bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real-time fMRI neurofeedback training as a neurorehabilitation approach on depressive disorders: A systematic review of randomized control trials
Authors: Méndez Pamela González , Sitaram Ranganatha , Stanley Jeffrey A. , Climent Julio Rodiño 
Published: August 2020

ABSTRACTBACKGROUNDDepressive disorders are a group of neuropsychiatric disorders that cause significant distress and impairment in social, occupational, and other important areas of functioning. In the last decade, Brain-Computer Interfaces based-neurofeedback training appears as an innovative therapy for this condition and other neuropsychiatric disorders, allowing to volitionally self-regulate brain activity and behavior. Up to date, non-invasive neurofeedback training have been built on different techniques, including EEG, NIRS and fMRI.OBJECTIVESThis systematic review aims to evaluate the clinical application of fMRI neurofeedback training and its efficacy on treating depressive disorders. As a secondary objective, we intend to extract additional information on the neurofeedback training technique, in order to provide recommendations for future research.METHODS AND ANALYSISThe systematic review complies with the PRISMA guidelines and it was submitted to PROSPERO registration. We will only include randomized control trials assessing participants with a depressive disorder. The intervention of interest is real-time fMRI neurofeedback training, the comparison of interest will be placebo neurofeedback, another active non-neurofeedback control or no treatment. The primary outcome will be effects on behavior (symptomatology/disease severity reduction). The secondary outcomes will assess quality of life, acceptability and adverse effects. Finally, we will evaluate ‘other outcomes’ regarding brain MRI metrics (BOLD activation/connectivity), cognitive tasks performance, and physiology measures. At least two reviewers will independently select studies, extract data and assess the risk of bias. If methodologically possible, for primary and secondary outcomes, a meta-analysis will be performed and the data will be presented in summary tables of results using the GRADE approach.STRENGTH AND LIMITATIONSAs the number of studies on neurofeedback is increasing every year, and better quality of evidence is available, this systematic review, will include only randomized control trials. To our knowledge, this is the first systematic review assessing randomized control trials on fMRI neurofeedback training as a neurorehabilitation approach on depressive disorders. The main limitation of this systematic review might arise from the low number of extant RCTs.
Why are rare variants hard to impute? Coalescent models reveal theoretical limits in existing algorithms
Authors: Si Yichen , Vanderwerff Brett , Zöllner Sebastian 
Published: August 2020

AbstractGenotype imputation is an indispensable step in human genetic studies. Large reference panels with deeply sequenced genomes now allow interrogating variants with minor allele frequency < 1% without sequencing. While it is critical to consider limits of this approach, imputation methods for rare variants have only done so empirically; the theoretical basis of their imputation accuracy has not been explored. To provide theoretical consideration of imputation accuracy under the current imputation framework, we develop a coalescent model of imputing rare variants, leveraging the joint genealogy of the sample to be imputed and reference individuals. We show that broadly used imputation algorithms includes model misspecifications about this joint genealogy that limit the ability to correctly impute rare variants. We develop closed-form solutions for the probability distribution of this joint genealogy and quantify the inevitable error rate resulting from the model misspecification across a range of allele frequencies and reference sample sizes. We show that the probability of a falsely imputed minor allele decreases with reference sample size, but the proportion of falsely imputed minor alleles mostly depends on the allele count in the reference sample. We summarize the impact of this error on genotype imputation on association tests by calculating ther2between imputed and true genotype and show that even when modeling other sources of error, the impact of the model misspecification have a significant impact on ther2of rare variants. To evaluate these predictions in practice, we compare the imputation of the same dataset across imputation panels of different sizes. While this empirical imputation accuracy is substantially lower than our theoretical prediction, modeling misspecification seems to further decrease imputation accuracy for variants with low allele counts in the reference. These results provide a framework for developing new imputation algorithms and for interpreting rare variant association analyses.
Single amino acid-promoted reactions link a non-enzymatic chemical network to the early evolution of enzymatic pentose phosphate pathway
Authors: Piedrafita Gabriel , Varma Sreejith , Castro Cecilia , Messner Christoph , Szyrwiel Lukasz , Griffin Julian , Ralser Markus 
Published: August 2020

