bluuebunny/crossref_metadata_2025_split huggingface dataset:
Associations between Processing Speed and Psychopathology in a Transdiagnostic, Pediatric Sample
Authors: Kramer Eliza , Koo Bonhwang , Restrepo Anita , Koyama Maki , Neuhaus Rebecca , Pugh Kenneth , Andreotti Charissa , Milham Michael 
Published: August 2019

ABSTRACTObjectiveThe present study sought to examine the relationships between processing speed (PS), mental health disorders, and learning disorders. Prior work has tended to explore relationships between PS deficits and individual diagnoses (i.e., anxiety, autism, ADHD, depressive) in isolation of one another, often relying on relatively modest sample sizes. In contrast, the present work simultaneously investigated associations between PS deficits and these diagnoses, along with specific learning disabilities (i.e., reading, math), in a large-scale, transdiagnostic, community self-referred sample.MethodA total of 843 children, ages 8-16 were included from the Healthy Brain Network (HBN) Biobank. Given the presence of four PS tasks in HBN, principal component analysis (PCA) was employed to create a composite measure that represented the shared variance of the four PS tasks, referred to as PC1. Intraclass correlation coefficient (ICC) between the four PS measures, as well as PC1, were calculated to assess reliability. We then used multiple linear regression models to assess specific relationships between PS deficits and psychiatric diagnoses.ResultsICCs were moderate between WISC-V tasks (0.663), and relatively modest between NIH Toolbox Pattern Comparison and other PS scales (0.14-0.27). Regression analyses revealed specific significant relationships between PS and reading and math disabilities, ADHD-inattentive type (ADHD-I), and ADHD-combined type (ADHD-C). Secondary analyses accounting for inattention dimensionally diminished associations with ADHD-C, but not ADHD-I or specific learning disability subtypes. The present study did not find a significant relationship with Autism Spectrum Disorder after accounting for inattentive symptoms. Consistent with prior work, demographic variables, including sex, socioeconomic status, and motor control exhibited independent relationships with PC1 as well.DiscussionThis study provided a comprehensive examination of PS, mental health disorders, and learning disabilities through a transdiagnostic approach. Implications for understanding how PS interacts with a highly heterogeneous childhood sample, as well as the need for increased focus on detection of affected populations are discussed.
CD4+T follicular helper (Tfh) cells in human tonsil and blood are clonally convergent, but divergent from non-Tfh CD4+cells
Authors: Brenna Elena , Davydov Alexey N , Ladell Kristin , McLaren James E , Bonaiuti Paolo , Metsger Maria , Gilbert Sarah C , Lambe Teresa , Price David A , Campion Suzanne L , Chudakov Dmitriy M , Borrow Persephone , McMichael Andrew J 
Published: August 2019

ABSTRACTT follicular helper (Tfh) cells are fundamental for B cell selection and antibody maturation in germinal centers. Circulating Tfh (cTfh) cells constitute a minor proportion of the CD4+T cells in peripheral blood, but their clonotypic relationship to Tfh populations resident in lymph nodes and the extent to which they differ from non-Tfh CD4+cells has been unclear. Using donor-matched blood and tonsil samples we investigated T cell receptor (TCR) sharing between tonsillar Tfh cells and peripheral Tfh and non-Tfh cell populations. TCR transcript sequencing revealed considerable clonal overlap between peripheral and tonsillar Tfh cell subsets as well as a clear distinction between Tfh and non-Tfh cells. Furthermore, influenza-specific cTfh cell clones derived from blood could be found in the repertoire of tonsillar Tfh cells. Therefore, human blood samples can be used to gain insight into the specificity of Tfh responses occurring in lymphoid tissues, provided cTfh subsets are studied.
Hippocampal Remapping as Hidden State Inference
Authors: Sanders Honi , Wilson Matthew A. , Gershman Samuel J. 
Published: August 2019

