Neural mechanisms of context effects on face recognition: automatic binding and context shift decrements.

Although people do not normally try to remember associations between faces and physical contexts, these associations are established automatically, as indicated by the difficulty of recognizing familiar faces in different contexts ("butcher-on-the-bus" phenomenon). The present fMRI study investigated the automatic binding of faces and scenes. In the face-face (F-F) condition, faces were presented alone during both encoding and retrieval, whereas in the face/scene-face (FS-F) condition, they were presented overlaid on scenes during encoding but alone during retrieval (context change). Although participants were instructed to focus only on the faces during both encoding and retrieval, recognition performance was worse in the FS-F than in the F-F condition ("context shift decrement" [CSD]), confirming automatic face-scene binding during encoding. This binding was mediated by the hippocampus as indicated by greater subsequent memory effects (remembered > forgotten) in this region for the FS-F than the F-F condition. Scene memory was mediated by right parahippocampal cortex, which was reactivated during successful retrieval when the faces were associated with a scene during encoding (FS-F condition). Analyses using the CSD as a regressor yielded a clear hemispheric asymmetry in medial temporal lobe activity during encoding: Left hippocampal and parahippocampal activity was associated with a smaller CSD, indicating more flexible memory representations immune to context changes, whereas right hippocampal/rhinal activity was associated with a larger CSD, indicating less flexible representations sensitive to context change. Taken together, the results clarify the neural mechanisms of context effects on face recognition.

Shifting ranges and conservation challenges for lemurs in the face of climate change.

Geospatial modeling is one of the most powerful tools available to conservation biologists for estimating current species ranges of Earth's biodiversity. Now, with the advantage of predictive climate models, these methods can be deployed for understanding future impacts on threatened biota. Here, we employ predictive modeling under a conservative estimate of future climate change to examine impacts on the future abundance and geographic distributions of Malagasy lemurs. Using distribution data from the primary literature, we employed ensemble species distribution models and geospatial analyses to predict future changes in species distributions. Current species distribution models (SDMs) were created within the BIOMOD2 framework that capitalizes on ten widely used modeling techniques. Future and current SDMs were then subtracted from each other, and areas of contraction, expansion, and stability were calculated. Model overprediction is a common issue associated Malagasy taxa. Accordingly, we introduce novel methods for incorporating biological data on dispersal potential to better inform the selection of pseudo-absence points. This study predicts that 60% of the 57 species examined will experience a considerable range of reductions in the next seventy years entirely due to future climate change. Of these species, range sizes are predicted to decrease by an average of 59.6%. Nine lemur species (16%) are predicted to expand their ranges, and 13 species (22.8%) distribution sizes were predicted to be stable through time. Species ranges will experience severe shifts, typically contractions, and for the majority of lemur species, geographic distributions will be considerably altered. We identify three areas in dire need of protection, concluding that strategically managed forest corridors must be a key component of lemur and other biodiversity conservation strategies. This recommendation is all the more urgent given that the results presented here do not take into account patterns of ongoing habitat destruction relating to human activities.

A comparison of the effectiveness of the team-based learning readiness assessments completed at home to those completed in class.

PURPOSE: The readiness assurance process (RAP) of team-based learning (TBL) is an important element that ensures that students come prepared to learn. However, the RAP can use a significant amount of class time which could otherwise be used for application exercises. The authors administered the TBL-associated RAP in class or individual readiness assurance tests (iRATs) at home to compare medical student performance and learning preference for physiology content. METHODS: Using cross-over study design, the first year medical student TBL teams were divided into two groups. One group was administered iRATs and group readiness assurance tests (gRATs) consisting of physiology questions during scheduled class time. The other group was administered the same iRAT questions at home, and did not complete a gRAT. To compare effectiveness of the two administration methods, both groups completed the same 12-question physiology assessment during dedicated class time. Four weeks later, the entire process was repeated, with each group administered the RAP using the opposite method. RESULTS: The performance on the physiology assessment after at-home administration of the iRAT was equivalent to performance after traditional in-class administration of the RAP. In addition, a majority of students preferred the at-home method of administration and reported that the at-home method was more effective in helping them learn course content. CONCLUSION: The at-home administration of the iRAT proved effective. The at-home administration method is a promising alternative to conventional iRATs and gRATs with the goal of preserving valuable in-class time for TBL application exercises.

CT Scan Dosimetric Parameters Routine Monitoring: First Results of Radiation Dose Optimization Strategies Promptly Provided by a Multidisciplinary Team

CONCLUSION Radiation dose reduction, while saving image quality could be easily implemented with this approach. Furthermore, the availability of a dosimetric data archive provides immediate feedbacks, related to the implemented optimization strategies. Background JCI Standards and European Legislation (EURATOM 59/2013) require the implementation of patient radiation protection programs in diagnostic radiology. Aim of this study is to demonstrate the possibility to reduce patients radiation exposure without decreasing image quality, through a multidisciplinary team (MT), which analyzes dosimetric data of diagnostic examinations. Evaluation Data from CT examinations performed with two different scanners (Siemens DefinitionTM and GE LightSpeed UltraTM) between November and December 2013 are considered. CT scanners are configured to automatically send images to DoseWatch© software, which is able to store output parameters (e.g. kVp, mAs, pitch ) and exposure data (e.g. CTDIvol, DLP, SSDE). Data are analyzed and discussed by a MT composed by Medical Physicists and Radiologists, to identify protocols which show critical dosimetric values, then suggest possible improvement actions to be implemented. Furthermore, the large amount of data available allows to monitor diagnostic protocols currently in use and to identify different statistic populations for each of them. Discussion We identified critical values of average CTDIvol for head and facial bones examinations (respectively 61.8 mGy, 151 scans; 61.6 mGy, 72 scans), performed with the GE LightSpeed CTTM. Statistic analysis allowed us to identify the presence of two different populations for head scan, one of which was only 10% of the total number of scans and corresponded to lower exposure values. The MT adopted this protocol as standard. Moreover, the constant output parameters monitoring allowed us to identify unusual values in facial bones exams, due to changes during maintenance service, which the team promptly suggested to correct. This resulted in a substantial dose saving in CTDIvol average values of approximately 15% and 50% for head and facial bones exams, respectively. Diagnostic image quality was deemed suitable for clinical use by radiologists.