Cortical hemodynamics and motor recovery after cortical infarcts

textStroke is the leading cause of disability and the fourth leading cause of death in the United States. Of those that survive a stroke, many are left with long term functional motor impairments. Spontaneous recovery of motor function occurs after a stroke and the reorganization of spared neural tissue is a contributing factor. To study motor recovery following a stroke, rodent models have been especially useful because experimental manipulations can be paired with controlled infarcts to understand physiologically relevant changes. For example, stroke to the sensory-motor cortex (SMC) in mice produces functional motor impairments which are dependent on the reorganization of the remaining cortex. Ironically, after about 20 years of research on the reorganization of the peri-lesion following cortical ischemia, there has been a lack of focus on the neuro-vascular changes as they relate to functional outcome after stroke. The central hypothesis of this report is that spontaneous vascular remodeling contributes to behavioral recovery and cortical reorganization following ischemic insult. To investigate the relationship between blood flow recovery and improvement of motor function after an ischemic insult, we developed a mouse model of upper extremity impairment after a stroke that can be repeatedly imaged in vivo. Specifically, 14 C57/BL6 mice either received photo-thrombotic cortical lesions (n=7) or vehicle procedures (n=7), were allowed 3 days to recover, and then received forelimb function probes using the pasta matrix reaching task (PMRT), an assay for skilled forelimb function, in tandem with the imaging of cortical blood flow using multi-exposure speckle imaging (MESI) at Days 3, 5, 10, and 20. Results indicate that the mice that received injections with Rose Bengal displayed significantly decreased performance on the PMRT and a significantly reduced amount of cortical blood flow compared to both their baseline performance and the control group. Skilled forelimb performance following the ischemic lesion correlated strongly with stroke severity (as indexed by cortical blood flow in the lesion core 2 hours following lesion induction). Additionally, the re-establishment of cortical blood flow to the infarct core precedes the recovery of motor performance, indicating potential importance for the re-establishment of blood flow to support the adaptive plasticity required for motor recovery.Psycholog

Scholarly Metrics Baseline: A Survey of Faculty Knowledge, Use, and Opinion About Scholarly Metrics

This article presents the results of a faculty survey conducted at the University of Vermont during academic year 2014-2015. The survey asked faculty about: familiarity with scholarly metrics, metric seeking habits, help seeking habits, and the role of metrics in their department’s tenure and promotion process. The survey also gathered faculty opinions on how well scholarly metrics reflect the importance of scholarly work and how faculty feel about administrators gathering institutional scholarly metric information. Results point to the necessity of understanding the campus landscape of faculty knowledge, opinion, importance, and use of scholarly metrics before engaging faculty in further discussions about quantifying the impact of their scholarly work

Human in vitro models for understanding mechanisms of autism spectrum disorder.

Early brain development is a critical epoch for the development of autism spectrum disorder (ASD). In vivo animal models have, until recently, been the principal tool used to study early brain development and the changes occurring in neurodevelopmental disorders such as ASD. In vitro models of brain development represent a significant advance in the field. Here, we review the main methods available to study human brain development in vitro and the applications of these models for studying ASD and other psychiatric disorders. We discuss the main findings from stem cell models to date focusing on cell cycle and proliferation, cell death, cell differentiation and maturation, and neuronal signaling and synaptic stimuli. To be able to generalize the results from these studies, we propose a framework of experimental design and power considerations for using in vitro models to study ASD. These include both technical issues such as reproducibility and power analysis and conceptual issues such as the brain region and cell types being modeled

Sfermion Interference in Neutralino Decays at the LHC

If the two lightest neutralinos of the Minimal Supersymmetric Standard Model have a mass splitting less than the Z boson mass, interference effects in the three-body decay chi_2^0 --> chi_1^0 f f can be important. We formulate an observable that contains information on the nature of the interference: the ratio BR(chi_2^0 --> chi_1^0 b b) / BR(chi_2^0 --> chi_1^0 l+ l-). This will give a constraint on the supersymmetry breaking parameters that is complementary to many techniques already existing in the literature. We present some ideas on how to perform a simple counting experiment to determine this ratio.Comment: 14 pages, 6 figure

On the Correlation Between the Spin-Independent and Spin-Dependent Direct Detection of Dark Matter

We study the correlation between spin-independent and spin-dependent scattering in the context of MSSM neutralino dark matter for both thermal and non-thermal histories. We explore the generality of this relationship with reference to other models. We discuss why either fine-tuning or numerical coincidences are necessary for the correlation to break down. We derive upper bounds on spin-dependent scattering mediated by a Z boson.Comment: 31 pages, 6 figures, 3 appendices; v2: refs added, minor typos corrected, journal versio

Unsupervised Training for 3D Morphable Model Regression

We present a method for training a regression network from image pixels to 3D morphable model coordinates using only unlabeled photographs. The training loss is based on features from a facial recognition network, computed on-the-fly by rendering the predicted faces with a differentiable renderer. To make training from features feasible and avoid network fooling effects, we introduce three objectives: a batch distribution loss that encourages the output distribution to match the distribution of the morphable model, a loopback loss that ensures the network can correctly reinterpret its own output, and a multi-view identity loss that compares the features of the predicted 3D face and the input photograph from multiple viewing angles. We train a regression network using these objectives, a set of unlabeled photographs, and the morphable model itself, and demonstrate state-of-the-art results.Comment: CVPR 2018 version with supplemental material (http://openaccess.thecvf.com/content_cvpr_2018/html/Genova_Unsupervised_Training_for_CVPR_2018_paper.html