Search results for "Cognition"

Lipid Mediators in the Regulation of Emotions, Memory, and Cognitive Functions

2017

This chapter aims at highlighting the diverse roles of endocannabinoids in the coordination of balanced neuronal activities, which finally set the basis for the organism’s characteristics to store and remember important and useful things, to forget non-useful things, and to cope with new challenges. Altogether, the fine-tuned regulation of these processes is crucial for optimal life and survival. The endocannabinoid system appears to be a central intrinsic homeostatic factor in the organism, modulating these processes. Receptors for (endo)cannabinoids are also targets for exogenous cannabinoids, putting also relevance of external substances in the interference with these processes. The gene…

Disease–Genes Must Guide Data Source Integration in the Gene Prioritization Process

2019

One of the main issues in detecting the genes involved in the etiology of genetic human diseases is the integration of different types of available functional relationships between genes. Numerous approaches exploited the complementary evidence coded in heterogeneous sources of data to prioritize disease-genes, such as functional profiles or expression quantitative trait loci, but none of them to our knowledge posed the scarcity of known disease-genes as a feature of their integration methodology. Nevertheless, in contexts where data are unbalanced, that is, where one class is largely under-represented, imbalance-unaware approaches may suffer a strong decrease in performance. We claim that …

Toll-like receptors in neuroinflammation, neurodegeneration, and alcohol-induced brain damage

2021

Toll-like receptors (TLRs) or pattern recognition receptors respond to pathogen-associated molecular patterns (PAMPs) or internal damage-associated molecular patterns (DAMPs). TLRs are integral membrane proteins with both extracellular leucine-rich and cytoplasmic domains that initiate downstream signaling through kinases by activating transcription factors like AP-1 and NF-κB, which lead to the release of various inflammatory cytokines and immune modulators. In the central nervous system, different TLRs are expressed mainly in microglia and astroglial cells, although some TLRs are also expressed in oligodendroglia and neurons. Activation of TLRs triggers signaling cascades by the host as a…

2018

The expertise of humans for recognizing faces is largely based on holistic processing mechanism, a sophisticated cognitive process that develops with visual experience. The various visual features of a face are thus glued together and treated by the brain as a unique stimulus, facilitating robust recognition. Holistic processing is known to facilitate fine discrimination of highly similar visual stimuli, and involves specialized brain areas in humans and other primates. Although holistic processing is most typically employed with face stimuli, subjects can also learn to apply similar image analysis mechanisms when gaining expertise in discriminating novel visual objects, like becoming exper…

Application of Graph Clustering and Visualisation Methods to Analysis of Biomolecular Data

2018

In this paper we present an approach based on integrated use of graph clustering and visualisation methods for semi-supervised discovery of biologically significant features in biomolecular data sets. We describe several clustering algorithms that have been custom designed for analysis of biomolecular data and feature an iterated two step approach involving initial computation of thresholds and other parameters used in clustering algorithms, which is followed by identification of connected graph components, and, if needed, by adjustment of clustering parameters for processing of individual subgraphs.

Improving Docking Performance Using Negative Image-Based Rescoring

2017

Despite the large computational costs of molecular docking, the default scoring functions are often unable to recognize the active hits from the inactive molecules in large-scale virtual screening experiments. Thus, even though a correct binding pose might be sampled during the docking, the active compound or its biologically relevant pose is not necessarily given high enough score to arouse the attention. Various rescoring and post-processing approaches have emerged for improving the docking performance. Here, it is shown that the very early enrichment (number of actives scored higher than 1% of the highest ranked decoys) can be improved on average 2.5-fold or even 8.7-fold by comparing th…

L’adaptation optimale du mouvement humain au milieu gravitaire

2017

International audience

Network-Wide Adaptive Burst Detection Depicts Neuronal Activity with Improved Accuracy

2017

Neuronal networks are often characterized by their spiking and bursting statistics. Previously, we introducedan adaptive burst analysis methodwhich enhances the analysis power for neuronal networks with highly varying firing dynamics. The adaptation is based on single channels analyzing each element of a network separately. Such kind of analysis was adequate for the assessment of local behavior, where the analysis focuses on the neuronal activity in the vicinity of a single electrode. However, the assessment of the whole network may be hampered, if parts of the network are analyzed using different rules. Here, we test how using multiple channels and measurement time points affect adaptive b…

Automatic detection of hemangiomas using unsupervised segmentation of regions of interest

2016

In this paper we compare the performances of three automatic methods of identifying hemangioma regions in images: 1) unsupervised segmentation using the Otsu method, 2) Fuzzy C-means clustering (FCM) and 3) an improved region growing algorithm based on FCM (RG-FCM). For each image, the starting point of the algorithms is a rectangular region of interest (ROI) containing the hemangioma. For computing the performances of each method, the ROIs had been manually labeled in 2 classes: pixels of hemangioma and pixels of non-hemangioma. The computed scores are given separately for each image, as well as global performances across all ROIs for both classes. The best classification of non-hemangioma…

Deep learning network for exploiting positional information in nucleosome related sequences

2017

A nucleosome is a DNA-histone complex, wrapping about 150 pairs of double-stranded DNA. The role of nucleosomes is to pack the DNA into the nucleus of the Eukaryote cells to form the Chromatin. Nucleosome positioning genome wide play an important role in the regulation of cell type-specific gene activities. Several biological studies have shown sequence specificity of nucleosome presence, clearly underlined by the organization of precise nucleotides substrings. Taking into consideration such advances, the identification of nucleosomes on a genomic scale has been successfully performed by DNA sequence features representation and classical supervised classification methods such as Support Vec…