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Thalamocortical interaction is a ubiquitous functional motif in the mammalian brain. Previously (Hwang et al., 2021), we reported that lesions to network hubs in the human thalamus are associated with multi-domain behavioral impairments in language, memory, and executive functions. Here, we show how task-evoked thalamic activity is organized to support these broad cognitive abilities. We analyzed functional magnetic resonance imaging (MRI) data from human subjects that performed 127 tasks encompassing a broad range of cognitive representations. We first investigated the spatial organization of task-evoked activity and found a basis set of activity patterns evoked to support processing needs of each task. Specifically, the anterior, medial, and posterior-medial thalamus exhibit hub-like activity profiles that are suggestive of broad functional participation. These thalamic task hubs overlapped with network hubs interlinking cortical systems. To further determine the cognitive relevance of thalamic activity and thalamocortical functional connectivity, we built a data-driven thalamocortical model to test whether thalamic activity can be used to predict cortical task activity. The thalamocortical model predicted task-specific cortical activity patterns, and outperformed comparison models built on cortical, hippocampal, and striatal regions. Simulated lesions to low-dimensional, multi-task thalamic hub regions impaired task activity prediction. This simulation result was further supported by profiles of neuropsychological impairments in human patients with focal thalamic lesions. In summary, our results suggest a general organizational principle of how the human thalamocortical system supports cognitive task activity. [ABSTRACT FROM AUTHOR]

Hubs in the human brain support behaviors that arise from brain network interactions. Previous studies have identified hub regions in the human thalamus that are connected with multiple functional networks. However, the behavioral significance of thalamic hubs has yet to be established. Our framework predicts that thalamic subregions with strong hub properties are broadly involved in functions across multiple cognitive domains. To test this prediction, we studied human patients with focal thalamic lesions in conjunction with network analyses of the human thalamocortical functional connectome. In support of our prediction, lesions to thalamic subregions with stronger hub properties were associated with widespread deficits in executive, language, and memory functions, whereas lesions to thalamic subregions with weaker hub properties were associated with more limited deficits. These results highlight how a large- scale network model can broaden our understanding of thalamic function for human cognition. [ABSTRACT FROM AUTHOR]

Hubs are highly connected brain regions important for coordinating processing in brain networks. It is unclear, however, which measures of network "hubness" are most useful in identifying brain regions critical to human cognition. We tested how closely two measures of hubness--edge density and participation coefficient, derived from white and gray matter, respectively--were associated with general cognitive impairment after brain damage in two large cohorts of patients with focal brain lesions (N = 402 and 102, respectively) using cognitive tests spanning multiple cognitive domains. Lesions disrupting white matter regions with high edge density were associated with cognitive impairment, whereas lesions damaging gray matter regions with high participation coefficient had a weaker, less consistent association with cognitive outcomes. Similar results were observed with six other gray matter hubness measures. This suggests that damage to densely connected white matter regions is more cognitively impairing than similar damage to gray matter hubs, helping to explain interindividual differences in cognitive outcomes after brain damage. [ABSTRACT FROM AUTHOR]

The human thalamus has been suggested to be involved in executive function, based on animal studies and correlational evidence from functional neuroimaging in humans. Human lesion studies, examining behavioral deficits associated with focal brain injuries, can directly test the necessity of the human thalamus for executive function. The goal of our study was to determine the specific lesion location within the thalamus as well as the potential disruption of specific thalamocortical functional networks, related to executive dysfunction. We assessed executive function in 15 patients with focal thalamic lesions and 34 comparison patients with lesions that spared the thalamus. We found that patients with mediodorsal thalamic lesions exhibitedmore severe impairment in executive function when compared to both patients with thalamic lesions that spared themediodorsal nucleus and to comparison patients with lesions outside the thalamus. Furthermore, we employed a lesion network mapping approach to map cortical regions that show strong functional connectivity with the lesioned thalamic subregions in the normative functional connectome. We found that thalamic lesion sites associated with more severe deficits in executive function showed stronger functional connectivity with ACC, dorsomedial PFC, and frontoparietal network, compared to thalamic lesions not associated with executive dysfunction. These are brain regions and functional networks whose dysfunction could contribute to impaired executive functioning. In aggregate, our findings provide new evidence that delineates a thalamocortical network for executive function. [ABSTRACT FROM AUTHOR]

The thalamus is globally connected with distributed cortical regions, yet the functional significance of this extensive thalamocortical connectivity remains largely unknown. By performing graph-theoretic analyses on thalamocortical functional connectivity data collected from human participants, we found that most thalamic subdivisions display network properties that are capable of integrating multimodal information across diverse cortical functional networks. From a meta-analysis of a large dataset of functional brain-imaging experiments, we further found that the thalamus is involved in multiple cognitive functions. Finally, we found that focal thalamic lesions in humans have widespread distal effects, disrupting the modular organization of cortical functional networks. This converging evidence suggests that the human thalamus is a critical hub region that could integrate diverse information being processed throughout the cerebral cortex as well as maintain the modular structure of cortical functional networks. [ABSTRACT FROM AUTHOR]

The ability to inhibit prepotent responses is critical for successful goal-directed behaviors. To investigate the neural basis of inhibitory control, we conducted a magnetoencephalography study where human participants performed the antisaccade task. Results indicated that neural oscillations in the prefrontal cortex (PFC) showed significant task modulations in preparation to suppress saccades. Before successfully inhibiting a saccade, beta-band power (18 -38 Hz) in the lateral PFC and alpha-band power (10 -18 Hz) in the frontal eye field (FEF) increased. Trial-by-trial prestimulus FEF alpha-band power predicted successful saccadic inhibition. Further, inhibitory control enhanced cross-frequency amplitude coupling between PFC beta-band (18 -38 Hz) activity and FEF alpha-band activity, and the coupling appeared to be initiated by the PFC. Our results suggest a generalized mechanism for top-down inhibitory control: prefrontal beta-band activity initiates alpha-band activity for functional inhibition of the effector and/or sensory system. [ABSTRACT FROM AUTHOR]

The ability to voluntarily inhibit responses to task-irrelevant stimuli, which is a fundamental component of cognitive control, has a protracted development through adolescence. Previous human developmental imaging studies have found immaturities in localized brain activity in children and adolescents. However, little is known about how these regions integrate with age to form the distributed networks known to support cognitive control. In the present study, we used Granger causality analysis to characterize developmental changes in effective connectivity underlying inhibitory control (antisaccade task) compared with reflexive responses (prosaccade task) in human participants. By childhood, few top-down connectivities were evident with increased parietal interconnectivity. By adolescence, connections from prefrontal cortex increased and parietal interconnectivity decreased. From adolescence to adulthood, there was evidence of increased number and strength of frontal connections to cortical regions as well as subcortical regions. Together, results suggest that developmental improvements in inhibitory control may be supported by age-related enhancements in top-down effective connectivity between frontal, oculomotor, and subcortical regions. [ABSTRACT FROM AUTHOR]

Collusive piracy is the main source of intellectual property violations within the boundary of a P2P network. Paid clients (colluders) may illegally share copyrighted content files with unpaid clients (pirates). Such online piracy has hindered the use of open P2P networks for commercial content delivery. We propose a proactive content poisoning scheme to stop colluders and pirates from alleged copyright infringements in P2P file sharing. The basic idea is to detect pirates timely with identity-based signatures and time-stamped tokens. The scheme stops collusive piracy without hurting legitimate P2P clients by targeting poisoning on detected violators, exclusively. We developed a new peer authorization protocol (PAP) to distinguish pirates from legitimate clients. Detected pirates will receive poisoned chunks in their repeated attempts, Pirates are thus severely penalized with no chance to download successfully in tolerable time. Based on simulation results we find 99.9 percent prevention rate in Gnutella KaZaA and Freenet. We achieved 85-98 percent prevention rate on eMule, eDonkey, Morpheus, etc. The scheme is shown less effective in protecting some poison-resilient networks like BitTorrent and Azureus. Our work opens up the low-cost P2P technology for copyrighted content delivery. The advantage lies mainly in minimum delivery cost, higher content availability, and copyright compliance in exploring P2P network resources. [ABSTRACT FROM AUTHOR]

