Brain-age estimation accuracy is significantly increased using multishell free-water reconstruction.

Although free-water diffusion reconstruction for diffusion-weighted imaging (DWI) data can be applied to both single-shell and multishell data, recent finding in synthetic data suggests that the free-water indices from single-shell acquisition should be interpreted with care, as they are heavily influenced by initialization parameters and cannot discriminate between free-water and mean diffusivity modifications. However, whether using a longer multishell acquisition protocol significantly improve reconstruction for real human MRI data is still an open question. In this study, we compare canonical diffusion tensor imaging (DTI), single-shell and multishell free-water imaging (FW) indices derived from a short, clinical compatible diffusion protocol (b = 500 s/mm2 , b = 1,000 s/mm2 , 32 directions each) on their power to predict brain age. Age was chosen as it is well-known to be related to widespread modification of the white matter and because brain-age estimation has recently been found to be relevant to several neurodegenerative diseases. We used a previously developed and validated data-driven whole-brain machine learning pipeline to directly compare the precision of brain-age estimates in a sample of 89 healthy males between 20 and 85 years old. We found that multishell FW outperform DTI indices in estimating brain age and that multishell FW, even when using low (500 ms2 ) b-values secondary shell, outperform single-shell FW. Single-shell FW led to lower brain-age estimation accuracy even of canonical DTI indices, suggesting that single-shell FW indices should be used with caution. For all considered reconstruction algorithms, the most discriminant indices were those measuring free diffusion of water in the white matter.

Insular functional connectivity in migraine with aura.

INTRODUCTION: Insula plays an integrating role in sensory, affective, emotional, cognitive and autonomic functions in migraine, especially in migraine with aura (MA). Insula is functionally divided into 3 subregions, the dorsoanterior, the ventroanterior and the posterior insula respectively related to cognition, emotion, and somatosensory functions. This study aimed at investigating functional connectivity of insula subregions in MA. METHODS: Twenty-one interictal patients with MA were compared to 18 healthy controls (HC) and 12 interictal patients with migraine without aura (MO) and were scanned with functional MRI during the resting state. Functional coupling of the insula was comprehensively tested with 12 seeds located in the right and left, dorsal, middle, ventral, anterior and posterior insula, by using a seed-to-voxel analysis. RESULTS: Seed-to-voxel analysis revealed, in MA, a strong functional coupling of the right and left antero-dorsal insula with clusters located in the upper cerebellum. The overlap of these cerebellar clusters corresponded to the vermis VI. These functional couplings were not correlated to duration of MA, frequency of MA attacks nor time since last MA attack, and were not found in MO. DISCUSSION: The anterior insula and superior cerebellum, including vermis VI, are components of the central Autonomic Nervous System (ANS) network. As these regions are involved in the control of cardiovascular parasympathetic tone, we hypothesize that this connectivity may reflect the cardiovascular features of MA. CONCLUSION: The anterior dorsal insula is connected with vermis VI in MA patients in the resting state. This connectivity may reflect the cardiovascular features of MA. TRIAL REGISTRATION: NCT02708797.

Functional and Structural Integrity of Frontoparietal Connectivity in Traumatic and Anoxic Coma.

OBJECTIVES: Recovery from coma might critically depend on the structural and functional integrity of frontoparietal networks. We aimed to measure this integrity in traumatic brain injury and anoxo-ischemic (cardiac arrest) coma patients by using an original multimodal MRI protocol. DESIGN: Prospective cohort study. SETTING: Three Intensive Critical Care Units affiliated to the University in Toulouse (France). PATIENTS: We longitudinally recruited 43 coma patients (Glasgow Coma Scale at the admission < 8; 29 cardiac arrest and 14 traumatic brain injury) and 34 age-matched healthy volunteers. Exclusion criteria were disorders of consciousness lasting more than 30 days and focal brain damage within the explored brain regions. Patient assessments were conducted at least 2 days (5 ± 2 d) after complete withdrawal of sedation. All patients were followed up (Coma Recovery Scale-Revised) 3 months after acute brain injury. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Functional and structural MRI data were recorded, and the analysis was targeted on the posteromedial cortex, the medial prefrontal cortex, and the cingulum. Univariate analyses and machine learning techniques were used to assess diagnostic and predictive values. Coma patients displayed significantly lower medial prefrontal cortex-posteromedial cortex functional connectivity (area under the curve, 0.94; 95% CI, 0.93-0.95). Cardiac arrest patients showed specific structural disturbances within posteromedial cortex. Significant cingulum architectural disturbances were observed in traumatic brain injury patients. The machine learning medial prefrontal cortex-posteromedial cortex multimodal classifier had a significant predictive value (area under the curve, 0.96; 95% CI, 0.95-0.97), best combination of subregions that discriminates a binary outcome based on Coma Recovery Scale-Revised). CONCLUSIONS: This exploratory study suggests that frontoparietal functional disconnections are specifically observed in coma and their structural counterpart provides information about brain injury mechanisms. Multimodal MRI biomarkers of frontoparietal disconnection predict 3-month outcome in our sample. These findings suggest that fronto-parietal disconnection might be particularly relevant for coma outcome prediction and could inspire innovative precision medicine approaches.

