Finding optimal stimuli ensemble of a cortical network

We explore the determination of the optimal stimuli ensemble of a cortical network on the basis of numerical simulations of a local recurrent network. The optimal stimulus ensemble is determined with the Blahut-Arimoto algorithm using indices of population activity (multiunit activity and local field potentials). We show that the optimal stimulus ensemble is characterized by a distribution where the stimulus which induces a change in the dynamics of the network is highly represented. These results suggests that bifurcation points in the networks dynamic are highly informative and were in accordance with preliminary observation of electrophysiological recordings

Two is better than one: The effects of strategic cooperation on intra- and inter-brain connectivity by fNIRS

Inter-brain synchronization during joint actions is a core question in social neuroscience, and the differential contribution of intra- and inter-brain functional connectivity has yet to be clarified along with the role of psychological variables such as perceived self-efficacy. The cognitive performance and the neural activation underlying the execution of joint actions were recorded by functional Near-Infrared imaging during a synchronicity game. An 8-channel array of optodes was positioned over the frontal and prefrontal regions. During the task, the dyads received reinforcing feedback that was experimentally manipulated to induce adoption of common strategies. Intra- and inter-brain connectivity indices were computed along with an inter-brain/intra-brain connectivity index (ConIndex). Finally, correlation analyses were run to assess the relationship between behavioral and physiological levels. The results showed that the external feedback could modulate participant responses in both behavioral and neural components. After the reinforcing manipulation, there were faster response times and increased inter-brain connectivity, and ConIndex emerged primarily over the dorsolateral prefrontal cortex. Additionally, the presence of significant correlations between response times and inter-brain connectivity revealed that only the \ue2\u80\u9ctwo-players connection\ue2\u80\u9d may guarantee an efficient performance. The present study provides a significant contribution to the identification of intra- and inter-brain functional connectivity when social reinforcement is provided

CO 2 Migration Monitoring Methodology in the Shallow Subsurface: Lessons Learned From the CO 2 FIELDLAB Project

International audienceA CO 2 migration field laboratory for testing of monitoring methods has been established in the glaciofluvial-glaciomarine Holocene deposits of the Svelvik ridge, near Oslo. A shallow CO 2 injection experiment was conducted in September 2011 in which approximately 1700 kg of CO 2 was injected at 18 m depth below surface. The objectives of this experiment were to (i) detect and, where possible, quantify migrated CO 2 concentrations, (ii) evaluate the sensitivity of the monitoring tools and (iii) study the impact of the vadose zone on measurements. This paper describes the injection, discusses the joint interpretation of the results and suggests some recommendations for further work

Innovative downhole geophysical methods for high frequency seawater intrusion dynamics monitoring

The detailed characterization of salt water intrusion is a key to understand both submarine groundwater discharge and manage often intensively exploited groundwater resources in coastal areas. With the objective to study the response of a coastal aquifer to a series of boundary conditions, a new experimental site has been developed through a clastic aquifer located north of Barcelona (Spain). This hectometer scale site is located 50 m from the seashore and equipped with 17 nearby shallow holes, with depths ranging from 15 to 28 m. In order to study not only the sedimentary structure but also the response of the aquifer to a set of natural boundary conditions, downhole geophysical measurements have been deployed over the past 3 years in an innovative manner, either in a time-lapse or stationary manner. The downhole measurements are complicated by the unconsolidated nature of the sediment, obliging to perform all measurements through PVC. Also, the granitic nature of the sediment prevents clays identification from a direct use of gamma ray profiles. For this, constituting minerals (quartz, albite, feldspar, microcline, illite) were identified from X-ray diffraction on cores, and spectral gamma logs used to determine the illite fractions from Th/K ratios. In time lapse, high frequency electrical resistivity induction measurements show that preferential flow paths through the aquifer can be identified in a fast and reliable manner. Also, changes in depth of the fresh to salt water interface (FSWI) are precisely described, either in response to marine tides, or to a short but intense mediterranean rain event. Changes on the order of than 1.70 m are obtain in less than a day of heavy rain. Overnight as well as seasonal changes such as months of dryness are also illustrated due to the variability of pore fluid salinity and temperature, even over short periods of time such as tens of minutes. In stationary mode, the spectral natural gamma sensor located in front of the FSWI fluctuation zones records changes in front of all radioactive peaks (from K, Tl, Bi, but also Ra with Rn) during intense rain events such as that of October 18-19, 2017. This places constraints on Ra and Rn production rate during such an event, leading to trace fresh water outpour into the sea.Peer reviewe

