Presymptomatic spinal cord pathology in c9orf72 mutation carriers: A longitudinal neuroimaging study.

OBJECTIVE: C9orf72 hexanucleotide repeats expansions account for almost half of familial amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) cases. Recent imaging studies in asymptomatic C9orf72 carriers have demonstrated cerebral white (WM) and gray matter (GM) degeneration before the age of 40 years. The objective of this study was to characterize cervical spinal cord (SC) changes in asymptomatic C9orf72 hexanucleotide carriers. METHODS: Seventy-two asymptomatic individuals were enrolled in a prospective study of first-degree relatives of ALS and FTD patients carrying the c9orf72 hexanucleotide expansion. Forty of them carried the pathogenic mutation (C9+ ). Each subject underwent quantitative cervical cord imaging. Structural GM and WM metrics and diffusivity parameters were evaluated at baseline and 18 months later. Data were analyzed in C9+ and C9- subgroups, and C9+ subjects were further stratified by age. RESULTS: At baseline, significant WM atrophy was detected at each cervical vertebral level in C9+ subjects older than 40 years without associated changes in GM and diffusion tensor imaging parameters. At 18-month follow-up, WM atrophy was accompanied by significant corticospinal tract (CST) fractional anisotropy (FA) reductions. Intriguingly, asymptomatic C9+ subjects older than 40 years with family history of ALS (as opposed to FTD) also exhibited significant CST FA reduction at baseline. INTERPRETATION: Cervical SC imaging detects WM atrophy exclusively in C9+ subjects older than 40 years, and progressive CST FA reductions can be identified on 18-month follow-up. Cervical SC magnetic resonance imaging readily captures presymptomatic pathological changes and disease propagation in c9orf72-associated conditions. ANN NEUROL 2019;86:158-167.

Long-term cognitive disability after traumatic brain injury: Contribution of the DEX relative questionnaires.

Executive functions are high-level cognitive processes commonly impaired after severe traumatic brain injury (sTBI), which may be associated with persistent anosognosia. The dysexecutive questionnaire (DEX) was designed to assess different domains of executive functioning in daily life. Two versions of the DEX exist (DEX-S completed by the patient, DEX-O completed by a relative) to compare cognitive complaints and patient's awareness. This work was aimed at studying the relevance of DEX-O for assessing daily-life limitations, the persistence of anosognosia and its association with global disability (GOSE) and magnetic resonance imaging (MRI) markers of brain alterations. Sixty-three patients (and relatives) were included within 63.4 months (±20.7) after sTBI. DEX-S and DEX-O scores were significantly positively correlated. We obtained significant correlations between DEX-S and episodic memory and phasic alert but not with executive assessment, GOSE and diffusion MRI markers. DEX-O was significantly correlated with executive function, episodic memory, attention (phasic alert sustained and divided attention), with the GOSE and the volume of the body of the corpus callosum (MRI marker). Anosognosia score (DEX-O minus DEX-S) correlated with mean diffusivity measure. These results highlight the clinical interest of DEX-O in assessing long-term disability.

Brain responses to pictures of children in men with pedophilic disorder: a functional magnetic resonance imaging study.

Structural and functional neuroimaging techniques have recently been used to investigate the mechanisms of sexual attraction to children, a hallmark of pedophilic disorder, and have reported many contradictory or non-replicated findings. Here, our purpose was to identify through functional magnetic resonance imaging the brain responses of 25 male outpatients with pedophilic disorder to visual stimuli depicting children (VSc) and to compare them with 24 male healthy controls matched on sexual orientation (to female or male adults), age, and handedness. No region was differentially activated across the two groups in response to VSc. However, as shown by a random-effects statistical analysis (cluster-level pFWE-corrected < 0.05), in patients with pedophilia, but not in controls, the presentation of VSc induced a bilateral activation in the lateral occipital and temporal cortices, in particular in the right inferior temporal gyrus, as well as an activation in the declive of the cerebellar vermis. In addition, in patients the level of bilateral activation in the above-mentioned regions was positively correlated with ratings of perceived sexual arousal elicited by VSc. These results implicate these regions as possible candidate areas mediating sexual arousal in patients with pedophilic disorder.

Taking the brakes off the learning curve.

