Using high angular resolution diffusion imaging data to discriminate cortical regions

Brodmann's 100-year-old summary map has been widely used for cortical localization in neuroscience. There is a pressing need to update this map using non-invasive, high-resolution and reproducible data, in a way that captures individual variability. We demonstrate here that standard HARDI data has sufficiently diverse directional variation among grey matter regions to inform parcellation into distinct functional regions, and that this variation is reproducible across scans. This characterization of the signal variation as non-random and reproducible is the critical condition for successful cortical parcellation using HARDI data. This paper is a first step towards an individual cortex-wide map of grey matter microstructure, The gray/white matter and pial boundaries were identified on the high-resolution structural MRI images. Two HARDI data sets were collected from each individual and aligned with the corresponding structural image. At each vertex point on the surface tessellation, the diffusion-weighted signal was extracted from each image in the HARDI data set at a point, half way between gray/white matter and pial boundaries. We then derived several features of the HARDI profile with respect to the local cortical normal direction, as well as several fully orientationally invariant features. These features were taken as a fingerprint of the underlying grey matter tissue, and used to distinguish separate cortical areas. A support-vector machine classifier, trained on three distinct areas in repeat 1 achieved 80-82% correct classification of the same three areas in the unseen data from repeat 2 in three volunteers. Though gray matter anisotropy has been mostly overlooked hitherto, this approach may eventually form the foundation of a new cortical parcellation method in living humans. Our approach allows for further studies on the consistency of HARDI based parcellation across subjects and comparison with independent microstructural measures such as ex-vivo histology

CD6 and Syntaxin Binding Protein 6 Variants and Response to Tumor Necrosis Factor Alpha Inhibitors in Danish Patients with Rheumatoid Arthritis

<div><h3>Background</h3><p>TNFα inhibitor therapy has greatly improved the treatment of patients with rheumatoid arthritis, however at least 30% do not respond. We aimed to investigate insertions and deletions (INDELS) associated with response to TNFα inhibitors in patients with rheumatoid arthritis (RA).</p> <h3>Methodology and Principal Findings</h3><p>In the DANBIO Registry we identified 237 TNFα inhibitor naïve patients with RA (81% women; median age 56 years; disease duration 6 years) who initiated treatment with infliximab (n = 160), adalimumab (n = 56) or etanercept (n = 21) between 1999 and 2008 according to national treatment guidelines. Clinical response was assessed at week 26 using EULAR response criteria. Based on literature, we selected 213 INDELS potentially related to RA and treatment response using the GeneVa® (Compugen) <em>in silico</em> database of 350,000 genetic variations in the human genome. Genomic segments were amplified by polymerase chain reaction (PCR), and genotyped by Sanger sequencing or fragment analysis. We tested the association between genotypes and EULAR good response versus no response, and EULAR good response versus moderate/no response using Fisher’s exact test. At baseline the median DAS28 was 5.1. At week 26, 68 (29%) patients were EULAR good responders, while 81 (34%) and 88 (37%) patients were moderate and non-responders, respectively. A 19 base pair insertion within the CD6 gene was associated with EULAR good response vs. no response (OR = 4.43, 95% CI: 1.99–10.09, p = 7.211×10⁻⁵) and with EULAR good response vs. moderate/no response (OR = 4.54, 95% CI: 2.29–8.99, p = 3.336×10⁻⁶). A microsatellite within the syntaxin binding protein 6 (STXBP6) was associated with EULAR good response vs. no response (OR = 4.01, 95% CI: 1.92–8.49, p = 5.067×10⁻⁵).</p> <h3>Conclusion</h3><p>Genetic variations within CD6 and STXBP6 may influence response to TNFα inhibitors in patients with RA.</p> </div

Reward-Related Dorsal Striatal Activity Differences between Former and Current Cocaine Dependent Individuals during an Interactive Competitive Game

