Phase transitions and nonlinear phenomena in neuronal network models

Communication and cooperation between billions of neurons underlie the power of the brain. How do complex functions of the brain arise from its cellular constituents? How do groups of neurons self-organize into patterns of activity? These are crucial questions in neuroscience. In order to answer them, it is necessary to have solid theoretical understanding of how single neurons communicate at the microscopic level, and how cooperative activity emerges. In this thesis we aim to understand how complex collective phenomena can arise in a simple model of neuronal networks. We use a model with balanced excitation and inhibition and complex network architecture, and we develop analytical and numerical methods for describing its neuronal dynamics. We study how interaction between neurons generates various collective phenomena, such as spontaneous appearance of network oscillations and seizures, and early warnings of these transitions in neuronal networks. Within our model, we show that phase transitions separate various dynamical regimes, and we investigate the corresponding bifurcations and critical phenomena. It permits us to suggest a qualitative explanation of the Berger effect, and to investigate phenomena such as avalanches, band-pass filter, and stochastic resonance. The role of modular structure in the detection of weak signals is also discussed. Moreover, we find nonlinear excitations that can describe paroxysmal spikes observed in electroencephalograms from epileptic brains. It allows us to propose a method to predict epileptic seizures. Memory and learning are key functions of the brain. There are evidences that these processes result from dynamical changes in the structure of the brain. At the microscopic level, synaptic connections are plastic and are modified according to the dynamics of neurons. Thus, we generalize our cortical model to take into account synaptic plasticity and we show that the repertoire of dynamical regimes becomes richer. In particular, we find mixed-mode oscillations and a chaotic regime in neuronal network dynamics.

Development and Progress as Historical Phenomena in Tanzania: “Maendeleo? We Had That in the Past”

Academic discussions of development continue to grow, yet critical engagements with communities affected by development interventions remain limited. Drawing from life history interviews conducted in southern Tanzania, this article details the varied experiences of development interventions among older people and how these affect broader understandings of progress. Many juxtapose their negative views of ujamaa villagization with more positive recollections of previous interventions (especially the Groundnut Scheme), which are infused with what is described here as “development nostalgia.” Perceptions of the past clearly inform the social, political, and economic aspirations forwarded today, with the richness of the constructed narratives adding further nuance to existing depictions of Tanzanian historiography.

Fractional dynamics and MDS visualization of earthquake phenomena

This paper analyses earthquake data in the perspective of dynamical systems and fractional calculus (FC). This new standpoint uses Multidimensional Scaling (MDS) as a powerful clustering and visualization tool. FC extends the concepts of integrals and derivatives to non-integer and complex orders. MDS is a technique that produces spatial or geometric representations of complex objects, such that those objects that are perceived to be similar in some sense are placed on the MDS maps forming clusters. In this study, over three million seismic occurrences, covering the period from January 1, 1904 up to March 14, 2012 are analysed. The events are characterized by their magnitude and spatiotemporal distributions and are divided into fifty groups, according to the Flinn–Engdahl (F–E) seismic regions of Earth. Several correlation indices are proposed to quantify the similarities among regions. MDS maps are proven as an intuitive and useful visual representation of the complex relationships that are present among seismic events, which may not be perceived on traditional geographic maps. Therefore, MDS constitutes a valid alternative to classic visualization tools for understanding the global behaviour of earthquakes.

Power law and entropy analysis of catastrophic phenomena

Catastrophic events, such as wars and terrorist attacks, tornadoes and hurricanes, earthquakes, tsunamis, floods and landslides, are always accompanied by a large number of casualties. The size distribution of these casualties has separately been shown to follow approximate power law (PL) distributions. In this paper, we analyze the statistical distributions of the number of victims of catastrophic phenomena, in particular, terrorism, and find double PL behavior. This means that the data sets are better approximated by two PLs instead of a single one. We plot the PL parameters, corresponding to several events, and observe an interesting pattern in the charts, where the lines that connect each pair of points defining the double PLs are almost parallel to each other. A complementary data analysis is performed by means of the computation of the entropy. The results reveal relationships hidden in the data that may trigger a future comprehensive explanation of this type of phenomena.

Dynamic analysis of earthquake phenomena by means of pseudo phase plane

This paper analyses earthquake data in the perspective of dynamical systems and its Pseudo Phase Plane representation. The seismic data is collected from the Bulletin of the International Seismological Centre. The geological events are characterised by their magnitude and geographical location and described by means of time series of sequences of Dirac impulses. Fifty groups of data series are considered, according to the Flinn-Engdahl seismic regions of Earth. For each region, Pearson’s correlation coefficient is used to find the optimal time delay for reconstructing the Pseudo Phase Plane. The Pseudo Phase Plane plots are then analysed and characterised.

A review of power laws in real life phenomena

Power law distributions, also known as heavy tail distributions, model distinct real life phenomena in the areas of biology, demography, computer science, economics, information theory, language, and astronomy, amongst others. In this paper, it is presented a review of the literature having in mind applications and possible explanations for the use of power laws in real phenomena. We also unravel some controversies around power laws.

Fractional order inductive phenomena based on the skin effect

The Maxwell equations play a fundamental role in the electromagnetic theory and lead to models useful in physics and engineering. This formalism involves integer-order differential calculus, but the electromagnetic diffusion points towards the adoption of a fractional calculus approach. This study addresses the skin effect and develops a new method for implementing fractional-order inductive elements. Two genetic algorithms are adopted, one for the system numerical evaluation and another for the parameter identification, both with good results.

