Miracle-dz/UniFAR-FTUs huggingface dataset:
Hasty sensorimotor decisions rely on an overlap of broad and selective changes in motor activity

Humans and other animals are able to adjust their speed-accuracy tradeoff (SAT) at will depending on the urge to act, favoring either cautious or hasty decision policies in different contexts. An emerging view is that SAT regulation relies on influences exerting broad changes on the motor system, tuning its activity up globally when hastiness is at premium. The present study aimed to test this hypothesis. Fifty subjects performed a task involving choices between left and right index fingers, in which incorrect choices led either to a high or to a low penalty in two contexts, inciting them to emphasize either cautious or hasty policies. We applied transcranial magnetic stimulation on multiple motor representations, eliciting motor evoked potentials (MEP) in nine finger and leg muscles. MEP amplitudes allowed us to probe activity changes in the corresponding finger and leg representations, while subjects were deliberating about which index to choose. Our data indicate that hastiness entails a broad amplification of motor activity, though this amplification was limited to the chosen side. On top of this effect, we identified a local suppression of motor activity, surrounding the chosen index representation. Hence, a decision policy favoring speed over accuracy appears to rely on overlapping processes producing a broad (but not global) amplification and a surround suppression of motor activity. The latter effect may help to increase the signal-to-noise ratio of the chosen representation, as supported by single-trial correlation analyses indicating a stronger differentiation of activity changes in finger representations in the hasty context.
The DeepFaune initiative: a collaborative effort towards the automatic identification of French fauna in camera-trap images

Camera traps have revolutionized how ecologists monitor wildlife, but their full potential is realized only when the hundreds of thousands of collected images can be readily classified with minimal human intervention. Deep-learning classification models have allowed extraordinary progress towards this end, but trained models remain rare and are only now emerging for European fauna. We report on the first milestone of the DeepFaune initiative (https://www.deepfaune.cnrs.fr), a large-scale collaboration between more than 50 partners involved in wildlife research, conservation and management in France. We developed a classification model trained to recognize 26 species or higher-level taxa. The classification model achieved 0.97 validation accuracy and often >0.95 precision and recall for many classes. These performances were generally higher than 0.90 when tested on independent out-of-sample datasets for which we used image redundancy contained in sequence of images. We implemented our model in a software to classify images stored locally on a personal computer, so as to provide a free, user-friendly and high-performance tool for wildlife practitioners to automatically classify camera-trap images.
A correlational study between microstructural, macrostructural and functional age-related changes in the human visual cortex

Age-related changes in the human brain can be investigated from either structural or functional perspectives. Analysis of structural and functional age-related changes throughout the lifespan may help to understand the normal brain development process and monitor the structural and functional pathology of the brain. This study, combining dedicated electroencephalography (EEG) and magnetic resonance imaging (MRI) approaches in adults (20-78 years), highlights the complex relationship between micro/macrostructural properties and the functional responses to visual stimuli. Here, we aimed to relate age-related changes of the latency of visual evoked potentials (VEPs) to micro/macrostructural indexes and find any correlation between micro/macrostructural features, as well. We studied age-related structural changes in the brain, by using the MRI and diffusion-weighted imaging (DWI) as preferred imaging methods for extracting brain macrostructural parameters such as the cortical thickness, surface area, folding and curvature index, gray matter volume, and microstructural parameters such as mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD). All the mentioned features were significantly correlated with age in V1 and V2 regions of the visual cortex. Furthermore, we highlighted, negative correlations between structural features extracted from T1-weighted images and DWI. The latency and amplitude of the three dominants peaks (C1, P1, N1) of the VEP were considered as the brain functional features to be examined for correlation with age and structural features of the corresponding age. We observed significant correlations between mean C1 latency and GM volume averaged in V1 and V2. In hierarchical models, the structural index did not contributed to significant additional variance in the C1 latency after accounting for the variance associated with age. However, the age explained significant additional variance in the model after accounting for the variance associated with the structural feature.
The Influence of Neural Activity and Neural Cytoarchitecture on Cerebrovascular Arborization: A Computational Model