Discriminating between neurofibromatosis-1 and typically developing children by means of multimodal MRI and multivariate analyses.

Neurofibromatosis Type 1 leads to brain anomalies involving both gray and white matter. The extent and granularity of these anomalies, together with their possible impact on brain activity, is still unknown. In this multicentric cross-sectional study we submitted a sample of 42 typically developing and 38 neurofibromatosis-1 children to a multimodal MRI assessment including T1, diffusion weighted and resting state functional sequences. We used a pipeline involving several features selection steps coupled with multivariate statistical analysis (supporting vector machine) to discriminate between the two groups while having interpretable models. We used MRI indexes measuring macro (gray matter volume) and microstructural (fractional anisotropy, mean diffusivity) characteristics of the brain, as well as indexes of brain activity (fractional amplitude of low frequency fluctuations) and connectivity (local and global correlation) at rest. We found that structural indexes could discriminate between the two groups, with the mean diffusivity leading to performance as high as the combination of all structural indexes combined (accuracy = 0.86), while functional indexes had worse performances. The MRI signature of NF1 brain pathology is a combination of gray and white matter abnormalities, as measured with gray matter volume, fractional anisotropy, and mean diffusivity.

MRI supervised and unsupervised classification of Parkinson's disease and multiple system atrophy.

BACKGROUND: Multimodal MRI approach is based on a combination of MRI parameters sensitive to different tissue characteristics (eg, volume atrophy, iron deposition, and microstructural damage). The main objective of the present study was to use a multimodal MRI approach to identify brain differences that could discriminate between matched groups of patients with multiple system atrophy, Parkinson's disease, and healthy controls. We assessed the 2 different MSA variants, namely, MSA-P, with predominant parkinsonism, and MSA-C, with more prominent cerebellar symptoms. METHODS: Twenty-six PD patients, 29 MSA patients (16 MSA-P, 13 MSA-C), and 26 controls underwent 3-T MRI comprising T2*-weighted, T1-weighted, and diffusion tensor imaging scans. Using whole-brain voxel-based MRI, we combined gray-matter density, T2* relaxation rates, and diffusion tensor imaging scalars to compare and discriminate PD, MSA-P, MSA-C, and healthy controls. RESULTS: Our main results showed that this approach reveals multiparametric modifications within the cerebellum and putamen in both MSA-C and MSA-P patients, compared with PD patients. Furthermore, our findings revealed that specific single multimodal MRI markers were sufficient to discriminate MSA-P and MSA-C patients from PD patients. Moreover, the unsupervised analysis based on multimodal MRI data could regroup individuals according to their clinical diagnosis, in most cases. CONCLUSIONS: This study demonstrates that multimodal MRI is able to discriminate patients with PD from those with MSA with high accuracy. The combination of different MR biomarkers could be a great tool in early stage of disease to help diagnosis. © 2018 International Parkinson and Movement Disorder Society.

Grit Is Associated with Structure of Nucleus Accumbens and Gains in Cognitive Training.

