Brain energy metabolism measured by (13) C magnetic resonance spectroscopy in vivo upon infusion of [3-(13) C]lactate.

The brain uses lactate produced by glycolysis as an energy source. How lactate originated from the blood stream is used to fuel brain metabolism is not clear. The current study measures brain metabolic fluxes and estimates the amount of pyruvate that becomes labeled in glial and neuronal compartments upon infusion of [3-(13) C]lactate. For that, labeling incorporation into carbons of glutamate and glutamine was measured by (13) C magnetic resonance spectroscopy at 14.1 T and analyzed with a two-compartment model of brain metabolism to estimate rates of mitochondrial oxidation, glial pyruvate carboxylation, and the glutamate-glutamine cycle as well as pyruvate fractional enrichments. Extracerebral lactate at supraphysiological levels contributes at least two-fold more to replenish the neuronal than the glial pyruvate pools. The rates of mitochondrial oxidation in neurons and glia, pyruvate carboxylase, and glutamate-glutamine cycles were similar to those estimated by administration of (13) C-enriched glucose, the main fuel of brain energy metabolism. These results are in agreement with primary utilization of exogenous lactate in neurons rather than astrocytes. © 2014 Wiley Periodicals, Inc.

A Cellular Perspective on Brain Energy Metabolism and Functional Imaging.

The energy demands of the brain are high: they account for at least 20% of the body's energy consumption. Evolutionary studies indicate that the emergence of higher cognitive functions in humans is associated with an increased glucose utilization and expression of energy metabolism genes. Functional brain imaging techniques such as fMRI and PET, which are widely used in human neuroscience studies, detect signals that monitor energy delivery and use in register with neuronal activity. Recent technological advances in metabolic studies with cellular resolution have afforded decisive insights into the understanding of the cellular and molecular bases of the coupling between neuronal activity and energy metabolism and point at a key role of neuron-astrocyte metabolic interactions. This article reviews some of the most salient features emerging from recent studies and aims at providing an integration of brain energy metabolism across resolution scales.

Wnt-3a and Wnt-3 differently stimulate proliferation and neurogenesis of spinal neural precursors and promote neurite outgrowth by canonical signaling

Wnt factors regulate neural stem cell development and neuronal connectivity. Here we investigated whether Wnt-3a and Wnt-3, expressed in the developing spinal cord, regulate proliferation and the neuronal differentiation of spinal cord neural precursors (SCNP). Wnt-3a promoted a sustained increase of SCNP proliferation, whereas Wnt-3 enhanced SCNP proliferation transiently and increased neurogenesis through β-catenin signaling. Consistent with this, Wnt-3a and Wnt-3 differently regulate the expression of Cyclin-dependent kinase inhibitors. Furthermore, Wnt-3a and Wnt-3 stimulated neurite outgrowth in SCNP-derived neurons through ß-catenin and TCF4-dependent transcription. GSK-3ß inhibitors mimicked Wnt signaling and promoted neurite outgrowth in established cultures. We conclude that Wnt-3a and Wnt-3 signal through the canonical Wnt/β-catenin pathway to regulate different aspects of SCNP development. These findings may be of therapeutic interest for the treatment of neurodegenerative diseases and nerve injury.

Chemokines induce axon outgrowth downstream of Hepatocyte Growth Factor and TCF/β-catenin signaling

Axon morphogenesis is a complex process regulated by a variety of secreted molecules, including morphogens and growth factors, resulting in the establishment of the neuronal circuitry. Our previous work demonstrated that growth factors [Neurotrophins (NT) and Hepatocyte Growth Factor (HGF)] signal through β-catenin during axon morphogenesis. HGF signaling promotes axon outgrowth and branching by inducing β-catenin phosphorylation at Y142 and transcriptional regulation of T-Cell Factor (TCF) target genes. Here, we asked which genes are regulated by HGF signaling during axon morphogenesis. An array screening indicated that HGF signaling elevates the expression of chemokines of the CC and CXC families. In line with this, CCL7, CCL20, and CXCL2 significantly increase axon outgrowth in hippocampal neurons. Experiments using blocking antibodies and chemokine receptor antagonists demonstrate that chemokines act downstream of HGF signaling during axon morphogenesis. In addition, qPCR data demonstrates that CXCL2 and CCL5 expression is stimulated by HGF through Met/b-catenin/TCF pathway. These results identify CC family members and CXCL2 chemokines as novel regulators of axon morphogenesis downstream of HGF signaling.