Influence de la formation des echographistes sur le dépistage des cardiopathies congénitales (12 ans d'étude dans la population générale)

Objective: Multidisciplinary prenatal diagnosis centers were created in France in 1998 and offer an opportunity of training to ultrasonographers. We aimed to measure the impact of their creation on the prenatal detection rates of congenital heart diseases (CHD).Methods: We analyzed the sensitivity of the screening performed by first level ultrasonographers (FLU) between 1994 and 2006 by comparing CHD prenatal diagnoses and CHD observed after birth in Angers universitary hospital. Two groups of FLU were compared (those attending the training and a control group of those who didn t). The evolution of these 2 groups detection rates was analyzed on two periods of 6 years (1994-1999 & 2000-2006) for significant CHD.Results: Of 947 CHD, 438 (46%) were detected prenatally. The control group sensitivity was 16% versus 37% for the FLU attending the training course. Concerning significant CHD, the control group didn t improve its sensitivity between the two periods whereas the other did (54% vs 75%, p<0.05).Conclusion : this study quantifies the beneficial effect of multidisciplinary prenatal diagnosis centers, not only for their primary purpose, management of pathological pregnancies or threatened fetuses, but also as learning centers which help FLU to improve their practice.ANGERS-BU Médecine-Pharmacie (490072105) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Dynamical paradigm in psychopathology : « Chaos theory », from physics to psychiatry

International audienceFor the last thirty years, progress in the field of physics, known as "Chaos theory"--or more precisely: non-linear dynamical systems theory--has increased our understanding of complex systems dynamics. This framework's formalism is general enough to be applied in other domains, such as biology or psychology, where complex systems are the rule rather than the exception. Our goal is to show here that this framework can become a valuable tool in scientific fields such as neuroscience and psychiatry where objects possess natural time dependency (i.e. dynamical properties) and non-linear characteristics. The application of non-linear dynamics concepts on these topics is more precise than a loose metaphor and can throw a new light on mental functioning and dysfunctioning. A class of neural networks (recurrent neural networks) constitutes an example of the implementation of the dynamical system concept and provides models of cognitive processes (15). The state of activity of the network is represented in its state space and the time evolution of this state is a trajectory in this space. After a period of time those networks settle on an equilibrium (a kind of attractor). The strength of connections between neurons define the number and relations between those attractors. The attractors of the network are usually interpreted as "mental representations". When an initial condition is imposed to the network, the evolution towards an attractor is considered as a model of information processing (27). This information processing is not defined in a symbolic manner but is a result of the interaction between distributed elements. Several properties of dynamical models can be used to define a way where the symbolic properties emerge from physical and dynamical properties (28) and thus they can be candidates for the definition of the emergence of mental properties on the basis of neuronal dynamics (42). Nevertheless, mental properties can also be considered as the result of an underlying dynamics without explicit mention of the neuronal one (47). In that case, dynamical tools can be used to elucidate the Freudian psychodynamics (34, 35). Recurrent neuronal networks have been used to propose interpretation of several mental dysfunctions (12). For example in the case of schizophrenia, it has been proposed that troubles in the cortical pruning during development (13) may cause a decrease in neural network storage ability and lead to the creation of spurious attractors. Those attractors do not correspond to stored memories and attract a large amount of initial conditions: they were thus associated to reality distorsion observed in schizophrenia (14). Nevertheless, the behavior of these models are too simple to be directly compared with real physiological data. In fact, equilibrium attractors are hardly met in biological dynamics. More complex behaviors (such as oscillations or chaos) should thus to be taken into account. The study of chaotic behavior have lead to the development of numerical methods devoted to the analysis of complex time series (17). These methods may be used to characterise the dynamical processes at the time-scales of both the cerebral dynamics and the clinical symptoms variations. The application of these methods to physiological signals have shown that complex behaviors are related to healthy states whereas simple dynamics are related to pathology (8). These studies have thus confirmed the notion of "dynamical disease" (20, 21) which denotes pathological conditions characterised by changes in physiological rhythms. Depression has been studied within this framework (25, 32) in order to define possible changes in brain electrical rhythms related to this trouble and its evolution. It has been shown that controls' brain dynamics is more complex than depressive one and that the recovery of a complex brain activity depends on the number of previous episodes. In the case of the symptoms time evolution, several studies have demonstrated that non-linear dynamical process may be involved in the recurrence of symptoms in troubles such as manic-depressive illness (9) or schizophrenia (51). These observations can contribute to more parcimonious interpretation of the time course of these illnesses than usual theories. In the search of a relationship between brain dynamics and mental troubles, it has been shown in three depressed patients an important correlation between the characteristics of brain dynamics and the intensity of depressive mood (49). This preliminary observation is in accordance with the emergence hypothesis according which changes in neuronal dynamics should be related to changes in mental processes. We reviewed here some theoretical and experimental results related to the use of "physical" dynamical theory in the field of psychopathology. It has been argued that these applications go beyond metaphor and that they are empirically founded. Nevertheless, these studies only constitute first steps on the way of a cautious development and definition of a "dynamical paradigm" in psychopathology. The introduction of concepts from dynamics such as complexity and dynamical changes (i.e. bifurcations) permits a new perspective on function and dysfunction of the mind/brain and the time evolution of symptoms. Moreover, it offers a ground for the hypothesis of the emergence of mental properties on the basis of neuronal dynamics (42). Since this theory can help to throw light on classical problems in psychopathology, we consider that a precise examination of both its theoretical and empirical consequences is requested to define its validity on this topic.Depuis une trentaine d’années, certains développements de la physique ont amélioré notre compréhension de la dynamique des systèmes complexes. Connues sous le nom de « Théorie du chaos » – ou plus sobrement : théorie des systèmes dynamiques non-linéaires –, ces avancées possèdent une généralité qui permet d’envisager leur utilisationdans des domaines autres que ceux dans lesquels elles ont vu le jour. Notre objectif est de montrer qu’elles peuvent devenir des outils importants dans des disciplines telles queles neurosciences et la psychiatrie où les phénomènes étudiés possèdent naturellement une inscription temporelle i.e. une dynamique. L’introduction des concepts de la dynamiquenon-linéaire dans ces disciplines dépasse la simple métaphore et peut fournir à terme un nouvel éclairage du fonctionnement mental et de ses dérèglements. À partir d’exemplestirés de la littérature, nous montrons comment ces nouveaux concepts permettent un renouvellement des façons d’envisager des problèmes classiques comme l’évolutiontemporelle des symptômes ou la relation entre le cérébral et le mental

