Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting Semantic Priming at the Single-Trial Level

Semantic priming is usually studied by examining ERPs over many trials and subjects. This article aims at detecting semantic priming at the single-trial level. By using machine learning techniques it is possible to analyse and classify short traces of brain activity, which could, for example, be used to build a Brain Computer Interface (BCI). This article describes an experiment where subjects were presented with word pairs and asked to decide whether the words were related or not. A classifier was trained to determine whether the subjects judged words as related or unrelated based on one second of EEG data. The results show that the classifier accuracy when training per subject varies between 54% and 67%, and is significantly above chance level for all subjects (N = 12) and the accuracy when training over subjects varies between 51% and 63%, and is significantly above chance level for 11 subjects, pointing to a general effect.
Clinical Outcomes After Posterior Open Elbow Arthrolysis for Posttraumatic Elbow Stiffness

Background: Loss of motion is a well-known complication after elbow trauma and in severe cases, arthrolysis of elbow is the procedure of choice. The posterior approach might have some advantages especially in post-traumatic patients who have undergone the same surgical approach in the past. Objectives: The aim of this study was to evaluate the short-term outcomes of elbow arthrolysis through posterior approach. Moreover, we assessed the effect of operation on the patients’ quality of life. Patients and Methods: During a retrospective-cohort study, the medical records of 14 patients (12 men, two women) whose range of movement had been limited post-traumatically and had undergone elbow arthrolysis with posterior approach were reviewed. Before intervention, the patients had a flexion less than 100 degrees or an extension lag of 30 degrees or more. For evaluation of the final outcomes, they were invited to participate in our study and the final range of motion, visual analogue score (VAS), disability of arm, shoulder and hand (DASH), Mayo elbow score (MES) and short form health survey (SF-36) scores were measured in the patients. Results: Mean age of the participants was 28.7 years. The interval from initial injury and arthrolysis was 16 months and the patients were followed for 14 months. The mean range of motion in patients before surgery was 35.8 degrees, which was increased to a mean of 108.9 after the surgery, indicating a 73.1 degrees improvement. The means of VAS, DASH, Mayo elbow and SF-36 scores in the patients were 1.6, 34, 68 and 43, respectively. A significant inverse correlation was found between the preoperative range of motion and final range of motion. Conclusions: According to our results, elbow arthrolysis through posterior approach could be an effective technique with low complications. Since the final range of motion improved significantly, it might be a valuable method in promoting the patients’ quality of life.
Understanding the Adaptive Growth Strategy of Lactobacillus plantarum by In Silico Optimisation

In the study of metabolic networks, optimization techniques are often used to predict flux distributions, and hence, metabolic phenotype. Flux balance analysis in particular has been successful in predicting metabolic phenotypes. However, an inherent limitation of a stoichiometric approach such as flux balance analysis is that it can predict only flux distributions that result in maximal yields. Hence, previous attempts to use FBA to predict metabolic fluxes in Lactobacillus plantarum failed, as this lactic acid bacterium produces lactate, even under glucose-limited chemostat conditions, where FBA predicted mixed acid fermentation as an alternative pathway leading to a higher yield. In this study we tested, however, whether long-term adaptation on an unusual and poor carbon source (for this bacterium) would select for mutants with optimal biomass yields. We have therefore adapted Lactobacillus plantarum to grow well on glycerol as its main growth substrate. After prolonged serial dilutions, the growth yield and corresponding fluxes were compared to in silico predictions. Surprisingly, the organism still produced mainly lactate, which was corroborated by FBA to indeed be optimal. To understand these results, constraint-based elementary flux mode analysis was developed that predicted 3 out of 2669 possible flux modes to be optimal under the experimental conditions. These optimal pathways corresponded very closely to the experimentally observed fluxes and explained lactate formation as the result of competition for oxygen by the other flux modes. Hence, these results provide thorough understanding of adaptive evolution, allowing in silico predictions of the resulting flux states, provided that the selective growth conditions favor yield optimization as the winning strategy.
Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition

The primate visual system achieves remarkable visual object recognition performance even in brief presentations, and under changes to object exemplar, geometric transformations, and background variation (a.k.a. core visual object recognition). This remarkable performance is mediated by the representation formed in inferior temporal (IT) cortex. In parallel, recent advances in machine learning have led to ever higher performing models of object recognition using artificial deep neural networks (DNNs). It remains unclear, however, whether the representational performance of DNNs rivals that of the brain. To accurately produce such a comparison, a major difficulty has been a unifying metric that accounts for experimental limitations, such as the amount of noise, the number of neural recording sites, and the number of trials, and computational limitations, such as the complexity of the decoding classifier and the number of classifier training examples. In this work, we perform a direct comparison that corrects for these experimental limitations and computational considerations. As part of our methodology, we propose an extension of “kernel analysis” that measures the generalization accuracy as a function of representational complexity. Our evaluations show that, unlike previous bio-inspired models, the latest DNNs rival the representational performance of IT cortex on this visual object recognition task. Furthermore, we show that models that perform well on measures of representational performance also perform well on measures of representational similarity to IT, and on measures of predicting individual IT multi-unit responses. Whether these DNNs rely on computational mechanisms similar to the primate visual system is yet to be determined, but, unlike all previous bio-inspired models, that possibility cannot be ruled out merely on representational performance grounds.
Resting-state functional connectivity of ventral parietal regions associated with attention reorienting and episodic recollection

In functional neuroimaging studies, ventral parietal cortex (VPC) is recruited by very different cognitive tasks. Explaining the contributions of VPC to these tasks has become a topic of intense study and lively debate. Perception studies frequently find VPC activations during tasks involving attention-reorienting, and memory studies frequently find them during tasks involving episodic recollection. According to the Attention to Memory (AtoM) model, both phenomena can be explained by the same VPC function: bottom-up attention. Yet, a recent functional MRI (fMRI) meta-analysis suggested that attention-reorienting activations are more frequent in anterior VPC, whereas recollection activations are more frequent in posterior VPC. Also, there is evidence that anterior and posterior VPC regions have different functional connectivity patterns. To investigate these issues, we conducted a resting-state functional connectivity analysis using as seeds the center-of-mass of attention-reorienting and recollection activations in the meta-analysis, which were located in the supramarginal gyrus (SMG, around the temporo-parietal junction—TPJ) and in the angular gyrus (AG), respectively. The SMG seed showed stronger connectivity with ventrolateral prefrontal cortex (VLPFC) and occipito-temporal cortex, whereas the AG seed showed stronger connectivity with the hippocampus and default network regions. To investigate whether these connectivity differences were graded or sharp, VLPFC and hippocampal connectivity was measured in VPC regions traversing through the SMG and AG seeds. The results showed a graded pattern: VLPFC connectivity gradually decreases from SMG to AG, whereas hippocampal connectivity gradually increases from SMG to AG. Importantly, both gradients showed an abrupt break when extended beyond VPC borders. This finding suggests that functional differences between SMG and AG are more subtle than previously thought. These connectivity differences can be explained by differences in the input and output to anterior and posterior VPC regions, without the need of postulating markedly different functions. These results are as consistent with integrative accounts of VPC function, such as the AtoM model, as they are with models that ascribe completely different functions to VPC regions.
L2 speakers decompose morphologically complex verbs: fMRI evidence from priming of transparent derived verbs

In this functional magnetic resonance imaging (fMRI) long-lag priming study, we investigated the processing of Dutch semantically transparent, derived prefix verbs. In such words, the meaning of the word as a whole can be deduced from the meanings of its parts, e.g., wegleggen “put aside. ” Many behavioral and some fMRI studies suggest that native (L1) speakers decompose transparent derived words. The brain region usually implicated in morphological decomposition is the left inferior frontal gyrus (LIFG). In non-native (L2) speakers, the processing of transparent derived words has hardly been investigated, especially in fMRI studies, and results are contradictory: some studies find more reliance on holistic (i.e., non-decompositional) processing by L2 speakers; some find no difference between L1 and L2 speakers. In this study, we wanted to find out whether Dutch transparent derived prefix verbs are decomposed or processed holistically by German L2 speakers of Dutch. Half of the derived verbs (e.g., omvallen “fall down”) were preceded by their stem (e.g., vallen “fall”) with a lag of 4–6 words (“primed”); the other half (e.g., inslapen “fall asleep”) were not (“unprimed”). L1 and L2 speakers of Dutch made lexical decisions on these visually presented verbs. Both region of interest analyses and whole-brain analyses showed that there was a significant repetition suppression effect for primed compared to unprimed derived verbs in the LIFG. This was true both for the analyses over L2 speakers only and for the analyses over the two language groups together. The latter did not reveal any interaction with language group (L1 vs. L2) in the LIFG. Thus, L2 speakers show a clear priming effect in the LIFG, an area that has been associated with morphological decomposition. Our findings are consistent with the idea that L2 speakers engage in decomposition of transparent derived verbs rather than processing them holistically.
A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation

While many models of biological object recognition share a common set of “broad-stroke” properties, the performance of any one model depends strongly on the choice of parameters in a particular instantiation of that model—e.g., the number of units per layer, the size of pooling kernels, exponents in normalization operations, etc. Since the number of such parameters (explicit or implicit) is typically large and the computational cost of evaluating one particular parameter set is high, the space of possible model instantiations goes largely unexplored. Thus, when a model fails to approach the abilities of biological visual systems, we are left uncertain whether this failure is because we are missing a fundamental idea or because the correct “parts” have not been tuned correctly, assembled at sufficient scale, or provided with enough training. Here, we present a high-throughput approach to the exploration of such parameter sets, leveraging recent advances in stream processing hardware (high-end NVIDIA graphic cards and the PlayStation 3's IBM Cell Processor). In analogy to high-throughput screening approaches in molecular biology and genetics, we explored thousands of potential network architectures and parameter instantiations, screening those that show promising object recognition performance for further analysis. We show that this approach can yield significant, reproducible gains in performance across an array of basic object recognition tasks, consistently outperforming a variety of state-of-the-art purpose-built vision systems from the literature. As the scale of available computational power continues to expand, we argue that this approach has the potential to greatly accelerate progress in both artificial vision and our understanding of the computational underpinning of biological vision.
Chemical Analyses of Wasp-Associated Streptomyces Bacteria Reveal a Prolific Potential for Natural Products Discovery

Identifying new sources for small molecule discovery is necessary to help mitigate the continuous emergence of antibiotic-resistance in pathogenic microbes. Recent studies indicate that one potentially rich source of novel natural products is Actinobacterial symbionts associated with social and solitary Hymenoptera. Here we test this possibility by examining two species of solitary mud dauber wasps, Sceliphron caementarium and Chalybion californicum. We performed enrichment isolations from 33 wasps and obtained more than 200 isolates of Streptomyces Actinobacteria. Chemical analyses of 15 of these isolates identified 11 distinct and structurally diverse secondary metabolites, including a novel polyunsaturated and polyoxygenated macrocyclic lactam, which we name sceliphrolactam. By pairing the 15 Streptomyces strains against a collection of fungi and bacteria, we document their antifungal and antibacterial activity. The prevalence and anti-microbial properties of Actinobacteria associated with these two solitary wasp species suggest the potential role of these Streptomyces as antibiotic-producing symbionts, potentially helping defend their wasp hosts from pathogenic microbes. Finding phylogenetically diverse and chemically prolific Actinobacteria from solitary wasps suggests that insect-associated Actinobacteria can provide a valuable source of novel natural products of pharmaceutical interest.
Consensus on guidelines for stereotactic neurosurgery for psychiatric disorders

Background For patients with psychiatric illnesses remaining refractory to ‘standard’ therapies, neurosurgical procedures may be considered. Guidelines for safe and ethical conduct of such procedures have previously and independently been proposed by various local and regional expert groups. Methods To expand on these earlier documents, representative members of continental and international psychiatric and neurosurgical societies, joined efforts to further elaborate and adopt a pragmatic worldwide set of guidelines. These are intended to address a broad range of neuropsychiatric disorders, brain targets and neurosurgical techniques, taking into account cultural and social heterogeneities of healthcare environments. Findings The proposed consensus document highlights that, while stereotactic ablative procedures such as cingulotomy and capsulotomy for depression and obsessive-compulsive disorder are considered ‘established’ in some countries, they still lack level I evidence. Further, it is noted that deep brain stimulation in any brain target hitherto tried, and for any psychiatric or behavioural disorder, still remains at an investigational stage. Researchers are encouraged to design randomised controlled trials, based on scientific and data-driven rationales for disease and brain target selection. Experienced multidisciplinary teams are a mandatory requirement for the safe and ethical conduct of any psychiatric neurosurgery, ensuring documented refractoriness of patients, proper consent procedures that respect patient's capacity and autonomy, multifaceted preoperative as well as postoperative long-term follow-up evaluation, and reporting of effects and side effects for all patients. Interpretation This consensus document on ethical and scientific conduct of psychiatric surgery worldwide is designed to enhance patient safety.
The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data

