Emergence of a small-world functional network in cultured neurons

The functional networks of cultured neurons exhibit complex network properties similar to those found in vivo. Starting from random seeding, cultures undergo significant reorganization during the initial period in vitro, yet despite providing an ideal platform for observing developmental changes in neuronal connectivity, little is known about how a complex functional network evolves from isolated neurons. In the present study, evolution of functional connectivity was estimated from correlations of spontaneous activity. Network properties were quantified using complex measures from graph theory and used to compare cultures at different stages of development during the first 5 weeks in vitro. Networks obtained from young cultures (14 days in vitro) exhibited a random topology, which evolved to a small-world topology during maturation. The topology change was accompanied by an increased presence of highly connected areas (hubs) and network efficiency increased with age. The small-world topology balances integration of network areas with segregation of specialized processing units. The emergence of such network structure in cultured neurons, despite a lack of external input, points to complex intrinsic biological mechanisms. Moreover, the functional network of cultures at mature ages is efficient and highly suited to complex processing tasks.

Parameter-free extraction of the functional network topology from intracranial EEG recordings: a time-resolved study of graph properties in focal onset seizures

Rationale: Focal onset epileptic seizures are due to abnormal interactions between distributed brain areas. By estimating the cross-correlation matrix of multi-site intra-cerebral EEG recordings (iEEG), one can quantify these interactions. To assess the topology of the underlying functional network, the binary connectivity matrix has to be derived from the cross-correlation matrix by use of a threshold. Classically, a unique threshold is used that constrains the topology [1]. Our method aims to set the threshold in a data-driven way by separating genuine from random cross-correlation. We compare our approach to the fixed threshold method and study the dynamics of the functional topology. Methods: We investigate the iEEG of patients suffering from focal onset seizures who underwent evaluation for the possibility of surgery. The equal-time cross-correlation matrices are evaluated using a sliding time window. We then compare 3 approaches assessing the corresponding binary networks. For each time window: * Our parameter-free method derives from the cross-correlation strength matrix (CCS)[2]. It aims at disentangling genuine from random correlations (due to finite length and varying frequency content of the signals). In practice, a threshold is evaluated for each pair of channels independently, in a data-driven way. * The fixed mean degree (FMD) uses a unique threshold on the whole connectivity matrix so as to ensure a user defined mean degree. * The varying mean degree (VMD) uses the mean degree of the CCS network to set a unique threshold for the entire connectivity matrix. * Finally, the connectivity (c), connectedness (given by k, the number of disconnected sub-networks), mean global and local efficiencies (Eg, El, resp.) are computed from FMD, CCS, VMD, and their corresponding random and lattice networks. Results: Compared to FMD and VMD, CCS networks present: *topologies that are different in terms of c, k, Eg and El. *from the pre-ictal to the ictal and then post-ictal period, topological features time courses that are more stable within a period, and more contrasted from one period to the next. For CCS, pre-ictal connectivity is low, increases to a high level during the seizure, then decreases at offset. k shows a ‘‘U-curve’’ underlining the synchronization of all electrodes during the seizure. Eg and El time courses fluctuate between the corresponding random and lattice networks values in a reproducible manner. Conclusions: The definition of a data-driven threshold provides new insights into the topology of the epileptic functional networks.

Optimizing Functional Network Representation of Multivariate Time Series

By combining complex network theory and data mining techniques, we provide objective criteria for optimization of the functional network representation of generic multivariate time series. In particular, we propose a method for the principled selection of the threshold value for functional network reconstruction from raw data, and for proper identification of the network's indicators that unveil the most discriminative information on the system for classification purposes. We illustrate our method by analysing networks of functional brain activity of healthy subjects, and patients suffering from Mild Cognitive Impairment, an intermediate stage between the expected cognitive decline of normal aging and the more pronounced decline of dementia. We discuss extensions of the scope of the proposed methodology to network engineering purposes, and to other data mining tasks.

Altered brain rhythms and functional network disruptions involved in patients with generalized fixation-off epilepsy

Fixation-off sensitivity (FOS) denotes the forms of epilepsy elicited by elimination of fixation. FOS-IGE patients are rare cases [1]. In a previous work [2] we showed that two FOS-IGE patients had different altered EEG rhythms when closing eyes; only beta band was altered in patient 1 while theta, alpha and beta were altered in patient 2. In the present work, we explain the relationship between the altered brain rhythms in these patients and the disruption in functional brain networks.

