Network Interventions

Resting-state EEG Dynamics Reveals Differences in Network Organization and its Fluctuation between Frequency Bands

The view of the human brain as a complex network has led to considerable advances in understanding the brain’s network organization during rest and task, in both health and disease. Here, we propose that examining brain networks within the task aftereffect model, in which we compare resting-state networks immediately before and after a cognitive engagement task, may enhance differentiation between those with normal cognition and those with increased risk for cognitive decline. We validated this model by comparing the pre- and post-task resting-state functional network organization of neurologically intact elderly and those with mild cognitive impairment (MCI) derived from electroencephalography recordings. We have demonstrated that a cognitive task among MCI patients induced, compared to healthy controls, a significantly higher increment in global network integration with an increased number of vertices taking a more central role within the network from the pre- to post-task resting state. Such modified network organization may aid cognitive performance by increasing the flow of information through the most central vertices among MCI patients who seem to require more communication and recruitment across brain areas to maintain or improve task performance. This could indicate that MCI patients are engaged in compensatory activation, especially as both groups did not differ in their task performance. In addition, no significant group differences were observed in network topology during the pre-task resting state. Our findings thus emphasize that the task aftereffect model is relevant for enhancing the identification of network topology abnormalities related to cognitive decline, and also for improving our understanding of inherent differences in brain network organization for MCI patients, and could therefore represent a valid marker of cortical capacity and/or cortical health.

Purpose: The paper aims to identify and analyze key factors determining network organizations' success, assuming that there is common cooperation on the information platform created by network organizations. The aim is also to identify and analyze basic barriers of establishing such cooperation. Design/Methodology/Approach: The research includes the statistical analysis of information flows efficiency in network organizations. The presented analysis has been conducted using the selected statistical testing methods. Findings: The obtained research findings confirm Polish companies' understanding of the importance of information in their functioning. The obtained results indicate that enterprises treat the network data flow as an element that only improves their offer. Practical Implications: Activities aimed at information cooperation with the environment, including network structures, are not optimal. Only a full transition to functioning in the information space allows us to achieve a maximum of positive effects. Originality/value: The presented approach not only applies to companies that have direct contact with the customer; it can be applied in every sector of economic activity by any organization operating under conditions of uncertainty and dynamic change.

Accurate and readily available information is a crucial basis for decision making, problem solving, or performing knowledge intensive work. Routine activities and well-defined work flows are supported by sophisticated solutions, like enterprise information systems or production planning systems. But for deviations from daily routine, ad-hoc processes, work in distributed teams with changing members or seemingly unstructured innovation activities, quickly finding the right information for a given purpose often is a challenge. Recent studies show that users spend a lot of time in searching for the right information, which causes unnecessary delays and costs. In networked organizations with geographically distributed work force and processes, this challenge is even more substantial due to dynamically changing project teams or shortcomings in systems interoperability. Research in information logistics addresses these challenges with an aim to improve information flow, i.e. applying logistic principles to information supply. Starting from industrial needs, this paper discusses challenges, selected concepts and solutions for demand-oriented information supply. Relevant research fields contributing to this area are context modeling, ontology engineering, semantic matching and information retrieval.

Functional consequences of acute tryptophan depletion on raphe nuclei connectivity and network organization in healthy women

The child brain is a small-world network, which is hypothesized to change toward more ordered configurations with development. In graph theoretical studies, comparing network topologies under different conditions remains a critical point. Constructing a minimum spanning tree (MST) might present a solution, since it does not require setting a threshold and uses a fixed number of nodes and edges. In this study, the MST method is introduced to examine developmental changes in functional brain network topology in young children. Resting-state electroencephalography was recorded from 227 children twice at 5 and 7 years of age. Synchronization likelihood (SL) weighted matrices were calculated in three different frequency bands from which MSTs were constructed, which represent constructs of the most important routes for information flow in a network. From these trees, several parameters were calculated to characterize developmental change in network organization. The MST diameter and eccentricity significantly increased, while the leaf number and hierarchy significantly decreased in the alpha band with development. Boys showed significant higher leaf number, betweenness, degree and hierarchy and significant lower SL, diameter, and eccentricity than girls in the theta band. The developmental changes indicate a shift toward more decentralized line-like trees, which supports the previously hypothesized increase toward regularity of brain networks with development. Additionally, girls showed more line-like decentralized configurations, which is consistent with the view that girls are ahead of boys in brain development. MST provides an elegant method sensitive to capture subtle developmental changes in network organization without the bias of network comparison.

Policy, project and operational networks: Channels and conduits for learning in forest biodiversity conservation

This paper presents the research results about the social network NGO Group for CRC which is an articulation of non governmental organizations related to children's rights. This paper analyzes the information flow inside the network, among its members and among the network organizations. The Convention on the Rights of the Child (CRC) was approved in 1989 by the General Assembly of the United Nations, being ratified in its totality by the countries members, with the exception of the United States of America. The investigated questions are: 1) How is the role of the information flow in the network structure? 2) How is the information flow configured to support the implementation monitoring process of the Convention on the Rights of the Child?

