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Background: Transcranial ultrasound stimulation (TUS) is a non-invasive brain stimulation technique; when skull aberrations are compensated for, this technique allows, with millimetric accuracy, circumvention of the invasive surgical procedure associated with deep brain stimulation (DBS) and the limited spatial specificity of transcranial magnetic stimulation. Objective: /hypothesis: We hypothesize that MR-guided low-power TUS can induce a sustained decrease of tremor power in patients suffering from medically refractive essential tremor. Methods: The dominant hand only was targeted, and two anatomical sites were sonicated in this exploratory study: the ventral intermediate nucleus of the thalamus (VIM) and the dentato-rubro-thalamic tract (DRT). Patients (N = 9) were equipped with MR-compatible accelerometers attached to their hands to monitor their tremor in real-time during TUS. Results: VIM neurostimulations followed by a low-duty cycle (5 %) DRT stimulation induced a substantial decrease in the tremor power in four patients, with a minimum of 89.9 % reduction when compared with the baseline power a few minutes after the DRT stimulation. The only patient stimulated in the VIM only and with a low duty cycle (5 %) also experienced a sustained reduction of the tremor (up to 93.4 %). Four patients (N = 4) did not respond. The temperature at target was 37.2 ± 1.4 °C compared to 36.8 ± 1.4 °C for a 3 cm away control point. Conclusions: MR-guided low power TUS can induce a substantial and sustained decrease of tremor power. Follow-up studies need to be conducted to reproduce the effect and better to understand the variability of the response amongst patients. MR thermometry during neurostimulations showed no significant thermal rise, supporting a mechanical effect.

Abstract Asymptomatic Leucine-Rich Repeat Kinase 2 Gene (LRRK2) carriers are at risk for developing Parkinson's disease (PD). We studied presymptomatic substantia nigra pars compacta (SNc) regional neurodegeneration in asymptomatic LRRK2 carriers compared to idiopathic PD patients using neuromelanin-sensitive MRI technique (NM-MRI). Fifteen asymptomatic LRRK2 carriers, 22 idiopathic PD patients, and 30 healthy controls (HCs) were scanned using NM-MRI. We computed volume and contrast-to-noise ratio (CNR) derived from the whole SNc and the sensorimotor, associative, and limbic SNc regions. An analysis of covariance was performed to explore the differences of whole and regional NM-MRI values among the groups while controlling the effect of age and sex. In whole SNc, LRRK2 had significantly lower CNR than HCs but non-significantly higher volume and CNR than PD patients, and PD patients significantly lower volume and CNR compared to HCs. Inside SNc regions, there were significant group effects for CNR in all regions and for volumes in the associative region, with a trend in the sensorimotor region but no significant changes in the limbic region. PD had reduced volume and CNR in all regions compared to HCs. Asymptomatic LRRK2 carriers showed globally decreased SNc volume and CNR suggesting early nigral neurodegeneration in these subjects at risk of developing PD.

Abstract In Parkinson’s disease (PD), it remains unclear whether sleep disorders including insomnia, REM sleep behavior disorder (RBD), excessive daytime sleepiness (EDS), restless legs syndrome (RLS) and sleep-disordered breathing (SDB), are isolated or combined, interact with each other and are associated with clinical factors. We sought to determine the prevalence and combinations of the main sleep disorders, and their clinical and polysomnographic associations in early stage PD. Sleep disorders were systematically diagnosed after medical interview and video-polysomnography in 162 participants with early stage PD and 58 healthy controls from the baseline of the longitudinal ICEBERG cohort. Demographic, clinical (motor, cognitive, autonomic, psychological and sensory tests), therapeutic and polysomnographic associations of sleep disorders were investigated. Sleep disorders were frequent (71%) and combined in half of the patients. The number of sleep disorders increased with disease duration and dysautonomia. Insomnia was the most common (41%), followed by definite RBD (25%), EDS (25%), and RLS (16%). These disorders were more frequent than in controls whereas SDB was rare, moderate and similar in both groups. In patients, insomnia (mainly difficulties maintaining sleep) was associated with female gender, shorter sleep time and RLS, but not with motor or psychological symptoms. RBD was associated with dysautonomia and advanced age, but not with motor and cognitive measures. EDS was associated with psychiatric and motor symptoms as well as the sedative effects of dopamine agonists but not with other sleep disturbances. Sleep disturbances are frequent and combined in early patients with PD. Their determinants and markers are more organic than psychological.