Hippocampal functional connectivity reflects verbal episodic memory network integrity

Using functional magnetic resonance imaging during a verbal memory task, we investigated correlations of signal fluctuations within the hippocampus and ipsilateral frontal as well as temporal areas in temporal lobe epilepsy patients. Declarative memory abilities were additionally examined before and after temporal lobe epilepsy surgery. A significant difference exists in functional connectivity between patients whose mnemonic functions deteriorated and those who remained stable or improved. Univariate analyses showed significantly higher preoperative coupling between the hippocampus and Brodmann area 22 for the group that decreased in verbal learning. We suggest greater coupling to reflect higher functional network integrity. Postoperatively reduced learning ability in patients with higher preoperative coupling underlines the importance of hippocampal interaction with cortical areas for successful memory formation.

Functional brain network efficiency predicts intelligence

The neuronal causes of individual differences in mental abilities such as intelligence are complex and profoundly important. Understanding these abilities has the potential to facilitate their enhancement. The purpose of this study was to identify the functional brain network characteristics and their relation to psychometric intelligence. In particular, we examined whether the functional network exhibits efficient small-world network attributes (high clustering and short path length) and whether these small-world network parameters are associated with intellectual performance. High-density resting state electroencephalography (EEG) was recorded in 74 healthy subjects to analyze graph-theoretical functional network characteristics at an intracortical level. Ravens advanced progressive matrices were used to assess intelligence. We found that the clustering coefficient and path length of the functional network are strongly related to intelligence. Thus, the more intelligent the subjects are the more the functional brain network resembles a small-world network. We further identified the parietal cortex as a main hub of this resting state network as indicated by increased degree centrality that is associated with higher intelligence. Taken together, this is the first study that substantiates the neural efficiency hypothesis as well as the Parieto-Frontal Integration Theory (P-FIT) of intelligence in the context of functional brain network characteristics. These theories are currently the most established intelligence theories in neuroscience. Our findings revealed robust evidence of an efficiently organized resting state functional brain network for highly productive cognitions.

Multiple Pathways Analysis of Brain Functional Networks from EEG Signals: An Application to Real Data

In the present study, we propose a theoretical graph procedure to investigate multiple pathways in brain functional networks. By taking into account all the possible paths consisting of h links between the nodes pairs of the network, we measured the global network redundancy R (h) as the number of parallel paths and the global network permeability P (h) as the probability to get connected. We used this procedure to investigate the structural and dynamical changes in the cortical networks estimated from a dataset of high-resolution EEG signals in a group of spinal cord injured (SCI) patients during the attempt of foot movement. In the light of a statistical contrast with a healthy population, the permeability index P (h) of the SCI networks increased significantly (P < 0.01) in the Theta frequency band (3-6 Hz) for distances h ranging from 2 to 4. On the contrary, no significant differences were found between the two populations for the redundancy index R (h) . The most significant changes in the brain functional network of SCI patients occurred mainly in the lower spectral contents. These changes were related to an improved propagation of communication between the closest cortical areas rather than to a different level of redundancy. This evidence strengthens the hypothesis of the need for a higher functional interaction among the closest ROIs as a mechanism to compensate the lack of feedback from the peripheral nerves to the sensomotor areas.

Epileptic seizures as condensed sleep: an analysis of network dynamics from electroencephalogram signals

Both deepening sleep and evolving epileptic seizures are associated with increasing slow-wave activity. Larger-scale functional networks derived from electroencephalogram indicate that in both transitions dramatic changes of communication between brain areas occur. During seizures these changes seem to be 'condensed', because they evolve more rapidly than during deepening sleep. Here we set out to assess quantitatively functional network dynamics derived from electroencephalogram signals during seizures and normal sleep. Functional networks were derived from electroencephalogram signals from wakefulness, light and deep sleep of 12 volunteers, and from pre-seizure, seizure and post-seizure time periods of 10 patients suffering from focal onset pharmaco-resistant epilepsy. Nodes of the functional network represented electrical signals recorded by single electrodes and were linked if there was non-random cross-correlation between the two corresponding electroencephalogram signals. Network dynamics were then characterized by the evolution of global efficiency, which measures ease of information transmission. Global efficiency was compared with relative delta power. Global efficiency significantly decreased both between light and deep sleep, and between pre-seizure, seizure and post-seizure time periods. The decrease of global efficiency was due to a loss of functional links. While global efficiency decreased significantly, relative delta power increased except between the time periods wakefulness and light sleep, and pre-seizure and seizure. Our results demonstrate that both epileptic seizures and deepening sleep are characterized by dramatic fragmentation of larger-scale functional networks, and further support the similarities between sleep and seizures.

