3,679 Works

Unique functional digit representation in human motor cortex across columns and layers

Laurentius Huber, Emily Finn, Daniel Handwerker, Marlene Bönstrup, Daniel Glen, Rick Reynolds, , Dimo Ivanov, Natalia Petrodou, Sean Marrett, Jozien Goense, Benedikt Poser & Peter Bandettini
The sensorimotor system consists of multiple brain areas, incl. M1 and S1. The neural connections between sensorimotor areas follows pathways that are uniquely distributed across cortical layers and columns. Recently, we found that the analysis of laminar resting-state fMRI fluctuations in M1 are indicative of afferent vs. efferent connectivity in M1 [Huber, Neuron(96), 2017]. In this study, we seek to characterize both the columnar and laminar topology of body-part representations across M1 and S1 using...

Raccoons in human-dominated landscapes of North America

Mathieu Basille, Valeria Guerrero & Caitlin Jarvis

Raccoons are one of the most adaptable and ubiquitous species. Raccoons are distributed throughout North America and thrive in both natural and heavily modified or urbanized environments. Raccoons can arguably be considered a keystone species: they play a key role in ecosystem functions, with a major predation impact on small mammal and bird populations, among others. In this context, raccoons are an ideal model species to investigate the impact of humans on wildlife populations. We...

Isolating compounds that inhibit EV 71 virus

, , , , &
This presentation concerns EV 71 (Enterovirus 71) which is responsible for Hand, Foot, and Mouth Disease. My goal was to discover a combination of drugs that works best to inhibit the activity of ATPase in regard to the 2C protein through creating an ATPase assay. The 2C protein is responsible for viral replication and proliferation, and is a highly conserved protein among viruses. ATPase activity was measured because it is an enzyme which is essential...

Open Land Use for Africa (OLU4Africa)

, Bente Lilja Bye & Dmitri Kožuch
The Plan4business project (2012-2014) has identified a gap in land use data availability, especially outside big cities, in suburban and rural areas. The Urban Atlas of the European Environmental Agency covers only cities above 100,000 inhabitants. So for example in the Czech Republic, only 13 cities are covered. For the rest, there is the Corine Land Cover, which can be used only for regional and national analysis. The lack of land use data on local...

Suggested revisions to the IHC Key Concepts and responses 2016-2018

Andrew David Oxman, Iain Chalmers, Astrid Austvoll-Dahlgren &

Debunking active data management plans

João Cardoso, Tomasz Miksa & José Borbinha
This poster focuses on the topic of active or machine-actionable data management plans. It aims at clarifying the concept and present an overview on its state of the art. With particular focus on the work by the RDA DMP Common Standards working group and the 10 rules for maDMP (Miksa et al. 2018).

Increasing study power using a machine learning approach

Danielle Beaulieu, Albert A. Taylor, Andrew Conklin, , Mike Keymer & David L. Ennist
Using predictions of ALS outcomes from our machine-learning models as covariates in the analysis of clinical trial primary endpoints has been shown, through simulations, to give on average more than a 10% boost to study power across disease endpoints.

Mind-wandering in chronic pain and control participants during a smartphone-based mindfulness task

Muhammad Abid Azam, Vered Latman & Joel Katz
Introduction/Aim: Mindful breathing is a commonly used approach in pain management. Repetitive and intrusive mind-wandering related to pain is likely to be stressful for people with chronic pain, but few studies have measured pain-related mind-wandering during mindfulness meditation (MM) for chronic pain.

This study examined mind-wandering during a smartphone-based MM task in 99 participants (AgeM=20.7 years, SD=4.03; Male=37, Female=62). Participants were classified into 2 groups: 1) chronic pain (CP; n=44) if they self-reported a diagnosed CP...

Deep quality control of infant T1w brain MRI

, & Alan C. Evans
Convolutional Neural Network that learns quality control labels of T1w MRI images using a novel slice sampling strategy. The network is trained on 2D slices about the centre of unregistered images, and validation/testing is done on the entire range of slices, taking the average slicewise probability of pass or fail as the final prediction. The network achieves very high sensitivity and moderately high specificity in a 10-fold cross-validation experiment. Temperature scaling is learned on the...

How to 'build' a journal

Vicky Hellon
Slides on 'how to build a journal' - part of the talk given at the Open Science workshop at the University of Cork 02/11/18.

Committing to a path in science policy

Adriana Bankston
Talk for the Professional Skills and Ethics (BIOL 863) at Kansas State University on April 18, 2018 (via zoom).

Mapping scRNA-seq data onto cell type taxonomies

Valentine Svensson & Lior Pachter
The explosive popularity of scRNA-seq has led to the definition of hundreds of new cell types. A strategy to maintain in- terpretability of so many discrete classes is to define them in terms of taxonomic trees: broad cell types are successively divided into several fine grained types. No explicit formulation has been made in how gene expression link individual cells to the cell types in taxonomies.

We present a generalized linear model using a novel likelihood...

Sociodemographic characteristics, and results from the IHLQ and LSQ questionnaires, before, immediately after and 3 weeks after intervention for control and intervention groups.

, Zohreh Mahmoodi, Mahnaz Akbari Kamrani, Maryam Tehranizadeh & Kourosh Kabir

Raw data for absorbance values from MTT assay and subsequent calculation of IC50 values on Vero cells for extracts of Solanum nigrum from Kisii and controls.

Christine N. Mutoro, Johnson K. Kinyua, Joseph K. Ng'ang'a, Daniel W. Kariuki, & Christopher O. Anjili
For sorted raw absorbance data, columns 3, 6, 9 and 12 contain untreated cells; wells A1, A2, A4, A5, A7, A8, A10, A11, B1, B2, B4, B5, B7, B8, B10 and B11 contain medium only. Rows C-H contain indicated test samples, with extract concentrations of 31.25, 62.5, 125 , 250 µg/ml, 500 and 1000 µg/ml, respectively, and control drug concentrations of 16.125, 31.25, 62.5, 125, 250 and 500 µg/ml, respectively.

Registration Year

  • 2018

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