Recent imaging connectome studies demonstrated that the human functional brain network follows an efficient small-world topology with cohesive functional modules and highly connected hubs. However, the functional motif patterns that represent the underlying information flow remain largely unknown. Here, we investigated motif patterns within directed human functional brain networks, which were derived from resting-state functional magnetic resonance imaging data with controlled confounding hemodynamic latencies. We found several significantly recurring motifs within the network, including the two-node reciprocal motif and five classes of three-node motifs. These recurring motifs were distributed in distinct patterns to support intra- and inter-module functional connectivity, which also promoted integration and segregation in network organization. Moreover, the significant participation of several functional hubs in the recurring motifs exhibited their critical role in global integration. Collectively, our findings highlight the basic architecture governing brain network organization and provide insight into the information flow mechanism underlying intrinsic brain activities. Hum Brain Mapp 38:2734-2750, 2017. © 2017 Wiley Periodicals, Inc.

The topology of complex brain networks allows efficient dynamic interactions between spatially distinct regions. Neuroimaging studies have provided consistent evidence of dysfunctional connectivity among the cortical circuitry in Parkinson’s disease; however, little is known about the topological properties of brain networks underlying these alterations. This paper introduces a methodology to explore aberrant changes in hierarchical patterns of nodal centrality through cortical networks, combining graph theoretical analysis and morphometric connectivity. The edges in graph were estimated by correlation analysis and thresholding between 148 nodes defined by cortical regions. Our findings demonstrated that the networks organization was disrupted in the patients with PD. We found a reconfiguration in hierarchical weighting of high degree hubs in structural networks associated with levels of cognitive decline, probably related to a system-wide compensatory mechanism. Simulated targeted attack on the network’s nodes as measures of network resilience showed greater effects on information flow in advanced stages of disease.

This paper describes an Enterprise Social Analytics Dashboard (ESAD) to support human capital management, competence valorization, diversity management, and early detection of potential problems within large, networked organizations. The system can be used by managers for career promotion, team building, and diversity management, as well as by company’s social analysts, to monitor social behaviors and information flow in the workplace. Toward this end, we defined a measure of informal leadership which draws on organization theory and on a computational model based on multiplex networks. This model, along with a social network analysis toolkit developed in the context of the present study, enabled the systematic empirical analysis of social behaviors in a three-year dataset of message threads exchanged within a large multinational enterprise, as a function of gender, time, roles, and discussed topics. The results of our empirical analysis demonstrate the power of social analytics in organizations as a tool for human capital management, competence valorization, and early detection of potential problems. Our study clearly shows that Enterprise Social Networks are a favorable environment to highlight women’s leadership qualities and intermediary abilities. The ESAD offers innovative features, such as a sociologically motivated leadership model based on multiplex networks, text mining, and text classification techniques, to extract relevant discussion topics.

We previously demonstrated that patients with IDH1-WT compared to IDH1-M malignant astrocytoma exhibited worse cognitive function. We hypothesized that this is due to greater lesion momentum that may preclude compensatory brain reorganization. Therefore, in the present study, we examined the structural of patients with IDH1-M and -WT tumors to determine if brain network organization differed between these patient groups. Volumetric, T1 MRI scans were evaluated retrospectively from 15 IDH1-M and 15 IDH1-WT. There were no differences between groups in terms of age, sex or education. Groups did not differ in tumor laterality but IDH1-M demonstrated less incidence of glioblastoma (p = .025), more frequent temporal lobe tumor location (p = .036) and moderately larger tumor volumes (p = .10). Discrete cortical and subcortical gray matter volumes were extracted from the MRI for each subject and cross-correlated across subjects to create an association matrix for each group. Matrices were corrected for tumor volume and histology. Graph theory was applied to these matrices to construct a large-scale structural brain network, or connectome for each group. We then measured the global efficiency (Geff) for each group. Geff is a measure of network organization pertaining to integration and information flow. Nonparametric permutation analysis indicated that Geff was significantly lower in the IDH1-WT group (Geff = .41) compared to IDH1-M (Geff = .59, p = .001). IDH1-WT also demonstrated less network hubs than IDH1-M suggesting disconnection of critical brain regions. In summary, brain network integration, efficiency and connectivity are lower in IDH1-WT tumor compared to IDH1-M. This finding was independent of tumor volume and histology. This may reflect the slower growth of the IDH1-M tumor, which may allow the brain time to adapt to the tumor's presence and reorganize critical neurocircuitry.

This chapter focuses on the three forces highlighted in Figure 7-1. Information technology has the inherent characteristic of being able to shrink the effects of time and space and provide humans with information sup port. Thus, electronic tools such as workstations can leverage a human’s mind, shorten the time needed to accomplish tasks, and through networks speed up information flow. The time between an event and its consequences, such as placing an order or changing a design, is shorter than ever before.

Infants and adults have similar regional functional brain organization for the perception of emotions

Psychopathy is associated with shifts in the organization of neural networks in a large incarcerated male sample.