Test-retest reliability of FreeSurfer automated hippocampal subfield segmentation within and across scanners

The human hippocampus is vulnerable to a range of degenerative conditions and as such, accurate in vivo measurement of the hippocampus and hippocampal substructures via neuroimaging is of great interest for understanding mechanisms of disease as well as for use as a biomarker in clinical trials of novel therapeutics. Although total hippocampal volume can be measured relatively reliably, it is critical to understand how this reliability is affected by acquisition on different scanners, as multiple scanning platforms would likely be utilized in large-scale clinical trials. This is particularly true for hippocampal subregional measurements, which have only relatively recently been measurable through common image processing platforms such as FreeSurfer. Accurate segmentation of these subregions is challenging due to their small size, magnetic resonance imaging (MRI) signal loss in medial temporal regions of the brain, and lack of contrast for delineation from standard neuroimaging procedures. Here, we assess the test-retest reliability of the FreeSurfer automated hippocampal subfield segmentation procedure using two Siemens model scanners (a Siemens Trio and Prismafit Trio upgrade). T1-weighted images were acquired for 11 generally healthy younger participants (two scans on the Trio and one scan on the Prismafit). Each scan was processed through the standard cross-sectional stream and the recently released longitudinal pipeline in FreeSurfer v6.0 for hippocampal segmentation. Test-retest reliability of the volumetric measures was examined for individual subfields as well as percent volume difference and Dice overlap among scans and intra-class correlation coefficients (ICC). Reliability was high in the molecular layer, dentate gyrus, and whole hippocampus with the inclusion of three time points with mean volume differences among scans less than 3%, overlap greater than 80%, and ICC >0.95. The parasubiculum and hippocampal fissure showed the least improvement in reliability with mean volume difference greater than 5%, overlap less than 70%, and ICC scores ranging from 0.78 to 0.89. Other subregions, including the CA regions, were stable in their mean volume difference and overlap (75% respectively) and showed improvement in reliability with the inclusion of three scans (ICC ​> ​0.9). Reliability was generally higher within scanner (Trio-Trio), however, Trio-Prismafit reliability was also high and did not exhibit an obvious bias. These results suggest that the FreeSurfer automated segmentation procedure is a reliable method to measure total as well as hippocampal subregional volumes and may be useful in clinical applications including as an endpoint for future clinical trials of conditions affecting the hippocampus

Rapidly Measuring the Speed of Unconscious Learning: Amnesics Learn Quickly and Happy People Slowly

BACKGROUND We introduce a method for quickly determining the rate of implicit learning. METHODOLOGY/PRINCIPAL FINDINGS The task involves making a binary prediction for a probabilistic sequence over 10 minutes; from this it is possible to determine the influence of events of a different number of trials in the past on the current decision. This profile directly reflects the learning rate parameter of a large class of learning algorithms including the delta and Rescorla-Wagner rules. To illustrate the use of the method, we compare a person with amnesia with normal controls and we compare people with induced happy and sad moods. CONCLUSIONS/SIGNIFICANCE Learning on the task is likely both associative and implicit. We argue theoretically and demonstrate empirically that both amnesia and also transient negative moods can be associated with an especially large learning rate: People with amnesia can learn quickly and happy people slowl

Mutations in or near the Transmembrane Domain Alter PMEL Amyloid Formation from Functional to Pathogenic