Detecting Functional Hubs of Ictogenic Networks

Quantitative EEG (qEEG) has modified our understanding of epileptic seizures, shifting our view from the traditionally accepted hyper-synchrony paradigm toward more complex models based on re-organization of functional networks. However, qEEG measurements are so far rarely considered during the clinical decision-making process. To better understand the dynamics of intracranial EEG signals, we examine a functional network derived from the quantification of information flow between intracranial EEG signals. Using transfer entropy, we analyzed 198 seizures from 27 patients undergoing pre-surgical evaluation for pharmaco-resistant epilepsy. During each seizure we considered for each network the in-, out- and total "hubs", defined respectively as the time and the EEG channels with the maximal incoming, outgoing or total (bidirectional) information flow. In the majority of cases we found that the hubs occur around the middle of seizures, and interestingly not at the beginning or end, where the most dramatic EEG signal changes are found by visual inspection. For the patients who then underwent surgery, good postoperative clinical outcome was on average associated with a higher percentage of out- or total-hubs located in the resected area (for out-hubs p = 0.01, for total-hubs p = 0.04). The location of in-hubs showed no clear predictive value. We conclude that the study of functional networks based on qEEG measurements may help to identify brain areas that are critical for seizure generation and are thus potential targets for focused therapeutic interventions.

Chow–Liu trees are sufficient predictive models for reproducing key features of functional networks of periictal EEG time-series

Seizure freedom in patients suffering from pharmacoresistant epilepsies is still not achieved in 20–30% of all cases. Hence, current therapies need to be improved, based on a more complete understanding of ictogenesis. In this respect, the analysis of functional networks derived from intracranial electroencephalographic (iEEG) data has recently become a standard tool. Functional networks however are purely descriptive models and thus are conceptually unable to predict fundamental features of iEEG time-series, e.g., in the context of therapeutical brain stimulation. In this paper we present some first steps towards overcoming the limitations of functional network analysis, by showing that its results are implied by a simple predictive model of time-sliced iEEG time-series. More specifically, we learn distinct graphical models (so called Chow–Liu (CL) trees) as models for the spatial dependencies between iEEG signals. Bayesian inference is then applied to the CL trees, allowing for an analytic derivation/prediction of functional networks, based on thresholding of the absolute value Pearson correlation coefficient (CC) matrix. Using various measures, the thus obtained networks are then compared to those which were derived in the classical way from the empirical CC-matrix. In the high threshold limit we find (a) an excellent agreement between the two networks and (b) key features of periictal networks as they have previously been reported in the literature. Apart from functional networks, both matrices are also compared element-wise, showing that the CL approach leads to a sparse representation, by setting small correlations to values close to zero while preserving the larger ones. Overall, this paper shows the validity of CL-trees as simple, spatially predictive models for periictal iEEG data. Moreover, we suggest straightforward generalizations of the CL-approach for modeling also the temporal features of iEEG signals.

Assessment of the Spatial and Temporal Distribution of Functional Connectivity in Resting-State BOLD fMRI

Recent research into resting-state functional magnetic resonance imaging (fMRI) has shown that the brain is very active during rest. This thesis work utilizes blood oxygenation level dependent (BOLD) signals to investigate the spatial and temporal functional network information found within resting-state data, and aims to investigate the feasibility of extracting functional connectivity networks using different methods as well as the dynamic variability within some of the methods. Furthermore, this work looks into producing valid networks using a sparsely-sampled sub-set of the original data.

In this work we utilize four main methods: independent component analysis (ICA), principal component analysis (PCA), correlation, and a point-processing technique. Each method comes with unique assumptions, as well as strengths and limitations into exploring how the resting state components interact in space and time.

Correlation is perhaps the simplest technique. Using this technique, resting-state patterns can be identified based on how similar the time profile is to a seed region’s time profile. However, this method requires a seed region and can only identify one resting state network at a time. This simple correlation technique is able to reproduce the resting state network using subject data from one subject’s scan session as well as with 16 subjects.