AbstractCells in the hippocampus tuned to spatial location (place cells) typically change their tuning when an animal changes context, a phenomenon known as remapping. A fundamental challenge to understanding remapping is the fact that what counts as a “context change” has never been precisely defined. Furthermore, different remapping phenomena have been classified on the basis of how much the tuning changes after different types and degrees of context change, but the relationship between these variables is not clear. We address these ambiguities by formalizing remapping in terms of hidden state inference. According to this view, remapping does not directly reflect objective, observable properties of the environment, but rather subjective beliefs about the hidden state of the environment. We show how the hidden state framework can resolve a number of puzzles about the nature of remapping.
An uncertainty principle for neural coding: Conjugate representations of position and velocity are mapped onto firing rates and co-firing rates of neural spike trains
Authors: Grgurich Ryan , Blair Hugh T. 
Published: August 2019

AbstractThe hippocampal system contains neural populations that encode an animal’s position and velocity as it navigates through space. Here, we show that such populations can embed two codes within their spike trains: afiring rate code(R) conveyed by within-cell spike intervals, and aco-firing rate code(Ṙ) conveyed by between-cell spike intervals. These two codes behave asconjugatesof one another, obeying an analog of the uncertainty principle from physics: information conveyed inRcomes at the expense of information inṘ, and vice versa. An exception to this trade-off occurs when spike trains encode a pair of conjugate variables, such as position and velocity, which do not compete for capacity acrossRandṘ. To illustrate this, we describe two biologically inspired methods for decodingRandṘ, referred to assigmaandsigma-chidecoding, respectively. Simulations of head direction (HD) and grid cells show that if firing rates are tuned for position (but not velocity), then position is recovered by sigma decoding, whereas velocity is recovered by sigma-chi decoding. Conversely, simulations of oscillatory interference among theta-modulated “speed cells” show that if co-firing rates are tuned for position (but not velocity), then position is recovered by sigma-chi decoding, whereas velocity is recovered by sigma decoding. Between these two extremes, information about both variables can be distributed across both channels, and partially recovered by both decoders. These results suggest that neurons with different spatial and temporal tuning properties—such as speed versus grid cells—might not encode different information, but rather, distribute similar information about position and velocity in different ways acrossRandṘ. Such conjugate coding of position and velocity may influence how hippocampal populations are interconnected to form functional circuits, and how biological neurons integrate their inputs to decode information from firing rates and spike correlations.
Mapping effective connectivity between the frontal and contralateral primary motor cortex using dual-coil transcranial magnetic stimulation
Authors: Bunday Karen L. , Bonaiuto James , Betti Sonia , Orban Guy A. , Davare Marco 
Published: August 2019

AbstractCytoarchitectonic, anatomical and electrophysiological studies have divided the frontal cortex into distinct functional subdivisions. Many of these subdivisions are anatomically connected with the contralateral primary motor cortex (M1); however, effective neurophysiological connectivity between these regions is not well defined in humans. Therefore, we aimed to use dual-coil transcranial magnetic stimulation (TMS) to map, with high spatial resolution, the effective connectivity between different frontal regions of the right hemisphere and contralateral M1 (cM1). TMS was applied over the left M1 alone (test pulse) or after a conditioning pulse was applied to different grid points covering the right frontal cortex, while subjects were at rest, prepared an index finger abduction (Prep-ABD) or precision grip (Prep-PG). MEP motor maps were generated by creating synthetic fMRI volumes, including the normalised MEP values at vertices corresponding to the TMS grid locations. These maps were registered to a common atlas, and statistical parametric mapping was used to identify cortical clusters in which stimulation differentially modulated conditioned MEPs across conditions. We found five significant clusters in the frontal cortex. Three clusters in ventral premotor regions (areas 6v and 44) showed significant differential modulations of contralateral MEPs when rest was compared to Prep-ABD and Prep-PG. Two clusters in rostral dorsolateral prefrontal cortex (areas 8Av and 46) showed differential modulation in MEPs when Prep-ABD was compared to Prep-PG. Our findings demonstrate distinct regions that show task-related connectivity whereby interactions between ventral premotor regions and cM1 differentiate between rest and movement preparation and the dorsolateral prefrontal cortex differentiates primarily between preparation of different types of hand movements. These results thus demonstrate the utility of dual-coil TMS and MEP motor maps to define fine-grained sub-regions in the human frontal cortex, which are functional and causally involved in hand movements.HighlightsDual-coil TMS mapping allows defining of fine-grained frontal cortex subdivisionsFrontal cortex houses multiple areas with different neurophysiological propertiesInteractions between premotor areas and M1 control rest vs movementInteractions between prefrontal areas and M1 reflect movement selection
Whole genome sequencing of orofacial cleft trios from the Gabriella Miller Kids First Pediatric Research Consortium identifies a new locus on chromosome 21
Authors: Mukhopadhyay Nandita , Bishop Madison , Mortillo Michael , Chopra Pankaj , Hetmanski Jacqueline B. , Taub Margaret A. , Moreno Lina M. , Valencia-Ramirez Luz Consuelo , Restrepo Claudia , Wehby George L. , Hecht Jacqueline T. , Deleyiannis Frederic , Butali Azeez , Weinberg Seth M. , Beaty Terri H. , Murray Jeffrey C. , Leslie Elizabeth J. , Feingold Eleanor , Marazita Mary L. 
Published: August 2019

