The brain signature of paracetamol in healthy volunteers: a double-blind randomized trial

International audienceBackground: Paracetamol’s (APAP) mechanism of action suggests the implication of supraspinal structures but no neuroimaging study has been performed in humans.Methods and results: This randomized, double-blind, crossover, placebo-controlled trial in 17 healthy volunteers (NCT01562704) aimed to evaluate how APAP modulates pain-evoked functional magnetic resonance imaging signals. We used behavioral measures and functional magnetic resonance imaging to investigate the response to experimental thermal stimuli with APAP or placebo administration. Region-of-interest analysis revealed that activity in response to noxious stimulation diminished with APAP compared to placebo in prefrontal cortices, insula, thalami, anterior cingulate cortex, and periaqueductal gray matter.Conclusion: These findings suggest an inhibitory effect of APAP on spinothalamic tracts leading to a decreased activation of higher structures, and a top-down influence on descending inhibition. Further binding and connectivity studies are needed to evaluate how APAP modulates pain, especially in the context of repeated administration to patients with pain

Introducing Soft Topology Constraints in Deep Learning-based Segmentation using Projected Pooling Loss

International audienceDeep learning methods have achieved impressive results for 3D medical image segmentation. However, when the network is only guided by voxel-level information, it may provide anatomically aberrant segmentations. When performing manual segmentations, experts heavily rely on prior anatomical knowledge. Topology is an important prior information due to its stability across patients. Recently, several losses based on persistent homology were proposed to constrain topology. Persistent homology offers a principled way to control topology. However, it is computationally expensive and complex to implement, in particular in 3D. In this paper, we propose a novel loss function to introduce topological priors in deep learning-based segmentation, which is fast to compute and easy to implement. The loss performs a projected pooling within two steps. We first focus on errors from a global perspective by using 3D MaxPooling to obtain projections of 3D data onto three planes: axial, coronal and sagittal. Then, 2D MaxPooling layers with different kernel sizes are used to extract topological features from the multi-view projections. These two steps are combined using only MaxPooling, thus ensuring the efficiency of the loss function. Our approach was evaluated in several medical image datasets (spleen, heart, hippocampus, red nucleus). It allowed reducing topological errors and, in some cases, improving voxel-level accuracy

Fourier Disentangled Multimodal Prior Knowledge Fusion for Red Nucleus Segmentation in Brain MRI

Early and accurate diagnosis of parkinsonian syndromes is critical to provide appropriate care to patients and for inclusion in therapeutic trials. The red nucleus is a structure of the midbrain that plays an important role in these disorders. It can be visualized using iron-sensitive magnetic resonance imaging (MRI) sequences. Different iron-sensitive contrasts can be produced with MRI. Combining such multimodal data has the potential to improve segmentation of the red nucleus. Current multimodal segmentation algorithms are computationally consuming, cannot deal with missing modalities and need annotations for all modalities. In this paper, we propose a new model that integrates prior knowledge from different contrasts for red nucleus segmentation. The method consists of three main stages. First, it disentangles the image into high-level information representing the brain structure, and low-frequency information representing the contrast. The high-frequency information is then fed into a network to learn anatomical features, while the list of multimodal low-frequency information is processed by another module. Finally, feature fusion is performed to complete the segmentation task. The proposed method was used with several iron-sensitive contrasts (iMag, QSM, R2*, SWI). Experiments demonstrate that our proposed model substantially outperforms a baseline UNet model when the training set size is very small

The sooner the better: clinical and neural correlates of impulsive choice in Tourette disorder.

Reward sensitivity has been suggested as one of the central pathophysiological mechanisms in Tourette disorder. However, the subjective valuation of a reward by introduction of delay has received little attention in Tourette disorder, even though it has been suggested as a trans-diagnostic feature of numerous neuropsychiatric disorders. We aimed to assess delay discounting in Tourette disorder and to identify its brain functional correlates. We evaluated delayed discounting and its brain functional correlates in a large group of 54 Tourette disorder patients and 31 healthy controls using a data-driven approach. We identified a subgroup of 29 patients with steeper reward discounting, characterised by a higher burden of impulse-control disorders and a higher level of general impulsivity compared to patients with normal behavioural performance or to controls. Reward discounting was underpinned by resting-state activity of a network comprising the orbito-frontal, cingulate, pre-supplementary motor area, temporal and insular cortices, as well as ventral striatum and hippocampus. Within this network, (i) lower connectivity of pre-supplementary motor area with ventral striatum predicted a higher impulsivity and a steeper reward discounting and (ii) a greater connectivity of pre-supplementary motor area with anterior insular cortex predicted steeper reward discounting and more severe tics. Overall, our results highlight the heterogeneity of the delayed reward processing in Tourette disorder, with steeper reward discounting being a marker of burden in impulsivity and impulse control disorders, and the pre-supplementary motor area being a hub region for the delay discounting, impulsivity and tic severity

Brain correlates of apathy in Kleine Levin syndrome: a mean apparent propagator study