Motor learning is characterized by patterns of cerebello-striato-cortical activations shifting in time, yet the early dynamic and function of these activations remains unclear. Five groups of subjects underwent either continuous or intermittent theta-burst stimulation of one cerebellar hemisphere, or no stimulation just before learning a new motor sequence during fMRI scanning. We identified three phases during initial learning: one rapid, one slow, and one quasi-asymptotic performance phase. These phases were not changed by left cerebellar stimulation. Right cerebellar inhibition, however, accelerated learning and enhanced brain activation in critical motor learning-related areas during the first phase, continuing with reduced brain activation but high-performance in late phase. Right cerebellar excitation did not affect the early learning process, but slowed learning significantly in late phase, along with increased brain activation. We conclude that the right cerebellum is a key factor coordinating other neuronal loops in the early acquisition of an explicit motor sequential skill. Hum Brain Mapp 38:1676-1691, 2017. © 2016 Wiley Periodicals, Inc.

Validation of a semiautomated spinal cord segmentation method.

PURPOSE: To validate semiautomated spinal cord segmentation in healthy subjects and patients with neurodegenerative diseases and trauma. MATERIALS AND METHODS: Forty-nine healthy subjects, as well as 29 patients with amyotrophic lateral sclerosis, 19 with spinal muscular atrophy, and 14 with spinal cord injuries were studied. Cord area was measured from T2 -weighted 3D turbo spin echo images (cord levels from C2 to T9) using the semiautomated segmentation method of Losseff et al (Brain [1996] 119(Pt 3):701-708), compared with manual segmentation. Reproducibility was evaluated using the inter- and intraobserver coefficient of variation (CoV). Accuracy was assessed using the Dice similarity coefficient (DSC). Robustness to initialization was assessed by simulating modifications to the contours drawn manually prior to segmentation. RESULTS: Mean interobserver CoV was 4.00% for manual segmentation (1.90% for Losseff's method) in the cervical region and 5.62% (respectively 2.19%) in the thoracic region. Mean intraobserver CoV was 2.34% for manual segmentation (1.08% for Losseff's method) in the cervical region and 2.35% (respectively 1.34%) in the thoracic region. DSC was high (0.96) in both cervical and thoracic regions. DSC remained higher than 0.8 even when modifying initial contours by 50%. CONCLUSION: The semiautomated segmentation method showed high reproducibility and accuracy in measuring spinal cord area.

Hierarchical clustering of brain activity during human nonrapid eye movement sleep.

Consciousness is reduced during nonrapid eye movement (NREM) sleep due to changes in brain function that are still poorly understood. Here, we tested the hypothesis that impaired consciousness during NREM sleep is associated with an increased modularity of brain activity. Cerebral connectivity was quantified in resting-state functional magnetic resonance imaging times series acquired in 13 healthy volunteers during wakefulness and NREM sleep. The analysis revealed a modification of the hierarchical organization of large-scale networks into smaller independent modules during NREM sleep, independently from EEG markers of the slow oscillation. Such modifications in brain connectivity, possibly driven by sleep ultraslow oscillations, could hinder the brain's ability to integrate information and account for decreased consciousness during NREM sleep.

Quantitative effect of the neonatal fontanel on synthetic near infrared spectroscopy measurements.

Near infrared spectroscopy (NIRS) is a functional imaging technique allowing measurement of local cerebral oxygenation. This modality is particularly adapted to critically ill neonates, as it can be used at the bedside and is a suitable and noninvasive tool for carrying out longitudinal studies. However, NIRS is sensitive to the imaged medium and consequently to the optical properties of biological tissues in which photons propagate. In this study, the effect of the neonatal fontanel was investigated by predicting photon propagation using a probabilistic Monte Carlo approach. Two anatomical newborn head models were created from computed tomography and magnetic resonance images: (1) a realistic model including the fontanel tissue and (2) a model in which the fontanel was replaced by skull tissue. Quantitative change in absorption due to simulated activation was compared for the two models for specific regions of activation and optical arrays simulated in the temporal area. A correction factor was computed to quantify the effect of the fontanel and defined by the ratio between the true and recovered change. The results show that recovered changes in absorption were more precise when determined with the anatomical model including the fontanel. The results suggest that the fontanel should be taken into account in quantification of NIRS responses to avoid misinterpretation in experiments involving temporal areas, such as language or auditory studies.