In a neuropathological series of 20 COVID-19 cases, we analyzed six cases (three biopsies and three autopsies) with multiple foci predominantly affecting the white matter as shown by MRI. The cases presented with microhemorrhages evocative of small artery diseases. This COVID-19 associated cerebral microangiopathy (CCM) was characterized by perivascular changes: arterioles were surrounded by vacuolized tissue, clustered macrophages, large axonal swellings and a crown arrangement of aquaporin-4 immunoreactivity. There was evidence of blood-brain-barrier leakage. Fibrinoid necrosis, vascular occlusion, perivascular cuffing and demyelination were absent. While no viral particle or viral RNA was found in the brain, the SARS-CoV-2 spike protein was detected in the Golgi apparatus of brain endothelial cells where it closely associated with furin, a host protease known to play a key role in virus replication. Endothelial cells in culture were not permissive to SARS-CoV-2 replication. The distribution of the spike protein in brain endothelial cells differed from that observed in pneumocytes. In the latter, the diffuse cytoplasmic labeling suggested a complete replication cycle with viral release, notably through the lysosomal pathway. In contrast, in cerebral endothelial cells the excretion cycle was blocked in the Golgi apparatus. Interruption of the excretion cycle could explain the difficulty of SARS-CoV-2 to infect endothelial cells in vitro and to produce viral RNA in the brain. Specific metabolism of the virus in brain endothelial cells could weaken the cell walls and eventually lead to the characteristic lesions of COVID-19 associated cerebral microangiopathy. Furin as a modulator of vascular permeability could provide some clues for the control of late effects of microangiopathy.

IntroductionThe impact of multi-domain preventive interventions on older adults, in particular on those with higher risk to develop Alzheimer's disease (AD), could be beneficial, as it may delay cognitive decline. However, the precise mechanism of such positive impact is not fully understood and may involve brain reserve and adaptability of brain functional connectivity (FC).MethodsTo determine the effect of multidomain interventions (involving physical activity, cognitive training, nutritional counseling alone or in combination with omega-3 fatty acid supplementation and vs. a placebo) on the brain, longitudinal FC changes were assessed after 36 months of intervention on 100 older adults (above 70 year-old) with subjective cognitive complaints.ResultsNo global change in FC was detected after uni or multidomain preventive interventions. However, an effect of omega-3 fatty acid supplementation dependent on cognitive decline status was underlined for frontoparietal, salience, visual and sensorimotor networks FC. These findings were independent of the cortical thickness and vascular burden.DiscussionThese results emphasize the importance of patient stratification, based on risk factors, for preventive interventions.

AbstractMyelin plays a crucial role in how well information travels between brain regions. Complementing the structural connectome, obtained with diffusion MRI tractography, with a myelin-sensitive measure could result in a more complete model of structural brain connectivity and give better insight into white-matter myeloarchitecture. In this work we weight the connectome by the longitudinal relaxation rate (R1), a measure sensitive to myelin, and then we assess its added value by comparing it with connectomes weighted by the number of streamlines (NOS). Our analysis reveals differences between the two connectomes both in the distribution of their weights and the modular organization. Additionally, the rank-based analysis shows that R1 can be used to separate transmodal regions (responsible for higher-order functions) from unimodal regions (responsible for low-order functions). Overall, the R1-weighted connectome provides a different perspective on structural connectivity taking into account white matter myeloarchitecture.

