Pycortex: an interactive surface visualizer for fMRI.

Surface visualizations of fMRI provide a comprehensive view of cortical activity. However, surface visualizations are difficult to generate and most common visualization techniques rely on unnecessary interpolation which limits the fidelity of the resulting maps. Furthermore, it is difficult to understand the relationship between flattened cortical surfaces and the underlying 3D anatomy using tools available currently. To address these problems we have developed pycortex, a Python toolbox for interactive surface mapping and visualization. Pycortex exploits the power of modern graphics cards to sample volumetric data on a per-pixel basis, allowing dense and accurate mapping of the voxel grid across the surface. Anatomical and functional information can be projected onto the cortical surface. The surface can be inflated and flattened interactively, aiding interpretation of the correspondence between the anatomical surface and the flattened cortical sheet. The output of pycortex can be viewed using WebGL, a technology compatible with modern web browsers. This allows complex fMRI surface maps to be distributed broadly online without requiring installation of complex software

PrAGMATiC: a Probabilistic and Generative Model of Areas Tiling the Cortex

Much of the human cortex seems to be organized into topographic cortical maps. Yet few quantitative methods exist for characterizing these maps. To address this issue we developed a modeling framework that can reveal group-level cortical maps based on neuroimaging data. PrAGMATiC, a probabilistic and generative model of areas tiling the cortex, is a hierarchical Bayesian generative model of cortical maps. This model assumes that the cortical map in each individual subject is a sample from a single underlying probability distribution. Learning the parameters of this distribution reveals the properties of a cortical map that are common across a group of subjects while avoiding the potentially lossy step of co-registering each subject into a group anatomical space. In this report we give a mathematical description of PrAGMATiC, describe approximations that make it practical to use, show preliminary results from its application to a real dataset, and describe a number of possible future extensions

Humans and language models diverge when predicting repeating text

Language models that are trained on the next-word prediction task have been shown to accurately model human behavior in word prediction and reading speed. In contrast with these findings, we present a scenario in which the performance of humans and LMs diverges. We collected a dataset of human next-word predictions for five stimuli that are formed by repeating spans of text. Human and GPT-2 LM predictions are strongly aligned in the first presentation of a text span, but their performance quickly diverges when memory (or in-context learning) begins to play a role. We traced the cause of this divergence to specific attention heads in a middle layer. Adding a power-law recency bias to these attention heads yielded a model that performs much more similarly to humans. We hope that this scenario will spur future work in bringing LMs closer to human behavior.Comment: To appear in the 26th Conference on Computational Natural Language Learning (CoNLL 2023). Code and data are available at https://github.com/HuthLab/lm-repeating-tex

Visual Motion Area MT+/V5 Responds to Auditory Motion in Human Sight-Recovery Subjects

Using functional magnetic resonance imaging, we found that cortical visual motion area MT+/V5 responded to auditory motion in two rare subjects who had been blind since early childhood and whose vision was partially recovered in adulthood. Visually normal control subjects did not show similar auditory responses. These auditory responses in MT+ were specific to motion compared with other complex auditory stimuli including frequency sweeps and speech. Thus, MT+ developed motion-specific responses to nonvisual input, suggesting that cross-modal plasticity can be influenced by the normal functional specialization of a cortical region. Regarding sight recovery after early blindness, our results further demonstate that cross-modal responses coexist with regained visual responses within the visual cortex

Treatment course and outcomes following drug and alcohol-related traumatic injuries

Both authors are with the NeuroTexas Institute at St. David's HealthCare, St. David's Medical Center, 1015 East 32nd Street, Suite 404, Austin, Texas 78705, USA -- Matthew C. Cowperthwaite is with the Center for Systems and Synthetic Biology, The University of Texas at Austin, 1 University Station, A4800, Austin, Texas 78712, USABackground: Alcohol and drug use is known to be a major factor affecting the incidence of traumatic injury. However, the ways in which immediate pre-injury substance use affects patients' clinical care and outcomes remains unclear. The goal of the present study is to determine the associations between pre-injury use of alcohol or drugs and patient injury severity, hospital course, and clinical outcome. Materials and methods: This study used more than 200,000 records from the National Trauma Data Bank (NTDB), which is the largest trauma registry in the United States. Incidents in the NTDB were placed into one of four classes: alcohol related, drug related, alcohol-and-drug related, and substance negative. Logistic regression models were used to determine comorbid conditions or treatment complications that were significantly associated with pre-injury substance use. Hospital charges were associated with the presence or absence of drugs and alcohol, and patient outcomes were assessed using discharge disposition as delimited by the NTDB. Results: The rates of complications arising during treatment were 8.3, 10.9, 9.9 and 8.6 per one hundred incidents in the alcohol related, drug related, alcohol-and-drug related, and substance-negative classes, respectively. Regression models suggested that pre-injury alcohol use is associated with a 15% higher risk of infection, whereas pre-injury drug use is associated with a 30% higher risk of infection. Pre-injury substance use did not appear to significantly impact clinical outcomes following treatment for traumatic injury, however. Conclusion: This study suggests that pre-injury drug use is associated with a significantly higher complication rate. In particular, infection during hospitalization is a significant risk for both alcohol and drug related trauma visits, and drug-related trauma incidents are associated with increased risk for additional circulatory complications. Although drug and alcohol related trauma incidents are not associated with appreciably worse clinical outcomes, patients experiencing such complications are associated with significantly greater length of stay and higher hospitalization costs. Therefore significant benefits to trauma patients could be gained with enhanced surveillance for pre-injury substance use upon admission to the ED, and closer monitoring for infection or circulatory complications during their period of hospitalization.Center for Systems and Synthetic [email protected]

Standalone vertex finding in the ATLAS muon spectrometer

A dedicated reconstruction algorithm to find decay vertices in the ATLAS muon spectrometer is presented. The algorithm searches the region just upstream of or inside the muon spectrometer volume for multi-particle vertices that originate from the decay of particles with long decay paths. The performance of the algorithm is evaluated using both a sample of simulated Higgs boson events, in which the Higgs boson decays to long-lived neutral particles that in turn decay to bbar b final states, and pp collision data at √s = 7 TeV collected with the ATLAS detector at the LHC during 2011

Measurements of Higgs boson production and couplings in diboson final states with the ATLAS detector at the LHC

Measurements are presented of production properties and couplings of the recently discovered Higgs boson using the decays into boson pairs, H →γ γ, H → Z Z∗ →4l and H →W W∗ →lνlν. The results are based on the complete pp collision data sample recorded by the ATLAS experiment at the CERN Large Hadron Collider at centre-of-mass energies of √s = 7 TeV and √s = 8 TeV, corresponding to an integrated luminosity of about 25 fb−1. Evidence for Higgs boson production through vector-boson fusion is reported. Results of combined fits probing Higgs boson couplings to fermions and bosons, as well as anomalous contributions to loop-induced production and decay modes, are presented. All measurements are consistent with expectations for the Standard Model Higgs boson

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal