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International audience; The greater expansion of the frontal lobes along the phylogeny scale has been interpreted as the signature of evolutionary changes underlying higher cognitive abilities in humans functions in humans. However, it is unknown how an increase in number of gyri, sulci and cortical areas in the frontal lobe have coincided with a parallel increase in connectivity. Here, using advanced tractography based on spherical deconvolution, we produced an atlas of human frontal association connections that we compared with axonal tracing studies of the monkey brain. We report several similarities between human and monkey in the cingulum, uncinate, superior longitudinal fasciculus, frontal aslant tract and orbito-polar tract. These similarities suggest to preserved functions across anthropoids. In addition, we found major differences in the arcuate fasciculus and the inferior fronto-occipital fasciculus. These differences indicate possible evolutionary changes in the connectional anatomy of the frontal lobes underlying unique human abilities.

International audience; Right hemisphere dominance for visuospatial attention is characteristic for most humans, but its anatomical basis remains unknown. We report the first evidence in humans for a larger parieto-frontal network in the right than left hemisphere; and a significant correlation between the degree of anatomical lateralization and asymmetry of performance on visuospatial tasks. Our results suggest that hemispheric specialization is associated with an unbalanced speed of visuospatial processing.

Diffusion tensor imaging (DTI) methods are widely used to reconstruct white matter trajectories and to quantify tissue changes using the average diffusion properties of each brain voxel. Spherical deconvolution (SD) methods have been developed to overcome the limitations of the diffusion tensor model in resolving crossing fibers and to improve tractography reconstructions. However, the use of SD methods to obtain quantitative indices of white matter integrity has not been extensively explored. In this study, we show that the hindrance modulated orientational anisotropy (HMOA) index, defined as the absolute amplitude of each lobe of the fiber orientation distribution, can be used as a compact measure to characterize the diffusion properties along each fiber orientation in white matter regions with complex organization. We demonstrate that the HMOA is highly sensitive to changes in fiber diffusivity (e.g., myelination processes or axonal loss) and to differences in the microstructural organization of white matter like axonal diameter and fiber dispersion. Using simulations to describe diffusivity changes observed in normal brain development and disorders, we observed that the HMOA is able to identify white matter changes that are not detectable with conventional DTI indices. We also show that the HMOA index can be used as an effective threshold for in vivo data to improve tractography reconstructions and to better map white matter complexity inside the brain. In conclusion, the HMOA represents a true tract‐specific and sensitive index and provides a compact characterization of white matter diffusion properties with potential for widespread application in normal and clinical populations. Hum Brain Mapp 34:2464–2483, 2013. © 2012 Wiley Periodicals, Inc.

Looking for a friend in the crowd, avoiding a sudden danger or contemplating a work of art are some examples of actions based on the efficiency of our visuo-spatial attention system. The specialization of the right brain hemisphere for visuo-spatial attention is a characteristic of most humans, but its anatomical basis remains largely unknown. Our study is the first to report in humans the existence of a bilateral parieto-frontal network whose hemispheric lateralization predicts the degree of specialization of the right hemisphere for visuo-spatial attention. Our results also suggest that this specialization is associated with an unbalanced speed of visuo-spatial processing between the two hemispheres. This lateralization may be predictive of visuo-spatial recovery in patients with lesions of parieto-frontal networks.

Diffusion magnetic resonance imaging (MRI) tractography is a method that can be used for the in vivo quantification of tissue microstructural integrity and the virtual reconstruction of white matter pathways[3]. The diffusion-weighted MRI pulse sequences are sensitive to the displacement of water molecules within biological tissues [2]. Generally the displacement of water molecules follows Einstein’s equation, where the mean squared displacement r 2 is directly proportional to the observation time (t) according to: $$\left\langle {{r^2}} \right\rangle = 6Dt.$$ .

Introduction Repetitive behaviour and inhibitory control deficits are core features of autism; and it has been suggested that they result from differences in the anatomy of striatum; and/or the ‘connectivity’ of subcortical regions to frontal cortex. There are few studies, however, that have measured the micro-structural organisation of white matter tracts connecting striatum and frontal cortex. Aims To investigate differences in bulk volume of striatum and micro-structural organisation of fronto-striatal white matter in people with autism; and their association with repetitive behaviour and inhibitory control. Methods We compared the bulk volume of striatum (caudate nucleus, putamen and nucleus accumbens) and white matter organisation of fronto-striatal tracts using (respectively) structural magnetic resonance imaging (sMRI) and tract specific diffusion tensor imaging (DTI) measures in 21 adults with autism and 22 controls. We also assessed performance on a cognitive inhibition (go/nogo) task. Results Bulk volume of striatal structures did not differ between groups. However, adults with autism had a significantly smaller total brain white matter volume, lower fractional anisotropy of white matter tracts connecting putamen to frontal cortical areas, higher mean diffusivity of white matter tracts connecting accumbens to frontal cortex and worse performance on the go/nogo task. Also, performance on the go/nogo task was significantly related to anatomical variation when both groups were combined; but not within the autism group alone. Conclusions These data suggest that autism may be associated with differences in the anatomy of fronto-striatal white matter tracts.

Spherical Deconvolution methods have been applied to diffusion MRI to improve diffusion tensor tractography results in brain regions with multiple fibre crossing. Recent developments, such as the introduction of non-negative constraints on the solution, allow a more accurate estimation of fibre orientations by reducing instability effects due to noise robustness. Standard convolution methods do not, however, adequately model the effects of partial volume from isotropic tissue, such as gray matter, or cerebrospinal fluid, which may degrade spherical deconvolution results. Here we use a newly developed spherical deconvolution algorithm based on an adaptive regularization (damped version of the Richardson-Lucy algorithm) to reduce isotropic partial volume effects. Results, from both simulated and in vivo datasets, show that, compared to a standard non-negative constrained algorithm the damped Richardson Lucy algorithm reduces spurious fibre orientations and preserves angular resolution of the main fibre orientations. These findings suggest that, in some brain regions, non-negative constraints alone may not be sufficient to reduce spurious fibre orientations. Considering both the speed of processing and the scan time required, this new method has the potential for better characterizing white matter anatomy and the integrity of pathological tissue. Spherical deconvolution methods have been applied to diffusion MRI to improve diffusion tensor tractography results in brain regions with multiple fibre crossing. Recent developments, such as the introduction of non-negative constraints on the solution, allow a more accurate estimation of fibre orientations by reducing instability effects due to noise robustness. Standard convolution methods do not, however, adequately model the effects of partial volume from isotropic tissue, such as gray matter, or cerebrospinal fluid, which may degrade spherical deconvolution results. Here we use a newly developed spherical deconvolution algorithm based on an adaptive regularization (damped version of the Richardson-Lucy algorithm) to reduce isotropic partial volume effects. Results from both simulated and in vivo datasets show that, compared to a standard non-negative constrained algorithm, the damped Richardson-Lucy algorithm reduces spurious fibre orientations and preserves angular resolution of the main fibre orientations. These findings suggest that, in some brain regions, non-negative constraints alone may not be sufficient to reduce spurious fibre orientations. Considering both the speed of processing and the scan time required, this new method has the potential for better characterizing white matter anatomy and the integrity of pathological tissue. © 2009 Elsevier Inc. All rights reserved.

Background: NGR-hTNF consists of human tumour necrosis factor-alpha (hTNF-alpha) fused to the tumour-homing peptide NGR, a ligand of an aminopeptidase N/CD13 isoform, which is overexpressed on endothelial cells of newly formed tumour blood vessels. NGR-TNF showed a biphasic dose-response curve in preclinical models. This study exploring the low-dose range aimed to define safety and optimal biological dose of NGR-hTNF. Patients and methods: Pharmacokinetics, plasma biomarkers and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) were evaluated at baseline and after each cycle in 16 patients enrolled at four doubling-dose levels (0.2-0.4-0.8-1.6 mu g/m(2)). NGR-hTNF was given intravenously as 1-h infusion every 3 weeks (q3w). Tumour response was assessed q6w. Results: Eighty-three cycles (median, 2; range, 1-29) were administered. Most frequent treatment-related toxicity was grade 1-2 chills (69%), occurring during the first infusions. Only one patient treated at 1.6 mu g/m(2) had a grade 3 drug-related toxicity (chills and dyspnoea). Both C(max) and AUC increased proportionally with dose. No shedding of soluble TNF-alpha receptors was observed up to 0.8 mu g/m(2). Seventy-five percent of DCE-MRI assessed patients showed a decrease over time of K(trans), which was more pronounced at 0.8 mu g/m(2). Seven patients (44%) had stable disease for a median time of 5.9 months, including a colon cancer patient who experienced an 18-month progression-free time. Conclusion: Based on tolerability, soluble TNF-receptors kinetics, anti-vascular effect and disease control, NGR-hTNF 0.8 mu g/m(2) will be further developed either as single-agent or with standard chemotherapy. (C) 2009 Elsevier Ltd. All rights reserved.