Background: Parkinson’s disease (PD) demonstrates neurodegenerative changes in the substantia nigra pars compacta (SNc) using neuromelanin-sensitive (NM)-MRI. As SNc manual segmentation is prone to substantial inter-individual variability across raters, development of a robust automatic segmentation framework is necessary to facilitate nigral neuromelanin quantification. Artificial intelligence (AI) is gaining traction in the neuroimaging community for automated brain region segmentation tasks using MRI. Objective: Developing and validating AI-based NigraNet, a fully automatic SNc segmentation framework allowing nigral neuromelanin quantification in patients with PD using NM-MRI. Methods: We prospectively included 199 participants comprising 144 early-stage idiopathic PD patients (disease duration = 1.5 ± 1.0 years) and 55 healthy volunteers (HV) scanned using a 3 Tesla MRI including whole brain T1-weighted anatomical imaging and NM-MRI. The regions of interest (ROI) were delineated in all participants automatically using NigraNet, a modified U-net, and compared to manual segmentations performed by two experienced raters. The SNc volumes (Vol), volumes corrected by total intracranial volume (Cvol), normalized signal intensity (NSI) and contrast-to-noise ratio (CNR) were computed. One-way GLM-ANCOVA was performed while adjusting for age and sex as covariates. Diagnostic performance measurement was assessed using the receiver operating characteristic (ROC) analysis. Inter and intra-observer variability were estimated using Dice similarity coefficient (DSC). The agreements between methods were tested using intraclass correlation coefficient (ICC) based on a mean-rating, two-way, mixed-effects model estimates for absolute agreement. Cronbach’s alpha and Bland-Altman plots were estimated to assess inter-method consistency. Results: Using both methods, Vol, Cvol, NSI and CNR measurements differed between PD and HV with an effect of sex for Cvol and CNR. ICC values between the methods demonstrated optimal agreement for Cvol and CNR (ICC > 0.9) and high reproducibility (DSC: 0.80) was also obtained. The SNc measurements also showed good to excellent consistency values (Cronbach's alpha > 0.87). Bland-Altman plots of agreement demonstrated no association of SNc ROI measurement differences between the methods and ROI average measurements while confirming that 95 % of the data points were ranging between the limits of mean difference (d ± 1.96xSD). Percentage changes between PD and HV were −27.4 % and −17.7 % for Vol, −30.0 % and –22.2 % for Cvol, −15.8 % and −14.4 % for NSI, −17.1 % and −16.0 % for CNR for automatic and manual measurements respectively. Using automatic method, in the entire dataset, we obtained the areas under the ROC curve (AUC) of 0.83 for Vol, 0.85 for Cvol, 0.79 for NSI and 0.77 for CNR whereas in the training dataset of 0.96 for Vol, 0.95 for Cvol, 0.85 for NSI and 0.85 for CNR. Disease duration correlated negatively with NSI of the patients for both the automatic and manual measurements. Conclusions: We presented an AI-based NigraNet framework that utilizes a small MRI training dataset to fully automatize the SNc segmentation procedure with an increased precision and more reproducible results. Considering the consistency, accuracy and speed of our approach, this study could be a crucial step towards the implementation of a time-saving non-rater dependent fully automatic method for studying neuromelanin changes in clinical settings and large-scale neuroimaging studies.

Several postmortem studies have shown iron accumulation in the substantia nigra of Parkinson’s disease patients. Iron concentration can be estimated via MRI-R2∗ mapping. To assess the changes in R2∗ occurring in Parkinson’s disease patients compared to controls, a multicentre transversal study was carried out on a large cohort of Parkinson’s disease patients (n = 163) with matched controls (n = 82). In this study, 44 patients and 11 controls were removed due to motion artefacts, 21 patient and 6 controls to preserve matching. Thus, 98 patients and 65 age and sex-matched healthy subjects were selected with enough image quality.The study was conducted on patients with early to late stage Parkinson's disease. The images were acquired at 3Tesla in 12 clinical centres. R2∗ values were measured in subcortical regions of interest (substantia nigra, red nucleus, striatum, globus pallidus externus and globus pallidus internus) contralateral (dominant side) and ipsilateral (non dominant side) to the most clinically affected hemibody.As the observed inter-subject R2∗ variability was significantly higher than the disease effect, an original strategy (intrasubject subcortical quantitative referencing, ISQR) was developed using the measurement of R2∗ in the red nucleus as an intra-subject reference.R2∗ values significantly increased in Parkinson’s disease patients when compared with controls; in the substantia nigra (SN) in the dominant side (D) and in the non dominant side (ND), respectively (PSN_D and PSN_ND

Many articles have used voice analysis to detect Parkinson's disease (PD), but few have focused on the early stages of the disease and the gender effect. In this article, we have adapted the latest speaker recognition system, called x-vectors, in order to detect PD at an early stage using voice analysis. X-vectors are embeddings extracted from Deep Neural Networks (DNNs), which provide robust speaker representations and improve speaker recognition when large amounts of training data are used. Our goal was to assess whether, in the context of early PD detection, this technique would outperform the more standard classifier MFCC-GMM (Mel-Frequency Cepstral Coefficients—Gaussian Mixture Model) and, if so, under which conditions. We recorded 221 French speakers (recently diagnosed PD subjects and healthy controls) with a high-quality microphone and via the telephone network. Men and women were analyzed separately in order to have more precise models and to assess a possible gender effect. Several experimental and methodological aspects were tested in order to analyze their impacts on classification performance. We assessed the impact of the audio segment durations, data augmentation, type of dataset used for the neural network training, kind of speech tasks, and back-end analyses. X-vectors technique provided better classification performances than MFCC-GMM for the text-independent tasks, and seemed to be particularly suited for the early detection of PD in women (7–15% improvement). This result was observed for both recording types (high-quality microphone and telephone).