Independent component analysis, the second technique, has established software programs that can be used to implement this technique. ICA can extract multiple components from a data set in a single analysis. The disadvantage is that the resting state networks it produces are all independent of each other, making the assumption that the spatial pattern of functional connectivity is the same across all the time points. ICA is successfully able to reproduce resting state connectivity patterns for both one subject and a 16 subject concatenated data set.

Using principal component analysis, the dimensionality of the data is compressed to find the directions in which the variance of the data is most significant. This method utilizes the same basic matrix math as ICA with a few important differences that will be outlined later in this text. Using this method, sometimes different functional connectivity patterns are identifiable but with a large amount of noise and variability.

To begin to investigate the dynamics of the functional connectivity, the correlation technique is used to compare the first and second halves of a scan session. Minor differences are discernable between the correlation results of the scan session halves. Further, a sliding window technique is implemented to study the correlation coefficients through different sizes of correlation windows throughout time. From this technique it is apparent that the correlation level with the seed region is not static throughout the scan length.

The last method introduced, a point processing method, is one of the more novel techniques because it does not require analysis of the continuous time points. Here, network information is extracted based on brief occurrences of high or low amplitude signals within a seed region. Because point processing utilizes less time points from the data, the statistical power of the results is lower. There are also larger variations in DMN patterns between subjects. In addition to boosted computational efficiency, the benefit of using a point-process method is that the patterns produced for different seed regions do not have to be independent of one another.

This work compares four unique methods of identifying functional connectivity patterns. ICA is a technique that is currently used by many scientists studying functional connectivity patterns. The PCA technique is not optimal for the level of noise and the distribution of the data sets. The correlation technique is simple and obtains good results, however a seed region is needed and the method assumes that the DMN regions is correlated throughout the entire scan. Looking at the more dynamic aspects of correlation changing patterns of correlation were evident. The last point-processing method produces a promising results of identifying functional connectivity networks using only low and high amplitude BOLD signals.

