilization: 1) wavelength reservation, which is analogous to trunk reservation in circuit switching; and, 2) preemptive priority, which is a new form of protection where bursts that have not been deflected are given preemptive priority over bursts that have been deflected. Our main contribution is a one-moment reduced-load approximation to evaluate the blocking performance of OBS networks using deflection routing protected by either wavelength reservation or preemptive priority. Our reduced-load approximation relies on the usual assumptions of link independence and Poisson distributed link arrivals. We quantify the error admitted in making these two assumptions via simulation. Using our reduced-load approximation, we evaluate the blocking performance of protected and unprotected deflection routing in several randomly generated networks. The chief conclusion of our study is that deflection routing in OBS should be given some form of protection to avoid destabilization resulting from upward load variations, and in terms of blocking performance, preemptive priority is the best form of protection for OBS. We use simulation to verify that our conclusions remain valid for a realistic traffic scenario.

This paper proposes a new optical burst switching (OBS) paradigm known as dynamic two-way reservation OBS (DTWR/OBS), in which the burst length is dynamically determined at an ingress router, according to the minimum length reservation period available on each wavelength channel within a lightpath, from the ingress router to the egress router. The dynamic nature of DTWR/OBS ensures the packet transmission rate is controlled at the ingress routers, based on the level of network congestion. This increases network utilization and eliminates burst blocking due to wavelength contention. An analytical model for a single isolated optical cross-connect (OXC) is derived to determine the waiting time distribution of an arbitrary IP packet at the ingress router using the proposed DTWR/OBS. The accuracy of the analytical model is confirmed by simulations.

We consider a simple model for distributed video on demand (VoD) systems. The model is analyzed by the Erlang fixed point (EFP) approximation and by a new method referred to as overflow priority classification (OPC). The OPC method imposes a preemptive priority regime in a non-priority system to capture the traffic load dependence among VoD servers. Comparison between OPC and EFP reveals that OPC is more accurate. The comparison is made with respect to two quality of service (QoS) measures, the loss probability and the probability that a video request is not served by the preferred VoD server given that it is not lost.

Limited wavelength conversion and deflection routing are considered as viable methods to reduce the burst blocking probability in optical burst switched (OBS) networks. The question of which of the two methods is most effective has yet to be resolved. In this paper, an analytical model is derived that provides an accurate and quick means to evaluate and compare the effectiveness of limited wavelength conversion and deflection routing. First, an overflow load fixed point approximation model is derived for a single link in isolation. Then the single link model is integrated into a reduced load fixed point approximation model for a general network topology with deflection routing. The accuracy of the analytical model is verified through simulation.

Methods to resolve wavelength contention are needed to improve the performance of optical burst switched (OBS) networks. Network simulations and Markovian queuing models for nodes in isolation have suggested that deflection routing (alternate routing) may be a viable method to resolve wavelength contention. However, we show that deflection routing may destabilise OBS networks operating at high loads. To prevent the destabilising effect of deflection routing, we propose and analyse a technique called wavelength reservation to intentionally limit the amount of deflection at high loads. Wavelength reservation is analogous to trunk reservation in circuit switched networks. This paper is the first to present a new reduced load Erlang fixed point analysis of OBS networks with deflection routing and wavelength reservation. We apply the new analysis to evaluate the benefit of deploying deflection routing and wavelength reservation in a sample OBS network.