AbstractHow metabolic pathways emerged in early evolution remains largely unknown. Recently discovered chemical networks driven by iron and sulfur resemble reaction sequences found within glycolysis, gluconeogenesis, the oxidative and reductive Krebs cycle, the Wood Ljungdahl as well as the S-adenosylmethionine pathways, components of the core cellular metabolic network. These findings suggest that the evolution of central metabolism was primed by environmental chemical reactions, implying that non-enzymatic reaction networks served as a “template” in the evolution of enzymatic activities. We speculated that the turning point for this transition would depend on the catalytic properties of the simplest structural components of proteins, single amino acids. Here, we systematically combine constituents of Fe(II)-driven non-enzymatic reactions resembling glycolysis and pentose phosphate pathway (PPP), with single proteinogenic amino acids. Multiple reaction rates are enhanced by amino acids. In particular, cysteine is able to replace (and/or complement) the metal ion Fe(II) in driving the non-enzymatic formation of the RNA-backbone metabolite ribose 5-phosphate from 6-phosphogluconate, a rate-limiting reaction of the oxidative PPP. In the presence of both Fe(II) and cysteine, a complex is formed, enabling the non-enzymatic reaction to proceed at a wide range of temperatures. At mundane temperatures, this ‘minimal enzyme-like complex’ achieves a much higher specificity in the formation of ribose 5-phosphate than the Fe(II)-driven reaction at high temperatures. Hence, simple amino acids can accelerate key steps within metal-promoted metabolism-like chemical networks. Our results imply a stepwise scenario, in which environmental chemical networks served as primers in the early evolution of the metabolic network structure.Significance StatementThe evolutionary roots of metabolic pathways are barely understood. Here we show results consistent with a stepwise scenario during the evolution of (enzymatic) metabolism, starting from non-enzymatic chemical networks. By systematic screening of metabolic-like reactivitiesin vitro, and using high-throughput analytical techniques, we identify an iron/cysteine complex to act as a ‘minimal enzymelike complex’, which consists of a metal ion, an amino acid, and a sugar phosphate ligand. Integrated in a metal-driven, non-enzymatic pentose phosphate pathway, it promotes the formation of the RNA-backbone precursor ribose 5-phosphate at ambient temperature.
Adolescent alcohol binge-drinking induces delayed appearance of behavioral defects in mice
Authors: Van Hees Laura , Didone Vincent , Charlet-Briart Manon , Van Ingelgom Théo , Alexandre Alysson , Quertemont Etienne , Nguyen Laurent , Laguesse Sophie 
Published: August 2020

AbstractAdolescence is a developmental period characterized by significant changes in brain architecture and behavior. The immaturity of the adolescent brain is associated with heightened vulnerability to exogenous agents, including alcohol. Alcohol is the most consumed drug among teenagers, and binge-drinking during adolescence is a major public health concern. Studies have suggested that adolescent alcohol exposure (AAE) may interfere with the maturation of frontal brain regions and lead to long-lasting behavioral consequences. In this study, we used a mouse model of AAE in which adolescent mice reach high blood alcohol concentration after voluntary binge-drinking. In order to assess short- and long-term consequences of AAE, a battery of behavioral tests was performed during late adolescence and during adulthood. We showed that AAE had no short-term effect on young mice behavior but rather increased anxiety- and depressive-like behaviors, as well as alcohol consumption during adulthood. Moreover, alcohol binge-drinking during adolescence dramatically decreased recognition memory performances and behavioral flexibility in both adult males and females. Furthermore, we showed that voluntary consumption of alcohol during adolescence did not trigger any major activation of the innate immune system in the prefrontal cortex (PFC). Together, our data suggest that voluntary alcohol binge-drinking in adolescent mice induces a delayed appearance of behavioral impairments in adulthood.
Human neonatal B cell immunity differs from the adult version by conserved Ig repertoires and rapid, but transient response dynamics
Authors: Budeus Bettina , Kibler Artur , Brauser Martina , Homp Ekaterina , Bronischewski Kevin , Ross J. Alexander , Görgens Andre , Weniger Marc A. , Dunst Josefine , Kreslavsky Taras , da Conceição Castro Symone Vitoriano , Murke Florian , Oakes Christopher C. , Rusch Peter , Andrikos Dimitrios , Kern Peter , Köninger Angela , Lindemann Monika , Johansson Patricia , Hansen Wiebke , Lundell Anna-Carin , Rudin Anna , Dürig Jan , Giebel Bernd , Hoffmann Daniel , Küppers Ralf , Seifert Marc 
Published: August 2020