The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% of all HPO classes using terms from ontologies for anatomy, cell types, function, embryology, pathology and other domains. This allows interoperability with several resources, especially those containing phenotype information on model organisms such as mouse and zebrafish. Here we describe the updated HPO database, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes such as frequency, references and negations are associated with each annotation. Several large-scale projects worldwide utilize the HPO for describing phenotype information in their datasets. We have therefore generated equivalence mappings to other phenotype vocabularies such as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration of existing datasets and interoperability with multiple biomedical resources. We have created various ways to access the HPO database content using flat files, a MySQL database, and Web-based tools. All data and documentation on the HPO project can be found online.
On Hokusai's Great wave off Kanagawa: localization, linearity and a rogue wave in sub-Antarctic waters

The Hokusai woodcut entitled The great wave off Kanagawa has been interpreted as an unusually large storm wave, likely to be classed as a rogue wave, and possibly generated from nonlinear wave dynamics (J. H. E. Cartwright and H. Nakamura, Notes Rec. R. Soc. 63, 119–135 (2009)). In this paper, we present a complementary discussion of this hypothesis, discussing in particular how linear and nonlinear mechanisms can both contribute to the emergence of rogue wave events. By making reference to the Great wave's simultaneous transverse and longitudinal localization, we show that the purely linear mechanism of directional focusing also predicts characteristics consistent with those of the Great wave. In addition, we discuss the properties of a particular rogue wave photographed on the open ocean in sub-Antarctic waters, which shows two-dimensional localization and breaking dynamics remarkably similar to Hokusai's depiction in the woodcut.
An Optimized Histochemical Method to Assess Skeletal Muscle Glycogen and Lipid Stores Reveals Two Metabolically Distinct Populations of Type I Muscle Fibers

Skeletal muscle energy metabolism has been a research focus of physiologists for more than a century. Yet, how the use of intramuscular carbohydrate and lipid energy stores are coordinated during different types of exercise remains a subject of debate. Controversy arises from contradicting data from numerous studies, which used different methodological approaches. Here we review the “pros and cons” of previously used histochemical methods and describe an optimized method to ensure the preservation and specificity of detection of both intramyocellular carbohydrate and lipid stores. For optimal preservation of muscle energy stores, air drying cryosections or cycles of freezing-thawing need to be avoided. Furthermore, optimization of the imaging settings in order to specifically image intracellular lipid droplets stained with oil red O or Bodipy-493/503 is shown. When co-staining lipid droplets with associated proteins, Bodipy-493/503 should be the dye of choice, since oil red O creates precipitates on the lipid droplets blocking the light. In order to increase the specificity of glycogen stain, an antibody against glycogen is used. The resulting method reveals the existence of two metabolically distinct myosin heavy chain I expressing fibers: I-1 fibers have a smaller crossectional area, a higher density of lipid droplets, and a tendency to lower glycogen content compared to I-2 fibers. Type I-2 fibers have similar lipid content than IIA. Exhaustive exercise lead to glycogen depletion in type IIA and IIX fibers, a reduction in lipid droplets density in both type I-1 and I-2 fibers, and a decrease in the size of lipid droplets exclusively in type I-1 fibers.
Acute stress differentially affects spatial configuration learning in high and low cortisol-responding healthy adults

Background Stress and stress hormones modulate memory formation in various ways that are relevant to our understanding of stress-related psychopathology, such as posttraumatic stress disorder (PTSD). Particular relevance is attributed to efficient memory formation sustained by the hippocampus and parahippocampus. This process is thought to reduce the occurrence of intrusions and flashbacks following trauma, but may be negatively affected by acute stress. Moreover, recent evidence suggests that the efficiency of visuo-spatial processing and learning based on the hippocampal area is related to PTSD symptoms. Objective The current study investigated the effect of acute stress on spatial configuration learning using a spatial contextual cueing task (SCCT) known to heavily rely on structures in the parahippocampus. Method Acute stress was induced by subjecting participants (N = 34) to the Maastricht Acute Stress Test (MAST). Following a counterbalanced within-subject approach, the effects of stress and the ensuing hormonal (i.e., cortisol) activity on subsequent SCCT performance were compared to SCCT performance following a no-stress control condition. Results Acute stress did not impact SCCT learning overall, but opposing effects emerged for high versus low cortisol responders to the MAST. Learning scores following stress were reduced in low cortisol responders, while high cortisol-responding participants showed improved learning. Conclusions The effects of stress on spatial configuration learning were moderated by the magnitude of endogenous cortisol secretion. These findings suggest a possible mechanism by which cortisol responses serve an adaptive function during stress and trauma, and this may prove to be a promising route for future research in this area.