There is a long-standing interest in the determinants of successful learning in children. "Grit" is an individual trait, reflecting the ability to pursue long-term goals despite temporary setbacks. Although grit is known to be predictive of future success in real-world learning situations, an understanding of the underlying neural basis and mechanisms is still lacking. Here we show that grit in a sample of 6-year-old children (n = 55) predicts the working memory improvement during 8 weeks of training on working memory tasks (p = .009). In a separate neuroimaging analysis performed on a partially overlapping sample (n = 27), we show that interindividual differences in grit were associated with differences in the volume of nucleus accumbens (peak voxel p = .021, x = 12, y = 11, z = -11). This was also confirmed in a leave-one-out analysis of gray matter density in the nucleus accumbens (p = .018). The results can be related to previous animal research showing the role of the nucleus accumbens to search out rewards regardless of delays or obstacles. The results provide a putative neural basis for grit and could contribute a cross-disciplinary connection of animal neuroscience to child psychology.

Quantitative susceptibility mapping of striatum in children and adults, and its association with working memory performance.

Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging (MRI) technique in which the magnetic susceptibility characteristic of molecular and cellular components, including iron and myelin, is quantified. Rapid iron accumulation in subcortical nuclei and myelination of the white matter tracts are two important developmental processes that contribute to cognitive functions. Both also contribute to the magnetic susceptibility of the brain tissues. Here, we used the QSM as indirect measures of iron in subcortical nuclei and myelin in caudo-frontal white matter pathways. We included two groups of participants; 21 children aged 6-7years and 25 adults aged 21-40years. All subjects also performed tests estimating their visuo-spatial working memory capacity. Adults had higher magnetic susceptibility in all subcortical nuclei, compared to children. The magnetic susceptibility of these nuclei highly correlated with their previously reported iron content. Moreover, working memory performance correlated significantly with the magnetic susceptibility in caudate nucleus in both children and adults, while the correlation was not significant for gray matter density. QSM of white matter in the caudo-frontal tract also differed between children and adults, but did not correlate with working memory scores. These results indicate that QSM is a feasible technique to measure developmental aspects of changes in the striatum, possibly related to iron content that is relevant to cognition.

Multimodal MRI assessment of nigro-striatal pathway in multiple system atrophy and Parkinson disease.

BACKGROUND: Parkinson's disease (PD) and multiple system atrophy (MSA) are two neurodegenerative alpha-synucleinopathies characterized by severe impairment of the nigro-striatal pathway. Based on T1-, T2*-, and diffusion-weighted magnetic resonance imaging (MRI), macro-structural and micro-structural abnormalities in these diseases can be detected. OBJECTIVE: This study was undertaken to compare the nigro-striatal changes that occur in patients with PD with those in patients with both variants of MSA (the parkinsonian variant, MSA-P, and the cerebellar variant, MSA-C), and to explore correlations between different MRI parameters and clinical data. METHODS: We simultaneously measured volume, T2* relaxation rates, and mean diffusivity in nigro-striatal structures (substantia nigra, caudate nucleus, and putamen) of 26 patients with PD and 29 patients with MSA (16 with MSA-P and 13 with MSA-C). RESULTS: Significant changes in the putamina in patients with MSA were observed compared with patients with PD. Patients with MSA-P had higher mean diffusivity values in their putamina than did patients with PD or MSA-C. The putamina of both subgroups of MSA had higher T2* relaxation rates values than PD. Remarkably, discriminant analysis showed that using two measurements of microstructural damage (T2* relaxation rates and mean diffusivity in the putamen) allowed 96% accuracy to distinguish patients with PD from those with MSA-P. Correlation analyses between MRI findings and clinical variables revealed that patients with PD showed significant correlations only at the nigra. In patients with MSA, clinical variables correlated with MRI findings in both the nigra and striatum. CONCLUSIONS: Multimodal MRI reveals different pattern of nigro-striatal involvement in patients with PD and patients with MSA.

A penny for your thoughts! patterns of fMRI activity reveal the content and the spatial topography of visual mental images.