Credential chains are needed in trusted peer-to-peer(P2P) applications, where trust delegation must be established between each pair of peers at specific role level. Role-based trust is refined from the coarse-grained trust model used in most P2P reputation systems. This paper offers a novel heuristic-weighting approach to selecting the most likely path to construct a role-based trust chain. We apply history-sensitive heuristics to measure the path complexity and to assess the chaining efficiency. Our method discovers successive edges of a trust chain, adaptively, to match with the demands in any given P2P application. New heuristic chaining algorithms are developed for backward, forward, and bidirectional discovery of trust chains. Our heuristic chain discovery scheme shortens the search time, reduces the memory requirement, and enhances the chaining accuracy in scalable P2P networks. Consider a trust graph over N credentials and M distinct role nodes. Our heuristic trust-chain discovery algorithms require O(N²logN) search time and O(M) memory space, if the secondary heuristics are generated offline in advance. These are improved from O(N³) search time and O(NM) space required in nonheuristic discovery algorithms developed by Li et al. [12]. Our analytical results are verified by extensive simulation experiments over typical classes of role-based trust graphs. [ABSTRACT FROM AUTHOR]

In peer-to-peer (P2P) networks, peer reputation aggregation and ranking are the most time-consuming and space-demanding operations. This paper proposes a gossip-based reputation system (GossipTrust) for fast aggregation of global peer reputation scores. The system leverages a Bloom filter architecture for efficient score ranking. GossipTrust does not require any secure hashing or fast lookup mechanism; thus, it is applicable to both unstructured and structured P2P networks. Randomized gossiping aided by the effective use of power nodes enables lightweight aggregation and fast dissemination of global scores in O(log2 n) time, where n is the P2P network size. The Gossip-based protocol not only tolerates dynamic peer joining and departure but also avoids peer collusions, with a gossiping overhead of O(n log2 n) messages over n nodes. Bloom filters demand at most 512 Kbytes per node for a 10,000-node network. We evaluate the performance of GossipTrust with distributed P2P file-sharing and parameter-sweeping applications. The results demonstrate small aggregation time, low memory demand, and high ranking accuracy. These are distinct advantages of GossipTrust over other reputation systems in supporting trusted P2P applications. [ABSTRACT FROM AUTHOR]

Selfish behaviors of individual machines in a Grid can potentially damage the performance of the system as a whole. However, scrutinizing the Grid by taking into account the noncooperativeness of machines is a largely unexplored research problem. In this paper, we first present a new hierarchical game-theoretic model of the Grid that matches well with the physical administrative structure in real-life situations. We then focus on the impact of selfishness in intrasite job execution mechanisms. Based on our novel utility functions, we analytically derive the Nash equilibrium and optimal strategies for the general case. To study the effects of different strategies, we have also performed extensive simulations by using a well-known practical scheduling algorithm over the NAS (Numerical Aerodynamic Simulation) and the PSA (Parameter Sweep Application) workloads. We have studied the overall job execution performance of the Grid system under a wide range of parameters. Specifically, we find that the Optimal selfish strategy significantly outperforms the Nash selfish strategy. Our performance evaluation results can serve as a valuable reference for designing appropriate strategies in a practical Grid. [ABSTRACT FROM AUTHOR]

