Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans

Reward learning depends on accurate reward associations with potential choices. These associations can be attained with reinforcement learning mechanisms using a reward prediction error (RPE) signal (the difference between actual and expected rewards) for updating future reward expectations. Despite an extensive body of literature on the influence of RPE on learning, little has been done to investigate the potentially separate contributions of RPE valence (positive or negative) and surprise (absolute degree of deviation from expectations). Here, we coupled single-trial electroencephalography with simultaneously acquired fMRI, during a probabilistic reversal-learning task, to offer evidence of temporally overlapping but largely distinct spatial representations of RPE valence and surprise. Electrophysiological variability in RPE valence correlated with activity in regions of the human reward network promoting approach or avoidance learning. Electrophysiological variability in RPE surprise correlated primarily with activity in regions of the human attentional network controlling the speed of learning. Crucially, despite the largely separate spatial extend of these representations our EEG-informed fMRI approach uniquely revealed a linear superposition of the two RPE components in a smaller network encompassing visuo mnemonic and reward areas. Activity in this network was further predictive of stimulus value updating indicating a comparable contribution of both signals to reward learning

Pupil-linked Phasic Arousal Predicts a Reduction of Choice Bias Across Species and Decision Domains

Decisions are often made by accumulating ambiguous evidence over time. The brain's arousal systems are activated during such decisions. In previous work in humans, we found that evoked responses of arousal systems during decisions are reported by rapid dilations of the pupil and track a suppression of biases in the accumulation of decision-relevant evidence (de Gee et al., 2017). Here, we show that this arousal-related suppression in decision bias acts on both conservative and liberal biases, and generalizes from humans to mice, and from perceptual to memory-based decisions. In challenging sound-detection tasks, the impact of spontaneous or experimentally induced choice biases was reduced under high phasic arousal. Similar bias suppression occurred when evidence was drawn from memory. All of these behavioral effects were explained by reduced evidence accumulation biases. Our results point to a general principle of interplay between phasic arousal and decision-making

Decoding solar wind–magnetosphere coupling

We employ a new NARMAX (Nonlinear Auto-Regressive Moving Average with eXogenous inputs) code to disentangle the time-varying relationship between the solar wind and SYM-H. The NARMAX method has previously been used to formulate a Dst model, using a preselected solar wind coupling function. In this work, which uses the higher-resolution SYM-H in place of Dst, we are able to reveal the individual components of different solar wind-magnetosphere interaction processes as they contribute to the geomagnetic disturbance. This is achieved with a graphics processing unit (GPU)-based NARMAX code that is around 10 orders of magnitude faster than previous efforts from 2005, before general-purpose programming on GPUs was possible. The algorithm includes a composite cost function, to minimize overfitting, and iterative reorthogonalization, which reduces computational errors in the most critical calculations by a factor of ∼106. The results show that negative deviations in SYM-H following a southward interplanetary magnetic field (IMF) are first a measure of the increased magnetic flux in the geomagnetic tail, observed with a delay of 20–30 min from the time the solar wind hits the bow shock. Terms with longer delays are found which represent the dipolarization of the magnetotail, the injections of particles into the ring current, and their subsequent loss by flowout through the dayside magnetopause. Our results indicate that the contribution of magnetopause currents to the storm time indices increase with solar wind electric field, E = v × B. This is in agreement with previous studies that have shown that the magnetopause is closer to the Earth when the IMF is in the tangential direction

Multivariate hierarchical analysis of car crashes data considering a spatial network lattice

Road traffic casualties represent a hidden global epidemic, demanding evidence-based interventions. This paper demonstrates a network lattice approach for identifying road segments of particular concern, based on a case study of a major city (Leeds, UK), in which 5,862 crashes of different severities were recorded over an eight-year period (2011-2018). We consider a family of Bayesian hierarchical models that include spatially structured and unstructured random effects, to capture the dependencies between the severity levels. Results highlight roads that are more prone to collisions, relative to estimated traffic volumes, in the northwest and south of city-centre. We analyse the Modifiable Areal Unit Problem (MAUP), proposing a novel procedure to investigate the presence of MAUP on a network lattice. We conclude that our methods enable a reliable estimation of road safety levels to help identify "hotspots" on the road network and to inform effective local interventions.Comment: 23 pages, 5 tables, 8 figure

PHYSTAT-LHC Workshop on Statistical Issues for LHC Physics

A PHYSTAT workshop on the topic of Statistical issues for LHC physics was held at CERN. The workshop focused on issues related to discovery that we hope will be relevant to the LHC. These proceedings contain written versions of nearly all the talks, several of which were given by professional statisticians. The talks varied from general overviews, to those describing searches for specific particles. The treatment of background uncertainties figured prominently. Many of the talks describing search strategies for new effects should be of interest not only to particle physicists but also to scientists in other fields

Chapter 12: Human Microbiome Analysis

Humans are essentially sterile during gestation, but during and after birth, every body surface, including the skin, mouth, and gut, becomes host to an enormous variety of microbes, bacterial, archaeal, fungal, and viral. Under normal circumstances, these microbes help us to digest our food and to maintain our immune systems, but dysfunction of the human microbiota has been linked to conditions ranging from inflammatory bowel disease to antibiotic-resistant infections. Modern high-throughput sequencing and bioinformatic tools provide a powerful means of understanding the contribution of the human microbiome to health and its potential as a target for therapeutic interventions. This chapter will first discuss the historical origins of microbiome studies and methods for determining the ecological diversity of a microbial community. Next, it will introduce shotgun sequencing technologies such as metagenomics and metatranscriptomics, the computational challenges and methods associated with these data, and how they enable microbiome analysis. Finally, it will conclude with examples of the functional genomics of the human microbiome and its influences upon health and disease

Practical Statistics for the LHC

This document is a pedagogical introduction to statistics for particle physics. Emphasis is placed on the terminology, concepts, and methods being used at the Large Hadron Collider. The document addresses both the statistical tests applied to a model of the data and the modeling itself.Comment: presented at the 2011 European School of High-Energy Physics, Cheile Gradistei, Romania, 7-20 September 2011 I expect to release updated versions of this document in the futur

Analysis of differences and commonalities in wildlife hunting across the Africa-Europe South-North gradient

Hunting and its impacts on wildlife are typically studied regionally, with a particular focus on the Global South. Hunting can, however, also undermine rewilding efforts or threaten wildlife in the Global North. Little is known about how hunting manifests under varying socioeconomic and ecological contexts across the Global South and North. Herein, we examined differences and commonalities in hunting characteristics across an exemplary Global South-North gradient approximated by the Human Development Index (HDI) using face-to-face interviews with 114 protected area (PA) managers in 25 African and European countries. Generally, we observed that hunting ranges from the illegal, economically motivated, and unsustainable hunting of herbivores in the South to the legal, socially and ecologically motivated hunting of ungulates within parks and the illegal hunting of mainly predators outside parks in the North. Commonalities across this Africa-Europe South-North gradient included increased conflict-related killings in human-dominated landscapes and decreased illegal hunting with beneficial community conditions, such as mutual trust resulting from community involvement in PA management. Nevertheless, local conditions cannot outweigh the strong effect of the HDI on unsustainable hunting. Our findings highlight regional challenges that require collaborative, integrative efforts in wildlife conservation across actors, while identified commonalities may outline universal mechanisms for achieving this goal.publishedVersio