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The NAROO program has been created at Paris Observatory, Meudon, as a unique centre dedicated to the digitization and the analysis of old astro-photographic plates for scientific purposes, only. The NAROO digitizer consists of a granite-based Newport-Microcontrol open frame air-bearing XY positioning table, a scientific sCMOS camera, and a telecentric optical system. The machine is placed in an overpressure, air-conditioned, ISO-5 clean room to maintain its positioning stability better than 15doi:10.5281/zenodo.7068439 fatcat:vccubqz5r5antdg6lqbsirg4vm
more »... m, and its accuracy better than 65 nm. The renewed interest about photographic plates concerns the expansion of the database of transient objects evolving in time, since 1) digitization now makes it possible to measure images with a high level of accuracy and to identify all the available objects, 2) the arrival of the Gaia reference catalogs allows to realize reductions for past observations with today accuracy. The information extracted from such materials can be of an astrometric, photometric, and spectroscopic nature, when not purely imaging, with consequences in planetology, near-Earth asteroid risk assessment, astrophysical phenomena, and general relativity, to mention but a few. Since we invite researchers to use our facilities and digitize their collection (free of charge), we detail current and upcoming uses for the community: precoveries, small bodies, planetary satellites, Sun, Be stars, SMC and LMC observations for example.
Springer Proceedings in Mathematics & Statistics
Computer simulations have played a critical role in functional magnetic resonance imaging (fMRI) research, notably in the validation of new data analysis methods. Many approaches have been used to generate fMRI simulations, but there is currently no generic framework to assess how realistic each one of these approaches may be. In this article, a statistical technique called parametric bootstrap was used to generate a simulation database that mimicked the parameters found in a real database,doi:10.1016/j.mri.2009.05.034 pmid:19570641 pmcid:PMC2783846 fatcat:jdmmr6wokjghxeklp3xhxklvem
more »... h comprised 40 subjects and five tasks. The simulations were evaluated by comparing the distributions of a battery of statistical measures between the real and simulated databases. Two popular simulation models were evaluated for the first time by applying the bootstrap framework. The first model was an additive mixture of multiple components and the second one implemented a non-linear motion process. In both models, the simulated components included the following brain dynamics: a baseline, physiological noise, neural activation and random noise. These models were found to successfully reproduce the relative variance of the components and the temporal autocorrelation of the fMRI time series. By contrast, the level of spatial autocorrelation was found to be drastically low using the additive model. Interestingly, the motion process in the second model intrisically generated some slow time drifts and increased the level of spatial autocorrelations. These experiments demonstrated that the bootstrap framework is a powerful new tool that can pinpoint the respective strengths and limitations of simulation models.
Brain and Language
Group representative large-scale networks were extracted for each fMRI session and for both healthy controls and participants with aphasia using sICA (Perlbarg et al., 2008) as implemented in NetBrainWork ...doi:10.1016/j.bandl.2012.11.004 pmid:23274798 fatcat:5plldp4gevbp5dpkhdfuxbj64a
Primary objective-Paroxysmal sympathetic hyperactivity (PSH) is observed in a sub-set of patients with moderate-to-severe traumatic brain injury (TBI). The neuroanatomical basis of PSH is poorly understood. It is hypothesized that PSH is linked to changes in connectivity within the central autonomic network. Research design-Retrospective analysis in a sub-set of patients from a multi-centre, prospective cohort study Methods and procedures-Adult patients who were <3 weeks after severe TBI weredoi:10.3109/02699052.2014.995229 pmid:25565392 pmcid:PMC4397147 fatcat:47rxubkwdfee7c4zbyzf3372pe
more »... rolled and screened for PSH using a standard definition. Patients underwent multimodal MRI, which included quantitative diffusion tensor imaging. Main outcomes and results-Principal component analysis (PCA) was used to resolve the set of tracts into components. Ability to predict PSH was evaluated via area under the receiver operating characteristic (AUROC) and tree-based classification analyses. Among 102 enrolled patients, 16 met criteria for PSH. The first principle component was significantly associated (p =
Motor skill learning is associated with profound changes in brain activation patterns over time. Associative and rostral premotor cortical and subcortical regions are mostly recruited during the early phase of explicit motor learning, while sensorimotor regions may increase their activity during the late learning phases. Distinct brain networks are therefore engaged during the early and late phases of motor skill learning. How these regions interact with one another and how information isdoi:10.1016/j.neuroimage.2009.08.048 pmid:19716894 pmcid:PMC2764831 fatcat:q3gqkx5cozh3ng36qbhqeisa3i
more »... erred from one circuit to the other has been less extensively studied. In this study, we used functional MRI (fMRI) at 3T to follow the changes in functional connectivity in the associative/ premotor and the sensorimotor networks, during extended practice (four weeks) of an explicitly known sequence of finger movements. Evolution of functional connectivity was assessed using integration, a measure that quantifies the total amout of interaction within a network. When comparing the integration associated with a complex finger movement sequence to that associated with a simple sequence, we observed two patterns of decrease during the four weeks of practice. One was not specific as it was observed for all sequences, whereas a specific decrease was observed only for the execution of the learned sequence. This second decrease was a consequence of a relative decrease in associative/premotor network integration, together with a relative increase in betweennetwork integration. These findings are in line with the hypothesis that information is transferred from the associative/premotor circuit to the sensorimotor circuit during the course of motor learning.
