Acting on social exclusion: neural correlates of punishment and forgiveness of excluders

This functional magnetic resonance imaging study examined the neural correlates of punishment and forgiveness of initiators of social exclusion (i.e. ‘excluders’). Participants divided money in a modified Dictator Game between themselves and people who previously either included or excluded them during a virtual ball-tossing game (Cyberball). Participants selectively punished the excluders by decreasing their outcomes; even when this required participants to give up monetary rewards. Punishment of excluders was associated with increased activation in the pre-supplementary motor area (pre-SMA) and bilateral anterior insula. Costly punishment was accompanied by higher activity in the pre-SMA compared with punishment that resulted in gains or was non-costly. Refraining from punishment (i.e. forgiveness) was associated with self-reported perspective-taking and increased activation in the bilateral temporoparietal junction, dorsomedial prefrontal cortex, dorsal anterior cingulate cortex, and ventrolateral and dorsolateral prefrontal cortex. These findings show that social exclusion can result in punishment as well as forgiveness of excluders and that separable neural networks implicated in social cognition and cognitive control are recruited when people choose either to punish or to forgive those who excluded them.Pathways through Adolescenc

Longitudinal links between childhood peer acceptance and the neural correlates of sharing

Pathways through Adolescenc

Longitudinal links between childhood peer acceptance and the neural correlates of sharing

Pathways through Adolescenc

Consensus parameter: research methodologies to evaluate neurodevelopmental effects of pubertal suppression in transgender youth

An international interdisciplinary team of experts achieved consensus around primary methods and domains for assessing neurodevelopmental effects (i.e., benefits and/or difficulties) of pubertal suppression treatment in transgender youth.Pathways through Adolescenc

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Behavioral and neural reactions to emotions of others in the distribution of resources

Neuro Imaging Researc

Penssynchronisatie: toetsing in voerderproeven = Synchronization of rumen fermentation: testing in feeding experiments

Een penssynchronisatiesysteem heeft als doel energie en stikstof gelijktijdig en in de juiste verhouding beschikbaar te laten komen voor de micro-organismen in de pens. Penssynchronisatie blijkt in vivo minder belangrijk dan theoretisch wordt aangenomen. Met het verschijnen van dit rapport en de overige publicaties uit het project “Penssynchronisatie”, hopen de betrokken organisaties een bijdrage te leveren aan een efficiëntere nutriëntenbenutting op Nederlandse melkveebedrijven, met name een efficiënt gebruik van stiksto

The ATLAS Readout System for LHC Runs 2 and 3

The ReadOut System (ROS) is a central part of the dataacquisition (DAQ) system of the ATLAS Experiment at the CERN LargeHadron Collider (LHC). The system is responsible for receiving andbuffering event data from all detector subsystems and serving theseto the High Level Trigger (HLT) system via a 10 GbE network,discarding or transporting data onward once the trigger hascompleted its selection process. The ATLAS ROS was completelyreplaced during the 2013–2014 experimental shutdown in order tomeet the demanding conditions expected during LHC Run 2 and Run 3(2015–2025). The ROS consists of roughly one hundred Linux-based2U-high rack-mounted servers equipped with PCIe I/O cards and10 GbE interfaces. This paper documents the system requirementsfor LHC Runs 2 and 3 and the design choices taken to meet them. Theresults of performance measurements and the re-use of ROS technologyfor the development of data sources, test platforms for othersystems, and another ATLAS DAQ system component, namely the Regionof Interest Builder (RoIB), are also discussed. Finally performanceresults for Run 2 operations are presented before looking at theupgrade for Run 3.The ReadOut System (ROS) is a central part of the data acquisition (DAQ) system of the ATLAS Experiment at the CERN Large Hadron Collider (LHC). The system is responsible for receiving and buffering event data from all detector subsystems and serving these to the High Level Trigger (HLT) system via a 10 GbE network, discarding or transporting data onward once the trigger has completed its selection process. The ATLAS ROS was completely replaced during the 2013-2014 experimental shutdown in order to meet the demanding conditions expected during LHC Run 2 and Run 3 (2015-2025). The ROS consists of roughly one hundred Linux-based 2U-high rack-mounted servers equipped with PCIe I/O cards and 10 GbE interfaces. This paper documents the system requirements for LHC Runs 2 and 3 and the design choices taken to meet them. The results of performance measurements and the re-use of ROS technology for the development of data sources, test platforms for other systems, and another ATLAS DAQ system component, namely the Region of Interest Builder (RoIB), are also discussed. Finally performance results for Run 2 operations are presented before looking at the upgrade for Run 3