Computational anatomy for studying use-dependant brain plasticity.

In this article we provide a comprehensive literature review on the in vivo assessment of use-dependant brain structure changes in humans using magnetic resonance imaging (MRI) and computational anatomy. We highlight the recent findings in this field that allow the uncovering of the basic principles behind brain plasticity in light of the existing theoretical models at various scales of observation. Given the current lack of in-depth understanding of the neurobiological basis of brain structure changes we emphasize the necessity of a paradigm shift in the investigation and interpretation of use-dependent brain plasticity. Novel quantitative MRI acquisition techniques provide access to brain tissue microstructural properties (e.g., myelin, iron, and water content) in-vivo, thereby allowing unprecedented specific insights into the mechanisms underlying brain plasticity. These quantitative MRI techniques require novel methods for image processing and analysis of longitudinal data allowing for straightforward interpretation and causality inferences.

Connectivity differences in brain networks.

The scenario considered here is one where brain connectivity is represented as a network and an experimenter wishes to assess the evidence for an experimental effect at each of the typically thousands of connections comprising the network. To do this, a univariate model is independently fitted to each connection. It would be unwise to declare significance based on an uncorrected threshold of α=0.05, since the expected number of false positives for a network comprising N=90 nodes and N(N-1)/2=4005 connections would be 200. Control of Type I errors over all connections is therefore necessary. The network-based statistic (NBS) and spatial pairwise clustering (SPC) are two distinct methods that have been used to control family-wise errors when assessing the evidence for an experimental effect with mass univariate testing. The basic principle of the NBS and SPC is the same as supra-threshold voxel clustering. Unlike voxel clustering, where the definition of a voxel cluster is unambiguous, 'clusters' formed among supra-threshold connections can be defined in different ways. The NBS defines clusters using the graph theoretical concept of connected components. SPC on the other hand uses a more stringent pairwise clustering concept. The purpose of this article is to compare the pros and cons of the NBS and SPC, provide some guidelines on their practical use and demonstrate their utility using a case study involving neuroimaging data.

Metabolic Flux and Compartmentation Analysis in the Brain In vivo.

Through significant developments and progresses in the last two decades, in vivo localized nuclear magnetic resonance spectroscopy (MRS) became a method of choice to probe brain metabolic pathways in a non-invasive way. Beside the measurement of the total concentration of more than 20 metabolites, (1)H MRS can be used to quantify the dynamics of substrate transport across the blood-brain barrier by varying the plasma substrate level. On the other hand, (13)C MRS with the infusion of (13)C-enriched substrates enables the characterization of brain oxidative metabolism and neurotransmission by incorporation of (13)C in the different carbon positions of amino acid neurotransmitters. The quantitative determination of the biochemical reactions involved in these processes requires the use of appropriate metabolic models, whose level of details is strongly related to the amount of data accessible with in vivo MRS. In the present work, we present the different steps involved in the elaboration of a mathematical model of a given brain metabolic process and its application to the experimental data in order to extract quantitative brain metabolic rates. We review the recent advances in the localized measurement of brain glucose transport and compartmentalized brain energy metabolism, and how these reveal mechanistic details on glial support to glutamatergic and GABAergic neurons.

Functional implication of the vitamin A signaling pathway in the brain.

Vitamin A is necessary for normal embryonic development, but its role in the adult brain is poorly understood. Vitamin A derivatives, retinoids, are involved in a complex signaling pathway that regulates gene expression and, in the central nervous system, controls neuronal differentiation and neural tube patterning. Although a major functional implication of retinoic signaling has been repeatedly suggested in synaptic plasticity, learning and memory, sleep, schizophrenia, depression, Parkinson disease, and Alzheimer disease, the targets and the underlying mechanisms in the adult brain remain elusive.

Suicide after successful deep brain stimulation for movement disorders.

The authors observed a high rate of suicide (6/140 patients, 4.3%) in a large cohort of patients with movement disorders treated with deep brain stimulation (DBS). Apparent risk factors included a previous history of severe depression and multiple successive DBS surgeries, whereas there was no relationship with the underlying condition, DBS target, electrical parameters, or modifications of treatment. Paradoxically, all patients experienced an excellent motor outcome following the procedure. The authors propose that patients at high risk for suicide should be excluded from DBS surgery.