Functional immaturity of cortico-basal ganglia networks in Gilles de la Tourette syndrome.

Gilles de la Tourette syndrome is a clinically heterogeneous disorder with poor known pathophysiology. Recent neuropathological and structural neuroimaging data pointed to the dysfunction of cortico-basal ganglia networks. Nonetheless, it is not clear how these structural changes alter the functional activity of the brain and lead to heterogeneous clinical expressions of the syndrome. The objective of this study was to evaluate global integrative state and organization of functional connections of sensori-motor, associative and limbic cortico-basal ganglia networks, which are likely involved in tics and behavioural expressions of Gilles de la Tourette syndrome. We also tested the hypothesis that specific regions and networks contribute to different symptoms. Data were acquired on 59 adult patients and 27 gender- and age-matched controls using a 3T magnetic resonance imaging scanner. Cortico-basal ganglia networks were constructed from 91 regions of interest. Functional connectivity was quantified using global integration and graph theory measures. We found a stronger functional integration (more interactions among anatomical regions) and a global functional disorganization of cortico-basal ganglia networks in patients with Gilles de la Tourette syndrome compared with controls. All networks were characterized by a shorter path length, a higher number of and stronger functional connections among the regions and by a loss of pivotal regions of information transfer (hubs). The functional abnormalities correlated to tic severity in all cortico-basal ganglia networks, namely in premotor, sensori-motor, parietal and cingulate cortices and medial thalamus. Tic complexity was correlated to functional abnormalities in sensori-motor and associative networks, namely in insula and putamen. Severity of obsessive-compulsive disorder was correlated with functional abnormalities in associative and limbic networks, namely in orbito-frontal and prefrontal dorsolateral cortices. The results suggest that the pattern of functional changes in cortico-basal ganglia networks in patients could reflect a defect in brain maturation. They also support the hypothesis that distinct regions of cortico-basal ganglia networks contribute to the clinical heterogeneity of this syndrome.

Brain Metabolic Profile in Presymptomatic GRN Carriers Throughout a 5-Year Follow-up.

BACKGROUND AND OBJECTIVES: GRN variants are a frequent cause of familial frontotemporal dementia (FTD). Monitoring disease progression in asymptomatic carriers of genetic variants is a major challenge in delivering preventative therapies before clinical onset. This study aimed to assess the usefulness of fluorodeoxyglucose (FDG)-PET in identifying metabolic changes in presymptomatic GRN carriers (PS-GRN+) and to trace their longitudinal progression. METHODS: Participants were longitudinally evaluated over 5 years in a prospective cohort study focused on GRN disease (Predict-PGRN). They underwent cognitive/behavioral assessment, plasma neurofilament measurement, brain MRI, and FDG-PET. Voxel-wise comparisons of structural and metabolic imaging data between 2 groups were performed for each time point. Longitudinal PET changes were evaluated with voxel-wise comparisons and the metabolic percent annual changes method. The association of regional brain metabolism with plasma neurofilament and cognitive changes was analyzed. RESULTS: Among the 80 individuals enrolled in the study, 58 (27 PS-GRN+ and 31 noncarriers) were included in the analyses. Cross-sectional comparisons between PS-GRN+ and controls found a significant hypometabolism in the left superior temporal sulcus (STS) region (encompassing the middle and superior temporal gyri), approximately 15 years before the expected disease onset, without significant cortical atrophy. The longitudinal metabolic decline over the following 5 years peaked around the right STS in carriers (p < 0.001), without significantly greater volume loss compared with that in controls. Their estimated annualized metabolic decrease (-1.37%) was higher than that in controls (-0.21%, p = 0.004). Lower glucose uptake was associated with higher neurofilament increase (p = 0.003) and lower frontal cognitive scores (p = 0.014) in PS-GRN+. DISCUSSION: This study detected brain metabolic changes in the STS region, preceding structural and cognitive alterations, thus contributing to the characterization of the pathochronology of preclinical GRN disease. Owing to the STS involvement in the perception of facially communicated cues, it is likely that its dysfunction contributes to social cognition deficits characterizing FTD. Overall, our study highlights brain metabolic changes as an early disease-tracking biomarker and proposes annualized percent decrease as a metric to monitor therapeutic response in forthcoming trials.