Peer-to-Peer (P2P) reputation systems are essential to evaluate the trustworthiness of participating peers and to combat the selfish, dishonest, and malicious peer behaviors. The system collects locally-generated peer feedbacks and aggregates them to yield the global reputation scores. Surprisingly, most previous work ignored the distribution of peer feedbacks. We use a trust overlay network (TON) to model the trust relationships among peers. After examining the eBay transaction trace of over 10,000 users, we discover a power-law distribution in user feedbacks. Our mathematical analysis justifies that power-law distribution is applicable to any dynamically growing P2P systems, either structured or unstructured. We develop a robust and scalable P2P reputation system, PowerTrust, to leverage the power-law feedback characteristics. The PowerTrust system dynamically selects small number of power nodes that are most reputable using a distributed ranking mechanism. By using a look-ahead random walk strategy and leveraging the power nodes, PowerTrust significantly improves in global reputation accuracy and aggregation speed. PowerTrust is adaptable to dynamics in peer joining and leaving and robust to disturbance by malicious peers. Through P2P network simulation experiments, we find significant performance gains in using PowerTrust. This power-law guided reputation system design proves to achieve high query success rate in P2P file-sharing applications. The system also reduces the total job makespan and failure rate in large-scale, parameter-sweeping P2P Grid applications. [ABSTRACT FROM AUTHOR]

This paper describes the design of a two-level hierarchical production scheduling engine, which captures the industrial practice of mass production semiconductor fabrication factories (fabs). The two levels of the hierarchy consist of a mid-term scheduler and a short-term scheduler, and are aimed at achieving coordination between the fab-wide objectives and local shop-floor operations. The mid-term scheduler maximizes weighted production flow to reduce the fab-wide cycle time and ensure on-time delivery by properly setting daily production target volumes and reference work-in-process (WIP) levels for individual part types and stages. Mid-term scheduling results are further broken down into more detailed schedules by the short-term scheduler. In addition to the same set of operational constraints in mid-term scheduling, the short-term scheduler includes the consideration of batching effects. It maximizes weighted production flow while tracking the daily production targets and the reference WIP levels specified by mid-term scheduling. The schedulers adopt a solution methodology with three ingredients; the Lagrange relaxation approach, network flow optimization, and Frank-Wolfe method. The methodology is optimization-based, exploits the separability of the scheduling problem formulations, and facilitates quick answers to "what if" analysis. Test results using field data indicate that the two-level scheduling tool is reasonably efficient in computation and leads to throughput increase and reduction of output variations. The scheduling results can further be utilized in variability analysis for cycle time reduction. [ABSTRACT FROM AUTHOR]

Presents a distributed disk-array architecture for achieving I/O performance in scalable cluster computing. Advantage of RAID-x; Development of cooperative disk drivers and Linux extensions; Areas of strength of RAID-x.

Task representations are critical for cognitive control and adaptive behavior. The hierarchical organization of task representations allows humans to maintain goals, integrate information across varying contexts, and select potential responses. In this study we characterized the structure and interactive dynamics of task representations that facilitate cognitive control. Human participants (both males and females) performed a hierarchical task that required them to select a response rule while considering the contingencies from different contextual inputs. By applying time- and frequency-resolved representational similarity analysis to human electroencephalography data, we characterized properties of task representations that are otherwise difficult to observe. We found that participants formed multiple representations of task-relevant contexts and features from the presented stimuli, beyond simple stimulus–response mappings. These disparate representations were hierarchically structured, with higher-order contextual representations dominantly influencing subordinate representations of task features and response rules. Furthermore, this cascade of top-down interactions facilitated faster responses. Our results describe key properties of task representations that support hierarchical cognitive control. [ABSTRACT FROM AUTHOR]

Evaluates six massively parallel processor systems through space-time adaptive processing (STAP) benchmark experiments. Phase-parallel scaling model; STAP benchmark characteristics; Single program and multiple data streams node program and internode communications; Latency and bandwidth of accelerated strategic computing initiative machines.