Principal components of functional connectivity: A new approach to study dynamic brain connectivity during rest.

Functional connectivity (FC) as measured by correlation between fMRI BOLD time courses of distinct brain regions has revealed meaningful organization of spontaneous fluctuations in the resting brain. However, an increasing amount of evidence points to non-stationarity of FC; i.e., FC dynamically changes over time reflecting additional and rich information about brain organization, but representing new challenges for analysis and interpretation. Here, we propose a data-driven approach based on principal component analysis (PCA) to reveal hidden patterns of coherent FC dynamics across multiple subjects. We demonstrate the feasibility and relevance of this new approach by examining the differences in dynamic FC between 13 healthy control subjects and 15 minimally disabled relapse-remitting multiple sclerosis patients. We estimated whole-brain dynamic FC of regionally-averaged BOLD activity using sliding time windows. We then used PCA to identify FC patterns, termed "eigenconnectivities", that reflect meaningful patterns in FC fluctuations. We then assessed the contributions of these patterns to the dynamic FC at any given time point and identified a network of connections centered on the default-mode network with altered contribution in patients. Our results complement traditional stationary analyses, and reveal novel insights into brain connectivity dynamics and their modulation in a neurodegenerative disease.

Am I my brain or my genitals? A nature-culture controversy in the hermaphrodite debate from the mid-1960s to the late 1990s.

The groundbreaking and prophetic rhetoric of neuroscience has recently highlighted the fetal brain as the most promising organ for understanding why transsexuals feel "trapped in the wrong body", and for predicting whether children born with "ambiguous" genitalia will grow up to feel like a man or a woman.This article proposes a recent history of the cerebralization of intersexuality and of transsexuality as atypical neurodevelopmental conditions. It examines the ways in which the organizational theory of brain sex differentiation developed in the late 1950s in behavioral neuroendocrinology has gained increased prominence in and through controversies over best practice issues in the case management of intersex newborns, and the etiology of transsexuality.It focuses on the American context and on the leading warrior in this battle: Milton Diamond, now a most prominent figure in professional debates about the clinical management of intersexuality, and the intersex person's best friend. Persons with an intersexed or transsexual condition consider, not their gonads, but their brains, their core sense of self, as the primary determinant of sex. (Diamond and Beh 2005, 6-7, note 1)

Langage et cerveau : vingt ans d'imagerie fonctionnelle [Language and the brain: 20 years of functional imagery]

La masse considérable de travaux publiés dans le domaine de la neuroimagerie fonctionnelle concernant les fonctions ou modalités du langage (compréhension et expression de la parole, lecture) ou les différents processus linguistiques qui les sous-tendent (sémantique, phonologie, syntaxe) permet de dégager de grandes tendances en termes de substrats anatomiques. Si les « fondamentaux » issus des origines aphasiologiques du domaine n'ont pas été bouleversés, certaines spécificités non explorées par l'approche lésionnelle sont identifiables. Les méta-analyses, en regroupant les résultats de la littérature, nous procurent aujourd'hui une vision globale des substrats cérébraux du langage. Cependant la variabilité inter-individuelle reste importante en raison de multiples facteurs dont certains sont mal identifiés ; cartographier exhaustivement les fonctions du langage à l'échelle individuelle reste une gageure. La quête des images du langage est sans doute aussi inachevable que celle de l'étude du langage lui-même.

Effect of chronic hypoglycaemia on glucose concentration and glycogen content in rat brain: A localized 13C NMR study.

