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Le Troter, A.

Publications and source records attributed to Le Troter, A..

4 recordsLinked to original sources

Longitudinal neuromelanin changes in prodromal and early Parkinson's disease in humans and rat model

Studies in animal models of Parkinsons disease (PD) suggested that the accumulation of the neuromelanin (NM), a pigment contained in nigral dopaminergic neurons, could trigger neurodegeneration above a pathogenic threshold. Here we investigated this hypothesis using NM-sensitive MRI in rodents and in patients with isolated rapid eye movement sleep disorders (iRBD) subjects, a prodromal phase of parkinsonism, and early PD. We first combined NM-sensitive MRI and histology to study NM accumulation and neurodegeneration in a humanized rat model of PD. NM-MRI signal changes were biphasic with an initial increase due to the accumulation of NM in dopaminergic neurons, followed signal decrease due to neurodegeneration. In healthy subjects and patients with iRBD, NM-MRI signal increased initially and then decreased similarly as in rodents after reaching a similar maximum signal intensity in both groups. In early PD and converted iRBD patients, NM-MRI signal drop was greater than in healthy individuals. Results in animals and humans show that NM-sensitive MRI is a marker of the intracellular NM accumulation up to a threshold then of neuronal degeneration beyond this threshold and agree with the hypothesis of a pathogenic threshold of NM triggering neurodegeneration.

neuroscience↗

Multi-scale structural alterations of basal ganglia in focal epilepsy as demonstrated by 7T MRI

Focal epilepsy is characterized by repeated spontaneous seizures that originate from cortical epileptogenic zone networks (EZN). More recently, analysis of intracerebral recordings showed that subcortical structures, and in particular the thalamus, play an important role in facilitating and/or propagating epileptic activity. This supports previously reported structural alterations of these structures. Nonetheless, between-patient differences in EZN (e.g., temporal vs. non-temporal lobe epilepsy) as well as other clinical features (e.g., number of epileptogenic regions) might impact the magnitude as well as spatial distribution of subcortical structural changes. Here we used 7 Tesla MRI T1 data to provide a comprehensive description of subcortical morphological (volume, tissue deformation, and shape) and longitudinal relaxation (T1) changes in focal epilepsy patients to evaluate the impact of the EZN and patient-specific clinical features. Our results showed widespread morphometric and T1 changes. Focusing on the thalamus, atrophy varied across nuclei but appeared most prominent for the TLE group and the ipsilateral side, while shortening of T1 was observed for the lateral thalamus, in particular. Multivariate analyses across thalamic nuclei and basal ganglia showed that volume acted as the dominant discriminator between patients and controls, while (posterolateral) thalamic T1 measures looked promising to further differentiate patients based on EZN. In particular, the observed differences in T1 changes between thalamic nuclei indicated differential involvement of thalamic nuclei based on EZN. Finally, the number of epileptogenic regions was found to best explain the observed variability between patients. To conclude, this work revealed multi-scale subcortical alterations in focal epilepsy as well as their dependence on several clinical characteristics. Our results provide a basis for further, in-depth investigations using (quantitative) MRI and SEEG data and warrant further personalization of intervention strategies, such as deep brain stimulation, for treating focal epilepsy patients.

neuroscience↗

A Motion Correction Strategy for Multi-Contrast based 3D parametric imaging: Application to Inhomogeneous Magnetization Transfer (ihMT)

PurposeTo propose an efficient retrospective image-based method for motion correction of multi-contrast acquisitions with a low number of available images (MC-MoCo) and evaluate its use in 3D inhomogeneous Magnetization Transfer (ihMT) experiments in the human brain. MethodsA framework for motion correction, including image pre-processing enhancement and rigid registration to an iteratively improved target image, was developed. The proposed method was compared to Motion Correction with FMRIBs Linear Image Registration Tool (MCFLIRT) function in FSL over 13 subjects. Native (pre-correction) and residual (post-correction) motions were evaluated by means of markers positioned at well-defined anatomical regions over each image. ResultsBoth motion correction strategies significantly reduced inter-image misalignment, and the MC-MoCo method yielded significantly better results than MCFLIRT. ConclusionMC-MoCo is a high-performance method for motion correction of multi-contrast volumes as in 3D ihMT imaging.

neuroscience↗

Modular slowing of resting-state dynamic Functional Connectivity as a marker of cognitive dysfunction induced by sleep deprivation

Dynamic Functional Connectivity (dFC) in the resting state (rs) is considered as a correlate of cognitive processing. Describing dFC as a flow across morphing connectivity configurations, our notion of dFC speed quantifies the rate at which FC networks evolve in time. Here we probe the hypothesis that variations of rs dFC speed and cognitive performance are selectively interrelated within specific functional subnetworks. In particular, we focus on Sleep Deprivation (SD) as a reversible model of cognitive dysfunction. We found that whole-brain level (global) dFC speed significantly slows down after 24h of SD. However, the reduction in global dFC speed does not correlate with variations of cognitive performance in individual tasks, which are subtle and highly heterogeneous. On the contrary, we found strong correlations between performance variations in individual tasks -including Rapid Visual Processing (RVP, assessing sustained visual attention)- and dFC speed quantified at the level of functional subnetworks of interest. Providing a compromise between classic static FC (no time) and global dFC (no space), modular dFC speed analyses allow quantifying a different speed of dFC reconfiguration independently for sub-networks overseeing different tasks. Importantly, we found that RVP performance robustly correlates with the modular dFC speed of a characteristic frontoparietal module. HighlightsO_LISleep Deprivation (SD) slows down the random walk in FC space implemented by Dynamic Functional Connectivity (dFC) at rest. C_LIO_LIWhole-brain level slowing of dFC speed does not selectively correlate with fine and taskspecific changes in performance C_LIO_LIWe quantify dFC speed separately for different link-based modules coordinated by distinct regional "meta-hubs" C_LIO_LIModular dFC speed variations capture subtle and task-specific variations of cognitive performance induced by SD. C_LI Author summaryWe interpreted dynamic Functional Connectivity (dFC) as a random walk in the space of possible FC networks performed with a quantifiable "speed". Here, we analyze a fMRI dataset in which subjects are scanned and cognitively tested both before and after Sleep Deprivation (SD), used as a reversible model of cognitive dysfunction. While global dFC speed slows down after a sleepless night, it is not a sufficiently sensitive metric to correlate with fine and specific cognitive performance changes. To boost the capacity of dFC speed analyses to account for fine and specific cognitive decline, we introduce the notion of modular dFC speed. Capitalizing on an edge-centric measure of functional connectivity, which we call Meta-Connectivity, we isolate subgraphs of FC describing relatively independent random walks (dFC modules) and controlled by distinct "puppet masters" (meta-hubs). We then find that variations of the random walk speed of distinct dFC modules now selectively correlate with SD-induced variations of performance in the different tasks. This is in agreement with the fact that different subsystems - distributed but functionally distinct- oversee different tasks. The high sensitivity of modular dFC analyses bear promise of future applications to the early detection and longitudinal characterization of pathologies such as Alzheimers disease.

neuroscience↗