Counter-intuitive moral judgement following traumatic brain injury

Several neurological patient populations, including Traumatic Brain Injury (TBI), appear to produce an abnormally ‘utilitarian’ pattern of judgements to moral dilemmas; they tend to make judgements that maximise the welfare of the majority, rather than deontological judgements based on the following of moral rules (e.g., do not harm others). However, this patient research has always used extreme dilemmas with highly valued moral rules (e.g., do not kill). Data from healthy participants, however, suggests that when a wider range of dilemmas are employed, involving less valued moral rules (e.g., do not lie), moral judgements demonstrate sensitivity to the psychological intuitiveness of the judgements, rather than their deontological or utilitarian content (Kahane et al., 2011). We sought the moral judgements of 30 TBI participants and 30 controls on moral dilemmas where content (utilitarian/deontological) and intuition (intuitive/counterintuitive) were measured concurrently. Overall TBI participants made utilitarian judgements in equal proportions to controls; disproportionately favouring utilitarian judgements only when they were counterintuitive, and deontological judgements only when they were counterintuitive. These results speak against the view that TBI causes a specific utilitarian bias, suggesting instead that moral intuition is broadly disrupted following TBI

Eigenvector-Based Centrality Measures for Temporal Networks

Numerous centrality measures have been developed to quantify the importances of nodes in time-independent networks, and many of them can be expressed as the leading eigenvector of some matrix. With the increasing availability of network data that changes in time, it is important to extend such eigenvector-based centrality measures to time-dependent networks. In this paper, we introduce a principled generalization of network centrality measures that is valid for any eigenvector-based centrality. We consider a temporal network with N nodes as a sequence of T layers that describe the network during different time windows, and we couple centrality matrices for the layers into a supra-centrality matrix of size NTxNT whose dominant eigenvector gives the centrality of each node i at each time t. We refer to this eigenvector and its components as a joint centrality, as it reflects the importances of both the node i and the time layer t. We also introduce the concepts of marginal and conditional centralities, which facilitate the study of centrality trajectories over time. We find that the strength of coupling between layers is important for determining multiscale properties of centrality, such as localization phenomena and the time scale of centrality changes. In the strong-coupling regime, we derive expressions for time-averaged centralities, which are given by the zeroth-order terms of a singular perturbation expansion. We also study first-order terms to obtain first-order-mover scores, which concisely describe the magnitude of nodes' centrality changes over time. As examples, we apply our method to three empirical temporal networks: the United States Ph.D. exchange in mathematics, costarring relationships among top-billed actors during the Golden Age of Hollywood, and citations of decisions from the United States Supreme Court.Comment: 38 pages, 7 figures, and 5 table

Topological data analysis of contagion maps for examining spreading processes on networks

Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth's surface; however, in modern contagions long-range edges -- for example, due to airline transportation or communication media -- allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct "contagion maps" that use multiple contagions on a network to map the nodes as a point cloud. By analyzing the topology, geometry, and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modeling, forecast, and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.Comment: Main Text and Supplementary Informatio

Cognitive correlates of pragmatic language comprehension in adult traumatic brain injury: A systematic review and meta-analyses

Effective pragmatic comprehension of language is critical for successful communication and interaction, but this ability is routinely impaired following Traumatic Brain Injury (TBI) [1,2]. Individual studies have investigated the cognitive domains associated with impaired pragmatic comprehension, but there remains little understanding of the relative importance of these domains in contributing to pragmatic comprehension impairment following TBI. This paper presents a systematic meta-analytic review of the observed correlations between pragmatic comprehension and cognitive processes following TBI. Five meta-analyses were computed, which quantified the relationship between pragmatic comprehension and five key cognitive constructs (declarative memory; working memory; attention; executive functions; social cognition). Significant moderate-to-strong correlations were found between all cognitive measures and pragmatic comprehension, where declarative memory was the strongest correlate. Thus, our findings indicate that pragmatic comprehension in TBI is associated with an array of domain general cognitive processes, and as such deficits in these cognitive domains may underlie pragmatic comprehension difficulties following TBI. The clinical implications of these findings are discussed