It has been suggested that people with autistic spectrum disorder (ASD) have altered development (and connectivity) of limbic circuits. However, direct evidence of anatomical differences specific to white matter pathways underlying social behaviour and emotions in ASD is lacking. We used Diffusion Tensor Imaging Tractography to compare, in vivo, the microstructural integrity and age-related differences in the extended limbic pathways between subjects with Asperger syndrome and healthy controls. Twenty-four males with Asperger syndrome (mean age 23+/-12 years, age range: 9-54 years) and 42 age-matched male controls (mean age 25+/-10 years, age range: 9-54 years) were studied. We quantified tract-specific diffusivity measurements as indirect indexes of microstructural integrity (e.g. fractional anisotropy, FA; mean diffusivity, MD) and tract volume (e.g. number of streamlines) of the main limbic tracts. The dissected limbic pathways included the inferior longitudinal fasciculus, inferior frontal occipital fasciculus, uncinate, cingulum and fornix. There were no significant between-group differences in FA and MD. However, compared to healthy controls, individuals with Asperger syndrome had a significantly higher number of streamlines in the right (p=.003) and left (p=.03) cingulum, and in the right (p=.03) and left (p=.04) inferior longitudinal fasciculus. In contrast, people with Asperger syndrome had a significantly lower number of streamlines in the right uncinate (p=.02). Within each group there were significant age-related differences in MD and number of streamlines, but not FA. However, the only significant age-related between-group difference was in mean diffusivity of the left uncinate fasciculus (Z(obs)=2.05) (p=.02). Our preliminary findings suggest that people with Asperger syndrome have significant differences in the anatomy, and maturation, of some (but not all) limbic tracts.

New complex tissue microstructure estimators have been presented recently in order to elucidate white matter fibre orientations. Since these algorithms are based on the diffusion- weighted signal profile, the estimations are affected by noise artefacts. The proven robustness of these methods cannot counteract distortions since the statistical Rician behavior has not been taken into account. In this study, two techniques to counteract the noise distortions are presented to improve the fibre orientation estimations. Simulations and in vivo experiments show an improvement in the angular resolution and convergence of the results. One of these strategies represents a good compromise between computational cost and result improvements.

A deconvolution approach, based on a multi-tensor model, is presented to solve fiber crossing in diffusion MRI. In order to provide a direct physical interpretation of the signal generation process, we re-wrote the classical multi-tensor model, identifying a significant scalar parameter alpha to characterize the deconvolution process. Simulations show that, in presence of noise, the method is able to correctly separate fiber crossing. Application on in-vivo data highlights the ability of our approach to distinguish more than two fibers within the same voxel, suggesting its application in fiber tracking or connectivity studies even of complex brain structures.

A deconvolution approach is presented to solve fiber crossing in diffusion magnetic resonance imaging. In order to provide a direct physical interpretation of the signal generation process, we started from the classical multicompartment model and rewrote this in terms of a convolution process, identifying a significant scalar parameter alpha to characterize the physical system response. Deconvolution is performed by a modified version of the Richardson-Lucy algorithm. Simulations show the ability of this method to correctly separate fiber crossing, even in the presence of noisy data, with lower signal-to-noise ratio, and imprecision in the impulse response function imposed during deconvolution. The in vivo data confirms the efficacy of this method to resolve fiber crossing in real complex brain structures. These results suggest the usefulness of our approach in fiber tracking or connectivity studies.

Introduction High potency cannabis has been associated with greater risk, and earlier onset of psychosis. However, its effect on brain structure, particularly white matter (WM), has never been explored. Objectives and Aims To elucidate the interplay between cannabis potency, pattern of use (frequency and age of first use) and CC microstructure; in patients with first-episode psychosis (FEP) and healthy controls. Methods 56 FEP and 43 healthy controls underwent Diffusion-Tensor Imaging combined with WM mapping-tractography. CC was virtually dissected and segmented to calculate Fractional Anisotropy (FA), Mean Diffusivity (MD), Axial Diffusivity (AD) and Radial Diffusivity (RD) for each CC segment. Results High potency cannabis users had higher Total CC MD and Total CC AD than both low potency users and those who never used (p=0.009 and p=0.02 respectively). Daily users also had higher Total CC MD and Total CC AD than both occasional users and those who never used (p=0.02 and p=0.01 respectively). Furthermore, daily/highpotency users had higher Total CC MD than those who never used or used weekly [F(2,57)=4.7, p=0.01]. There was no effect of diagnosis or diagnosis X potency/patterns of use interactions; neither differences between users who started before the age of 15 and those who started later were detected, in any diffusivity measures. Conclusions Frequent use of high-potency cannabis significantly affects callosal microstructure, regardless of the presence of a psychotic disorder. Given the increased availability and use of high potency preparations in Europe, raising awareness about some of their detrimental effects is an important avenue to pursue.