Visual mental imagery is a complex process that may be influenced by the content of mental images. Neuropsychological evidence from patients with hemineglect suggests that in the imagery domain environments and objects may be represented separately and may be selectively affected by brain lesions. In the present study, we used functional magnetic resonance imaging (fMRI) to assess the possibility of neural segregation among mental images depicting parts of an object, of an environment (imagined from a first-person perspective), and of a geographical map, using both a mass univariate and a multivariate approach. Data show that different brain areas are involved in different types of mental images. Imagining an environment relies mainly on regions known to be involved in navigational skills, such as the retrosplenial complex and parahippocampal gyrus, whereas imagining a geographical map mainly requires activation of the left angular gyrus, known to be involved in the representation of categorical relations. Imagining a familiar object mainly requires activation of parietal areas involved in visual space analysis in both the imagery and the perceptual domain. We also found that the pattern of activity in most of these areas specifically codes for the spatial arrangement of the parts of the mental image. Our results clearly demonstrate a functional neural segregation for different contents of mental images and suggest that visuospatial information is coded by different patterns of activity in brain areas involved in visual mental imagery.

Finding my own way: an fMRI single case study of a subject with developmental topographical disorientation.

Developmental topographical disorientation (DTD) causes impaired spatial orientation and navigation from early childhood with no evidence of cerebral damage. Using fMRI and a landmark sequencing task, we investigated the hypothesis that Dr Wai's abnormal cerebral activation pattern was related to his peculiar behavioral profile. Although Dr Wai was able to correctly perform landmark sequencing, he showed a lack of activity in regions activated in all control subjects and activity in areas that were not activated in any control subject. These results are discussed in light of cognitive and functional model of navigation, with relevant implications for DTD physiology.

Neuropsychology of environmental navigation in humans: review and meta-analysis of FMRI studies in healthy participants.

In the past 20 years, many studies in the cognitive neurosciences have analyzed human ability to navigate in recently learned and familiar environments by investigating the cognitive processes involved in successful navigation. In this study, we reviewed the main experimental paradigms and made a cognitive-oriented meta-analysis of fMRI studies of human navigation to underline the importance of the experimental designs and cognitive tasks used to assess navigational skills. We performed a general activation likelihood estimation (ALE) meta-analysis of 66 fMRI experiments to identify the neural substrates underpinning general aspects of human navigation. Four individual ALE analyses were performed to identify the neural substrates of different experimental paradigms (i.e., familiar vs. recently learned environments) and different navigational strategies (allocentric vs. egocentric). Results of the general ALE analysis highlighted a wide network of areas with clusters in the occipital, parietal, frontal and temporal lobes, especially in the parahippocampal cortex. Familiar environments seem to be processed by an extended temporal-frontal network, whereas recently learned environments require activation in the parahippocampal cortex and the parietal and occipital lobes. Allocentric strategy is subtended by the same areas as egocentric strategy, but the latter elicits greater activation in the right precuneus, middle occipital lobe and angular gyrus. Our results suggest that different neural correlates are involved in recalling a well-learned or recently acquired environment and that different networks of areas subtend egocentric and allocentric strategies.

Insight on AV-45 binding in white and grey matter from histogram analysis: a study on early Alzheimer's disease patients and healthy subjects.

PURPOSE: AV-45 amyloid biomarker is known to show uptake in white matter in patients with Alzheimer's disease (AD), but also in the healthy population. This binding, thought to be of a non-specific lipophilic nature, has not yet been investigated. The aim of this study was to determine the differential pattern of AV-45 binding in white matter in healthy and pathological populations. METHODS: We recruited 24 patients presenting with AD at an early stage and 17 matched, healthy subjects. We used an optimized positron emission tomography-magnetic resonance imaging (PET-MRI) registration method and an approach based on an intensity histogram using several indices. We compared the results of the intensity histogram analyses with a more canonical approach based on target-to-cerebellum Standard Uptake Value (SUVr) in white and grey matter using MANOVA and discriminant analyses. A cluster analysis on white and grey matter histograms was also performed. RESULTS: White matter histogram analysis revealed significant differences between AD and healthy subjects, which were not revealed by SUVr analysis. However, white matter histograms were not decisive to discriminate groups, and indices based on grey matter only showed better discriminative power than SUVr. The cluster analysis divided our sample into two clusters, showing different uptakes in grey, but also in white matter. CONCLUSION: These results demonstrate that AV-45 binding in white matter conveys subtle information not detectable using the SUVr approach. Although it is not more efficient than standard SUVr in discriminating AD patients from healthy subjects, this information could reveal white matter modifications.