SOURCE, FATE AND FUNCTION OF EARLY GLIAL CELLS EXPRESSING NKX2.1 IN MOUSE EMBRYONIC BRAINS

The brain tissue is made of neuronal and glial cells generated in the germinal layer bordering the ventricles. These cells divide, differentiate and migrate following specific pathways. The specification of GABAergic interneurons and glutamatergic neurons has been broadly studied but little is known about the origin, the fate and the function of early glial cells in the embryonic telencephalon. It has been commonly accepted since long that the glial cells and more particularly the astrocytes were generated after neurogenesis from the dorsal telencephalon. However, our work shows that, unlike what was previously thought, numerous glial cells (astroglia and polydendrocytes) are generated during neurogenesis in the early embryonic stages from E14.5 to E16.5, and originate from the ventral Nkx2.1-expressing precursors instead. NK2 homeobox 1 (Nkx2.1) is a member of the NK2 family of homeodomaincontaining transcription factors. The specification of the MGE precursors requires the expression of the Nkx2.1 homeobox gene. Moreover, Nkx2.1 is previously known to regulate the specification of GABAergic interneurons and early oligodendrocytes in the ventral telencephalon. Here, in my thesis work, I have discovered that, in addition, Nkx2.1 also regulates astroglia and polydendrocytes differentiation. The use of Nkx2.1 antibody and Nkx2.1 riboprobe have revealed the presence of numerous Nkx2.1-positive cells that express astroglial markers (like GLAST and GFAP) in the entire embryonic brain. Thus, to selectively fate map MGE-derived GABAergic interneurons and glia, we crossed Nkx2.1-Cre mice, Glast-Cre ERT+/- inducible mice and NG2-Cre mice with the Cre reporter Rosa26-lox-STOP-lox-YFP (Rosa26-YFP) mice. The precise origin of Nkx2.1-positive astroglia has been directly ascertained by combining glial immunostaining and focal electroporation of the pCAG-GS-EGFP plasmids into the subpallial domains of organotypic slices, as well as, by using in vitro neurosphere experiments and in utero electroporation of the pCAG-GS-tomato plasmid into the ventral pallium of E14.5 Nkx2.1-Cre+/Rosa-YFP+/- embryos. We have, thus, confirmed that the three germinal regions of the ventral telencephalon i.e. the MGE, the AEP/POA and the triangular septal nucleus are able to generate early astroglial cells. Moreover, immunohistochemistry for several astroglial cells and polydendrocyte markers, both in the Nkx2.1-/- and control embryos and in the neurospheres, has revealed a severe loss of both glial cell types in the Nkx2.1 mutants. We found that the loss of glia corresponded to a decrease of Nkx2.1-derived precursor division capacity and glial differentiation. There was a drastic decrease of BrdU+ dividing cells labeled for Nkx2.1 in the MGE*, the POA* and the septal nucleus* of Nkx2.1 mutants. In addition, we noticed that while some remaining Nkx2.1+ precursors still succeeded to give rise to post-mitotic neurons in vitro and in vivo in the Nkx2.1-/-, they completely lost the capacity to differentiate in astrocytes. Altogether, these observations indicate for the first time that the transcription factor Nkx2.1 regulates the proliferation and differentiation of precursors in three subpallial domains that generate early embryonic astroglia and polydendrocytes. Furthermore, in order to investigate the potential function of these early Nkx2.1- derived glia, we have performed multiple immunohistochemical stainings on Nkx2.1-/- and wild-type animals, and Nkx2.1-Cre mice that were crossed to Rosa-DTA+/- mice in which the highly toxic diphtheria toxin aided to selectively deplete a majority of the Nkx2.1-derived cells. Interestingly, in these two mutants, we observed a drastic and significant loss of GFAP+, GLAST+, NG2+ and S100ß+ astroglial cells at the telencephalic midline and in the medial cortical areas. This cells loss could be directly correlated with severe axonal guidance defects observed in the corpus callosum (CC), the hippocampal commissure (HIC), the fornix (F) and the anterior commissure (AC). Axonal guidance is a key step allowing neurons to form specific connections and to become organized in a functional network. The contribution of guidepost cells inside the CC and the AC in mediating the growth of commissural axons have until now been attributed to specialized midline guidepost astroglia. Previous published results in our group have unravelled that, during embryonic development, the CC is populated in addition to astroglia by numerous glutamatergic and GABAergic guidepost neurons that are essential for the correct midline crossing of callosal axons. Therefore, the relative contribution of individual neuronal or glial populations towards the guidance of commissural axons remains largely to be investigated to understand guidance mechanisms further. Thus, we crossed Nkx2.1-Cre mice with NSE-DTA+/- mice that express the diphtheria toxin only in neurons and allowed us to selectively deplete Nkx2.1-derived GABAergic neurons. Interestingly, in the Nkx2.1-/- mice, the CC midline was totally disorganized and the callosal axons partly lost their orientation, whereas in the Nkx2.1Cre+/Rosa-DTA+/- and the Nkx2.1Cre+/NSE-DTA+/- mice, the axonal organization of the CC was not affected. In the three types of mice, hippocampal axons of the fornix were not properly fasciculated and formed disoriented bundles through the septum. Additionally, the AC formation was completely absent in Nkx2.1-/- mice and the AC was divided into two/three separate paths in the Nkx2.1Cre+/Rosa-DTA+/- mice