AbstractOrofacial clefts (OFCs) are one of the most common birth defects worldwide and create a significant health burden. The majority of OFCs are non-syndromic, and the genetic component has been only partially determined. Here, we analyze whole genome sequence (WGS) data for association with risk of OFCs in European and Colombian families selected from a multicenter family-based OFC study. Part of the Gabriella Miller Kids First Pediatric Research Program, this is the first large-scale WGS study of OFC in parent-offspring trios. WGS provides deeper and more specific genetic data than currently available using imputation on single nucleotide polymorphic (SNP) marker panels. Here, association analysis of genome-wide single nucleotide variants (SNV) and short insertions and deletions (indels) identified a new locus on chromosome 21 in Colombian families, within a region known to be expressed during craniofacial development. This study reinforces the ancestry differences seen in the genetic etiology of OFCs, and the need for larger samples when for studying OFCs and other birth defects in admixed populations.
An MRI-Derived Neuroanatomical Atlas of the Fischer 344 Rat Brain
Authors: Goerzen Dana , Fowler Caitlin , Devenyi Gabriel A. , Germann Jurgen , Madularu Dan , Mallar Chakravarty M. , Near Jamie 
Published: August 2019

AbstractThis paper reports the development of a high-resolution 3-D MRI atlas of the Fischer 344 adult rat brain. The atlas is a 60 μm isotropic image volume composed of 256 coronal slices with 71 manually delineated structures and substructures. The atlas was developed using Pydpiper image registration pipeline to create an average brain image of 41 four-month-old male and female Fischer 344 rats. Slices in the average brain image were then manually segmented, individually and bilaterally, on the basis of image contrast in conjunction with Paxinos and Watson’s (2007) stereotaxic rat brain atlas. Summary statistics (mean and standard deviation of regional volumes) are reported for each brain region across the sample used to generate the atlas, and a statistical comparison of a chosen subset of regional brain volumes between male and female rats is presented. On average, the coefficient of variation of regional brain volumes across all rats in our sample was 4%, with no individual brain region having a coefficient of variation greater than 13%. A full description of methods used, as well as the atlas, the template that the atlas was derived from, and a masking file, can be found at Zenodo at https://doi.org/10.5281/zenodo.3555556. To our knowledge, this is the first MRI atlas created using Fischer 344 rats and will thus provide an appropriate neuroanatomical model for researchers working with this strain.HIGHLIGHTS⍰ Open-access high-resolution anatomical MRI template for Fischer 344 rat brain.⍰ Segmented atlas of 71 regions for use as a tool in Fischer 344 preclinical research paradigms.⍰ Analysis of population variability of regional brain volumes.⍰ Analysis of sex-differences in regional brain volumesKEYWORDS: Fischer 344; Structural MRI; Segmentation; Rat brain template; Digital brain atlas; Sex-differences;
Mechanical feedback and robustness of apical constrictions inDrosophilaembryo ventral furrow formation
Authors: Holcomb Michael C. , Gao Guo-Jie Jason , Servati Mahsa , Schneider Dylan , McNeely Presley K. , Thomas Jeffrey H. , Blawzdziewicz Jerzy 
Published: August 2019