The diagnosis of Parkinson's disease and atypical Parkinsonism remains clinically difficult, especially at the early stage of the disease, since there is a significant overlap of symptoms. Multimodal MRI has significantly improved diagnostic accuracy and understanding of the pathophysiology of Parkinsonian disorders. Structural and quantitative MRI sequences provide biomarkers sensitive to different tissue properties that detect abnormalities specific to each disease and contribute to the diagnosis. Machine learning techniques using these MRI biomarkers can effectively differentiate atypical Parkinsonian syndromes. Such approaches could be implemented in a clinical environment and improve the management of Parkinsonian patients. This review presents different structural and quantitative MRI techniques, their contribution to the differential diagnosis of atypical Parkinsonian disorders and their interest for individual-level diagnosis.

Background: Parkinson's disease (PD) is a progressive neurodegenerative disease whose main neuropathological feature is the loss of dopaminergic neurons of the substantia nigra (SN). There is also an increase in iron content in the SN in postmortem and imaging studies using iron-sensitive MRI techniques. However, MRI results are variable across studies.Objectives: We performed a systematic meta-analysis of SN iron imaging studies in PD to better understand the role of iron-sensitive MRI quantification to distinguish patients from healthy controls. We also studied the factors that may influence iron quantification and analyzed the correlations between demographic and clinical data and iron load.Methods: We searched PubMed and ScienceDirect databases (from January 1994 to December 2019) for studies that analyzed iron load in the SN of PD patients using T2*, R2*, susceptibility weighting imaging (SWI), or quantitative susceptibility mapping (QSM) and compared the values with healthy controls. Details for each study regarding participants, imaging methods, and results were extracted. The effect size and confidence interval (CI) of 95% were calculated for each study as well as the pooled weighted effect size for each marker over studies. Hence, the correlations between technical and clinical metrics with iron load were analyzed.Results: Forty-six articles fulfilled the inclusion criteria including 27 for T2*/R2* measures, 10 for SWI, and 17 for QSM (3,135 patients and 1,675 controls). Eight of the articles analyzed both R2* and QSM. A notable effect size was found in the SN in PD for R2* increase (effect size: 0.84, 95% CI: 0.60 to 1.08), for SWI measurements (1.14, 95% CI: 0.54 to 1.73), and for QSM increase (1.13, 95% CI: 0.86 to 1.39). Correlations between imaging measures and Unified Parkinson's Disease Rating Scale (UPDRS) scores were mostly observed for QSM.Conclusions: The consistent increase in MRI measures of iron content in PD across the literature using R2*, SWI, or QSM techniques confirmed that these measurements provided reliable markers of iron content in PD. Several of these measurements correlated with the severity of motor symptoms. Lastly, QSM appeared more robust and reproducible than R2* and more suited to multicenter studies.

Introduction: In vivo clinical, anatomical and metabolic differences between posterior cortical atrophy (PCA) patients presenting with different Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers profiles are still unknown. Methods: Twenty-seven PCA patients underwent CSF examination and were classified as 1) PCA with a typical CSF AD profile (PCA-tAD; abnormal amyloid and T-tau/P-tau biomarkers, n = 13); 2) PCA with an atypical AD CSF profile (PCA-aAD; abnormal amyloid biomarker only, n = 9); and 3) PCA not associated with AD (PCA-nonAD; normal biomarkers, n = 5). All patients underwent clinical and cognitive assessment, structural MRI, and a subset of them underwent brain 18F-FDG PET. Results: All patients' groups showed a common pattern of posterior GM atrophy and hypometabolism typical of PCA, as well as equivalent demographics and clinical/cognitive profiles. PCA-tAD patients showed a group-specific pattern of hypometabolism in the left fusiform gyrus and inferior temporal gyrus. PCA-aAD did not present a group-specific atrophy pattern. Finally, group-specific gray matter atrophy in the right dorsolateral prefrontal cortex, left caudate nucleus and right medial temporal regions and hypometabolism in the right supplementary motor area and paracentral lobule were observed in PCA-nonAD patients. Conclusion: Our findings suggest that both PCA-tAD and PCA-aAD patients are on the AD continuum, in agreement with the recently suggested A/T/N model. Furthermore, in PCA, the underlying pathology has an impact at least on the anatomo-functional presentation. Brain damage observed in PCA-tAD and PCA-aAD was mostly consistent with the well-described presentation of the disease, although it was more widespread in PCA-tAD group, especially in the left temporal lobe. Additional fronto-temporal (especially dorsolateral prefrontal) damage seems to be a clue to underlying non-AD pathology in PCA, which warrants the need for longitudinal follow-ups to investigate frontal symptoms in these patients. Keywords: Posterior cortical atrophy, Alzheimer's disease, Cerebrospinal fluid, Biomarkers, Gray matter atrophy, Brain metabolism, Neuropsychology, Atypical dementia, 18F-FDG PET, Voxel-based morphometry