that project in wrong territories. On the other hand, the AC didn't form or was reduced to a relatively narrower tract in the Nkx2.1Cre+/NSE-DTA+/- mice as compared to wild-type AC. These results clearly indicate that midline Nkx2.1-derived cells play a major role in commissural axons pathfinding and that both Nkx2.1-derived guidepost neurons and glia are necessary elements for the correct development of these commissures. Furthermore, during our investigations on Nkx2.1-/- and Nkx2.1Cre+/Rosa-DTA+/- mice, we noticed similar and severe defects in the erythrocytes distribution and the blood vessels network morphology in the embryonic brain of both mutants. As the Cre-mediated recombination was never observed to occur in the blood vessels of Nkx2.1-Cre mice, we inferred that the vessels defects observed were due to the loss of Nkx2.1-derived cells and not to the cells autonomous effects of Nkx2.1 in regulating endothelial cell precursors. Thereafter, the respective contribution of individual Nkx2.1-regulated neuronal or glial populations in the blood vessels network building were studied with the use of transgenic mice strains. Indeed, the use of Nkx2.1Cre+/NSE-DTA+/- mice indicated that the Nkx2.1-derived neurons were not implicated in this process. Finally, to discriminate between the two Nkx2.1-derived glial cell populations, the GLAST+ astroglia and the NG2+ polydendrocytes, an NG2-Cre mouse strain crossed to the Rosa-DTA+/- mice was used. In that mutant, the blood vessel network and the erythrocytes distribution were similarly affected as observed in Nkx2.1Cre+/Rosa-DTA+/- animals. Therefore, this result indicates that most probably, the NG2+ polydendrocytes are involved in helping to build the vessels network in the brain. Taken altogether, these observations show that during brain development, Nkx2.1- derived embryonic glial cells act as guidepost cells on the guidance of axons as well as forming vessels. Both Nkx2.1-regulated guidepost GABAergic neurons and glia collaborate to guide growing commissural axons, while polydendrocytes are implicated in regulating brain angiogenesis. - Le tissu cérébral est composé de cellules neuronales et gliales générées dans les couches germinales qui bordent les ventricules. Ces cellules se divisent, se différencient et migrent selon des voies particulières. La spécification des interneurones GABAergiques et des neurones glutamatergiques a été largement étudiée, par contre, l'origine, le destin et la fonction des cellules gliales précoces du télencéphale embryonnaire restent peu élucidées. Depuis longtemps, il était communément accepté que les cellules gliales, et plus particulièrement les astrocytes, sont générés après la neurogénèse à partir du télencéphale dorsal. Toutefois, notre travail montre que de nombreuses cellules gliales sont générées à partir de précurseurs ventraux qui expriment le gène Nkx2.1, entre E14.5 et E16.5, c'est-à dire,à des stades embryonnaires très précoces. Le gène NK2 homéobox 1 (Nkx2.1) appartient à une famille de facteurs de transcription appelée NK2. Il s'agit de protéines qui contiennent un homéo-domaine. La spécification des précurseurs de la MGE requiert l'expression du gène homéobox Nkx2.1. De plus, la fonction du gène Nkx2.1 dans la régulation de la spécification des interneurones GABAergiques et des oligodendrocytes dans le télencéphale ventral était déjà connue. Au cours de mon travail de thèse, j'ai également mis en évidence que, Nkx2.1 régule aussi les étapes de prolifération et de différenciation de divers sous-types de cellules gliales soit de type astrocytes ou bien polydendrocytes. L'utilisation d'un anticorps contre la protéine Nkx2.1 ainsi qu'une sonde à ribonucléotides contre l'ARN messager du gène Nkx2.1 ont révélé la présence de nombreuses cellules positives pour Nkx2.1 qui exprimaient des marqueurs astrocytaires (comme GLAST et GFAP) dans le télencéphale embryonnaire. Afin de déterminer de manière sélective le sort des interneurones GABAergiques, des polydendrocytes et des astrocytes dérivés de la MGE, nous avons croisé soit des souris Nkx2.1-Cre, des souris Glast-Cre ERT+/- inductibles ou bien des souris NG2-Cre avec des souris Rosa26-lox-STOP-lox-YFP (Rosa26-YFP) Cre rapportrices. L'origine précise des astroglies positives pour Nkx2.1 a été directement établie en combinant une coloration immunologique pour les glies et une électroporation focale d'un plasmide pCAG-GS-EGFP dans les domaines subpalliaux de tranches organotypiques, puis également, par des cultures de neurosphères in vitro et des expériences d'électroporation in utero d'un plasmide pCAG-GS-tomato dans le pallium ventral d'embryons Nkx2.1-Cre+/Rosa- YFP+/- au stade E14.5. Nous avons donc confirmé que les trois régions germinales du télencéphale ventral, c'est-à-dire, la MGE, l'AEP/POA et le noyau triangulaire septal sont capables de générer des cellules astrogliales. D'autre part, l'immunohistochimie pour plusieurs marqueurs d'astrocytes ou de polydendrocytes, dans les embryons Nkx2.1-/- et contrôles ainsi que dans les neurosphères, a révélé une sévère perte de ces deux types gliaux chez les mutants. Nous avons trouvé que la perte de glies correspondait à une diminution de la capacité de division des précurseurs dérivés de Nkx2.1, ainsi que l'incapacité de ces précurseurs de se différencier en cellules gliales. Nous avons en effet observé une diminution importante des cellules BrdU+ en division exprimant Nkx2.1dans la MGE*, la POA* et le noyau septal* des mutants pour Nkx2.1. D'autre part, nous avons pu mettre en évidence aussi bien in vitro, qu'in vivo, que certains