Investigating the discrimination ability of 3D convolutional neural networks applied to altered brain MRI parametric maps.

Convolutional neural networks (CNNs) are gradually being recognized in the neuroimaging community as a powerful tool for image analysis. Despite their outstanding performances, some aspects of CNN functioning are still not fully understood by human operators. We postulated that the interpretability of CNNs applied to neuroimaging data could be improved by investigating their behavior when they are fed data with known characteristics. We analyzed the ability of 3D CNNs to discriminate between original and altered whole-brain parametric maps derived from diffusion-weighted magnetic resonance imaging. The alteration consisted in linearly changing the voxel intensity of either one (monoregion) or two (biregion) anatomical regions in each brain volume, but without mimicking any neuropathology. Performing ten-fold cross-validation and using a hold-out set for testing, we assessed the CNNs' discrimination ability according to the intensity of the altered regions, comparing the latter's size and relative position. Monoregion CNNs showed that the larger the modified region, the smaller the intensity increase needed to achieve good performances. Biregion CNNs systematically outperformed monoregion CNNs, but could only detect one of the two target regions when tested on the corresponding monoregion images. Exploiting prior information on training data allowed for a better understanding of CNN behavior, especially when altered regions were combined. This can inform about the complexity of CNN pattern retrieval and elucidate misclassified examples, particularly relevant for pathological data. The proposed analytical approach may serve to gain insights into CNN behavior and guide the design of enhanced detection systems exploiting our prior knowledge.

Developmental dyslexia, developmental coordination disorder and comorbidity discrimination using multimodal structural and functional neuroimaging.

Developmental dyslexia (DD) and developmental coordination disorder (DCD) are two common neurodevelopmental disorders with a high co-occurrence rate. This led several authors to postulate that the two disorders share, at least partially, similar neural underpinning. However, even though several studies examined brain differences between typically developing (TD) children and children with either DD or DCD, no previous study directly compared DD, DCD and children with both disorders (COM) using neuroimaging. We acquired structural and resting-state functional MRI images of 136 children (TD = 42, DD = 45, DCD = 20, COM = 29). Difference between TD children and the other groups was assessed using univariate analysis of structural indexes including grey and white matter volumes and functional indexes quantifying activity (fraction of the amplitude of the low frequency fluctuations), local and global connectivity. Regional differences in structural and functional brain indexes were then used to train machine learning models to discriminate among DD, DCD and COM and to find the most discriminant regions. While no imaging index alone discriminated between the three groups, grouping grey and white matter volumes (structural model) or activity, local and global connectivity (functional model) made possible to discriminate among the DD, DCD and COM groups. The most important discrimination was obtained using the functional model, with regions in the cerebellum and the temporal lobe being the most discriminant for DCD and DD children, respectively. Results further showed that children with both DD and DCD have subtle but identifiable brain differences that can only be captured using several imaging indexes pertaining to both brain structure and function.

Atypical connectivity in the cortico-striatal network in NF1 children and its relationship with procedural perceptual-motor learning and motor skills.

INTRODUCTION: Neurofibromatosis type 1 (NF1) is considered a model of neurodevelopmental disorder because of the high frequency of learning deficits, especially developmental coordination disorder. In neurodevelopmental disorder, Nicolson and Fawcett formulated the hypothesis of an impaired procedural learning system that has its origins in cortico-subcortical circuits. Our aim was to investigate the relationship between cortico-striatal connectivity and procedural perceptual-motor learning performance and motor skills in NF1 children. METHODS: Seventeen NF1 and 18 typically developing children aged between 8 and 12 years old participated in the study. All were right-handed and did not present intellectual or attention deficits. In all children, procedural perceptual-motor learning was assessed using a bimanual visuo-spatial serial reaction time task (SRTT) and motor skills using the Movement Assessment Battery for Children (M-ABC). All participants underwent a resting-state functional MRI session. We used a seed-based approach to explore cortico-striatal connectivity in somatomotor and frontoparietal networks. A comparison between the groups' striato-cortical connectivity and correlations between connectivity and learning (SRTT) and motor skills (M-ABC) were performed. RESULTS: At the behavioral level, SRTT scores are not significantly different in NF1 children compared to controls. However, M-ABC scores are significantly impaired within 9 patients (scores below the 15th percentile). At the cerebral level, NF1 children present a higher connectivity in the cortico-striatal regions mapping onto the right angular gyrus compared to controls. We found that the higher the connectivity values between these regions, differentiating NF1 and controls, the lower the M-ABC scores in the whole sample. No correlation was found for the SRTT scores. CONCLUSION: NF1 children present atypical hyperconnectivity in cortico-striatal connections. The relationship with motor skills could suggest a sensorimotor dysfunction already found in children with developmental coordination disorder. These abnormalities are not linked to procedural perceptual-motor learning assessed by SRTT.

