Shapley Ratings in Brain Networks

Recent applications of network theory to brain networks as well as the expanding empirical databases of brain architecture spawn an interest in novel techniques for analyzing connectivity patterns in the brain. Treating individual brain structures as nodes in a directed graph model permits the application of graph theoretical concepts to the analysis of these structures within their large-scale connectivity networks. In this paper, we explore the application of concepts from graph and game theory toward this end. Specifically, we utilize the Shapley value principle, which assigns a rank to players in a coalition based upon their individual contributions to the collective profit of that coalition, to assess the contributions of individual brain structures to the graph derived from the global connectivity network. We report Shapley values for variations of a prefrontal network, as well as for a visual cortical network, which had both been extensively investigated previously. This analysis highlights particular nodes as strong or weak contributors to global connectivity. To understand the nature of their contribution, we compare the Shapley values obtained from these networks and appropriate controls to other previously described nodal measures of structural connectivity. We find a strong correlation between Shapley values and both betweenness centrality and connection density. Moreover, a stepwise multiple linear regression analysis indicates that approximately 79% of the variance in Shapley values obtained from random networks can be explained by betweenness centrality alone. Finally, we investigate the effects of local lesions on the Shapley ratings, showing that the present networks have an immense structural resistance to degradation. We discuss our results highlighting the use of such measures for characterizing the organization and functional role of brain networks

Perspectives of wild medicine harvesters from Cape Town, South Africa

Cape Town is a fast-growing cityscape in the Cape Floristic Region in South Africa with 24 formally protected conservation areas including the World Heritage Table Mountain National Park. These sites have been protected and managed as critical sites for local biodiversity, representing potentially one-third of all Cape Floristic Region flora species and 18% of South Africa’s plant diversity. Cape Town is also inhabited by a rapidly growing culturally and economically diverse citizenry with distinct and potentially conflicting perspectives on access to, and management of, local natural resources. In a qualitative study of 58 locally resident traditional healers of distinct cultural groups, we examined motivations underlying the generally illicit activity of harvesting of wild resources from Cape Town protected areas. Resource harvester motivations primarily link to local economic survival, health care and cultural links to particular resources and practices, ‘access for all’ outlooks, and wholesale profit-seeking perspectives. We describe these motivations, contrast them with the current formal, legal and institutional perspectives for biodiversity protection in the city, and propose managerial interventions that may improve sustainability of ongoing harvest activities

Criteria for Optimizing Cortical Hierarchies with Continuous Ranges

In a recent paper (Reid et al., 2009) we introduced a method to calculate optimal hierarchies in the visual network that utilizes continuous, rather than discrete, hierarchical levels, and permits a range of acceptable values rather than attempting to fit fixed hierarchical distances. There, to obtain a hierarchy, the sum of deviations from the constraints that define the hierarchy was minimized using linear optimization. In the short time since publication of that paper we noticed that many colleagues misinterpreted the meaning of the term “optimal hierarchy”. In particular, a majority of them were under the impression that there was perhaps only one optimal hierarchy, but a substantial difficulty in finding that one. However, there is not only more than one optimal hierarchy but also more than one option for defining optimality. Continuing the line of this work we look at additional options for optimizing the visual hierarchy: minimizing the number of violated constraints and minimizing the maximal size of a constraint violation using linear optimization and mixed integer programming. The implementation of both optimization criteria is explained in detail. In addition, using constraint sets based on the data from Felleman and Van Essen (1991), optimal hierarchies for the visual network are calculated for both optimization methods

Atoms-to-Circuits Simulation Investigation of CNT Interconnects for Next Generation CMOS Technology

In this study, we suggest a hierarchical model to investigate the electrical performance of carbon nanotube (CNT)- based interconnects. From the density functional theory, we have obtained important physical parameters, which are used in TCAD simulators to obtain the RC netlists. We then use these RC netlists for the circuit-level simulations to optimize interconnect design in VLSI. Also, we have compared various CNT-based interconnects such as single-walled CNTs, multi-walled CNTs, doped CNTs, and Cu-CNT composites in terms of conductivity, ring oscillator delay, and propagation time delay

Interactions between urban water policy, residential irrigation, and plant & bird diversity in the Fresno-Clovis Metro Area

*Background/Question/Methods:*

Ecological theory has begun to incorporate humans as part of coupled socio-ecological systems. Modern urban development provides an excellent laboratory to examine the interplay among socio-ecological relationships. Urban land and water management decisions result from dynamic interactions between institutional, individual and ecological factors. Landscaping and irrigation at any particular residence, for example, is a product of geography, hydrology, soil, and other local environmental conditions, the homeowners’ cultural preferences, socioeconomic status, identity construction, neighborhood dynamics, as well as zoning laws, market conditions, city policies, and county/state/federal government regulations. Since land and water management are key determinants of habitat for other species, urban biodiversity is strongly driven by the outcome of interactions between these variables. This study addresses the significance of water as a key variable in the Fresno-Clovis Metropolitan Area (FCMA), shaping current patterns of landscape and water use, at a time when the city of Fresno is installing meters as a regulatory tool to conserve water. We combine data from a citizen science bird monitoring project, field surveys of trees, and mail surveys of residents to address interactions among key components of the urban socioecological system.