AbstractThe human infant B cell system is considered premature or impaired. Here we show that most cord blood B cells are mature and functional as seen in adults, albeit with distinct transcriptional programs providing accelerated responsiveness to T cell-independent and T cell-dependent stimulation and facilitated IgA class switching. Stimulation drives extensive differentiation into antibody-secreting cells, thereby presumably limiting memory B cell formation. The neonatal Ig-repertoire is highly variable, but conserved, showing recurrent B cell receptor (BCR) clonotypes frequently shared between neonates. Our study demonstrates that cord blood B cells are not impaired but differ from their adult counterpart in a conserved BCR repertoire and rapid but transient response dynamics. These properties may account for the sensitivity of neonates to infections and limited effectivity of vaccination strategies. Humanized mice suggest that the distinctness of cord blood versus adult B cells is already reflected by the developmental program of hematopoietic precursors, arguing for a layered B-1/B-2 lineage system as in mice. Still, our findings reveal overall limited comparability of human cord blood B cells and murine B-1 cells.Significance StatementNeonates and infants suffer from enhanced susceptibility to infections. Our study contrasts with the current concept of a premature or impaired B cell system in neonates, by showing that most cord blood B cells are mature and functional. However, their responses are rapid but provide only short-term protection, which may help to improve infant vaccination strategies. We propose an altered perspective on the early human B cell system, which looks similar to but functions differently from the adult counterpart. Finally, our analysis indicates that cord blood- and adult B cell development occur layered as in mice, but certain mouse models still may offer a limited view on human neonatal B cell immunity.
Comparative Neuroanatomy of the Lumbosacral Spinal Cord of the Rat, Cat, Pig, Monkey, and Human
Authors: Toossi Amirali , Bergin Bradley , Marefatallah Maedeh , Parhizi Behdad , Tyreman Neil , Everaert Dirk G. , Rezaei Sabereh , Seres Peter , Gatenby J. Christopher , Perlmutter Steve I. , Mushahwar Vivian K. 
Published: August 2020

AbstractThe overall goal of this work was to create a high-resolution MRI atlas of the lumbosacral enlargement of the spinal cord of the rat (Sprague-Dawley), cat, domestic pig, rhesus monkey, and human. These species were chosen because they are commonly used in basic and translational research in spinal cord injuries and diseases. Six spinal cord specimens from each of the studied species (total of 30 specimens) were fixed, extracted, and imaged. Sizes of the spinal cord segments, cross-sectional dimensions, and locations of the spinal cord gray and white matter were quantified and compared across species. The obtained atlas establishes a reference for the neuroanatomy of the intact lumbosacral spinal cord in these species. It can also be used to guide the planning of surgical procedures of the spinal cord, technology design and development of spinal cord neuroprostheses, and the precise delivery of cells/drugs into target regions within the spinal cord parenchyma.
Joint Representation of Color and Shape in Convolutional Neural Networks: A Stimulus-rich Network Perspective
Authors: Taylor JohnMark , Xu Yaoda 
Published: August 2020

AbstractTo interact with real-world objects, any effective visual system must jointly code the unique features defining each object. Despite decades of neuroscience research, we still lack a firm grasp on how the primate brain binds visual features. Here we apply a novel network-based stimulus-rich representational similarity approach to study color and shape binding in five convolutional neural networks (CNNs) with varying architecture, depth, and presence/absence of recurrent processing. All CNNs showed near-orthogonal color and shape processing in early layers, but increasingly interactive feature coding in higher layers, with this effect being much stronger for networks trained for object classification than untrained networks. These results characterize for the first time how multiple visual features are coded together in CNNs. The approach developed here can be easily implemented to characterize whether a similar coding scheme may serve as a viable solution to the binding problem in the primate brain.
A New Paradigm of Developing Therapeutics to Infectious Diseases by Combining Insights from Nature and Engineering
Authors: Kim Suhyun 
Published: August 2020