Intrinsic Cortico-Subcortical Functional Connectivity in Developmental Dyslexia and Developmental Coordination Disorder.

Developmental dyslexia (DD) and developmental coordination disorder (DCD) are distinct diagnostic disorders. However, they also frequently co-occur and may share a common etiology. It was proposed conceptually a neural network framework that explains differences and commonalities between DD and DCD through impairments of distinct or intertwined cortico-subcortical connectivity pathways. The present study addressed this issue by exploring intrinsic cortico-striatal and cortico-cerebellar functional connectivity in a large (n = 136) resting-state fMRI cohort study of 8-12-year-old children with typical development and with DD and/or DCD. We delineated a set of cortico-subcortical functional circuits believed to be associated with the brain's main functions (visual, somatomotor, dorsal attention, ventral attention, limbic, frontoparietal control, and default-mode). Next, we assessed, using general linear and multiple kernel models, whether and which circuits distinguished between the groups. Findings revealed that somatomotor cortico-cerebellar and frontoparietal cortico-striatal circuits are affected in the presence of DCD, including abnormalities in cortico-cerebellar connections targeting motor-related regions and cortico-striatal connections mapping onto posterior parietal cortex. Thus, DCD but not DD may be considered as an impairment of cortico-subcortical functional circuits.

Are morphological and structural MRI characteristics related to specific cognitive impairments in neurofibromatosis type 1 (NF1) children?

INTRODUCTION: NF1 children have cognitive disorders, especially in executive functions, visuospatial, and language domains, the pathophysiological mechanisms of which are still poorly understood. MATERIALS AND METHODS: A correlation study was performed from neuropsychological assessments and brain MRIs of 38 NF1 patients and 42 controls, all right-handed, aged 8-12 years and matched in age and gender. The most discriminating neuropsychological tests were selected to assess their visuospatial, metaphonological and visuospatial working memory abilities. The MRI analyses focused on the presence and location of Unidentified Bright Objects (UBOs) (1), volume analysis (2) and diffusion analysis (fractional anisotropy and mean diffusivity) (3) of the regions of interest including subcortical structures and posterior fossa, as well as shape analysis of subcortical structures (4). The level of attention, intelligence quotient, age and gender of the patients were taken into account in the statistical analysis. Then, we studied how diffusion and volumes parameters were associated with neuropsychological characteristics in NF1 children. RESULTS: NF1 children present different brain imaging characteristics compared to the control such as (1) UBOs in 68%, (2) enlarged total intracranial volume, involving all subcortical structures, especially thalamus, (3) increased MD and decreased FA in thalamus, corpus callosum and hippocampus. These alterations are diffuse, without shape involvement. In NF1 group, brain microstructure is all the more altered that volumes are enlarged. However, we fail to find a link between these brain characteristics and neurocognitive scores. CONCLUSION: While NF1 patients have obvious pathological brain characteristics, the neuronal substrates of their cognitive deficits are still not fully understood, perhaps due to complex and multiple pathophysiological mechanisms underlying this disorder, as suggested by the heterogeneity observed in our study. However, our results are compatible with an interpretation of NF1 as a diffuse white matter disease.

Neuroplasticity and brain reorganization associated with positive outcomes of multidisciplinary rehabilitation in progressive multiple sclerosis: A fMRI study.