BDNF promoter I methylation correlates between post-mortem human peripheral and brain tissues.

Several psychiatric disorders have been associated with CpG methylation changes in CG rich promoters of the brain-derived neurotrophic factor (BDNF) mainly by extracting DNA from peripheral blood cells. Whether changes in peripheral DNA methylation can be used as a proxy for brain-specific alterations remains an open question. In this study we aimed to compare DNA methylation levels in BDNF promoter regions in human blood cells, muscle and brain regions using bisulfite-pyrosequencing. We found a significant correlation between the levels of BDNF promoter I methylation measured in quadriceps and vPFC tissues extracted from the same individuals (n = 98, Pearson, r = 0.48, p = 4.5 × 10(-7)). In the hippocampus, BDNF promoter I and IV methylation levels were strongly correlated (Pearson, n = 37, r = 0.74, p = 1.4 × 10(-7)). We found evidence for sex-dependent effect on BDNF promoter methylation levels in the various tissues and blood samples. Taken together, these data indicate a strong intra-individual correlation between peripheral and brain tissue. They also suggest that sex determines methylation patterns in BDNF promoter region across different types of tissue, including muscle, brain, and blood.

Imaging of prolonged BOLD response in the somatosensory cortex of the rat.

Blood oxygenation level-dependent (BOLD) functional MRI is a widely employed methodology in experimental and clinical neuroscience, although its nature is not fully understood. To gain insights into BOLD mechanisms and take advantage of the new functional methods, it is of interest to investigate prolonged paradigms of activation suitable for long experimental protocols and to observe any long-term modifications induced by these functional challenges. While different types of sustained stimulation paradigm have been explored in human studies, the BOLD response is typically limited to a few minutes in animal models, due to fatigue, anesthesia effects and physiological instability. In the present study, the rat forepaw was electrically stimulated for 2 h, which resulted in a prolonged and localized cortical BOLD response over that period. The stimulation paradigm, including an inter-stimulus interval (ISI) of 10 s, that is 25% of the total time, was applied at constant or variable frequency over 2 h. The steady-state level of the BOLD response was reached after 15-20 min of stimulation and was maintained until the end of the stimulation. On average, no substantial loss in activated volume was observed at the end of the stimulation, but less variability in the fraction of remaining activated volume and higher steady-state BOLD amplitude were observed when stimulation frequency was varied between 2 and 3 Hz every 5 min. We conclude that the combination of ISI and variable stimulus frequency reproducibly results in robust, prolonged and localized BOLD activation. Copyright © 2015 John Wiley & Sons, Ltd.

Decoding auditory EEG responses in healthy and clinical populations: A comparative study.

BACKGROUND: Analyses of brain responses to external stimuli are typically based on the means computed across conditions. However in many cognitive and clinical applications, taking into account their variability across trials has turned out to be statistically more sensitive than comparing their means. NEW METHOD: In this study we present a novel implementation of a single-trial topographic analysis (STTA) for discriminating auditory evoked potentials at predefined time-windows. This analysis has been previously introduced for extracting spatio-temporal features at the level of the whole neural response. Adapting the STTA on specific time windows is an essential step for comparing its performance to other time-window based algorithms. RESULTS: We analyzed responses to standard vs. deviant sounds and showed that the new implementation of the STTA gives above-chance decoding results in all subjects (in comparison to 7 out of 11 with the original method). In comatose patients, the improvement of the decoding performance was even more pronounced than in healthy controls and doubled the number of significant results. COMPARISON WITH EXISTING METHOD(S): We compared the results obtained with the new STTA to those based on a logistic regression in healthy controls and patients. We showed that the first of these two comparisons provided a better performance of the logistic regression; however only the new STTA provided significant results in comatose patients at group level. CONCLUSIONS: Our results provide quantitative evidence that a systematic investigation of the accuracy of established methods in normal and clinical population is an essential step for optimizing decoding performance.