précurseurs Nkx2.1+ chez le mutant gardent la capacité à se différencier en neurones tandis qu'ils perdent celle de se différencier en cellules gliales. Prises dans leur ensemble, ces observations indiquent pour la première fois que le facteur de transcription Nkx2.1 régule les étapes de prolifération et de différentiation des précurseurs des trois domaines subpalliaux qui génèrent les astroglies et polydendrocytes embryonnaires précoces. Par la suite, dans le but de comprendre la fonction potentielle de ces glies précoces, nous avons procédé à de multiples colorations immunohistochimiques sur des animaux Nkx2.1-/- et sauvages, ainsi que sur des souris Nkx2.1-Cre croisées à des souris Rosa-DTA+/- dans lesquelles la toxine diphthérique hautement toxique a permis de supprimer sélectivement la majorité des cellules dérivées de Nkx2.1. De manière intéressante, nous avons observé dans ces deux mutants, une perte drastique et significative de cellules astrogliales GFAP+, GLAST+ et polydendrocytaires NG2+ et S100ß+ dans le télencéphale, à la midline et dans les aires corticales médianes. Ces pertes ont pu être directement corrélées avec des défauts de guidage axonal observés dans le corps calleux (CC), la commissure hippocampique (HIC), le fornix (F) et la commissure antérieure (AC). Le guidage axonal est une étape clé permettant aux neurones de former des connections spécifiques et de s'organiser dans un réseau fonctionnel. La contribution des cellules « guidepost » dans le CC et dans la AC comme médiateurs de la croissance des axones commissuraux à jusqu'à aujourd'hui été attribuée spécifiquement à des astroglies « guidepost » de la midline. Des résultats publiés précédemment dans notre groupe, ont permis de montrer que, pendant le développement embryonnaire, le CC est peuplé en plus de la glie par de nombreux neurones « guidepost » glutamatergiques et GABAergiques qui sont essentiels pour le croisement correct des axones callosaux à la midline. Ainsi, la contribution relative des populations individuelles neuronales ou gliales pour le guidage des axones commissuraux demande à être approfondie afin de mieux comprendre les mécanismes de guidage. A ces fins, nous avons croisé des souris Nkx2.1-Cre avec des souris NSE-DTA+/- qui expriment la toxine diphthérique uniquement dans les neurones et ainsi, nous avons pu sélectivement supprimer les neurones dérivés de domaines Nkx2.1+. Dans les souris Nkx2.1-/-,nous avons découvert que le CC était désorganisé avec des axones callosaux perdant partiellement leur orientation, alors que dans les souris Nkx2.1Cre+/Rosa-DTA+/- et Nkx2.1Cre+/NSE-DTA+/-, l'organisation axonale n'était pas affectée. De plus, les faisceaux hippocampiques du fornix étaient défasciculés dans les trois types de mutants. Par ailleurs, la formation de la commissure antérieure (AC) était complètement absente dans les souris Nkx2.1-/- d'une part, et d'autre part, celle-ci était divisée en deux à trois voies séparées dans les souris Nkx2.1Cre+/Rosa-DTA+/-. Finalement, la AC était soit absente, soit réduite de manière ne former plus qu'un faisceau relativement plus étroit dans les souris Nkx2.1Cre+/NSE-DTA+/- en comparaison avec la AC sauvage. Ces derniers résultats indiquent clairement que les cellules dérivées de Nkx2.1 à la midline, jouent un rôle majeur dans le guidage des axones commissuraux et que, autant les neurones, que les astrocytes « guidepost » dérivés de Nkx2.1, sont des éléments nécessaires au développement correct de ces commissures. En outre, lors de nos investigations sur les souris Nkx2.1-/- et Nkx2.1Cre+/Rosa-DTA+/-, nous avons remarqués des défauts sévères et similaires dans la distribution des erythrocytes et dans la morphologie du réseau de vaisseaux sanguins dans le cerveau embryonnaire des deux mutants précités. Puisque nous n'avons jamais observé de recombinaison de la Cre recombinase dans les vaisseaux sanguins des souris Nkx2.1Cre, nous en avons déduit que les défauts de vaisseaux observés étaient dus à la perte de cellules dérivées de Nkx2.1. Il existerait donc en plus de la fonction cellulaire autonome de Nkx2.1 reconnue pour régulée directement la spécification des cellules endothéliales, une fonction indirecte de Nkx2.1. Afin de déterminer la contribution respective des populations individuelles neuronales ou gliales régulées par Nkx2.1 dans la construction du réseau de vaisseaux sanguins, nous avons utilisé diverses lignées de souris transgéniques. L'utilisation de souris Nkx2.1Cre+/NSE-DTA+/- a indiqué que les neurones dérivés de Nkx2.1 n'étaient pas impliqués dans ce processus. Finalement, afin de discriminer entre les deux populations de cellules gliales dérivées de Nkx2.1, les astroglies et les polydendrocytes, nous avons croisé une lignée de souris NG2-Cre avec des souris Rosa-DTA+/-. Dans ce dernier mutant, le réseau de vaisseaux sanguins du cortex ainsi que la distribution des erythrocytes étaient affectés de la même manière que dans le cortex des souris Nkx2.1Cre+/Rosa-DTA+/-. Par conséquent, ce résultat indique que très probablement, les polydendrocytes NG2+ sont impliqués dans la mise en place du réseau de vaisseaux dans le cerveau. Prises dans leur ensemble, ces observations montrent que durant le développement embryonnaire du cerveau, des sous-populations de glies régulées par Nkx2.1 jouent un rôle de cellules « guidepost » dans le guidage des axones, ainsi que des vaisseaux. Les polydendrocytes sont impliquées dans la régulation de l'angiogenèse tandis que, autant les neurones GABAergiques que les astrocytes collaborent dans le guidage des axones commissuraux en croissance.