Normal functioning of the brain relies on a continual and efficient delivery of energy by a vast network of cerebral blood vessels. The bidirectional coupling between neurons and blood vessels consists of vasodilatory energy demand signals from neurons to blood vessels, and the retrograde flow of energy substrates from the vessels to neurons, which fuel neural firing, growth and other housekeeping activities in the neurons. Recent works indicate that, in addition to the functional coupling observed in the adult brain, the interdependence between the neural and vascular networks begins at the embryonic stage, and continues into subsequent developmental stages. The proposed Vascular Arborization Model (VAM) captures the effect of neural cytoarchitecture and neural activity on vascular arborization. The VAM describes three important stages of vascular tree growth: (i) The prenatal growth phase, where the vascular arborization depends on the cytoarchitecture of neurons and non-neural cells, (ii) the post-natal growth phase during which the further arborization of the vasculature depends on neural activity in addition to neural cytoarchitecture, and (iii) the settling phase, where the fully grown vascular tree repositions its vascular branch points or nodes to ensure minimum path length and wire length. The vasculature growth depicted by VAM captures structural characteristics like vascular volume density, radii, mean distance to proximal neurons in the cortex. VAM-grown vasculature agrees with the experimental observation that the neural densities do not covary with the vascular density along the depth of the cortex but predicts a high correlation between neural areal density and microvascular density when compared over a global scale (across animals and regions). To explore the influence of neural activity on vascular arborization, the VAM was used to grow the vasculature in neonatal rat whisker barrel cortex under two conditions: (i) Control, where the whiskers were intact and (ii) Lesioned, where one row of whiskers was cauterized. The model captures a significant reduction in vascular branch density in lesioned animals compared to control animals, concurring with experimental observation.
Increases in vein length compensate for leaf area lost to lobing in grapevine

Premise There is considerable variation in leaf lobing and leaf size, including among grapevines, some of the most well-studied leaves. We examined the relationship between leaf lobing and leaf size across grapevine populations which varied in extent of leaf lobing. Methods We used homologous landmarking techniques to measure 2,632 leaves across two years in 476 unique, genetically distinct grapevines from 5 biparental crosses which vary primarily in the extent of lobing. We determined to what extent leaf area could explain variation in lobing, vein length, and vein to blade ratio. Results Although lobing was the primary source of variation in shape across the leaves we measured, leaf area varied only slightly as a function of lobing. Rather, leaf area increases as a function of total major vein length, total branching vein length, and decreases as a function of vein to blade ratio. These relationships are stronger for more highly lobed leaves, with the residuals for each model differing as a function of distal lobing. Conclusions For a given leaf area, more highly lobed leaves have longer veins and higher vein to blade ratios, allowing them to maintain similar leaf areas despite increased lobing. These findings show how more highly lobed leaves may compensate for what would otherwise result in a reduced leaf area, allowing for increased photosynthetic capacity through similar leaf size.
Is virulence phenotype evolution driven exclusively by Lr gene deployment in French Puccinia triticina populations?

Puccinia triticina is a highly damaging wheat pathogen. The efficacy of leaf rust control by genetic resistance is mitigated by the adaptive capacity of the pathogen, expressed as changes in its virulence combinations (pathotypes). An extensive P. triticina population survey has been carried out in France over the last 30 years, describing the evolution dynamics of this pathogen in response to cultivar deployment. We analyzed the dataset for the 2006-2016 period to determine the relationship between the Lr genes in the cultivars and virulence in the pathotypes. Rust populations were dominated by a small number of pathotypes, with variations in most of the virulence frequencies related to the corresponding Lr gene frequencies in the cultivated landscape. Furthermore, the emergence and spread of a new virulence matched the introduction and use of the corresponding Lr gene (Lr28), confirming that the deployment of qualitative resistance genes is an essential driver of evolution in P. triticina populations. However, PCA revealed that certain pathotype-cultivar associations cannot be explained solely by the distribution of Lr genes in the landscape. This conclusion is supported by the predominance of a few pathotypes on some cultivars, with the persistence of several other compatible pathotypes at low frequencies. Specific interactions are not, therefore, sufficient to explain the distribution of virulence in rust populations. Our findings suggest that aggressiveness is a driver of changes in pathotype frequencies. Accordingly, the hypothesis of “dual selection”, based on both qualitative and quantitative interactions between P. triticina populations and bread wheat cultivars, is favored.
Regulation of presynaptic Ca2+ channel abundance at active zones through a balance of delivery and turnover

Voltage-gated Ca2+ channels (VGCCs) mediate Ca2+ influx to trigger neurotransmitter release at specialized presynaptic sites termed active zones (AZs). The abundance of VGCCs at AZs regulates neurotransmitter release probability (Pr), a key presynaptic determinant of synaptic strength. Although biosynthesis, delivery and recycling cooperate to establish AZ VGCC abundance, experimentally isolating these distinct regulatory processes has been difficult. Here we describe how the AZ levels of Cacophony (Cac), the sole VGCC mediating synaptic transmission in Drosophila, are determined. We also analyzed the relationship between Cac, the conserved VGCC regulatory subunit α2δ, and the core AZ scaffold protein Bruchpilot (BRP) in establishing a functional AZ. We find Cac and BRP are independently regulated at growing AZs, as Cac is dispensable for AZ formation and structural maturation, and BRP abundance is not limiting for Cac accumulation. Additionally, AZs stop accumulating Cac after an initial growth phase, whereas BRP levels continue to increase given extended developmental time. AZ Cac is also buffered against moderate increases or decreases in biosynthesis, whereas BRP lacks this buffering. To probe mechanisms that determine AZ Cac abundance, intravital FRAP and Cac photoconversion were used to separately measure delivery and turnover at individual AZs over a multi-day period. Cac delivery occurs broadly across the AZ population, correlates with AZ size, and is rate-limited by α2δ. Although Cac does not undergo significant lateral transfer between neighboring AZs over the course of development, Cac removal from AZs does occur and is promoted by new Cac delivery, generating a cap on Cac accumulation at mature AZs. Together these findings reveal how Cac biosynthesis, synaptic delivery, and recycling set the abundance of VGCCs at individual AZs throughout synapse development and maintenance.
miR319-targeted TCP4/LANCEOLATE directly regulates OVATE and auxin responses to modulate tomato gynoecium patterning and fruit morphology