International audienceSynopsis Kleine-Levin syndrome (KLS) is a rare neurological disorder characterized by episodes of severe hypersomnia, apathy, cognitive impairment, derealization and behavioral disturbances. Between episodes, patients have normal sleep, mood and behavior. Apathy is a prominent clinical feature of KLS but its pathophysiology is not known. Here we used mean apparent propagator to investigate white matter changes in KLS and correlated diffusion changes with apathy scores. Results showed that the corpus callosum was involved in KLS during episodes and mean RTAP measures in the corpus callosum correlated with apathy scores. Results were in accordance with known motivation-based circuits involving the orbitomedial frontal cortex. Purpose Kleine-Levin syndrome (KLS) is a rare neurological disorder that mainly affects adolescents. KLS is characterized by relapsing-remitting episodes of severe hypersomnia, apathy, cognitive impairment, derealization and behavioral disturbances. Between episodes, patients have normal sleep, mood and behavior [1]. Each episode is of brief duration varying from a week to 1-2 months. No definite cause has been identified [1]. Anatomical MRI scan is normal, but brain scintigraphy can be abnormal during and between episodes [2]. Apathy is a prominent clinical feature of KLS [3] but its pathophysiology in the disease remains to be established. The mechanisms responsible for apathy may involve several circuits connecting the frontal lobes to the basal ganglia [4]. Here, we performed TBSS analyses on the return-to-the-axis probability (RTAP) measures that may be linked to apparent axonal diameter and inflammation [5] to analyze the integrity of white matter (WM) microstructure of healthy volunteers (HV) compared to symptomatic (KLS-S) and asymptomatic (KLS-AS) patients. Methods We prospectively included 20 KLS-AS (mean age: 22.2 ± 8.9 years, 9 males) and 20 HV age and sex-matched one by one. Twelve of these 20 patients were also scanned during episodes (KLS-S). Apathy was assessed using the Starkstein Apathy score [6]. Diffusion-weighted images were acquired using a Siemens Verio 3T with a 12-channel head coil (GRAPPA=2; TR/TE=7.7s/92ms; voxel size: 2.5mm isotropic; 64, 32 and 8 gradient directions for b-values of 1800, 700, and 300 s/mm² respectively) and 8 images without diffusion weighting were also acquired. We preprocessed the images using FSL (fsl.fmrib.ox.ac.uk/fsl/fslwiki/) and included correction for susceptibility (topup) and for eddy current distortions (eddycor) and creation of a binary mask of the brain (bet). Then, we generated RTAP maps of all subjects [7]. Voxelwise statistical analyses were carried out using TBSS, part of the FSL comparing RTAP maps of HV versus KLS-AS, HV versus KLS-S and KLS-AS versus KLS-S (paired t-test). Finally, in the TBSS-based ROI, we computed correlations between clinical scores (disease duration and apathy scores) and mean RTAP measures in this ROI and performed tractography on one healthy subject to determine its projection fibers. Results were considered significant at p<0.05, fully corrected for multiple comparisons across space. Results There were no significant differences in RTAP between HV and KLS-AS. In KLS-S compared to KLS-AS, RTAP increased in the corpus callosum (CC). There was a correlation between apathy scores and mean RTAP in the CC of KLS-S (p=0.03, r=0.61) (see Figure 2). There were no other correlations with clinical scores in KLS-AS as well as in KLS-S. Using the TBSS-ROI as a seed for tractography, fibers passing through the CC with abnormal RTAP measures projected to medial orbitofrontal cortex (see Figure 3). Discussion and conclusion The results highlight the presence of structural changes correlated to the apathy score in the anterior portion of the CC during episodes, a region where fibers project onto the medial orbitofrontal cortex. As, these prefrontal regions are involved in motivation processes [4], this suggests that apathy in KLS could result from difficulties to provide the affective/motivational value of a given behavioral context

Cerebellar and basal ganglia structural connections in humans: Effect of aging and relation with memory and learning