Spinal muscular atrophy (SMA) type III and IV are autosomal recessive, slowly progressive lower motor neuron syndromes. Nevertheless, wider cerebral involvement has been consistently reported in mouse models. The objective of this study is the characterisation of spinal and cerebral pathology in adult forms of SMA using multimodal quantitative imaging. Methods: Twenty-five type III and IV adult SMA patients and 25 age-matched healthy controls were enrolled in a spinal cord and brain imaging study. Structural measures of grey and white matter involvement and diffusion parameters of white matter integrity were evaluated at each cervical spinal level. Whole-brain and region-of-interest analyses were also conducted in the brain to explore cortical thickness, grey matter density and tract-based white matter alterations. Results: In the spinal cord, considerable grey matter atrophy was detected between C2-C6 vertebral levels. In the brain, increased grey matter density was detected in motor and extra-motor regions of SMA patients. No white matter pathology was identified neither at brain and spinal level. Conclusions: Adult forms of SMA are associated with selective grey matter degeneration in the spinal cord with preserved white matter integrity. The observed increased grey matter density in the motor cortex may represent adaptive reorganisation. Keywords: Spinal muscular atrophy, SMA, Multimodal MRI, Spinal cord MRI, Grey matter and white matter degeneration

The relationship between stroke topography and functional outcome has largely been studied with binary manual lesion segmentations. However, stroke topography may be better characterized by continuous variables capable of reflecting the severity of ischemia, which may be more pertinent for long-term outcome. Diffusion Tensor Imaging (DTI) constitutes a powerful means of quantifying the degree of acute ischemia and its potential relation to functional outcome. Our aim was to investigate whether using more clinically pertinent imaging parameters with powerful machine learning techniques could improve prediction models and thus provide valuable insight on critical brain areas important for long-term outcome. Eighty-seven thrombolyzed patients underwent a DTI sequence at 24 h post-stroke. Functional outcome was evaluated at 3 months post-stroke with the modified Rankin Score and was dichotomized into good (mRS ≤ 2) and poor (mRS > 2) outcome. We used support vector machines (SVM) to classify patients into good vs. poor outcome and evaluate the accuracy of different models built with fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity asymmetry maps, and lesion segmentations in combination with lesion volume, age, recanalization status, and thrombectomy treatment. SVM classifiers built with axial diffusivity maps yielded the best accuracy of all imaging parameters (median [IQR] accuracy = 82.8 [79.3–86.2]%), compared to that of lesion segmentations (76.7 [73.3–82.8]%) when predicting 3-month functional outcome. The analysis revealed a strong contribution of clinical variables, notably – in descending order – lesion volume, thrombectomy treatment, and recanalization status, in addition to the deep white matter at the crossroads of major white matter tracts, represented by brain regions where model weights were highest. Axial diffusivity is a more appropriate imaging marker to characterize stroke topography for predicting long-term outcome than binary lesion segmentations. Keywords: Acute stroke, Prediction, Prognosis, Functional outcome, Diffusion tensor imaging

Resting state functional MRI (rs-fMRI) is an imaging technique that allows the spontaneous activity of the brain to be measured. Measures of functional connectivity highly depend on the quality of the BOLD signal data processing. In this study, our aim was to study the influence of preprocessing steps and their order of application on small-world topology and their efficiency in resting state fMRI data analysis using graph theory. We applied the most standard preprocessing steps: slice-timing, realign, smoothing, filtering, and the tCompCor method. In particular, we were interested in how preprocessing can retain the small-world economic properties and how to maximize the local and global efficiency of a network while minimizing the cost. Tests that we conducted in 54 healthy subjects showed that the choice and ordering of preprocessing steps impacted the graph measures. We found that the csr (where we applied realignment, smoothing, and tCompCor as a final step) and the scr (where we applied realignment, tCompCor and smoothing as a final step) strategies had the highest mean values of global efficiency (eg). Furthermore, we found that the fscr strategy (where we applied realignment, tCompCor, smoothing, and filtering as a final step), had the highest mean local efficiency (el) values. These results confirm that the graph theory measures of functional connectivity depend on the ordering of the processing steps, with the best results being obtained using smoothing and tCompCor as the final steps for global efficiency with additional filtering for local efficiency.

Parkinson's disease is characterized by neurodegeneration of the dopaminergic neurons in the substantia nigra pars compacta. The 6-hydroxydopamine (6-OHDA) rat model has been used to study neurodegeneration in the nigro-striatal dopaminergic system. The goal of this study was to evaluate the reliability of diffusion MRI and resting-state functional MRI biomarkers in monitoring neurodegeneration in the 6-OHDA rat model assessed by quantitative histology. We performed a unilateral injection of 6-OHDA in the striatum of Sprague Dawley rats to produce retrograde degeneration of the dopamine neurons in the substantia nigra pars compacta. We carried out a longitudinal study with a multi-modal approach combining structural and functional MRI together with quantitative histological validation to follow the effects of the lesion. Functional and structural connectivity were assessed in the brain of 6-OHDA rats and sham rats (NaCl injection) at 3 and 6 weeks post-lesioning using resting-state functional MRI and diffusion-weighted. Our results showed (i) increased functional connectivity in ipsi- and contra-lesioned regions of the cortico-basal ganglia network pathway including the motor cortex, the globus pallidus, and the striatum regions at 3 weeks; (ii) increased fractional anisotropy (FA) in the ipsi- and contralateral striatum of the 6-OHDA group at 3 weeks, and increased axial diffusivity (AD) and mean diffusivity in the ipsilateral striatum at 6 weeks; (iii) a trend for increased FA in both substantia nigra of the 6-OHDA group at 3 weeks. Optical density measurements of tyrosine-hydroxylase (TH) staining of the striatum showed good correlations with the FA and AD measurements in the striatum. No correlations were found between the number of TH-stained dopaminergic neurons and MRI measurements in the substantia nigra. This study suggested that (i) FA and AD were reliable biomarkers to evaluate neurodegeneration in the cortico-basal ganglia network of the 6-OHDA model, (ii) diffusion MRI and resting-state functional MRI (rsfMRI) were not sensitive enough to detect changes in the substantia nigra in this model.

In Alzheimer's disease (AD), the hippocampus is an early site of tau pathology and neurodegeneration. Histological studies have shown that lesions are not uniformly distributed within the hippocampus. Moreover, alterations of different hippocampal layers may reflect distinct pathological processes. 7 T MRI dramatically improves the visualization of hippocampal subregions and layers. In this study, we aimed to assess whether 7 T MRI can detect volumetric changes in hippocampal layers in vivo in patients with AD. We studied four AD patients and seven control subjects. MR images were acquired using a whole-body 7 T scanner with an eight channel transmit–receive coil. Hippocampal subregions were manually segmented from coronal T2*-weighted gradient echo images with 0.3 × 0.3 × 1.2 mm3 resolution using a protocol that distinguishes between layers richer or poorer in neuronal bodies. Five subregions were segmented in the region of the hippocampal body: alveus, strata radiatum, lacunosum and moleculare (SRLM) of the cornu Ammonis (CA), hilum, stratum pyramidale of CA and stratum pyramidale of the subiculum. We found strong bilateral reductions in the SRLM of the cornu Ammonis and in the stratum pyramidale of the subiculum (p

OBJECTIVE:Word finding depends on the processing of semantic and lexical information, and it involves an intermediate level for mapping semantic-to-lexical information which also subserves lexical-to-semantic mapping during word comprehension. However, the brain regions implementing these components are still controversial and have not been clarified via a comprehensive lesion model encompassing the whole range of language-related cortices. Primary progressive aphasia (PPA), for which anomia is thought to be the most common sign, provides such a model, but the exploration of cortical areas impacting naming in its three main variants and the underlying processing mechanisms is still lacking. METHODS:We addressed this double issue, related to language structure and PPA, with thirty patients (11 semantic, 12 logopenic, 7 agrammatic variant) using a picture-naming task and voxel-based morphometry for anatomo-functional correlation. First, we analyzed correlations for each of the three variants to identify the regions impacting naming in PPA and to disentangle the core regions of word finding. We then combined the three variants and correlation analyses for naming (semantic-to-lexical mapping) and single-word comprehension (lexical-to-semantic mapping), predicting an overlap zone corresponding to a bidirectional lexical-semantic hub. RESULTS AND CONCLUSIONS:Our results showed that superior portions of the left temporal pole and left posterior temporal cortices impact semantic and lexical naming mechanisms in semantic and logopenic PPA, respectively. In agrammatic PPA naming deficits were rare, and did not correlate with any cortical region. Combined analyses revealed a cortical overlap zone in superior/middle mid-temporal cortices, distinct from the two former regions, impacting bidirectional binding of lexical and semantic information. Altogether, our findings indicate that lexical/semantic word processing depends on an anterior-posterior axis within lateral-temporal cortices, including an anatomically intermediate hub dedicated to lexical-semantic integration. Within this axis our data reveal the underpinnings of anomia in the PPA variants, which is of relevance for both diagnosis and future therapy strategies.