The Impact of Catechol-O-Methyltransferase and Dopamine D4 Receptor Genotypes on Neurophysiological Markers of Performance Monitoring

Dynamic adaptations of one"s behavior by means of performance monitoring are a central function of the human executive system, that underlies considerable interindividual variation. Converging evidence from electrophysiological and neuroimaging studies in both animals and humans hints atthe importance ofthe dopaminergic system forthe regulation of performance monitoring. Here, we studied the impact of two polymorphisms affecting dopaminergic functioning in the prefrontal cortex [catechol-O-methyltransferase (COMT) Val108/158Met and dopamine D4 receptor (DRD4) single-nucleotide polymorphism (SNP)-521] on neurophysiological correlates of performance monitoring. We applied a modified version of a standard flanker task with an embedded stop-signal task to tap into the different functions involved, particularly error monitoring, conflict detection and inhibitory processes. Participants homozygous for the DRD4 T allele produced an increased error-related negativity after both choice errors and failed inhibitions compared with C-homozygotes. This was associated with pronounced compensatory behavior reflected in higher post-error slowing. No group differences were seen in the incompatibility N2, suggesting distinct effects of the DRD4 polymorphism on error monitoring processes. Additionally, participants homozygous for the COMTVal allele, with a thereby diminished prefrontal dopaminergic level, revealed increased prefrontal processing related to inhibitory functions, reflected in the enhanced stop-signal-related components N2 and P3a. The results extend previous findings from mainly behavioral and neuroimaging data on the relationship between dopaminergic genes and executive functions and present possible underlying mechanisms for the previously suggested association between these dopaminergic polymorphisms and psychiatric disorders as schizophrenia or attention deficit hyperactivity disorder.

Automatic target validation based on neuroscientific literature mining for tractography.

Target identification for tractography studies requires solid anatomical knowledge validated by an extensive literature review across species for each seed structure to be studied. Manual literature review to identify targets for a given seed region is tedious and potentially subjective. Therefore, complementary approaches would be useful. We propose to use text-mining models to automatically suggest potential targets from the neuroscientific literature, full-text articles and abstracts, so that they can be used for anatomical connection studies and more specifically for tractography. We applied text-mining models to three structures: two well-studied structures, since validated deep brain stimulation targets, the internal globus pallidus and the subthalamic nucleus and, the nucleus accumbens, an exploratory target for treating psychiatric disorders. We performed a systematic review of the literature to document the projections of the three selected structures and compared it with the targets proposed by text-mining models, both in rat and primate (including human). We ran probabilistic tractography on the nucleus accumbens and compared the output with the results of the text-mining models and literature review. Overall, text-mining the literature could find three times as many targets as two man-weeks of curation could. The overall efficiency of the text-mining against literature review in our study was 98% recall (at 36% precision), meaning that over all the targets for the three selected seeds, only one target has been missed by text-mining. We demonstrate that connectivity for a structure of interest can be extracted from a very large amount of publications and abstracts. We believe this tool will be useful in helping the neuroscience community to facilitate connectivity studies of particular brain regions. The text mining tools used for the study are part of the HBP Neuroinformatics Platform, publicly available at http://connectivity-brainer.rhcloud.com/.

Aggressivity, violence, sociability and conflict resolution: What genes can tell us.

Conflicts are inherent to the human condition, as they are for all living beings. Disputes about resources or access to mating partners are among the most common causes of conflict. Conflict is herein defined as a struggle or contest between individuals or parties, and may involve a variety of aggressive behaviours. In humans, aggressiveness, violence and conflicts, including individual predisposal to conflict resolution, have traditionally been said to have deep cultural roots, but recent research in both neuroscience and genetics has shown the influence of genes on such complex behavioural traits. In this paper, recent data on the genetic aspects of these interrelated behaviours will be put together, including the effects of particular genes, the influence of stress and gender on gene regulation, and gene-environment interactions, all of which may influence biological predisposal to conflict resolution. Other genetically influenced behavioural aspects involved in conflicts and conflict resolution, such as sociability, will also be discussed. The importance of taking into account genetic and biological data to provide strategies for conflict resolution will be highlighted.

A New CRB1 Rat Mutation Links Müller Glial Cells to Retinal Telangiectasia.