IntroductionThe cerebellum and basal ganglia were initially considered anatomically distinct regions, each connected via thalamic relays which project to the same cerebral cortical targets, such as the motor cortex. In the last two decades, transneuronal viral transport studies in non-human primates showed bidirectional connections between the cerebellum and basal ganglia at the subcortical level, without involving the cerebral cortical motor areas. These findings have significant implications for our understanding of neurodevelopmental and neurodegenerative diseases. While these subcortical connections were established in smaller studies on humans, their evolution with natural aging is less understood.MethodsIn this study, we validated and expanded the previous findings of the structural connectivity within the cerebellum-basal ganglia subcortical network, in a larger dataset of 64 subjects, across different age ranges. Tractography and fixel-based analysis were performed on the 3 T diffusion-weighted dataset using Mrtrix3 software, considering fiber density and cross-section as indicators of axonal integrity. Tractography of the well-established cerebello-thalamo-cortical tract was conducted as a control. We tested the relationship between the structural white matter integrity of these connections with aging and with the performance in different domains of Addenbrooke’s Cognitive Examination.ResultsTractography analysis isolated connections from the dentate nucleus to the contralateral putamen via the thalamus, and reciprocal tracts from the subthalamic nucleus to the contralateral cerebellar cortex via the pontine nuclei. Control tracts of cerebello-thalamo-cortical tracts were also isolated, including associative cerebello-prefrontal tracts. A negative linear relationship was found between the fiber density of both the ascending and descending cerebellum-basal ganglia tracts and age. Considering the cognitive assessments, the fiber density values of cerebello-thalamo-putaminal tracts correlated with the registration/learning domain scores. In addition, the fiber density values of cerebello-frontal and subthalamo-cerebellar (Crus II) tracts correlated with the cognitive assessment scores from the memory domain.ConclusionWe validated the structural connectivity within the cerebellum-basal ganglia reciprocal network, in a larger dataset of human subjects, across wider age range. The structural features of the subcortical cerebello-basal ganglia tracts in human subjects display age-related neurodegeneration. Individual morphological variability of cerebellar tracts to the striatum and prefrontal cortex was associated with different cognitive functions, suggesting a functional contribution of cerebellar tracts to cognitive decline with aging. This study offers new perspectives to consider the functional role of these pathways in motor learning and the pathophysiology of movement disorders involving the cerebellum and striatum

Impulsive prepotent actions and tics in Tourette disorder underpinned by a common neural network.

Tourette disorder (TD), which is characterized by motor and vocal tics, is not in general considered as a product of impulsivity, despite a frequent association with attention deficit hyperactivity disorder and impulse control disorders. It is unclear which type of impulsivity, if any, is intrinsically related to TD and specifically to the severity of tics. The waiting type of motor impulsivity, defined as the difficulty to withhold a specific action, shares some common features with tics. In a large group of adult TD patients compared to healthy controls, we assessed waiting motor impulsivity using a behavioral task, as well as structural and functional underpinnings of waiting impulsivity and tics using multi-modal neuroimaging protocol. We found that unmedicated TD patients showed increased waiting impulsivity compared to controls, which was independent of comorbid conditions, but correlated with the severity of tics. Tic severity did not account directly for waiting impulsivity, but this effect was mediated by connectivity between the right orbito-frontal cortex with caudate nucleus bilaterally. Waiting impulsivity in unmedicated patients with TD also correlated with a higher gray matter signal in deep limbic structures, as well as connectivity with cortical and with cerebellar regions on a functional level. Neither behavioral performance nor structural or functional correlates were related to a psychometric measure of impulsivity or impulsive behaviors in general. Overall, the results suggest that waiting impulsivity in TD was related to tic severity, to functional connectivity of orbito-frontal cortex with caudate nucleus and to structural changes within limbic areas

Clinically Meaningful <scp>Magnetic Resonance</scp> Endpoints Sensitive to Preataxic Spinocerebellar Ataxia Types <scp>1</scp> and <scp>3</scp>

International audienceObjective: This study was undertaken to identify magnetic resonance (MR) metrics that are most sensitive to early changes in the brain in spinocerebellar ataxia type 1 (SCA1) and type 3 (SCA3) using an advanced multimodal MR imaging (MRI) protocol in the multisite trial setting. Methods: SCA1 or SCA3 mutation carriers and controls (n = 107) underwent MR scanning in the US-European READISCA study to obtain structural, diffusion MRI, and MR spectroscopy data using an advanced protocol at 3T. Morphometric, microstructural, and neurochemical metrics were analyzed blinded to diagnosis and compared between preataxic SCA (n = 11 SCA1, n = 28 SCA3), ataxic SCA (n = 14 SCA1, n = 37 SCA3), and control (n = 17) groups using nonparametric testing accounting for multiple comparisons. MR metrics that were most sensitive to preataxic abnormalities were identified using receiver operating characteristic (ROC) analyses

Diffusion MRI measured at multiple b-values

Data were acquired on a Siemens 3T PRISMA MRI (maximum gradient strength of 80 mT/m) using a 64 channel coil, at CENIR, ICM (Paris). The multiband epi2ddiff sequence from Minneapolis (http://www.cmrr.umn.edu/multiband/) was used with a multiband factor of 3, TR=3s TE=74ms flip angle=72 voxel size=2mm isotropic FOV=208*208*144 bandwidth=2090, monopolar acquisition scheme with a \delta of 15.7ms and a \Delta of 36.5ms (spoiler b-value 2.6 s/mm^2). For b=200, 400, 8 directions were used for each b-value. For other b-values, 90 directions for each b-value where chosen with http://www.emmanuelcaruyer.com/q-space-sampling.php so that we have different direction for each b-value. A b=0 image was interleaved every 8 or 9 directions. For each b-value you will find : the raw data (4D_dwi_xxx.nii.gz), the data preprocessed with topup and eddy tools from FSL (4D_dwi_eddycor_xxx.nii.gz), the directions and b-values in FSL format (bvals bvecs) and a .json file containing dicom metadata of each acquisition.Diffusion MRI at multiple b-values (200, 400, 1000, 2000, 3000) was collected on a 3T Siemens Prisma MRI instrument in a single healthy individual