[This corrects the article DOI: 10.1371/journal.pone.0152439.].

PURPOSE:The mechanisms underlying the topography of motor deficits in spinal muscular atrophy (SMA) remain unknown. We investigated the profile of spinal cord atrophy (SCA) in SMN1-linked SMA, and its correlation with the topography of muscle weakness. MATERIALS AND METHODS:Eighteen SMN1-linked SMA patients type III/V and 18 age/gender-matched healthy volunteers were included. Patients were scored on manual muscle testing and functional scales. Spinal cord was imaged using 3T MRI system. Radial distance (RD) and cord cross-sectional area (CSA) measurements in SMA patients were compared to those in controls and correlated with strength and disability scores. RESULTS:CSA measurements revealed a significant cord atrophy gradient mainly located between C3 and C6 vertebral levels with a SCA rate ranging from 5.4% to 23% in SMA patients compared to controls. RD was significantly lower in SMA patients compared to controls in the anterior-posterior direction with a maximum along C4 and C5 vertebral levels (p-values < 10-5). There were no correlations between atrophy measurements, strength and disability scores. CONCLUSIONS:Spinal cord atrophy in adult SMN1-linked SMA predominates in the segments innervating the proximal muscles. Additional factors such as neuromuscular junction or intrinsic skeletal muscle defects may play a role in more complex mechanisms underlying weakness in these patients.

BackgroundRecently, the concept of 'clinically relevant penumbra' was defined as an area saved by arterial recanalization and correlated with stroke outcome. This clinically relevant penumbra was located in the subcortical structures, especially the periventricular white matter. Our aims were to confirm this hypothesis, to investigate the impact of admission hyperglycemia and of insulin treatment on the severity of ischemic damages in this area and to study the respective contributions of infarct volume and ischemic damage severity of the clinically relevant penumbra on 3-month outcome.MethodsWe included 99 patients from the INSULINFARCT trial. Voxel-Based Analysis was carried on the Apparent Diffusion Coefficient (ADC) maps obtained at day one to localize the regions, which were more damaged in patients i) with poor clinical outcomes at three months and ii) without arterial recanalization. We determined the intersection of the detected areas, which represents the clinically relevant penumbra and investigated whether hyperglycemic status and insulin regimen affected the severity of ischemic damages in this area. We performed logistic regression to examine the contribution of infarct volume or early ADC decrease in this strategic area on 3-month outcome.FindingsLower ADC values were found in the corona radiata in patients with poor prognosis (p< 0.0001) and in those without arterial recanalization (p< 0.0001). The tracking analysis showed that lesions in this area interrupted many important pathways. ADC values in this area were lower in hyperglycemic than in normoglycemic patients (average decrease of 41.6 ± 20.8 x10(-6) mm2/s) and unaffected by the insulin regimen (p: 0.10). ADC values in the clinically relevant penumbra, but not infarct volumes, were significant predictors of 3-month outcome.ConclusionThese results confirm that the deep hemispheric white matter is part of the clinically relevant penumbra and show that hyperglycaemia exacerbates the apparition of irreversible ischemic damage within 24 hours in this area. However, early intensive insulin therapy fails to protect this area from infarction.Trial registrationClinicalTrials.gov NCT00472381.

Myopia is a common ocular disorder generally due to increased axial length of the eye-globe. Its extreme form high myopia (HM) is a multifactorial disease leading to retinal and scleral damage, visual impairment or loss and is an important health issue. Mutations in the endocytic receptor LRP2 gene result in Donnai-Barrow (DBS) and Stickler syndromes, both characterized by HM. To clearly establish the link between Lrp2 and congenital HM we inactivated Lrp2 in the mouse forebrain including the neural retina and the retinal and ciliary pigment epithelia. High resolution in vivo MRI imaging and ophthalmological analyses showed that the adult Lrp2-deficient eyes were 40% longer than the control ones mainly due to an excessive elongation of the vitreal chamber. They had an apparently normal intraocular pressure and developed chorioretinal atrophy and posterior scleral staphyloma features reminiscent of human myopic retinopathy. Immunomorphological and ultrastructural analyses showed that increased eye lengthening was first observed by post-natal day 5 (P5) and that it was accompanied by a rapid decrease of the bipolar, photoreceptor and retinal ganglion cells, and eventually the optic nerve axons. It was followed by scleral thinning and collagen fiber disorganization, essentially in the posterior pole. We conclude that the function of LRP2 in the ocular tissues is necessary for normal eye growth and that the Lrp2-deficient eyes provide a unique tool to further study human HM.

