66 research outputs found
Large-scale signatures of unconsciousness are consistent with a departure from critical dynamics
Loss of cortical integration and changes in the dynamics of
electrophysiological brain signals characterize the transition from wakefulness
towards unconsciousness. The common mechanism underlying these observations
remains unknown. In this study we arrive at a basic model, which explains these
empirical observations based on the theory of phase transitions in complex
systems. We studied the link between spatial and temporal correlations of
large-scale brain activity recorded with functional magnetic resonance imaging
during wakefulness, propofol-induced sedation and loss of consciousness, as
well as during the subsequent recovery. We observed that during unconsciousness
activity in frontal and thalamic regions exhibited a reduction of long-range
temporal correlations and a departure of functional connectivity from the
underlying anatomical constraints. These changes in dynamics and
anatomy-function coupling were correlated across participants, suggesting that
temporal complexity and an efficient exploration of anatomical connectivity are
inter-related phenomena. A model of a system exhibiting a phase transition
reproduced our findings, as well as the diminished sensitivity of the cortex to
external perturbations during unconsciousness. This theoretical framework
unifies different empirical observations about brain activity during
unconsciousness and predicts that the principles we identified are universal
and independent of the causes behind loss of awareness.Comment: to appear in Journal of the Royal Society Interfac
Cognitive complaints in older adults at risk for Alzheimer's disease are associated with altered resting-state networks
INTRODUCTION:
Pathophysiological changes that accompany early clinical symptoms in prodromal Alzheimer's disease (AD) may have a disruptive influence on brain networks. We investigated resting-state functional magnetic resonance imaging (rsfMRI), combined with brain connectomics, to assess changes in whole-brain functional connectivity (FC) in relation to neurocognitive variables.
METHODS:
Participants included 58 older adults who underwent rsfMRI. Individual FC matrices were computed based on a 278-region parcellation. FastICA decomposition was performed on a matrix combining all subjects' FC. Each FC pattern was then used as a response in a multilinear regression model including neurocognitive variables associated with AD (cognitive complaint index [CCI] scores from self and informant, an episodic memory score, and an executive function score).
RESULTS:
Three connectivity independent component analysis (connICA) components (RSN, VIS, and FP-DMN FC patterns) associated with neurocognitive variables were identified based on prespecified criteria. RSN-pattern, characterized by increased FC within all resting-state networks, was negatively associated with self CCI. VIS-pattern, characterized by an increase in visual resting-state network, was negatively associated with CCI self or informant scores. FP-DMN-pattern, characterized by an increased interaction of frontoparietal and default mode networks (DMN), was positively associated with verbal episodic memory.
DISCUSSION:
Specific patterns of FC were differently associated with neurocognitive variables thought to change early in the course of AD. An integrative connectomics approach relating cognition to changes in FC may help identify preclinical and early prodromal stages of AD and help elucidate the complex relationship between subjective and objective indices of cognitive decline and differences in brain functional organization
Tangent functional connectomes uncover more unique phenotypic traits
Functional connectomes (FCs) contain pairwise estimations of functional
couplings based on pairs of brain regions activity. FCs are commonly
represented as correlation matrices that are symmetric positive definite (SPD)
lying on or inside the SPD manifold. Since the geometry on the SPD manifold is
non-Euclidean, the inter-related entries of FCs undermine the use of
Euclidean-based distances. By projecting FCs into a tangent space, we can
obtain tangent functional connectomes (tangent-FCs). Tangent-FCs have shown a
higher predictive power of behavior and cognition, but no studies have
evaluated the effect of such projections with respect to fingerprinting. We
hypothesize that tangent-FCs have a higher fingerprint than regular FCs.
Fingerprinting was measured by identification rates (ID rates) on test-retest
FCs as well as on monozygotic and dizygotic twins. Our results showed that
identification rates are systematically higher when using tangent-FCs.
Specifically, we found: (i) Riemann and log-Euclidean matrix references
systematically led to higher ID rates. (ii) In tangent-FCs, Main-diagonal
regularization prior to tangent space projection was critical for ID rate when
using Euclidean distance, whereas barely affected ID rates when using
correlation distance. (iii) ID rates were dependent on condition and fMRI scan
length. (iv) Parcellation granularity was key for ID rates in FCs, as well as
in tangent-FCs with fixed regularization, whereas optimal regularization of
tangent-FCs mostly removed this effect. (v) Correlation distance in tangent-FCs
outperformed any other configuration of distance on FCs or on tangent-FCs
across the fingerprint gradient (here sampled by assessing test-retest,
Monozygotic and Dizygotic twins). (vi)ID rates tended to be higher in task
scans compared to resting-state scans when accounting for fMRI scan length.Comment: 29 pages, 10 figures, 2 table
Optimizing differential identifiability improves connectome predictive modeling of cognitive deficits from functional connectivity in Alzheimer's disease
Functional connectivity, as estimated using resting state functional MRI, has shown potential in bridging the gap between pathophysiology and cognition. However, clinical use of functional connectivity biomarkers is impeded by unreliable estimates of individual functional connectomes and lack of generalizability of models predicting cognitive outcomes from connectivity. To address these issues, we combine the frameworks of connectome predictive modeling and differential identifiability. Using the combined framework, we show that enhancing the individual fingerprint of resting state functional connectomes leads to robust identification of functional networks associated to cognitive outcomes and also improves prediction of cognitive outcomes from functional connectomes. Using a comprehensive spectrum of cognitive outcomes associated to Alzheimer's disease (AD), we identify and characterize functional networks associated to specific cognitive deficits exhibited in AD. This combined framework is an important step in making individual level predictions of cognition from resting state functional connectomes and in understanding the relationship between cognition and connectivity
Upper limb function in Duchenne muscular dystrophy: 24 month longitudinal data
The aim of the study was to establish 24 month changes in upper limb function using a revised version of the performance of upper limb test (PUL 2.0) in a large cohort of ambulant and non-ambulant boys with Duchenne muscular dystrophy and to identify possible trajectories of progression. Of the 187 patients studied, 87 were ambulant (age range: 7\u201315.8 years), and 90 non-ambulant (age range: 9.08\u201324.78). The total scores changed significantly over time (p<0.001). Non-ambulant patients had lower total scores at baseline (mean 19.7) when compared to the ambulant ones (mean 38.4). They also had also a bigger decrease in total scores over 24 months compared to the ambulant boys (4.36 vs 2.07 points). Multivariate model analysis showed that the Performance of Upper Limb changes reflected the entry level and ambulation status, that were independently associated to the slope of Performance of Upper Limb changes. This information will be of help both in clinical practice and at the time of designing clinical trials
Enhanced perioperative care in emergency general surgery:the WSES position paper
Enhanced perioperative care protocols become the standard of care in elective surgery with a significant improvement in patients' outcome. The key element of the enhanced perioperative care protocol is the multimodal and interdisciplinary approach targeted to the patient, focused on a holistic approach to reduce surgical stress and improve perioperative recovery. Enhanced perioperative care in emergency general surgery is still a debated topic with little evidence available. The present position paper illustrates the existing evidence about perioperative care in emergency surgery patients with a focus on each perioperative intervention in the preoperative, intraoperative and postoperative phase. For each item was proposed and approved a statement by the WSES collaborative group.</p
Low loss coatings for the VIRGO large mirrors
présentée par L. PinardThe goal of the VIRGO program is to build a giant Michelson type interferometer (3 kilometer long arms) to detect gravitational waves. Large optical components (350 mm in diameter), having extremely low loss at 1064 nm, are needed. Today, the Ion beam Sputtering is the only deposition technique able to produce optical components with such performances. Consequently, a large ion beam sputtering deposition system was built to coat large optics up to 700 mm in diameter. The performances of this coater are described in term of layer uniformity on large scale and optical losses (absorption and scattering characterization). The VIRGO interferometer needs six main mirrors. The first set was ready in June 2002 and its installation is in progress on the VIRGO site (Italy). The optical performances of this first set are discussed. The requirements at 1064 nm are all satisfied. Indeed, the absorption level is close to 1 ppm (part per million), the scattering is lower than 5 ppm and the R.M.S. wavefront of these optics is lower than 8 nm on 150 mm in diameter. Finally, some solutions are proposed to further improve these performances, especially the absorption level (lower than 0.1 ppm) and the mechanical quality factor Q of the mirrors (thermal noise reduction)
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