Cocaine addiction is characterized by impulsivity, impaired social relationships, and abnormal mesocorticolimbic reward processing, but their interrelationships relative to stages of cocaine addiction are unclear. We assessed blood-oxygenation-level dependent (BOLD) signal in ventral and dorsal striatum during functional magnetic resonance imaging (fMRI) in current (CCD; n = 30) and former (FCD; n = 28) cocaine dependent subjects as well as healthy control (HC; n = 31) subjects while playing an interactive competitive Domino game involving risk-taking and reward/punishment processing. Out-of-scanner impulsivity-related measures were also collected. Although both FCD and CCD subjects scored significantly higher on impulsivity-related measures than did HC subjects, only FCD subjects had differences in striatal activation, specifically showing hypoactivation during their response to gains versus losses in right dorsal caudate, a brain region linked to habituation, cocaine craving and addiction maintenance. Right caudate activity in FCD subjects also correlated negatively with impulsivity-related measures of self-reported compulsivity and sensitivity to reward. These findings suggest that remitted cocaine dependence is associated with striatal dysfunction during social reward processing in a manner linked to compulsivity and reward sensitivity measures. Future research should investigate the extent to which such differences might reflect underlying vulnerabilities linked to cocaine-using propensities (e.g., relapses)

Functional MRI and Diffusion Tensor Imaging of Brain Reorganization After Experimental Stroke

The potential of the adult brain to reorganize after ischemic injury is critical for functional recovery and provides a significant target for therapeutic strategies to promote brain repair. Despite the accumulating evidence of brain plasticity, the interaction and significance of morphological and physiological modifications in post-stroke brain tissue remain mostly unclear. Neuroimaging techniques such as functional MRI (fMRI) and diffusion tensor imaging (DTI) enable in vivo assessment of the spatial and temporal pattern of functional and structural changes inside and outside ischemic lesion areas. This can contribute to the elucidation of critical aspects in post-stroke brain remodeling. Task/stimulus-related fMRI, resting-state fMRI, or pharmacological MRI enables direct or indirect measurement of neuronal activation, functional connectivity, or neurotransmitter system responses, respectively. DTI allows estimation of the structural integrity and connectivity of white matter tracts. Together, these MRI methods provide an unprecedented means to (a) measure longitudinal changes in tissue structure and function close by and remote from ischemic lesion areas, (b) evaluate the organizational profile of neural networks after stroke, and (c) identify degenerative and restorative processes that affect post-stroke functional outcome. Besides, the availability of MRI in clinical institutions as well as research laboratories provides an optimal basis for translational research on stroke recovery. This review gives an overview of the current status and perspectives of fMRI and DTI applications to study brain reorganization in experimental stroke models

Measuring macroscopic brain connections in vivo

Decades of detailed anatomical tracer studies in non-human animals point to a rich and complex organization of long-range white matter connections in the brain. State-of-the art in vivo imaging techniques are striving to achieve a similar level of detail in humans, but multiple technical factors can limit their sensitivity and fidelity. In this review, we mostly focus on magnetic resonance imaging of the brain. We highlight some of the key challenges in analyzing and interpreting in vivo connectomics data, particularly in relation to what is known from classical neuroanatomy in laboratory animals. We further illustrate that, despite the challenges, in vivo imaging methods can be very powerful and provide information on connections that is not available by any other means

White matter changes in microstructure associated with a maladaptive response to stress in rats

In today's society, every individual is subjected to stressful stimuli with different intensities and duration. This exposure can be a key trigger in several mental illnesses greatly affecting one's quality of life. Yet not all subjects respond equally to the same stimulus and some are able to better adapt to them delaying the onset of its negative consequences. The neural specificities of this adaptation can be essential to understand the true dynamics of stress as well as to design new approaches to reduce its consequences. In the current work, we employed ex vivo high field diffusion magnetic resonance imaging (MRI) to uncover the differences in white matter properties in the entire brain between Fisher 344 (F344) and Sprague-Dawley (SD) rats, known to present different responses to stress, and to examine the effects of a 2-week repeated inescapable stress paradigm. We applied a tract-based spatial statistics (TBSS) analysis approach to a total of 25 animals. After exposure to stress, SD rats were found to have lower values of corticosterone when compared with F344 rats. Overall, stress was found to lead to an overall increase in fractional anisotropy (FA), on top of a reduction in mean and radial diffusivity (MD and RD) in several white matter bundles of the brain. No effect of strain on the white matter diffusion properties was observed. The strain-by-stress interaction revealed an effect on SD rats in MD, RD and axial diffusivity (AD), with lower diffusion metric levels on stressed animals. These effects were localized on the left side of the brain on the external capsule, corpus callosum, deep cerebral white matter, anterior commissure, endopiriform nucleus, dorsal hippocampus and amygdala fibers. The results possibly reveal an adaptation of the SD strain to the stressful stimuli through synaptic and structural plasticity processes, possibly reflecting learning processes.We thank Neurospin (high field MRI center CEA Saclay) for providing its support for MRI acquisition. JB was supported by grants from Fondation pour la Recherche Médicale (FRM) and Groupe Pasteur Mutualité (GPM). This work was supported by a grant from ANR (SIGMA). This work was performed on a platform of France Life Imaging (FLI) network partly funded by the grant ANR-11-INBS-0006. This work and RM were supported by a fellowship of the project FCT-ANR/NEU-OSD/0258/2012 founded by FCT/MEC (www.fct.pt) and by Fundo Europeu de Desenvolvimento Regional (FEDER). AC was supported by a grant from the Fondation NRJ.info:eu-repo/semantics/publishedVersio

