Automatic Generation of Connectivity for Large-Scale Neuronal Network Models through Structural Plasticity

With the emergence of new high performance computation technology in the last decade, the simulation of large scale neural networks which are able to reproduce the behavior and structure of the brain has finally become an achievable target of neuroscience. Due to the number of synaptic connections between neurons and the complexity of biological networks, most contemporary models have manually defined or static connectivity. However, it is expected that modeling the dynamic generation and deletion of the links among neurons, locally and between different regions of the brain, is crucial to unravel important mechanisms associated with learning, memory and healing. Moreover, for many neural circuits that could potentially be modeled, activity data is more readily and reliably available than connectivity data. Thus, a framework that enables networks to wire themselves on the basis of specified activity targets can be of great value in specifying network models where connectivity data is incomplete or has large error margins. To address these issues, in the present work we present an implementation of a model of structural plasticity in the neural network simulator NEST. In this model, synapses consist of two parts, a pre- and a post-synaptic element. Synapses are created and deleted during the execution of the simulation following local homeostatic rules until a mean level of electrical activity is reached in the network. We assess the scalability of the implementation in order to evaluate its potential usage in the self generation of connectivity of large scale networks. We show and discuss the results of simulations on simple two population networks and more complex models of the cortical microcircuit involving 8 populations and 4 layers using the new framework

Connectivité fonctionnelle cérébrale pendant l'état de repos (modélisation multi-échelle)

CAEN-BU Médecine pharmacie (141182102) / SudocSudocFranceF

Approach in green, avoid in red? Examining interindividual variabilities and personal color preferences through continuous measures of specific meaning associations

International audienc

Approach in green, avoid in red? Examining interindividual variabilities and personal color preferences through continuous measures of specific meaning associations

International audienc

Grey matter volume and CSF biomarkers predict neuropsychological subtypes of MCI

We demonstrated that mild cognitive impairment (MCI) participants of the ADNI database (N=640)can be discriminated into 3 coherent and neuropsychologically-defined subgroups. Our clusteringapproach revealed an amnestic MCI, a mixed MCI and a false positive subgroup. Furthermore, weinvestigated the neurobiological foundation of these automatically extracted MCI subgroups.Classification modelling exposed that specific predictive features can be used to differentiateamnestic and mixed MCI from healthy controls: CSF Aβ1-42 concentration for the former and CSF Aβ1-42concentration, tau concentration as well as cortical atrophies (especially in the temporal and occipitallobes) for the latter. In contrast, false positive participants exhibited an identical profile to healthyparticipants in terms of cognitive performance, brain structure and CSF biomarker levels. Ourcomprehensive data-analytics strategy provide further evidence that multimodal neuropsychologicalsubtyping is both clinically and neurobiologically meaningful

Grey matter volume and CSF biomarkers predict neuropsychological subtypes of MCI

We demonstrated that mild cognitive impairment (MCI) participants of the ADNI database (N=640)can be discriminated into 3 coherent and neuropsychologically-defined subgroups. Our clusteringapproach revealed an amnestic MCI, a mixed MCI and a false positive subgroup. Furthermore, weinvestigated the neurobiological foundation of these automatically extracted MCI subgroups.Classification modelling exposed that specific predictive features can be used to differentiateamnestic and mixed MCI from healthy controls: CSF Aβ1-42 concentration for the former and CSF Aβ1-42concentration, tau concentration as well as cortical atrophies (especially in the temporal and occipitallobes) for the latter. In contrast, false positive participants exhibited an identical profile to healthyparticipants in terms of cognitive performance, brain structure and CSF biomarker levels. Ourcomprehensive data-analytics strategy provide further evidence that multimodal neuropsychologicalsubtyping is both clinically and neurobiologically meaningful

Identification of biological targets for argon

CERVOXYNational audienc

Identification of biological targets for argon

CERVOXYNational audienc

A method for the identification of potentially bioactive argon binding sites in protein families

CERVOXYInternational audienceArgon belongs to the group of chemically inert noble gases, which display a remarkable spectrum of clinically useful biological properties. In an attempt to better understand noble gases, notably argon's mechanism of action, we mined a massive noble gas modelling database which lists all possible noble gas binding sites in the proteins from the Protein Data Bank. We developed a method of analysis to identify amongst all predicted noble gas binding sites, the potentially relevant ones within protein families which are likely to be modulated by Ar. Our method consists in determining within structurally aligned proteins, the conserved binding sites whose shape, localization, hydrophobicity and binding energies are to be further examined. This method was applied to the analysis of two protein families where crystallographic noble gas binding sites have been experimentally determined. Our findings indicate that amongst the most conserved binding sites, either the most hydrophobic one and/or the site which has the best binding energy correspond to the crystallographic noble gas binding sites with the best occupancies, therefore the best affinity for the gas. This method will allow us to predict relevant noble gas binding sites that have potential pharmacological interest and thus potential Ar targets that will be prioritized for further studies including in vitro validation

Contrôle et correction des variables physiologiques en IRM fonctionnelle cérébrale chez l'homme et le rat anesthésié

International audienceL’Imagerie par Résonance Magnétique fonctionnelle de repos (rs-fMRI) est une méthode utilisée pour explorer la connectivité fonctionnelle cérébrale aussi bien chez l’homme que chez l’animal. Le faible rapport signal sur bruit de cette méthode nécessite de corriger les données des sources de signal de non-intérêt. Dans cette étude nous nous sommes particulièrement intéressés aux techniques de correction des bruits physiologiques provenant de la variabilité cardio-respiratoire. Nous avons évalué leur impact à la fois chez l’homme et le rat anesthésié dans l’interprétation cognitive des résultats