AbstractFormation of the ventral furrow in theDrosophilaembryo relies on the apical constriction of cells in the ventral region to produce bending forces that drive tissue invagination. Recently [J Phys Condens Matter. 2016;28(41):414021], we observed that apical constrictions during the initial phase of ventral furrow formation produce elongated patterns of cellular constriction chains prior to invagination, and argued that these are indicative of tensile stress feedback. Here, we quantitatively analyze the constriction patterns preceding ventral furrow formation and find that they are consistent with the predictions of our active-granular-fluid model of a monolayer of mechanically coupled stress-sensitive constricting particles. Our model shows that tensile feedback causes constriction chains to develop along underlying precursor tensile stress chains that gradually strengthen with subsequent cellular constrictions. As seen in both our model and available optogenetic experiments, this mechanism allows constriction chains to penetrate or circumvent zones of reduced cell contractility, thus increasing the robustness of ventral furrow formation to spatial variation of cell contractility by rescuing cellular constrictions in the disrupted regions.
Multiple protein-DNA interfaces unravelled by evolutionary information, physico-chemical and geometrical properties
Authors: Corsi F. , Lavery R. , Laine E. , Carbone A. 
Published: August 2019

ABSTRACTThe usage made of protein surfaces by nucleic acids still remains largely unknown, due to the lack of available structural data and the inherent complexity associated to protein surface deformability and evolution. In this work, we present a method that contributes to decipher such complexity by predicting protein-DNA interfaces and characterizing their properties. It relies on three biologically and physically meaningful descriptors, namely evolutionary conservation, physico-chemical properties and surface geometry. We carefully assessed its performance on several hundreds of protein structures. We achieve a higher sensitivity compared to state-of-the-art methods, and similar precision. Importantly, we show that our method is able to unravel ‘hidden’ binding sites by applying it to unbound protein structures and to proteins binding to DNA via multiple sites and in different conformations. It is implemented as a fully automated tool, , freely accessible at: http://www.lcqb.upmc.fr/JET2DNA. We also provide a new reference dataset of 187 protein-DNA complex structures, representative of all types of protein-DNA interactions, along with a subset of associated unbound structures: http://www.lcqb.upmc.fr/PDNAbenchmarks.
Detecting brain network communities: considering the role of information flow and its different temporal scales
Authors: Sanchez-Rodriguez Lazaro M. , Iturria-Medina Yasser , Mouches Pauline , Sotero Roberto C. 
Published: August 2019

AbstractThe identification of community structure in graphs continues to attract great interest in several fields. Network neuroscience is particularly concerned with this problem considering the key roles communities play in brain processes and functionality. Most methods used for community detection in brain graphs are based on the maximization of a parameter-dependent modularity function that often obscures the physical meaning and hierarchical organization of the partitions of network nodes. In this work, we present a new method able to detect communities at different scales in a natural, unrestricted way. First, to obtain an estimation of the information flow in the network we release random walkers to freely move over it. The activity of the walkers is separated into oscillatory modes by using empirical mode decomposition. After grouping nodes by their co-occurrence at each time scale,k-modes clustering returns the desired partitions. Our algorithm was first tested on benchmark graphs with favorable performance. Next, it was applied to real and simulated anatomical and/or functional connectomes in the macaque and human brains. We found a clear hierarchical repertoire of community structures in both the anatomical and the functional networks. The observed partitions range from the evident division in two hemispheres –in which all processes are managed globally– to specialized communities seemingly shaped by physical proximity and shared function. Our results stimulate the research of hierarchical community organization in terms of temporal scales of information flow in the brain network.Highlights- Oscillatory modes of networks’ signals carry information on architectural rules.- Meaningful partitions of the brain networks are found over different temporal scales.- The multiscale organization of the brain responds to the function of its components.
The domain-general multiple demand (MD) network does not support core aspects of language comprehension: a large-scale fMRI investigation
Authors: Diachek Evgeniia , Blank Idan , Siegelman Matthew , Affourtit Josef , Fedorenko Evelina 
Published: August 2019

