Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis

Pattern recognition methods have become increasingly popular in fMRI data analysis, which are powerful in discriminating between multi-voxel patterns of brain activities associated with different mental states. However, when they are used in functional brain mapping, the location of discriminative voxels varies significantly, raising difficulties in interpreting the locus of the effect. Here we proposed a hierarchical framework of multivariate approach that maps informative clusters rather than voxels to achieve reliable functional brain mapping without compromising the discriminative power. In particular, we first searched for local homogeneous clusters that consisted of voxels with similar response profiles. Then, a multi-voxel classifier was built for each cluster to extract discriminative information from the multi-voxel patterns. Finally, through multivariate ranking, outputs from the classifiers were served as a multi-cluster pattern to identify informative clusters by examining interactions among clusters. Results from both simulated and real fMRI data demonstrated that this hierarchical approach showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods. In addition, the mapped clusters were highly overlapped for two perceptually equivalent object categories, further confirming the validity of our approach. In short, the hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies

Does time of surgery influence the rate of false-negative appendectomies?:A retrospective observational study of 274 patients

Background Multiple disciplines have described an “after-hours effect” relating to worsened mortality and morbidity outside regular working hours. This retrospective observational study aimed to evaluate whether diagnostic accuracy of a common surgical condition worsened after regular hours. Methods Electronic operative records for all non-infant patients (age > 4 years) operated on at a single centre for presumed acute appendicitis were retrospectively reviewed over a 56-month period (06/17/2012–02/01/2017). The primary outcome measure of unknown diagnosis was compared between those performed in regular hours (08:00–17:00) or off hours (17:01–07:59). Pre-clinical biochemistry and pre-morbid status were recorded to determine case heterogeneity between the two groups, along with secondary outcomes of length of stay and complication rate. Results Out of 289 procedures, 274 cases were deemed eligible for inclusion. Of the 133 performed in regular hours, 79% were appendicitis, compared to 74% of the 141 procedures performed off hours. The percentage of patients with an unknown diagnosis was 6% in regular hours compared to 15% off hours (RR 2.48; 95% CI 1.14–5.39). This was accompanied by increased numbers of registrars (residents in training) leading procedures off hours (37% compared to 24% in regular hours). Pre-morbid status, biochemistry, length of stay and post-operative complication rate showed no significant difference. Conclusions This retrospective study suggests that the rate of unknown diagnoses for acute appendicitis increases overnight, potentially reflecting increased numbers of unnecessary procedures being performed off hours due to poorer diagnostic accuracy. Reduced levels of staffing, availability of diagnostic modalities and changes to workforce training may explain this, but further prospective work is required. Potential solutions may include protocolizing the management of common acute surgical conditions and making more use of non-resident on call senior colleagues

Global lake responses to climate change

Climate change is one of the most severe threats to global lake ecosystems. Lake surface conditions, such as ice cover, surface temperature, evaporation and water level, respond dramatically to this threat, as observed in recent decades. In this Review, we discuss physical lake variables and their responses to climate change. Decreases in winter ice cover and increases in lake surface temperature modify lake mixing regimes and accelerate lake evaporation. Where not balanced by increased mean precipitation or inflow, higher evaporation rates will favour a decrease in lake level and surface water extent. Together with increases in extreme-precipitation events, these lake responses will impact lake ecosystems, changing water quantity and quality, food provisioning, recreational opportunities and transportation. Future research opportunities, including enhanced observation of lake variables from space (particularly for small water bodies), improved in situ lake monitoring and the development of advanced modelling techniques to predict lake processes, will improve our global understanding of lake responses to a changing climate