Prognostic value of global deep white matter DTI metrics for 1-year outcome prediction in ICU traumatic brain injury patients: an MRI-COMA and CENTER-TBI combined study.

PURPOSE: A reliable tool for outcome prognostication in severe traumatic brain injury (TBI) would improve intensive care unit (ICU) decision-making process by providing objective information to caregivers and family. This study aimed at designing a new classification score based on magnetic resonance (MR) diffusion metrics measured in the deep white matter between day 7 and day 35 after TBI to predict 1-year clinical outcome. METHODS: Two multicenter cohorts (29 centers) were used. MRI-COMA cohort (NCT00577954) was split into MRI-COMA-Train (50 patients enrolled between 2006 and mid-2014) and MRI-COMA-Test (140 patients followed up in clinical routine from 2014) sub-cohorts. These latter patients were pooled with 56 ICU patients (enrolled from 2014 to 2020) from CENTER-TBI cohort (NCT02210221). Patients were dichotomised depending on their 1-year Glasgow outcome scale extended (GOSE) score: GOSE 1-3, unfavorable outcome (UFO); GOSE 4-8, favorable outcome (FO). A support vector classifier incorporating fractional anisotropy and mean diffusivity measured in deep white matter, and age at the time of injury was developed to predict whether the patients would be either UFO or FO. RESULTS: The model achieved an area under the ROC curve of 0.93 on MRI-COMA-Train training dataset, and 49% sensitivity for 96.8% specificity in predicting UFO and 58.5% sensitivity for 97.1% specificity in predicting FO on the pooled MRI-COMA-Test and CENTER-TBI validation datasets. CONCLUSION: The model successfully identified, with a specificity compatible with a personalized decision-making process in ICU, one in two patients who had an unfavorable outcome at 1 year after the injury, and two-thirds of the patients who experienced a favorable outcome.

Brain functional integration decreases during propofol-induced loss of consciousness.

Consciousness has been related to the amount of integrated information that the brain is able to generate. In this paper, we tested the hypothesis that the loss of consciousness caused by propofol anesthesia is associated with a significant reduction in the capacity of the brain to integrate information. To assess the functional structure of the whole brain, functional integration and partial correlations were computed from fMRI data acquired from 18 healthy volunteers during resting wakefulness and propofol-induced deep sedation. Total integration was significantly reduced from wakefulness to deep sedation in the whole brain as well as within and between its constituent networks (or systems). Integration was systematically reduced within each system (i.e., brain or networks), as well as between networks. However, the ventral attentional network maintained interactions with most other networks during deep sedation. Partial correlations further suggested that functional connectivity was particularly affected between parietal areas and frontal or temporal regions during deep sedation. Our findings suggest that the breakdown in brain integration is the neural correlate of the loss of consciousness induced by propofol. They stress the important role played by parietal and frontal areas in the generation of consciousness.

Diffusion tensor imaging and white matter lesions at the subacute stage in mild traumatic brain injury with persistent neurobehavioral impairment.

Mild traumatic brain injury (mTBI) can induce long-term behavioral and cognitive disorders. Although the exact origin of these mTBI-related disorders is not known, they may be the consequence of diffuse axonal injury (DAI). Here, we investigated whether MRI at the subacute stage can detect lesions that are associated with poor functional outcome in mTBI by using anatomical images (T(1) ) and diffusion tensor imaging (DTI). Twenty-three patients with mTBI were investigated and compared with 23 healthy volunteers. All patients underwent an MRI investigation and clinical tests between 7 and 28 days (D15) and between 3 and 4 months (M3) after injury. Patients were divided in two groups of poor outcome (PO) and good outcome (GO), based on their complaints at M3. Groupwise differences in gray matter partial volume between PO patients, GO patients and controls were analyzed using Voxel-Based Morphometry (VBM) from T(1) data at D15. Differences in microstructural architecture were investigated using Tract-Based Spatial Statistics (TBSS) and the diffusion images obtained from DTI data at D15. Permutation-based non-parametric testing was used to assess cluster significance at p < 0.05, corrected for multiple comparisons. Twelve GO patients and 11 PO patients were identified on the basis of their complaints. In PO patients, gray matter partial volume was significantly lower in several cortical and subcortical regions compared with controls, but did not differ from that of GO patients. No difference in diffusion variables was found between GO and controls. PO patients showed significantly higher mean diffusivity values than both controls and GO patients in the corpus callosum, the right anterior thalamic radiations and the superior longitudinal fasciculus, the inferior longitudinal fasciculus and the fronto-occipital fasciculus bilaterally. In conclusion, PO patients differed from GO patients by the presence of diffusion changes in long association white matter fiber tracts but not by gray matter partial volume. These results suggest that DTI at the subacute stage may be a predictive marker of poor outcome in mTBI.