AbstractAside from the language-selective left-lateralized fronto-temporal network, language comprehension sometimes additionally recruits a domain-general bilateral fronto-parietal network implicated in executive functions: the multiple demand (MD) network. However, the nature of the MD network’s contributions to language comprehension remains debated. To illuminate the role of this network in language processing, we conducted a large-scale fMRI investigation using data from 30 diverse word and sentence comprehension experiments (481 unique participants, 678 scanning sessions). In line with prior findings, the MD network was active during many language tasks. Moreover, similar to the language-selective network, which is robustly lateralized to the left hemisphere, these responses were stronger in the left-hemisphere MD regions. However, in stark contrast with the language-selective network, the MD network responded more strongly (i) to lists of unconnected words than to sentences, and critically, (ii) in paradigms with an explicit task compared to passive comprehension paradigms. In fact, many passive comprehension tasks failed to elicit a response above the fixation baseline in the MD network, in contrast to strong responses in the language-selective network. In tandem, these results argue against a role for the MD network in core aspects of sentence comprehension like inhibiting irrelevant meanings or parses, keeping intermediate representations active in working memory, or predicting upcoming words or structures. These results align with recent evidence of relatively poor tracking of the linguistic signal by the MD regions during naturalistic comprehension, and instead suggest that the MD network’s engagement during language processing likely reflects effort associated with extraneous task demands.Significance StatementDomain-general executive processes, like working memory and cognitive control, have long been implicated in language comprehension, including in neuroimaging studies that have reported activation in domain-general multiple demand (MD) regions for linguistic manipulations. However, much prior evidence has come from paradigms where language interpretation is accompanied by extraneous tasks. Using a large fMRI dataset (30 experiments/481 participants/678 sessions), we demonstrate that MD regions are engaged during language comprehension in the presence of task demands, but not during passive reading/listening—conditions that strongly activate the fronto-temporal language network. These results present a fundamental challenge to proposals whereby linguistic computations, like inhibiting irrelevant meanings, keeping representations active in working memory, or predicting upcoming elements, draw on domain-general executive resources.
Failure to clear developmental apoptosis contributes to the pathology of RNASET2-deficient leukoencephalopathy
Authors: Hamilton Noémie , Rutherford Holly A. , Isles Hannah M. , Petts Jessica J. , Weber Thomas , Henneke Marco , Gärtner Jutta , Dunning Mark , Renshaw Stephen A. 
Published: August 2019

SummaryThe contribution of microglia in neurological disorders is emerging as a leading driver rather than a consequence of pathology. RNAseT2-deficient leukoencephalopathy is a severe childhood white matter disorder affecting patients in their first year of life and mimics a cytomegalovirus brain infection. The early onset and resemblance of the symptoms to an immune response suggest an inflammatory and embryonic origin of the pathology. In this study, we identify deficient microglia as an early marker of pathology. Using theex uterodevelopment and the optical transparency of anrnaset2-deficient zebrafish model, we found that dysfunctional microglia fail to clear apoptotic neurons during brain development. This was associated with increased number of apoptotic cells and behavioural defects lasting into adulthood. This zebrafish model recapitulates all aspect of the human disease to be used as a robust preclinical model. Using microglia-specific depletion and rescue experiments, we identified microglia as potential drivers of the pathology and highlight tissue-specific approaches as future therapeutic avenues.