From micro‐ to macro‐structures in multiple sclerosis: what is the added value of diffusion imaging

Diffusion imaging has been instrumental in understanding damage to the central nervous system as a result of its sensitivity to microstructural changes. Clinical applications of diffusion imaging have grown exponentially over the past couple of decades in many neurological and neurodegenerative diseases, such as multiple sclerosis (MS). For several reasons, MS has been extensively researched using advanced neuroimaging techniques, which makes it an ‘example disease’ to illustrate the potential of diffusion imaging for clinical applications. In addition, MS pathology is characterized by several key processes competing with each other, such as inflammation, demyelination, remyelination, gliosis and axonal loss, enabling the specificity of diffusion to be challenged. In this review, we describe how diffusion imaging can be exploited to investigate micro‐, meso‐ and macro‐scale properties of the brain structure and discuss how they are affected by different pathological substrates. Conclusions from the literature are that larger studies are needed to confirm the exciting results from initial investigations before current trends in diffusion imaging can be translated to the neurology clinic. Also, for a comprehensive understanding of pathological processes, it is essential to take a multiple‐level approach, in which information at the micro‐, meso‐ and macroscopic scales is fully integrated

Crowding Alone Cannot Account for Cosolute Effect on Amyloid Aggregation

Amyloid fiber formation is a specific form of protein aggregation, often resulting from the misfolding of native proteins. Aimed at modeling the crowded environment of the cell, recent experiments showed a reduction in fibrillation halftimes for amyloid-forming peptides in the presence of cosolutes that are preferentially excluded from proteins and peptides. The effect of excluded cosolutes has previously been attributed to the large volume excluded by such inert cellular solutes, sometimes termed “macromolecular crowding”. Here, we studied a model peptide that can fold to a stable monomeric β-hairpin conformation, but under certain solution conditions aggregates in the form of amyloid fibrils. Using Circular Dichroism spectroscopy (CD), we found that, in the presence of polyols and polyethylene glycols acting as excluded cosolutes, the monomeric β-hairpin conformation was stabilized with respect to the unfolded state. Stabilization free energy was linear with cosolute concentration, and grew with molecular volume, as would also be predicted by crowding models. After initiating the aggregation process with a pH jump, fibrillation in the presence and absence of cosolutes was followed by ThT fluorescence, transmission electron microscopy, and CD spectroscopy. Polyols (glycerol and sorbitol) increased the lag time for fibril formation and elevated the amount of aggregated peptide at equilibrium, in a cosolute size and concentration dependent manner. However, fibrillation rates remained almost unaffected by a wide range of molecular weights of soluble polyethylene glycols. Our results highlight the importance of other forces beyond the excluded volume interactions responsible for crowding that may contribute to the cosolute effects acting on amyloid formation

Single cell dissection of plasma cell heterogeneity in symptomatic and asymptomatic myeloma

Multiple myeloma, a plasma cell malignancy, is the second most common blood cancer. Despite extensive research, disease heterogeneity is poorly characterized, hampering efforts for early diagnosis and improved treatments. Here, we apply single cell RNA sequencing to study the heterogeneity of 40 individuals along the multiple myeloma progression spectrum, including 11 healthy controls, demonstrating high interindividual variability that can be explained by expression of known multiple myeloma drivers and additional putative factors. We identify extensive subclonal structures for 10 of 29 individuals with multiple myeloma. In asymptomatic individuals with early disease and in those with minimal residual disease post-treatment, we detect rare tumor plasma cells with molecular characteristics similar to those of active myeloma, with possible implications for personalized therapies. Single cell analysis of rare circulating tumor cells allows for accurate liquid biopsy and detection of malignant plasma cells, which reflect bone marrow disease. Our work establishes single cell RNA sequencing for dissecting blood malignancies and devising detailed molecular characterization of tumor cells in symptomatic and asymptomatic patients