Genetic Variants of Serum Uric Acid and Gout: An Analysis of > 170,000 Individuals

Background/Purpose: Gout is a common and excruciatingly painful inflammatory arthritis caused by hyperuricemia. In addition to various lifestyle risk factors, a substantial genetic predisposition to gout has long been recognized. The Global Urate Genetics Consortium (GUGC) has aimed to comprehensively investigate the genetics of serum uric acid and gout using data from _ 140,000 individuals of European-ancestry, 8,340 individuals of Indian ancestry, 5,820 African-Americans, and 15,286 Japanese. Methods: We performed discovery GWAS meta-analyses of serum urate levels (n_110,347 individuals) followed by replication analyses (n_32,813 different individuals). Our gout analysis involved 3,151 cases and 68,350 controls, including 1,036 incident gout cases that met the American College of Rheumatology Criteria. We also examined the association of gout with fractional excretion of uric acid (n_6,799). A weighted genetic urate score was constructed based on the number of risk alleles across urate-associated loci, and their association with the risk of gout was evaluated. Furthermore, we examined implicated transcript expression in cis (expression quantitative trait loci databases) for potential insights into the gene underlying the association signal. Finally, in order to further identify urate-associated genomic regions, we performed functional network analyses that incorporated prior knowledge on molecular interactions in which the gene products of implicated genes operate. Results: We identified and replicated 28 genome-wide significant loci in association with serum urate (P 5_10_8), including all previously-reported loci as well as 18 novel genetic loci. Unlike the majority of previouslyidentified loci, none of the novel loci appeared to be obvious candidates for urate transport. Rather, they were mapped to genes that encode for purine production, transcription, or growth factors with broad downstream responses. Besides SLC2A9 and ABCG2, no additional regions contained SNPs that differed significantly (P _ 5_10_8) between sexes. Urateincreasing alleles were associated with an increased risk of gout for all loci. The urate genetic risk score (ranging from 10 to 45) was significantly associated with an increased odds of prevalent gout (OR per unit increase, 1.11; 95% CI, 1.09-1.14) and incident gout (OR, 1.10; 95% CI, 1.08-1.13). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. Detailed characterization of the loci revealed associations with transcript expression and the fractional excretion of urate. Network analyses implicated the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. Conclusion: The novel genetic candidates identified in this urate/gout consortium study, the largest to date, highlight the importance of metabolic control of urate production and urate excretion. The modulation by signaling processes that influence metabolic pathways such as glycolysis and the pentose phosphate pathway appear to be central mechanisms underpinned by the novel GWAS candidates. These findings may have implications for further research into urate-lowering drugs to treat and prevent gout.

Model-Free Reconstruction of Excitatory Neuronal Connectivity from Calcium Imaging Signals

A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections are characterized by an elevated level of clustering compared to a random graph (although not extreme) and can be markedly non-local.