Diversity in fruit morphology is one of the hallmarks of varietal differences among modern cultivars of fruit-bearing crops. As evolutionarily related organs, fruits and leaves share developmental processes, but there are surprisingly few connections between regulatory pathways for fruit and leaf development. Here, we show the regulation of the leaf development-associated TEOSINTE BRANCHED1/CYCLOIDEA/PCF (TCP) TCP4/LANCEOLATE (TCP4/LA) transcription factor by the microRNA319 (miR319) is crucial for gynoecium patterning and establishment of fruit morphology. Loss of miR319 regulation leads to a premature, ectopic TCP4/LA expression during gynoecium patterning, which results in elongated fruits, resembling ovate mutants. TCP4/LA modulates tomato fruit development and morphology partially by directly repressing OVATE expression as early as 5-8 days post-inflorescence (dpi) flower buds. Furthermore, miR319-targeted CINCINNATA-like TCP4/LANCEOLATE controls auxin responses in developing flower buds by directly binding to the SlYUCCA4 promoter. Modulation of auxin biosynthesis by TCP4/LA is shared with other CINCINNATA-like TCPs during Arabidopsis gynoecium patterning. Our study defines a novel miRNA-based molecular link between OVATE, a fundamental gene associated with tomato domestication, and auxin responses in the control of fruit development and morphology. Given the striking variation in fruit shape among members of the Solanaceae family, fine-tuning regulation of gene expression by miRNA coupled with modulation of hormone dynamics may be a common driver in the evolution of fruit-shape diversity.
Exploring a diverse world of effector domains and amyloid signaling motifs in fungal NLR proteins

NLR proteins are intracellular receptors constituting a conserved component of the innate immune system of multicellular organisms. In fungi, NLRs are characterized by high diversity of architectures and presence of amyloid signaling. Here, we explore the diverse world of effector and signaling domains of fungal NLRs using state-of-the-art bioinformatic methods including MMseqs2 for fast clustering, probabilistic context-free grammars for sequence analysis, and AlphaFold2 deep neural networks for structure prediction. In addition to substantially improving the overall annotation, especially in basidiomycetes, the study identifies novel domains and reveals the structural similarity of MLKL-related HeLo- and Goodbye-like domains forming the most abundant superfamily of fungal NLR effectors. Moreover, compared to previous studies, we found several times more amyloid motifs, including novel families, and validated aggregating and prion-forming properties of the most abundant of them in vitro and in vivo. Also, through an extensive in silico search, the NLR-associated amyloid signaling is for the first time identified in basidiomycetes. The emerging picture highlights similarities and differences in the NLR architectures and amyloid signaling in ascomycetes, basidiomycetes and other branches of life.
The orphan ligand, activin C, signals through activin receptor-like kinase 7

Activin ligands are formed from two disulfide-linked inhibin β subunit chains. They exist as homodimeric proteins, as in the case of activin A (ActA; InhβA/InhβA) or activin C (ActC; InhβC/InhβC), or as heterodimers, as with activin AC (ActAC; InhβA:InhβC). While the biological functions of ActA and activin B (ActB) have been well-characterized, little is known about the biological function of ActC or ActAC. One thought is that the InhβC chain functions to interfere with ActA production by forming less active ActAC heterodimers. Here, we assessed and characterized the signaling capacity of ligands containing the InhβC chain. ActC and ActAC activated SMAD2/3-dependent signaling via the type I receptor, activin receptor-like kinase 7 (ALK7). Relative to ActA and ActB, ActC exhibited lower affinity for the cognate activin type II receptors and was resistant to neutralization by the extracellular antagonist, follistatin. In mature adipocytes, which exhibit high ALK7 expression, ActC elicited a SMAD2/3 response similar to ActB, which can also signal via ALK7. Collectively, these results establish that ActC and ActAC are active ligands that exhibit a distinct signaling receptor and antagonist profile compared to other activins.
Developmental phenomics suggests that H3K4 monomethylation catalyzed by Trr functions as a phenotypic capacitor