PMEL is a pigment cell-specific protein that forms physiological amyloid fibrils upon which melanins ultimately deposit in the lumen of the pigment organelle, the melanosome. Whereas hypomorphic PMEL mutations in several species result in a mild pigment dilution that is inherited in a recessive manner, PMEL alleles found in the Dominant white (DW) chicken and Silver horse (HoSi)—which bear mutations that alter the PMEL transmembrane domain (TMD) and that are thus outside the amyloid core—are associated with a striking loss of pigmentation that is inherited in a dominant fashion. Here we show that the DW and HoSi mutations alter PMEL TMD oligomerization and/or association with membranes, with consequent formation of aberrantly packed fibrils. The aberrant fibrils are associated with a loss of pigmentation in cultured melanocytes, suggesting that they inhibit melanin production and/or melanosome integrity. A secondary mutation in the Smoky chicken, which reverts the dominant DW phenotype, prevents the accumulation of PMEL in fibrillogenic compartments and thus averts DW–associated pigment loss; a secondary mutation found in the Dun chicken likely dampens a HoSi–like dominant mutation in a similar manner. We propose that the DW and HoSi mutations alter the normally benign amyloid to a pathogenic form that antagonizes melanosome function, and that the secondary mutations found in the Smoky and Dun chickens revert or dampen pathogenicity by functioning as null alleles, thus preventing the formation of aberrant fibrils. We speculate that PMEL mutations can model the conversion between physiological and pathological amyloid

QCD and strongly coupled gauge theories : challenges and perspectives

We highlight the progress, current status, and open challenges of QCD-driven physics, in theory and in experiment. We discuss how the strong interaction is intimately connected to a broad sweep of physical problems, in settings ranging from astrophysics and cosmology to strongly coupled, complex systems in particle and condensed-matter physics, as well as to searches for physics beyond the Standard Model. We also discuss how success in describing the strong interaction impacts other fields, and, in turn, how such subjects can impact studies of the strong interaction. In the course of the work we offer a perspective on the many research streams which flow into and out of QCD, as well as a vision for future developments.Peer reviewe

Density determination of the thermonuclear fuel region in inertial confinement fusion implosions

Understanding of the thermonuclear burn in an inertial confinement fusion implosion requires knowledge of the local deuterium–tritium (DT) fuel density. Neutron imaging of the core now provides this previously unavailable information. Two types of neutron images are required. The first is an image of the primary 14-MeV neutrons produced by the D + T fusion reaction. The second is an image of the 14-MeV neutrons that leave the implosion hot spot and are downscattered to lower energy by elastic and inelastic collisions in the fuel. These neutrons are measured by gating the detector to record the 6–12 MeV neutrons. Using the reconstructed primary image as a nonuniform source, a set of linear equations is derived that describes the contribution of each voxel of the DT fuel region to a pixel in the downscattered image. Using the measured intensity of the 14-MeV neutrons and downscattered images, the set of equations is solved for the density distribution in the fuel region. The method is validated against test problems and simulations of high-yield implosions. The calculated DT density distribution from one experiment is presented

Classical conditioning in the vegetative and minimally conscious state

Pavlovian trace conditioning depends on the temporal gap between the conditioned and unconditioned stimuli. It requires, in mammals, functional medial temporal lobe structures and, in humans, explicit knowledge of the temporal contingency. It is therefore considered to be a plausible objective test to assess awareness without relying on explicit reports. We found that individuals with disorders of consciousness (DOCs), despite being unable to report awareness explicitly, were able to learn this procedure. Learning was specific and showed an anticipatory electromyographic response to the aversive conditioning stimulus, which was substantially stronger than to the control stimulus and was augmented as the aversive stimulus approached. The amount of learning correlated with the degree of cortical atrophy and was a good indicator of recovery. None of these effects were observed in control subjects under the effect of anesthesia (propofol). Our results suggest that individuals with DOCs might have partially preserved conscious processing, which cannot be mediated by explicit reports and is not detected by behavioral assessment.Fil: Bekinschtein, Tristán Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina. Instituto de Neurología Cognitiva; Argentina. University of Cambridge; Reino UnidoFil: Shalóm, Diego Edgar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Neurología Cognitiva; Argentina. Fundación Favaloro; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Neurociencia Integrativa; ArgentinaFil: Forcato, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; ArgentinaFil: Herrera, Maria Silvia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Neurociencia Integrativa; ArgentinaFil: Coleman, Martin R.. University of Cambridge; Reino UnidoFil: Manes, Facundo Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fundación Favaloro; Argentina. Instituto de Neurología Cognitiva; Argentina. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; ArgentinaFil: Sigman, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Neurociencia Integrativa; Argentin