Filtering method in backlash phenomena analysis

The behavior of robotic manipulators with backlash is analyzed. Based on the pseudo-phase plane two indices are proposed to evaluate the backlash effect upon the robotic system: the root mean square error and the fractal dimension. For the dynamical analysis the noisy signals captured from the system are filtered through wavelets. Several tests are developed that demonstrate the coherence of the results.

Multidimensional scaling visualization of earthquake phenomena

Earthquakes are associated with negative events, such as large number of casualties, destruction of buildings and infrastructures, or emergence of tsunamis. In this paper, we apply the Multidimensional Scaling (MDS) analysis to earthquake data. MDS is a set of techniques that produce spatial or geometric representations of complex objects, such that, objects perceived to be similar/distinct in some sense are placed nearby/distant on the MDS maps. The interpretation of the charts is based on the resulting clusters since MDS produces a different locus for each similarity measure. In this study, over three million seismic occurrences, covering the period from January 1, 1904 up to March 14, 2012 are analyzed. The events, characterized by their magnitude and spatiotemporal distributions, are divided into groups, either according to the Flinn–Engdahl seismic regions of Earth or using a rectangular grid based in latitude and longitude coordinates. Space-time and Space-frequency correlation indices are proposed to quantify the similarities among events. MDS has the advantage of avoiding sensitivity to the non-uniform spatial distribution of seismic data, resulting from poorly instrumented areas, and is well suited for accessing dynamics of complex systems. MDS maps are proven as an intuitive and useful visual representation of the complex relationships that are present among seismic events, which may not be perceived on traditional geographic maps. Therefore, MDS constitutes a valid alternative to classic visualization tools, for understanding the global behavior of earthquakes.

Distributed Sensing of Fluid Dynamic Phenomena with the XDense Sensor Grid Network

IEEE International Conference on Cyber Physical Systems, Networks and Applications (CPSNA'15), Hong Kong, China.

New Features to Look at Natural Phenomena

Proceeding of the 3rd International Conference on Fractional Systems and Signals, at Ghent, Belgium

Study of the application of the high performance liquid chromatography-particle beam interface-mass spectrometry technique on some pesiticides and the reduction phenomena in the system

This work includes two major parts. The first part of the work concentrated on the studies of the application of the highperfonnance liquid chromatography-particle beam interface-mass spectrometry system of some pesticides. Factors that have effects on the detection sensitivity were studied. The linearity ranges and detection limits of ten pesticides are also given in this work. The second part of the work concentrated on the studies of the reduction phenomena of nitro compounds in the HPLC-PB-MS system. Direct probe mass spectrometry and gas chromatography-mass spectrometry techniques were also used in the work. Factors that have effects on the reduction of the nitro compounds were studied, and the possible explanation is proposed. The final part of this work included the studies of reduction behavior of some other compounds in the HPLC-PB-MS system, included in them are: quinones, sulfoxides, and sulfones.

The law of psychic phenomena : working hypothesis for the systematic study of hypnotism. spiritism, mental therapeutic, etc.

UANL

Developmental trajectories of marijuana use and psychological distress : exploring the co-occurrence of these phenomena in early adolescence

Le début de l’adolescence est une période de changements rapides où la détresse psychologique et l’expérimentation de la marijuana sont choses fréquentes. Certaines études longitudinales ont démontré que ces deux phénomènes ont tendance à se manifester conjointement tandis que d’autres n’ont pu observer de tel lien. Ces résultats divergents suggèrent que plusieurs questions persistent concernant la nature de cette relation. Cette thèse a pour objectif d’explorer la consommation de marijuana et la détresse psychologique en début d’adolescence afin de mieux saisir les changements à travers le temps, ainsi que d’examiner si ces deux problématiques évoluent conjointement et s’influencent réciproquement. Un échantillon de 448 adolescents garçons et filles fréquentant deux écoles secondaires de Montréal, ont été suivi de secondaire I à secondaire III. De 1999 à 2001, les participants ont complété un questionnaire à chaque année de l’étude incluant des mesures portant sur la consommation de marijuana et la détresse psychologique (IDPESQ-14). Un modèle de mixture semi-paramétrique (Nagin, 2005) a été utilisé afin d’identifier les trajectoires développementales de la consommation de marijuana et de détresse psychologique. Des analyses ont également été effectuées afin d’établir les liens d’appartenance entre chacune des trajectoires de consommation identifiées et la détresse psychologique lors de la première année de l`étude, ainsi qu’entre chacune des trajectoires de détresse psychologique et la consommation de marijuana en première année du secondaire. Finalement, des analyses de trajectoires jointes ont été effectuées afin de déterminer l’interrelation entre la consommation de marijuana et la détresse psychologique. Les résultats de notre étude suggèrent qu’il existe une grande hétérogénéité au niveau de la consommation de marijuana et la détresse psychologique. Trois trajectoires développementales ont été identifiées pour la consommation de marijuana: consommation légère, consommation grandissante et consommation élevée et stable. Trois trajectoires ont également été observées pour la détresse psychologique : basse, moyenne et élevée. Nos résultats démontrent la présence d’un lien entre la détresse psychologique rapportée lors de la première année de l’étude et les trajectoires de consommation problématiques. Ce lien a également été observé entre la consommation de marijuana rapportée lors de première année de l’étude et les trajectoires problématiques de détresse psychologique. Les analyses de trajectoires jointes démontrent la présence d’une concordance entre la consommation de marijuana et la détresse psychologique. Cette interrelation est toutefois complexe puisque les trajectoires de détresse psychologique élevée sont associées à un niveau de consommation de marijuana plus problématique mais l’inverse de cette association est moins probable. Notre étude met en lumière la nature asymétrique de la concordance entre la consommation de marijuana et la détresse psychologique.