Global mean diffusivity: A radiomarker discriminating good outcome long term after traumatic brain injury.

BACKGROUND: Traumatic brain injury (TBI) is a chronic pathology responsible for cognitive disorders impacting outcome. Global clinical outcome several years after TBI may be associated with anatomical sequelae. Anatomical lesions are not well described because characterizing diffuse axonal injury and brain atrophy require using specific MRI sequences with quantitative measures. The best radiologic parameter to describe the lesions long term after TBI is not known. OBJECTIVE: We aimed to first, assess the global volumetric and diffusion parameters related to long-term outcome after TBI and second, define the most discriminating parameter. METHODS: In this observational study, we included 96 patients with severe TBI and 22 healthy volunteers. The mean delay after TBI was 63.2 months [range 31-119]. The Glasgow Outcome Scale Extended (GOS-E) was used to assess the global long-term clinical outcome. All patients underwent multimodal MRI with measures of brain volume, ventricle volume, global fractional anisotropy (FA) and global mean diffusivity (MD). RESULTS: All 96 participants had significant impairment in global FA, global MD, brain volume and ventricle volume as compared with the 22 controls (P<0.01). Only global MD significantly differed between the "good recovery" group (GOS-E score 7-8) and the other two groups: GOS-E scores 3-4 and 5-6. Brain volume significantly differed between the GOS-E 7-8 and 3-4 groups. Global MD was the most discriminating radiological parameter for the "good recovery" group versus other patients, long term after TBI. FA appeared less relevant at this time. Global atrophy was higher in patients than controls but lacked reliability to discriminate groups of patients. CONCLUSION: Global mean diffusivity seems a more promising radiomarker than global FA for discriminating good outcome long term after TBI. Further work is needed to understand the evolution of these long-term radiological parameters after TBI.

Dynamics of motor-related functional integration during motor sequence learning.

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 is transferred 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 (4 weeks) of an explicitly known sequence of finger movements. Evolution of functional connectivity was assessed using integration, a measure that quantifies the total amount 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 4 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 between-network 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.

An enhanced voxel-based morphometry method to investigate structural changes: application to Alzheimer's disease.

INTRODUCTION: When characterizing regional cerebral gray matter differences in structural magnetic resonance images (sMRI) by voxel-based morphometry (VBM), one faces a known drawback of VBM, namely that histogram unequalization in the intensity images introduces false-positive results. METHODS: To overcome this limitation, we propose to improve VBM by a new approach (called eVBM for enhanced VBM) that takes the histogram distribution of the sMRI into account by adding a histogram equalization step within the VBM procedure. Combining this technique with two most widely used VBM software packages (FSL and SPM), we studied GM variability in a group of 62 patients with Alzheimer's disease compared to 73 age-matched elderly controls. RESULTS: The results show that eVBM can reduce the number of false-positive differences in gray matter concentration. CONCLUSION: Because it takes advantage of the properties of VBM while improving sMRI histogram distribution at the same time, the proposed method is a powerful approach for analyzing gray matter differences in sMRI and may be of value in the investigation of sMRI gray and white matter abnormalities in a variety of brain diseases.

Grid-wide neuroimaging data federation in the context of the NeuroLOG project.

Grid technologies are appealing to deal with the challenges raised by computational neurosciences and support multi-centric brain studies. However, core grids middleware hardly cope with the complex neuroimaging data representation and multi-layer data federation needs. Moreover, legacy neuroscience environments need to be preserved and cannot be simply superseded by grid services. This paper describes the NeuroLOG platform design and implementation, shedding light on its Data Management Layer. It addresses the integration of brain image files, associated relational metadata and neuroscience semantic data in a heterogeneous distributed environment, integrating legacy data managers through a mediation layer.

Support vector machine-based classification of Alzheimer's disease from whole-brain anatomical MRI.