AbstractBroad host-spectrum antibiotics not only kill pathogens, but also beneficial commensal bacteria of the host microbiome that play crucial roles for health. In Nature, bacteria kill other bacteria much more selectively than antibiotics do. Because there is metabolic cost involved in producing molecules to inhibit others, evolution endowed bacteria with bacteriocins to kill those who are similar enough to compete for the same niche, while leaving more distantly related bacteria, intact. The presence of such narrow host-spectrum antibacterial molecules suggests that by engineering and reprogramming what is found in nature, it may be possible to develop highly effective yet selective therapeutics to infectious diseases, either as purified drugs, or as live bacterial therapeutics. Here, I propose a new paradigm of developing highly selective therapeutics by combining insights from Nature and engineering and applied this against foodborne pathogens, one of the most common causes of bacterial infections for humans.
Beneficial effects of cerebellar tDCS on motor learning are associated with altered putamen-cerebellar connectivity: a simultaneous tDCS-fMRI study
Authors: Liebrand Matthias , Karabanov Anke , Antonenko Daria , Flöel Agnes , Siebner Hartwig R. , Classen Joseph , Krämer Ulrike M. , Tzvi Elinor 
Published: August 2020

AbstractNon-invasive transcranial stimulation of cerebellum and primary motor cortex (M1) has been shown to enhance motor learning. However, the mechanisms by which stimulation improves learning remain largely unknown. Here, we sought to shed light on the neural correlates of transcranial direct current stimulation (tDCS) during motor learning by simultaneously recording functional magnetic resonance imaging (fMRI). We found that right cerebellar tDCS, but not left M1 tDCS, led to enhanced sequence learning in the serial reaction time task. Performance was also improved following cerebellar tDCS compared to sham in a sequence production task, reflecting superior training effects persisting into the post-training period. These behavioral effects were accompanied by increased learning-specific activity in right M1, left cerebellum lobule VI, left inferior frontal gyrus and right inferior parietal lobule during cerebellar tDCS compared to sham. Despite the lack of group-level changes comparing left M1 tDCS to sham, activity increase in right M1, supplementary motor area, and bilateral superior frontal cortex, under M1 tDCS, was associated with better sequence performance. This suggests that lack of group effects in M1 tDCS relate to inter-individual variability in learning-related activation patterns. We further investigated how tDCS modulates effective connectivity in the cortico-striato-cerebellar learning network. Using dynamic causal modelling, we found altered connectivity patterns during both M1 and cerebellar tDCS when compared to sham. Specifically, during cerebellar tDCS, negative modulation of a connection from putamen to cerebellum was decreased for sequence learning only, effectively leading to decreased inhibition of the cerebellum. These results show specific effects of cerebellar tDCS on functional activity and connectivity in the motor learning network and may facilitate the optimization of motor rehabilitation involving cerebellar non-invasive stimulation.
Unpredictable hummingbirds: Flight path entropy is constrained by speed and wing loading
Authors: Berberi Ilias , Segre Paolo S. , Altshuler Douglas L. , Dakin Roslyn 
Published: August 2020

ABSTRACTUnpredictable movement can provide an advantage when animals avoid predators and other threats. Previous studies have examined how varying environments can elicit unpredictable movement, but the intrinsic causes of complex, unpredictable behavior are not yet known. We addressed this question by analyzing >200 hours of flight performed by hummingbirds, a group of aerial specialists noted for their extreme agility and escape performance. We used information theory to calculate unpredictability based on the positional entropy of short flight sequences during 30-min and 2-hour trials. We show that a bird’s entropy is repeatable, with stable differences among individuals that are negatively correlated with wing loading: birds with lower wing loading are less predictable. Unpredictability is also positively correlated with a bird’s overall acceleration and rotational performance, and yet we find that moment-to-moment changes in acceleration and rotational velocities do not directly influence entropy. This indicates that biomechanical performance must share an underlying basis with a bird’s ability to combine maneuvers into unpredictable sequences. Contrary to expectations, hummingbirds achieve their highest entropy at relatively slow speeds, pointing to a fundamental trade-off whereby individuals must choose to be either fast or unpredictable.
The sex-specific VC neurons are mechanically activated motor neurons that facilitate serotonin-induced egg laying inC. elegans
Authors: Kopchock Richard J. , Ravi Bhavya , Bode Addys , Collins Kevin M. 
Published: August 2020