Quantifying Neural Correlations Using Lempel-Ziv Complexity

ISBN : 978-2-9532965-0-1Spike train analysis generally focus on two purposes: (1) the estimate of the neuronal information quantity, and (2) the quantification of spikes or bursts synchronization. We introduce here a new multivariate index based on Lempel-Ziv complexity for spike train analysis. This index, called mutual Lempel-Ziv complexity (MLZC), can measure both spikes correlations and estimate the information quantity of spike trains (i.e. characterize the dynamic state). Using simulated spike trains from a Poisson process, we show that the MLZC is able to quantify spike correlations. In addition, using bursting activity generated by electrically coupled Hindmarsh-Rose neurons, the MLZC is able to quantify and characterize bursts synchronization, when classical measures fail

How do maternal emotional regulation difficulties modulate the mother–infant behavioral synchrony?

International audienceMother–infant synchrony is one of the most important processes in the development of socio-affective competencies in children. While maternal abilities and psychopathology are related to maladaptive mother–infant synchrony, it is as yet unclear how maternal emotion regulation difficulties contribute to it. Based on a panel of behavioral indicators (i.e., gaze, vocal, and motor), the present study examined mother–infant synchrony at 6 months of age in a modified version of Ainsworth's Strange Situation (n = 72 dyads). Mother–infant interaction sequences were characterized by indicators of complexity (LZ complexity of joint behavioral sequences) and of synchronization quality (cross-recurrence plot quantification). Results showed that mothers’ touch was greater in the reunion condition than in the initial condition. Mothers’ motor behaviors were associated with the global levels of infants’ behavioral involvement in the reunion condition, unlike the symmetrical influence observed between mothers and infants in the initial condition. Results show that maternal anxiety mediates the relationships between mothers’ emotion regulation difficulties and gaze, vocal, and motor synchrony between mothers and infants in the initial and reunion conditions. This study emphasizes the central role of maternal emotion regulation difficulties in the establishment of maladaptive synchrony and in the adjustments of maternal physical contacts with infants

Dynamics as a heuristic framework forpsychopathology

The development of the mathematics of dynamical systems now offers a rigourous framework to deal with complex phenomenon evolving with time. The possible euristic value of applying dynamical concepts to the field of psychopathology is investigated here. Three levels of applications found in the literature are reviewed: metaphoric, qualitative and quantitative.Psychopathology seems indeed a field where the concepts of dynamics can offer important tools, both theoretical and empirical. Nevetheless, specific problems should be emphasized to obtain a more profound insight in normal and pathological mental phenomenon