With the increasing demand for parallel processing and distributed computing, parallel programming languages are becoming indispensable. This paper presents a new language construct, called molecule, for the efficient implementation of algorithms on parallel computers. A molecule can be considered a procedure associated with a molecule type. Each molecule type characterizes a particular computation mode (sequential, pipelining, array processing, dataflow, multiprocessing, etc.). Basic concepts of molecule are introduced with a procedural language, called PAL. A concrete example is presented to illustrate layered software development using PAL on a multicomputer (the iPSC). The key message being conveyed is that high-level languages, augmented with the molecule construct, will offer application flexibility, user friendliness, and efficiency in implementing parallel programs. [ABSTRACT FROM AUTHOR]

A loosely coupled multiprocessor system contains multiple processors which have their own local memories. To balance the load among multiple processors is of fundamental importance in enhancing the performance of such a multiple processor system. Probabilistic load balancing in a heterogeneous multiple processor system with many job classes is considered in this study. The load balancing scheme is formulated as a nonlinear programming problem with linear constraints. An optimal probabilistic load balancing algorithm is proposed to solve this nonlinear programming problem. The proposed load balancing method is proven globally optimum in the sense that it results in a minimum overall average job response time on a probabilistic basis. [ABSTRACT FROM AUTHOR]

Hierarchical cognitive control enables us to execute actions guided by abstract goals. Previous research has suggested that neuronal oscillations at different frequency bands are associated with top-down cognitive control; however, whether distinct neural oscillations have similar or different functions for cognitive control is not well understood. The aim of the current study was to investigate the oscillatory neuronal mechanisms underlying two distinct components of hierarchical cognitive control: the level of abstraction of a rule, and the number of rules that must be maintained (set-size). We collected EEG data in 31 men and women who performed a hierarchical cognitive control task that varied in levels of abstraction and set-size. Results from time-frequency analysis in frontal electrodes showed an increase in theta amplitude for increased set-size, whereas an increase in S was associated with increased abstraction. Both theta and δ amplitude correlated with behavioral performance in the tasks but in an opposite manner: theta correlated with response time slowing when the number of rules increased, whereas δ correlated with response time when rules became more abstract. Phase-amplitude coupling analysis revealed that δ phase-coupled with β amplitude during conditions with a higher level of abstraction, whereby beta band may potentially represent motor output that was guided by the δ phase. These results suggest that distinct neural oscillatory mechanisms underlie different components of hierarchical cognitive control. [ABSTRACT FROM AUTHOR]

Presents a correction to the article "Optimal Load Balancing in a Multiple Processor System with Many Job Classes," by Lionel M. Ni and Kai Hwang in the May 1985 issue, with regards to the Load Balancing Algorithm.

This study is aimed at verifying the causal relationship of chronic circadian desynchronization and changes in body weight control. Eight male albino F344 rats aged between 12-15 wk were subjected to twice weekly 12-h shifts of the dally light-dark (LD) cycle for 13 wk (3 mo). Continuous circadian phase shifts consisting of intermittent phase delay and advance and reduced circadian amplitudes were consistently displayed in all five experimental rats implanted intraperitoneally with heart rate, body temperature, and activity transponders. The experimental rat maintained a greater body weight during LD shifts and even after 10 days of recovery than that of the age-matched control rat, which was maintained on a regular LD cycle. Body weight gain was greater in the first 2 mo of LD shifts in the experimental rat than in the control rat. Relative to the baseline, food intake and activity percentages were increased and reduced, respectively, for the experimental rats. Features of these results, such as increased body weight gain and food intake, and reduced activity, suggest a causal relationship of chronic circadian desynchronization and changes in body weight control in male albino F344 rats. [ABSTRACT FROM AUTHOR]

Presents the design and performance of a parallel graphics renderer for three-dimensional images. Comparison of the method over the adaptive supersampling technique; Similarity to the adaptive grid work in computational fluid dynamics; Proof of the advantages of the approach through experiments on different multiprocessors and workstation clusters.