Citation: Mesmoudi S, Perlbarg V, Rudrauf D, Messe A, Pinsard B, et al. (2013) Resting State Networks' Corticotopy: The Dual Intertwined Rings Architecture. PLoS ONE 8(7): e67444. ...doi:10.1371/journal.pone.0067444 pmid:23894288 pmcid:PMC3722222 fatcat:fix2tg3ienahlj3kzzyhqhurcq
A group t-map was associated with each selected class (Perlbarg et al., 2008) . ... S1 , Damoiseaux et al., 2006; Perlbarg et al., 2008) . Two were heavily loaded by primary or unimodal associative sensory or motor cortices, such as the visual (VIS) and the motor (MOT) networks. ...doi:10.1016/j.neuroimage.2011.04.020 pmid:21524704 fatcat:nkgbtumcwrba7er7g25utmchqq
Brain and Language
In this work we focus on examination and comparison of whole-brain functional connectivity patterns measured with fMRI across experimental conditions. Direct examination and comparison of condition-specific matrices is challenging due to the large number of elements in a connectivity matrix. We present a framework that uses network analysis to describe condition-specific functional connectivity. Treating the brain as a complex system in terms of a network, we extract the most relevantdoi:10.1016/j.bandl.2012.11.008 pmid:23274799 fatcat:tzn3pmnidfenhnbyxbicobdqp4
more »... ty information by partitioning each network into clusters representing functionally connected brain regions. Extracted clusters are used as features for predicting experimental condition in a new data set. The approach is illustrated on fMRI data examining functional connectivity patterns during processing of abstract and concrete concepts. Topological (brain regions) and functional (level of connectivity and information flow) systematic differences in the ROI-based functional networks were identified across participants for concrete and abstract concepts. These differences were sufficient for classification of previously unseen connectivity matrices as abstract or concrete based on training data derived from other people.
Perlbarg was involved in analysis and interpretation of data, statistical analysis of data and drafting/revising the manuscript. Dr. ...doi:10.1016/j.nicl.2018.06.011 pmid:29922574 pmcid:PMC6005808 fatcat:pbu2haxehvhzhgtic5f27tuboa
Perlbarg) to isolate the independent components from the raw fMRI data  . It was assumed that most of the cardiac variance would be captured within the first 30 components. ...doi:10.1016/j.mri.2008.07.019 pmid:18801632 fatcat:yer7d7at5vbrjnz7fvy24uc5xy
Heart rate has natural fluctuations that are typically ascribed to autonomic function. Recent evidence suggests that conscious processing can affect the timing of the heartbeat. We hypothesized that heart rate is modulated by conscious processing and therefore dependent on attentional focus. To test this we leverage the observation that neural processes can be synchronized between subjects by presenting an identical narrative stimulus. As predicted, we find significant inter-subject correlationdoi:10.1101/2020.05.26.116079 fatcat:idugyhqbxjadpkh2rtzglojpwi
more »... of the heartbeat (ISC-HR) when subjects are presented with an auditory or audiovisual narrative. Consistent with the conscious processing hypothesis, we find that ISC-HR is reduced when subjects are distracted from the narrative, and that higher heart rate synchronization predicts better recall of the narrative. Finally, patients with disorders of consciousness who are listening to a story have lower ISC, as compared to healthy individuals, and that individual ISC-HR might predict a patients' prognosis. We conclude that heart rate fluctuations are partially driven by conscious processing, depend on attentional state, and may represent a simple metric to assess conscious state in unresponsive patients.