To design a fast and accurate semi-automated segmentation method for spinal cord 3T MR images and to construct a template of the cervical spinal cord.A semi-automated double threshold-based method (DTbM) was proposed enabling both cross-sectional and volumetric measures from 3D T2-weighted turbo spin echo MR scans of the spinal cord at 3T. Eighty-two healthy subjects, 10 patients with amyotrophic lateral sclerosis, 10 with spinal muscular atrophy and 10 with spinal cord injuries were studied. DTbM was compared with active surface method (ASM), threshold-based method (TbM) and manual outlining (ground truth). Accuracy of segmentations was scored visually by a radiologist in cervical and thoracic cord regions. Accuracy was also quantified at the cervical and thoracic levels as well as at C2 vertebral level. To construct a cervical template from healthy subjects' images (n=59), a standardization pipeline was designed leading to well-centered straight spinal cord images and accurate probability tissue map.Visual scoring showed better performance for DTbM than for ASM. Mean Dice similarity coefficient (DSC) was 95.71% for DTbM and 90.78% for ASM at the cervical level and 94.27% for DTbM and 89.93% for ASM at the thoracic level. Finally, at C2 vertebral level, mean DSC was 97.98% for DTbM compared with 98.02% for TbM and 96.76% for ASM. DTbM showed similar accuracy compared with TbM, but with the advantage of limited manual interaction.A semi-automated segmentation method with limited manual intervention was introduced and validated on 3T images, enabling the construction of a cervical spinal cord template.

BackgroundMotor 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).MethodsTwenty-two 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.FindingsIn 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.ConclusionFunctional 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.

Post-concussion syndrome has been related to axonal damage in patients with mild traumatic brain injury, but little is known about the consequences of injury on brain networks. In the present study, our aim was to characterize changes in functional brain networks following mild traumatic brain injury in patients with post-concussion syndrome using resting-state functional magnetic resonance imaging data. We investigated 17 injured patients with persistent post-concussion syndrome (under the DSM-IV criteria) at 6 months post-injury compared with 38 mild traumatic brain injury patients with no post-concussion syndrome and 34 healthy controls. All patients underwent magnetic resonance imaging examinations at the subacute (1-3 weeks) and late (6 months) phases after injury. Group-wise differences in functional brain networks were analyzed using graph theory measures. Patterns of long-range functional networks alterations were found in all mild traumatic brain injury patients. Mild traumatic brain injury patients with post-concussion syndrome had greater alterations than patients without post-concussion syndrome. In patients with post-concussion syndrome, changes specifically affected temporal and thalamic regions predominantly at the subacute stage and frontal regions at the late phase. Our results suggest that the post-concussion syndrome is associated with specific abnormalities in functional brain network that may contribute to explain deficits typically observed in PCS patients.

Huntington disease (HD) is associated with early and severe damage to the basal ganglia and particularly the striatum. We investigated cortico-striatal connectivity modifications occurring in HD patients using a novel approach which focuses on the projection of the connectivity profile of the basal ganglia onto the cortex. This approach consists in computing, for each subcortical structure, surface connectivity measures representing its strength of connections to the cortex and comparing these measures across groups. In this study, we focused on Huntington disease as an application of this new approach. First, surface cortico-striatal connectivity measures of a group of healthy subjects were averaged in order to infer the "normal" connectivity profile of the striatum to the cortex. Second, a statistical analysis was performed from the surface connectivity measures of healthy subjects and HD patients in order to detect the cortical gyri presenting altered cortico-striatal connectivity in HD. Lastly, percentage differences of connectivity between healthy subjects and patients were inferred, for each nucleus of the striatum, from the connectivity measures of the cortical gyri presenting a significant connectivity difference between the two groups. These percentage differences characterize the axonal disruptions between the striatum and the cortex occurring in HD. We found selective region-specific degeneration of cortical connections predominating for associative and primary sensorimotor connections and with relative preservation of limbic connections. Our method can be used to infer novel connectivity-based markers of HD pathological process.

[This corrects the article DOI: 10.1371/journal.pone.0065470.].