Myocardial Dysfunction in an Animal Model of Cancer Cachexia

Aims Fatigue is a common occurrence in cancer patients regardless of tumor type or anti-tumor therapies and is an especially problematic symptom in persons with incurable tumor disease. In rodents, tumor-induced fatigue is associated with a progressive loss of skeletal muscle mass and increased expression of biomarkers of muscle protein degradation. The purpose of the present study was to determine if muscle wasting and expression of biomarkers of muscle protein degradation occur in the hearts of tumor-bearing mice, and if these effects of tumor growth are associated with changes in cardiac function. Main methods The colon26 adenocarcinoma cell line was implanted into female CD2F1 mice and skeletal muscle wasting, in vivo heart function, in vitro cardiomyocyte function, and biomarkers of muscle protein degradation were determined. Key findings Expression of biomarkers of protein degradation were increased in both the gastrocnemius and heart muscle of tumor-bearing mice and caused systolic dysfunction in vivo. Cardiomyocyte function was significantly depressed during both cellular contraction and relaxation. Significance These results suggest that heart muscle is directly affected by tumor growth, with myocardial function more severely compromised at the cellular level than what is observed using echocardiography

Time variability of Neptune's horizontal and vertical cloud structure revealed by VLT/SINFONI and Gemini/NIFS from 2009 to 2013

New observations of Neptune's clouds in the near infrared were acquired in October 2013 with SINFONI on ESO's Very Large Telescope (VLT) in Chile. SINFONI is an Integral Field Unit spectrometer returning a 64 × 64 pixel image with 2048 wavelengths. Image cubes in the J-band (1.09-1.41 μm) and H-band (1.43-1.87 μm) were obtained at spatial resolutions of 0.1″and 0.025″per pixel, while SINFONI's adaptive optics provided an effective resolution of approximately 0.1″. Image cubes were obtained at the start and end of three successive nights to monitor the temporal development of discrete clouds both at short timescales (i.e. during a single night) as well as over the longer period of the three-day observing run. These observations were compared with similar H-band observations obtained in September 2009 with the NIFS Integral Field Unit spectrometer on the Gemini-North telescope in Hawaii, previously reported by Irwin et al. (2011) [Icarus, 216, 141-158], and previously unreported Gemini/NIFS observations at lower spatial resolution made in 2011.We find both similarities and differences between these observations, spaced over four years. The same overall cloud structure is seen with high, bright clouds visible at mid-latitudes (30-40°N,S), with slightly lower clouds observed at lower latitudes, together with small discrete clouds seen circling the pole at a latitude of approximately 60°S. However, while discrete clouds were visible at this latitude at both the main cloud deck level (at 2-3 bar) and in the upper troposphere (100-500 mb) in 2009, no distinct deep (2-3 bar), discrete circumpolar clouds were visible in 2013, although some deep clouds were seen at the southern edge of the main cloud belt at 30-40°S, which have not been observed before. The nature of the deep sub-polar discrete clouds observed in 2009 is intriguing. While it is possible that in 2013 these deeper clouds were masked by faster moving, overlying features, we consider that it is unlikely that this should have happened in 2013, but not in 2009 when the upper-cloud activity was generally similar. Meanwhile, the deep clouds seen at the southern edge of the main cloud belt at 30-40°S in 2013, should also have been detectable in 2009, but were not seen. Hence, these observations may have detected a real temporal variation in the occurrence of Neptune's deep clouds, pointing to underlying variability in the convective activity at the pressure of the main cloud deck at 2-3 bar near Neptune's south pole and also in the main observable cloud belt at 30-40°S.</p

Simplified Multistep Outflow Method to Estimate Unsaturated Hydraulic Functions for Coarse-Textured Soils

Although the multistep outfl ow (MSO) method is well suited for the estimation of soil hydraulic properties by inverse solution techniques, this method has not been widely adopted because it requires advanced instrumentation and is time consuming. Th e objective of this study was to develop a modifi ed version of the multistep outfl ow technique that largely simplifi es laboratory procedures and reduces costs and time. Th e numerical inversion procedures require applying user-friendly HYDRUS soft ware to estimate fi tting parameters for soil water retention and unsaturated hydraulic conductivity curves. Whereas values of saturated water content and saturated hydraulic conductivity must be measured independently, the remaining functional parameters are estimated using an inverse solution of a transient drainage experiment using multiple suction steps and a hanging water column, with drainage outfl ows measured during drainage. A comparison test showed that the simplifi ed experiment without tensiometric measurements provided suffi cient information in the parameter identifi cation compared with a traditional pressure outfl ow experiment with tensiometric measurements for an Oso Flaco sand and a loamy sand fi eld soil in the suction range of 0 to 17 kPa