How epigenetic modulators of gene regulation affect the development and evolution of animals has been difficult to ascertain. Despite the widespread presence of histone 3 lysine 4 monomethylation (H3K4me1) on enhancers, hypomethylation appears to have minor effects on animal development and viability. In this study, we performed quantitative, unbiased and multi-dimensional explorations of key phenotypes on Drosophila melanogaster with genetically induced hypomethylation. Hypomethylation reduced transcription factor enrichment in nuclear microenvironments, leading to reduced gene expression, and phenotypes outside of standard laboratory conditions. Our developmental phenomics survey further showed that H3K4me1 hypomethylation led to context-dependent changes in morphology, metabolism, and behavior. Therefore, H3K4me1 may contribute to phenotypic evolution as a phenotypic capacitor by buffering the effects of chance, genotypes and environmental conditions on transcriptional enhancers. Quote “Developmental biologists are often not so much opposed to a role for ecology as they simply ignore it” –Doug Erwin1
Plasmid stability in fluctuating environments: population genetics of multi-copy plasmids

Plasmids are extra-chromosomal genetic elements that encode a wide variety of phenotypes and can be maintained in bacterial populations through vertical and horizontal transmission, thus increasing bacterial adaptation to hostile environmental conditions like those imposed by antimicrobial substances. To circumvent the segregational instability resulting from randomly distributing plasmids between daughter cells upon division, non-transmissible plasmids tend to be carried in multiple copies per cell, with the added benefit of exhibiting increased gene dosage. But carrying multiple copies also results in a high metabolic burden to the bacterial host, therefore reducing the overall fitness of the population. This trade-off poses an existential question for plasmids: What is the optimal plasmid copy number? In this manuscript, we address this question using a combination of population genetics modeling with microbiology experiments consisting of Escherichia coli K12 bearing a multi-copy plasmid encoding for blaTEM-1, a gene conferring resistance to β-lactam antibiotics. We postulate and analyze a Wright-Fisher model to evaluate the interaction between selective pressure, the number of plasmid copies carried by each cell, and the energetic cost associated with plasmid bearing. By numerically determining the optimal plasmid copy number for constant and fluctuating selection regimes, we show that the stability of multi-copy plasmids is maximized at intermediate plasmid copy numbers. We conclude by arguing that plasmid copy number is a highly optimized evolutionary trait that depends on the rate of environmental fluctuation and balances the benefit between increased stability in the absence of selection with the burden associated with carrying multiple copies of the plasmid.
Lineage tracing via associative chromosome/plasmid barcoding with siBar

We describe a new method, siBar, which enables simultaneous tracking of plasmids and chromosomal lineages within a bacterial host. siBar involves integration of a linearized plasmid construct carrying a unique combination of two molecular barcodes. Upon recircularization one barcode remains integrated into the host chromosome, while the other remains on the plasmid allowing direct observation of expansion and contraction of adaptive lineages. We also performed a pilot evolution experiment that allowed us to assess the barcode complexity and establish an analytical framework for the analysis of siBar data.
Temporal Dynamics of Competition between Statistical Learning and Episodic Memory in Intracranial Recordings of Human Visual Cortex

The function of long-term memory is not just to reminisce about the past, but also to make predictions that help us behave appropriately and efficiently in the future. This predictive function of memory provides a new perspective on the classic question from memory research of why we remember some things but not others. If prediction is a key outcome of memory, then the extent to which an item generates a prediction signifies that this information already exists in memory and need not be encoded. We tested this principle using human intracranial EEG as a time-resolved method to quantify prediction in visual cortex during a statistical learning task and link the strength of these predictions to subsequent episodic memory behavior. Epilepsy patients of both sexes viewed rapid streams of scenes, some of which contained regularities that allowed the category of the next scene to be predicted. We verified that statistical learning occurred using neural frequency tagging and measured category prediction with multivariate pattern analysis. Although neural prediction was robust overall, this was driven entirely by predictive items that were subsequently forgotten. Such interference provides a mechanism by which prediction can regulate memory formation to prioritize encoding of information that could help learn new predictive relationships. SIGNIFICANCE STATEMENT When faced with a new experience, we are rarely at a loss for what to do. Rather, because many aspects of the world are stable over time, we rely on past experiences to generate expectations that guide behavior. Here we show that these expectations during a new experience come at the expense of memory for that experience. From intracranial recordings of visual cortex, we decoded what humans expected to see next in a series of photographs based on patterns of neural activity. Photographs that generated strong neural expectations were more likely to be forgotten in a later behavioral memory test. Prioritizing the storage of experiences that currently lead to weak expectations could help improve these expectations in future encounters.