BACKGROUND: Multiple sclerosis (MS) is characterized by a range of symptoms, including motor, sensorimotor and cognitive impairments, that limit the quality of life. A multidisciplinary rehabilitation approach in people affected by multiple sclerosis was recently reported to improve the functional abilities of MS patients in daily activities. The purpose of the study was to assess the effect of multidisciplinary rehabilitation on the whole brain of MS patients by means of functional magnetic resonance imaging (fMRI). METHODS: Thirty individuals affected by MS (49.9 ± 12.1 years; disease duration: 16.0 ± 8.5 years) with a medium-high severity of disease were enrolled. The fMRI examination assessed a range of action-related tasks involving passive movement, mental simulation of action and miming of action triggered by external stimuli, such as object photography. The three tasks were performed using each arm separately. The fMRI acquisitions were performed at T1 (inclusion in the study), T2 (3 months later, at the start of rehabilitation) and T3 (after 3 months of multidisciplinary rehabilitation). RESULTS: The fMRI results revealed a significant reduction in the activity of brain areas related to task-specific networks as well as the activation of cerebral regions not usually involved in task-specific related network, such as the medial prefrontal area. CONCLUSIONS: The effectiveness of multidisciplinary rehabilitation on activity and participation has been established in previous studies. Our study sheds new light on the effect of such treatment on brain reorganization.

Neural modifications in lower limb amputation: an fMRI study on action and non-action oriented body representations.

The loss of sensorimotor and visual information that follows limb amputation is known to affect both the action-oriented (body schema, BS) and non-action oriented (NA) body representations. However, the neural underpinnings of these effects have not yet been fully understood. We investigated the neural correlates of body representations in a group of 9 healthy right-handed individuals with left lower limb amputation (LLA) and 11 healthy age-matched controls (HC) by using event-related functional magnetic resonance imaging. Participants were scanned while performing mental rotation of body parts (i.e. hand, foot and eye) and objects (i.e. a rear-view mirror). Although the performance of LLA were similar to that of HC, they showed a different activation profile in relation to both BS and to NA within a wide range of brain areas. The bilateral intraparietal sulcus was less activated in LLA than HC, whereas the bilateral anterior insula as well as the fusiform body area, the precentral gyrus, the supplementary motor area in the left hemisphere and the inferior occipital gyrus in the right hemisphere were more activated during the mental rotation of left stimuli in the LLA. Also, the left EBA showed higher activation during the mental rotation of the foot than that of the eye in the LLA but not in the HC. Our results are consistent with the hypothesis that left LLA yields to a modification in the body representation network even when it does not lead to clear behavioral deficits.

Can the Cognitive Phenotype in Neurofibromatosis Type 1 (NF1) Be Explained by Neuroimaging? A Review.

Neurofibromatosis type 1 (NF1) is one of the most frequent monogenetic disorders. It can be associated with cognitive dysfunctions in several domains such as executive functioning, language, visual perception, motor skills, social skills, memory and/or attention. Neuroimaging is becoming more and more important for a clearer understanding of the neural basis of these deficits. In recent years, several studies have used different imaging techniques to examine structural, morphological and functional alterations in NF1 disease. They have shown that NF1 patients have specific brain characteristics such as Unidentified Bright Objects (UBOs), macrocephaly, a higher volume of subcortical structures, microstructure integrity alterations, or connectivity alterations. In this review, which focuses on the studies published after the last 2 reviews of this topic (in 2010 and 2011), we report on recent structural, morphological and functional neuroimaging studies in NF1 subjects, with special focus on those that examine the neural basis of the NF1 cognitive phenotype. Although UBOs are one of the most obvious and visible elements in brain imaging, correlation studies have failed to establish a robust and reproducible link between major cognitive deficits in NF1 and their presence, number or localization. In the same vein, the results among structural studies are not consistent. Functional magnetic resonance imaging (fMRI) studies appear to be more sensitive, especially for understanding the executive function deficit that seems to be associated with a dysfunction in the right inferior frontal areas and the middle frontal areas. Similarly, fMRI studies have found that visuospatial deficits could be associated with a dysfunction in the visual cortex and especially in the magnocellular pathway involved in the processing of low spatial frequency and high temporal frequency. Connectivity studies have shown a reduction in anterior-posterior "long-range" connectivity and a deficit in deactivation in default mode network (DMN) during cognitive tasks. In conclusion, despite the contribution of new imaging techniques and despite relative advancement, the cognitive phenotype of NF1 patients is not totally understood.