While chronic hypoglycaemia has been reported to increase unidirectional glucose transport across the blood-brain barrier (BBB) and to increase GLUT1 expression at the endothelium, the effect on steady-state brain d-glucose and brain glycogen content is currently unknown. Brain glucose and glycogen concentrations were directly measured in vivo using localized 13C magnetic resonance spectroscopy (MRS) following 12-14 days of hypoglycaemia. Brain glucose content was significantly increased by 48%, which is consistent with an increase in the maximal glucose transport rate, Tmax, by 58% compared with the sham-treated animals. The localized 13C NMR measurements of brain glucose were directly validated by comparison with biochemically determined brain glucose content after rapid focused microwave fixation (1.4 s at 4 kW). Both in vivo MRS and biochemical measurements implied that brain glycogen content was not affected by chronic hypoglycaemia, consistent with brain glucose being a major factor controlling brain glycogen content. We conclude that the increased glucose transporter expression in chronic hypoglycaemia leads to increased brain glucose content at a given level of glycaemia. Such increased brain glucose concentrations can result in a lowered glycaemic threshold of counter-regulation observed in chronic hypoglycaemia.

Generic approach for the sensitive absolute quantification of large undigested peptides in plasma using a particular liquid chromatography-mass spectrometry setup.

A generic LC-MS approach for the absolute quantification of undigested peptides in plasma at mid-picomolar levels is described. Nine human peptides namely, brain natriuretic peptide (BNP), substance P (SubP), parathyroid hormone 1-34 (PTH), C-peptide, orexines A and B (Orex-A and -B), oxytocin (Oxy), gonadoliberin-1 (gonadothropin releasing-hormone or luteinizing hormone-releasing hormone, LHRH) and α-melanotropin (α-MSH) were targeted. Plasma samples were extracted via a 2-step procedure: protein precipitation using 1vol of acetonitrile followed by ultrafiltration of supernatants on membranes with a MW cut-off of 30 kDa. By applying a specific LC-MS setup, large volumes of filtrates (e.g., 2×750 μL) were injected and the peptides were trapped on a 1mm i.d.×10 mm length C8 column using a 10× on-line dilution. Then, the peptides were back-flushed and a second on-line dilution (2×) was applied during the transfer step. The refocalized peptides were resolved on a 0.3mm i.d. C18 analytical column. Extraction recovery, matrix effect and limits of detection were evaluated. Our comprehensive protocol demonstrates a simple and efficient sample preparation procedure followed by the analysis of peptides with limits of detection in the mid-picomolar range. This generic approach can be applied for the determination of most therapeutic peptides and possibly for endogenous peptides with latest state-of-the-art instruments.

Atlas-based segmentation of pathological brain MR images

We propose a method for brain atlas deformation inpresence of large space-occupying tumors, based on an apriori model of lesion growth that assumes radialexpansion of the lesion from its starting point. First,an affine registration brings the atlas and the patientinto global correspondence. Then, the seeding of asynthetic tumor into the brain atlas provides a templatefor the lesion. Finally, the seeded atlas is deformed,combining a method derived from optical flow principlesand a model of lesion growth (MLG). Results show that themethod can be applied to the automatic segmentation ofstructures and substructures in brains with grossdeformation, with important medical applications inneurosurgery, radiosurgery and radiotherapy.

Brain tissue properties differentiate between motor and limbic basal ganglia circuits.

Despite advances in understanding basic organizational principles of the human basal ganglia, accurate in vivo assessment of their anatomical properties is essential to improve early diagnosis in disorders with corticosubcortical pathology and optimize target planning in deep brain stimulation. Main goal of this study was the detailed topological characterization of limbic, associative, and motor subdivisions of the subthalamic nucleus (STN) in relation to corresponding corticosubcortical circuits. To this aim, we used magnetic resonance imaging and investigated independently anatomical connectivity via white matter tracts next to brain tissue properties. On the basis of probabilistic diffusion tractography we identified STN subregions with predominantly motor, associative, and limbic connectivity. We then computed for each of the nonoverlapping STN subregions the covariance between local brain tissue properties and the rest of the brain using high-resolution maps of magnetization transfer (MT) saturation and longitudinal (R1) and transverse relaxation rate (R2*). The demonstrated spatial distribution pattern of covariance between brain tissue properties linked to myelin (R1 and MT) and iron (R2*) content clearly segregates between motor and limbic basal ganglia circuits. We interpret the demonstrated covariance pattern as evidence for shared tissue properties within a functional circuit, which is closely linked to its function. Our findings open new possibilities for investigation of changes in the established covariance pattern aiming at accurate diagnosis of basal ganglia disorders and prediction of treatment outcome.