AbstractSuccessful execution of behavior requires coordinated activity and communication between multiple cell types. Studies using the relatively simple neural circuits of invertebrates have helped to uncover how conserved molecular and cellular signaling events shape animal behavior. To understand the mechanisms underlying neural circuit activity and behavior, we have been studying a simple circuit that drives egg-laying behavior in the nematode wormC. elegans. Here we show that the sex-specific, Ventral C (VC) motor neurons are important for vulval muscle contractility and egg laying in response to serotonin. Ca2+imaging experiments show the VCs are active during times of vulval muscle contraction and vulval opening, and optogenetic stimulation of the VCs promotes vulval muscle Ca2+activity. Blocking VC neurotransmission inhibits egg laying in response to serotonin and increases the failure rate of egg-laying attempts, indicating that VC signaling facilitates full vulval muscle contraction and opening of the vulva for efficient egg laying. We also find the VCs are mechanically activated in response to vulval opening. Optogenetic stimulation of the vulval muscles is sufficient to drive VC Ca2+activity and requires muscle contractility, showing the presynaptic VCs and the postsynaptic vulval muscles can mutually excite each other. Together, our results demonstrate that the VC neurons facilitate efficient execution of egg-laying behavior by coordinating postsynaptic muscle contractility in response to serotonin and mechanosensory feedback.Significance StatementMany animal motor behaviors are modulated by the neurotransmitters serotonin and acetylcholine. Such motor circuits also respond to mechanosensory feedback, but how neurotransmitters and mechanoreceptors work together to coordinate behavior is not well understood. We address these questions using the egg-laying circuit inC. eleganswhere we can manipulate presynaptic neuron and postsynaptic muscle activity in behaving animals while recording circuit responses through Ca2+imaging. We find that the cholinergic VC motoneurons are important for proper vulval muscle contractility and egg laying in response to serotonin. Muscle contraction also activates the VCs, forming a positive feedback loop that promotes full contraction for egg release. In all, mechanosensory feedback provides a parallel form of modulation that shapes circuit responses to neurotransmitters.
Predicting ovulation from brain connectivity: Dynamic causal modelling of the menstrual cycle
Authors: Hidalgo-Lopez Esmeralda , Zeidman Peter , Harris TiAnni , Razi Adeel , Pletzer Belinda 
Published: August 2020

AbstractLongitudinal menstrual cycle research allows the assessment of sex hormones effects on brain organization in a natural framework. Here, we used spectral dynamic causal modelling (spDCM) in a triple network model consisting of the default mode, salience and executive central networks (DMN, SN, and ECN), in order to address the changes in effective connectivity across the menstrual cycle. Sixty healthy young women were scanned three times (menses, pre-ovulatory and luteal phase) and spDCM was estimated for a total of 174 scans. Group level analysis using Parametric empirical Bayes showed lateralized and anterior-posterior changes in connectivity patterns depending on the cycle phase and related to the endogenous hormonal milieu. Right before ovulation the left insula recruited the frontoparietal network, while the right middle frontal gyrus decreased its connectivity to the precuneus. In exchange, the precuneus engaged bilateral angular gyrus, decoupling the DMN into anterior/posterior parts. During the luteal phase, bilateral insula engaged to each other decreasing the connectivity to parietal ECN, which in turn engaged the posterior DMN. Remarkably, the specific cycle phase in which a woman was in could be predicted by the connections that showed the strongest changes. These findings further corroborate the plasticity of the female brain in response to acute hormone fluctuations and have important implications for understanding the neuroendocrine interactions underlying cognitive changes along the menstrual cycle.