Introduction The impact of cannabis use on brain structure, particularly white matter (WM), is poorly understood. The CC is the largest WM structure in the brain. Abnormalities revealed in the CC may underlie functional anomalies of cannabis use. This is the largest study to explore the effect of cannabis on callosal WM connectivity among first episode psychosis (FEP) and controls. Objectives To investigate the relationship between cannabis use and WM micro-structural integrity of the CC, in FEP and healthy controls. Methods We evaluated 56 FEP patients (67% current cannabis users), and 43 healthy controls (44% current cannabis users). We used Diffusion Tensor Imaging combined with a WM mapping-tractography technique to investigate the microstructural integrity of the CC. Results Total CC Fractional anisotropy (FA) was lower in patients than controls (p=0.05). Cannabis-using patients had lower FA of the total CC than cannabis-using controls (p=0.04). There were no differences in FA between cannabis-using patients and those who had never used. However, cannabis-using patients had higher mean diffusivity (MD) of total CC (p= 0.02), Rostral-Body (p=0.003), Anterior Mid-Body (p=0.03) and the Splenium (p=0.06) than patients who never used cannabis. There were no differences in MD between patient users who started before the age of 16 and those who started later. Conclusion Cannabis is associated with a significant effect on callosal WM integrity only in patients with psychosis. Disturbed callosal connectivity may explain some of the abnormalities with regard to the functional and clinical outcomes in FEP cannabis users, including measures of cognitive impairment.

Wedeen et al . (Reports, 30 March 2012, p. 1628) proposed a geometrical grid pattern in the brain that could help the understanding of the brain’s organization and connectivity. We show that whole-brain fiber crossing quantification does not support their theory. Our results suggest that the grid pattern is most likely an artifact attributable to the limitations of their method.

PURPOSE OF REVIEW After more than 10 years of methodological developments and clinical applications, diffusion imaging tractography has reached a crossroad. Although the method is still in its infancy, the time has come to address some important questions. Can tractography reproduce reliably known anatomy or describe new anatomical pathways? Are interindividual differences, for example in tract lateralization, important to understand heterogeneity of clinical manifestations? Do novel tractography algorithms provide a real advantage over previous methods? Here we focus on some of the most exciting recent advancements in diffusion tractography and critically highlight their advantages and limitations. RECENT FINDINGS A flourishing of diffusion methods and models are bringing new solutions to the well known limitations of classical tractography based on the tensor model. However, these methods pose also new challenges and require the convergence and integration of different disciplines before they can replace what is currently widely available. SUMMARY Rigorous postmortem validation, clinical optimization and experimental confirmation are obligatory steps before advanced diffusion technologies can translate into clear benefits for neurological patients.

Nat. Neurosci. 14, 1245–1246 (2011); published online 18 September 2011; corrected after print 13 October 2011 In the version of this article initially published, the institute identifier was omitted from the INSERM affiliation of author Michel Thiebaut de Schotten. The correct affiliation should read Unite Mixte de Recherche (UMR) S 975.

Summary Objectives : A novel approach to the PET image reconstruction is presented, based on the inclusion of image deconvolution during conventional OSEM reconstruction. Deconvolution is here used to provide a recovered PET image to be included as “a priori" information to guide OSEM toward an improved solution. Methods : Deconvolution was implemented using the Lucy-Richardson (LR) algorithm: Two different deconvolution schemes were tested, modifying the conventional OSEM iterative formulation: 1) We built a regularizing penalty function on the recovered PET image obtained by deconvolution and included i in the OSEM iteration. 2) After each conventional global OSEM iteration, we deconvolved the resulting PET image and used this “recovered" version as the initialization image for the next OSEM iteration. Tests were performed on both simulated and acquired data. Results : Compared to the conventional OSEM, both these strategies, applied to simulated and acquired data, showed an improvement in image spatial resolution with better behavior in the second case. In this way, small lesions, present on data, could be better discriminated in terms of contrast. Conclusions : Application of this approach to both simulated and acquired data suggests its efficacy in obtaining PET images of enhanced quality.

Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here, we developed a phenotypic stratification model that makes highly accurate (97–99%) out-of-sample SC = RRB, SC > RRB, and RRB > SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n = 509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC > RRB and visual association circuitry in SC = RRB. The SC = RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry., Natasha Bertelsen et al. develop a computational model to categorize patients with autism spectrum disorder (ASD) into distinct subgroups, based on social-communicative or restricted repetitive behaviors. By integrating publicly available neuroimaging and genetic data, they report neural and molecular signatures in two of these subgroups, altogether highlighting subtle differences in neural circuitry and genomic networks that could underlie phenotypic differences among ASD patients.