When applied to functional Magnetic Resonance Imaging (fMRI) data, spatial Independent Component Analysis (sICA), a data-driven technique that adresses the blind source separation problem, seems able to extract components specifically related to physiological noise and brain movements. These components should be removed from the data to achieve structured-noise reduction and improve any subsequent detection and analysis of signal fluctuations related to neural activity. We propose a newdoi:10.1016/j.mri.2006.09.042 pmid:17222713 fatcat:l7wh6zvhmraprahflrw36662oy
more »... c method called CORSICA to identify the components related to physiological noise, using prior information on the spatial localization of the main physiological fluctuations in fMRI data. As opposed to existing spectral priors, which may be subject to aliasing effects for long-TR datasets (typically acquired with TR > 1 s), such spatial priors can be applied to fMRI data regardless of the TR of the acquisitions. By comparing the proposed automatic selection to a manual selection performed visually by a human operator, we first show that CORSICA is able to identify the noise-related components for long-TR data with a high sensitivity and a specificity of 1. On short-TR datasets, we validate that the proposed method of noise reduction allows a substantial improvement of the signal-to-noise ratio evaluated at the cardiac and respiratory frequencies, even in the gray matter, while preserving the main fluctuations related to neural activity.
Compliance with ethical standards Conflict of interest Maria del Mar Amador, Marion Masingue, Rabab Debs, Foudil Lamari, Vincent Perlbarg, Emmanuel Roze, Bertrand Degos declare that they have no conflict ...doi:10.1007/s10545-018-0162-7 pmid:29560583 fatcat:og43jqhaybhhpafcgsswhvspue
Motor outcome after stroke is associated with reorganisation of cortical networks and corticospinal tract (CST) integrity. However, the relationships between motor severity, CST damage, and functional brain connectivity are not well understood. Here, the main objective was to study the effect of CST damage on the relationship between functional motor network connectivity and hand motor function in two groups of stroke patients: the severely (n=8) and the mildly impaired (n=14). Methods:doi:10.1371/journal.pone.0073164 pmid:24086272 pmcid:PMC3785485 fatcat:mrnbm4zcinedhlk4blzze4xlqi
more »... wo carotid stroke patients with motor deficits were studied with magnetic resonance imaging (MRI) at 3 weeks, at 3 and 6 months. Healthy subjects (n=28) were scanned once. The CST injury was assessed by fractional anisotropy values. Functional connectivity was studied from a whole-hand grip task fMRI in a cortical and cerebellar motor network. Functional connectivity indexes were computed between these regions at each time point. The relationship between hand motor strength, ipsilesional CST damage and functional connectivity from the primary motor cortex (M1) was investigated using global and partial correlations. Findings: In mildly impaired patients, cortico-cortical connectivity was disturbed at three weeks but returned to a normal pattern after 3 months. Cortico-cerebellar connectivity was still decreased at 6 months. In severely impaired patients, the cortico-cortical connectivity tended to return to a normal pattern, but the cortico-cerebellar connectivity was totally abolished during the follow-up. In the entire group of patients, the hand motor strength was correlated to the ipsilesional functional connectivity from M1. Partial correlations revealed that these associations were not anymore significant when the impact of CST damage was removed, except for the ipsilesional M1-contralateral cerebellum connectivity. Conclusion: Functional brain connectivity changes can be observed, even in severely impaired patients with no recovery. Upper limb function is mainly explained by the CST damage and by the ipsilesional cortico-cerebellar connectivity. Citation: Rosso C, Valabregue R, Attal Y, Vargas P, Gaudron M, et al. (2013) Contribution of Corticospinal Tract and Functional Connectivity in Hand Motor Impairment after Stroke. PLoS ONE 8(9): e73164.
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