We have identified and characterized a spontaneous Brown Norway from Janvier rat strain (BN-J) presenting a progressive retinal degeneration associated with early retinal telangiectasia, neuronal alterations, and loss of retinal Müller glial cells resembling human macular telangiectasia type 2 (MacTel 2), which is a retinal disease of unknown cause. Genetic analyses showed that the BN-J phenotype results from an autosomal recessive indel novel mutation in the Crb1 gene, causing dislocalization of the protein from the retinal Müller glia (RMG)/photoreceptor cell junction. The transcriptomic analyses of primary RMG cultures allowed identification of the dysregulated pathways in BN-J rats compared with wild-type BN rats. Among those pathways, TGF-β and Kit Receptor Signaling, MAPK Cascade, Growth Factors and Inflammatory Pathways, G-Protein Signaling Pathways, Regulation of Actin Cytoskeleton, and Cardiovascular Signaling were found. Potential molecular targets linking RMG/photoreceptor interaction with the development of retinal telangiectasia are identified. This model can help us to better understand the physiopathologic mechanisms of MacTel 2 and other retinal diseases associated with telangiectasia.

Proximity of excitatory synapses and astroglial gap junctions in layer IV of the mouse barrel cortex.

Neurons and astrocytes, the two major cell populations in the adult brain, are characterized by their own mode of intercellular communication--the synapses and the gap junctions (GJ), respectively. In addition, there is increasing evidence for dynamic and metabolic neuroglial interactions resulting in the modulation of synaptic transmission at the so-called "tripartite synapse". Based on this, we have investigated at the ultrastructural level how excitatory synapses (ES) and astroglial GJ are spatially distributed in layer IV of the barrel cortex of the adult mouse. We used specific antibodies for connexin (Cx) 30 and 43 to identify astroglial GJ, these two proteins are known to be present in the majority of astroglial GJ in the cerebral cortex. In electron-microscopic images, we measured the distance between two ES, between two GJ and between a GJ and its nearest ES. We found a ratio of two GJ per three ES in the hollow and septal areas. Taking into account the size of an astrocyte domain, the high density of GJ suggests the occurrence of reflexive type, i.e. GJ between processes of the same astrocyte. Interestingly, the distance between an ES and an astroglial GJ was found to be significantly lower than that between either two synapses or between two GJ. These observations indicate that the two modes of cell-to-cell communication are not randomly distributed in layer IV of the barrel cortex. Consequently, this feature may provide the morphological support for the recently reported functional interactions between neuronal circuits and astroglial networks.

New genes for focal epilepsies with speech and language disorders.

The last 2 years have seen exciting advances in the genetics of Landau-Kleffner syndrome and related disorders, encompassed within the epilepsy-aphasia spectrum (EAS). The striking finding of mutations in the N-methyl-D-aspartate (NMDA) receptor subunit gene GRIN2A as the first monogenic cause in up to 20 % of patients with EAS suggests that excitatory glutamate receptors play a key role in these disorders. Patients with GRIN2A mutations have a recognizable speech and language phenotype that may assist with diagnosis. Other molecules involved in RNA binding and cell adhesion have been implicated in EAS; copy number variations are also found. The emerging picture highlights the overlap between the genetic determinants of EAS with speech and language disorders, intellectual disability, autism spectrum disorders and more complex developmental phenotypes.

Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders.

Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed.

Quantifying the time for accurate EEG decoding of single value-based decisions.

BACKGROUND: Recent neuroimaging studies suggest that value-based decision-making may rely on mechanisms of evidence accumulation. However no studies have explicitly investigated the time when single decisions are taken based on such an accumulation process. NEW METHOD: Here, we outline a novel electroencephalography (EEG) decoding technique which is based on accumulating the probability of appearance of prototypical voltage topographies and can be used for predicting subjects' decisions. We use this approach for studying the time-course of single decisions, during a task where subjects were asked to compare reward vs. loss points for accepting or rejecting offers. RESULTS: We show that based on this new method, we can accurately decode decisions for the majority of the subjects. The typical time-period for accurate decoding was modulated by task difficulty on a trial-by-trial basis. Typical latencies of when decisions are made were detected at ∼500ms for 'easy' vs. ∼700ms for 'hard' decisions, well before subjects' response (∼340ms). Importantly, this decision time correlated with the drift rates of a diffusion model, evaluated independently at the behavioral level. COMPARISON WITH EXISTING METHOD(S): We compare the performance of our algorithm with logistic regression and support vector machine and show that we obtain significant results for a higher number of subjects than with these two approaches. We also carry out analyses at the average event-related potential level, for comparison with previous studies on decision-making. CONCLUSIONS: We present a novel approach for studying the timing of value-based decision-making, by accumulating patterns of topographic EEG activity at single-trial level.