*Results/Conclusions:*

We present results of multivariate analyses of bird and tree surveys to show that neighborhood income and irrigation levels interact to influence species diversity of both taxa. Data from the Fresno Bird Count found that bird species richness and functional group diversity are both strongly correlated with residential irrigation and neighborhood income levels. Tree species diversity shows a similar pattern. We examine these results to test and develop several theoretical models explaining outdoor water use behaviors, with the aim of assessing the resilience of such behaviors with the introduction of water metering in Fresno, and the resilience of urban plant and bird communities to resulting changes in water use in the landscape. We argue that socioeconomic status results from a complex interplay of cultural, economic, structural, and social-psychological factors, influencing institutional policies regarding the governance of water resources, and in turn impacts biodiversity within the urban landscape through spatial and temporal variations in water usage. This study is part of a long-term research project that examines the impacts of human water usage and water use policies on biodiversity within an urban environment

Evaluating the Outcomes of the Menthol Cigarette Ban in England by Comparing Menthol Cigarette Smoking Among Youth in England, Canada, and the US, 2018-2020

Importance: Menthol cigarettes were prohibited in England in May 2020 and nationally in Canada in October 2017 but remain permitted in the US. Evidence on the outcomes of menthol cigarette bans among youth outside of Canada, and the characteristics of youth smokers, is lacking. Objectives: To evaluate the outcomes of menthol cigarette bans on youth menthol cigarette smoking and to characterize youth menthol cigarette smokers in terms of demographics and cigarette consumption and dependence. Design, Setting, and Participants: This survey study uses data from online repeat cross-sectional International Tobacco Control Youth Tobacco and Vaping Surveys conducted in 2018, 2019, February 2020, and August 2020. Participants included past 30-day smokers aged 16 to 19 years. Data analysis was performed from March 2021 to January 2022. Main Outcomes and Measures: Usually smoke a brand of cigarettes that was menthol, including capsule. Exposures: Menthol cigarette ban, comparing 3 countries over time: Canada, where a ban already existed, England, where a ban was implemented during the study, and the US, where no national ban was present. Age, sex, race, and consumption and dependence were also examined by menthol smoking in each country, and in England before vs after the ban. Results: The analytical sample comprised 7067 participants aged 16 to 19 years, of whom 4129 were female and 5019 were White. In England, the weighted percentage of youth smokers who reported smoking a menthol or capsule cigarette brand was stable in the 3 survey waves before the menthol ban (2018 to February 2020, 9.4% vs 12.1%; adjusted odds ratio [AOR], 1.03; 95% CI, 0.99-1.06; P = .15) but decreased to 3.0% after the ban (February 2020 vs August 2020, AOR, 1.07; 95% CI, 1.04-1.10; P 5 vs 1, AOR, 1.10; 95% CI, 1.03-1.18; P = .007), or had urges to smoke every or most days (AOR, 1.08; 95% CI, 1.02-1.14; P = .006); and among smokers in Canada who perceived themselves as addicted to cigarettes (AOR, 1.02; 95% CI, 1.00-1.03; P = .01). Conclusions and Relevance: In this survey study, the proportion of youth smokers who smoke menthol (including capsule) cigarettes decreased substantially after the menthol ban in England. This association was consistent across all demographic groups. Perceived addiction among menthol smokers was also lower where menthol cigarettes were banned

Advancing functional connectivity research from association to causation

Cognition and behavior emerge from brain network interactions, such that investigating causal interactions should be central to the study of brain function. Approaches that characterize statistical associations among neural time series-functional connectivity (FC) methods-are likely a good starting point for estimating brain network interactions. Yet only a subset of FC methods ('effective connectivity') is explicitly designed to infer causal interactions from statistical associations. Here we incorporate best practices from diverse areas of FC research to illustrate how FC methods can be refined to improve inferences about neural mechanisms, with properties of causal neural interactions as a common ontology to facilitate cumulative progress across FC approaches. We further demonstrate how the most common FC measures (correlation and coherence) reduce the set of likely causal models, facilitating causal inferences despite major limitations. Alternative FC measures are suggested to immediately start improving causal inferences beyond these common FC measures

Tract-specific statistics based on diffusion-weighted probabilistic tractography

Diffusion-weighted neuroimaging approaches provide rich evidence with which to estimate the structural integrity of white matter in vivo, but typically do not provide a direct assessment of white matter integrity for connections between two specific regions of the brain. Here, we present a method for deriving tract-specific diffusion statistics, based upon arbitrarily-defined regions of interest. Our approach makes use of an empirically-derived population distribution based on probabilistic tractography, using the Nathan Kline Institute (NKI) Enhanced Rockland sample. We use a heuristic method to determine the most likely geometry of a path between two regions and express this as a spatial distribution. We then estimate the average orientation of streamlines traversing this path, at discrete distances along its trajectory, and compute the fraction of diffusion directed along this orientation for each participant. This allows us to obtain participant-wise metrics along the specific tract (tract-specific anisotropy; TSA), which can then be used to perform statistical analysis on any comparable population. Based on this method, we report both negative and positive associations between age and TSA for two networks derived from published meta-analytic studies (the "default mode" and "what-where" networks), along with more moderate sex differences and age-by-sex interactions in both networks