PURPOSE: We present and evaluate a new automated method based on support vector machine (SVM) classification of whole-brain anatomical magnetic resonance imaging to discriminate between patients with Alzheimer's disease (AD) and elderly control subjects. MATERIALS AND METHODS: We studied 16 patients with AD [mean age +/- standard deviation (SD) = 74.1 +/- 5.2 years, mini-mental score examination (MMSE) = 23.1 +/- 2.9] and 22 elderly controls (72.3 +/- 5.0 years, MMSE = 28.5 +/- 1.3). Three-dimensional T1-weighted MR images of each subject were automatically parcellated into regions of interest (ROIs). Based upon the characteristics of gray matter extracted from each ROI, we used an SVM algorithm to classify the subjects and statistical procedures based on bootstrap resampling to ensure the robustness of the results. RESULTS: We obtained 94.5% mean correct classification for AD and control subjects (mean specificity, 96.6%; mean sensitivity, 91.5%). CONCLUSIONS: Our method has the potential in distinguishing patients with AD from elderly controls and therefore may help in the early diagnosis of AD.

Deep brain activation patterns involved in virtual gait without and with a doorway: An fMRI study.

The human gait program involves many brain areas such as motor cortices, cerebellum, basal ganglia, brainstem, and spinal cord. The mesencephalic locomotor region (MLR), which contains the pedunculopontine (PPN) and cuneiform (CN) nuclei, is thought to be one of the key supraspinal gait generators. In daily life activities, gait primarily occurs in complex conditions, such as through narrow spaces, or while changing direction or performing motor or cognitive tasks. Here, we aim to explore the activity of these subcortical brain areas while walking through narrow spaces, using functional MRI in healthy volunteers and designing a virtual reality task mimicking walking down a hallway, without and with an open doorway to walk through. As a control, we used a virtual moving walkway in the same environment. Twenty healthy volunteers were scanned. Fifteen subjects were selected for second level analysis based on their ability to activate motor cortices. Using the contrast Gait versus Walkway, we found activated clusters in motor cortices, cerebellum, red nucleus, thalamus, and the left MLR including the CN and PPN. Using the contrast Gait with Doorway versus Walkway with Doorway, we found activated clusters in motor cortices, left putamen, left internal pallidum, left substantia nigra, right subthalamic area, and bilateral MLR involving the CN and PPN. Our results suggest that unobstructed gait involves a motor network including the PPN whereas gait through a narrow space requires the additional participation of basal ganglia and bilateral MLR, which may encode environmental cues to adapt locomotion.

Extrapyramidal deficits in ALS: a combined biomechanical and neuroimaging study.

INTRODUCTION: Extrapyramidal deficits are poorly characterised in amyotrophic lateral sclerosis (ALS) despite their contribution to functional disability, increased fall risk and their quality-of-life implications. Given the concomitant pyramidal and cerebellar degeneration in ALS, the clinical assessment of extrapyramidal features is particularly challenging. OBJECTIVE: The comprehensive characterisation of postural instability in ALS using standardised clinical assessments, gait analyses and computational neuroimaging tools in a prospective study design. METHODS: Parameters of gait initiation in the anticipatory postural adjustment phase (APA) and execution phase (EP) were evaluated in ALS patients with and without postural instability and healthy controls. Clinical and gait analysis parameters were interpreted in the context of brain imaging findings. RESULTS: ALS patients with postural instability exhibit impaired gait initiation with an altered APA phase, poor dynamic postural control and significantly decreased braking index. Consistent with their clinical profile, "unsteady" ALS patients have reduced caudate and brain stem volumes compared to "steady" ALS patients. INTERPRETATION: Our findings highlight that the ALS functional rating scale (ALSFRS-r) does not account for extrapyramidal deficits, which are major contributors to gait impairment in a subset of ALS patients. Basal ganglia degeneration in ALS does not only contribute to cognitive and behavioural deficits, but also adds to the heterogeneity of motor disability.

CORSICA: correction of structured noise in fMRI by automatic identification of ICA components.

When applied to functional magnetic resonance imaging (fMRI) data, spatial independent component analysis (sICA), a data-driven technique that addresses 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 new automatic method called CORSICA (CORrection of Structured noise using spatial Independent Component Analysis) 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 data sets (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 data sets, 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.