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.

Cultural journalism in a digital environment : new models, practices and possibilities

Both culture coverage and digital journalism are contemporary phenomena that have undergone several transformations within a short period of time. Whenever the media enters a period of uncertainty such as the present one, there is an attempt to innovate in order to seek sustainability, skip the crisis or find a new public. This indicates that there are new trends to be understood and explored, i.e., how are media innovating in a digital environment? Not only does the professional debate about the future of journalism justify the need to explore the issue, but so do the academic approaches to cultural journalism. However, none of the studies so far have considered innovation as a motto or driver and tried to explain how the media are covering culture, achieving sustainability and engaging with the readers in a digital environment. This research examines how European media which specialize in culture or have an important cultural section are innovating in a digital environment. Specifically, we see how these innovation strategies are being taken in relation to the approach to culture and dominant cultural areas, editorial models, the use of digital tools for telling stories, overall brand positioning and extensions, engagement with the public and business models. We conducted a mixed methods study combining case studies of four media projects, which integrates qualitative web features and content analysis, with quantitative web content analysis. Two major general-interest journalistic brands which started as physical newspapers – The Guardian (London, UK) and Público (Lisbon, Portugal) – a magazine specialized in international affairs, culture and design – Monocle (London, UK) – and a native digital media project that was launched by a cultural organization – Notodo, by La Fábrica – were the four case studies chosen. Findings suggest, on one hand, that we are witnessing a paradigm shift in culture coverage in a digital environment, challenging traditional boundaries related to cultural themes and scope, angles, genres, content format and delivery, engagement and business models. Innovation in the four case studies lies especially along the product dimensions (format and content), brand positioning and process (business model and ways to engage with users). On the other hand, there are still perennial values that are crucial to innovation and sustainability, such as commitment to journalism, consistency (to the reader, to brand extensions and to the advertiser), intelligent differentiation and the capability of knowing what innovation means and how it can be applied, since this thesis also confirms that one formula doesn´t suit all. Changing minds, exceeding cultural inertia and optimizing the memory of the websites, looking at them as living, organic bodies, which continuously interact with the readers in many different ways, and not as a closed collection of articles, are still the main challenges for some media.

Increased numbers of circulating polyfunctional Th17 memory cells in patients with seronegative spondylarthritides

OBJECTIVE: A distinct subset of proinflammatory CD4+ T cells that produce interleukin-17 was recently identified. These cells are implicated in different autoimmune disease models, such as experimental autoimmune encephalomyelitis and collagen-induced arthritis, but their involvement in human autoimmune disease has not yet been clearly established. The purpose of this study was to assess the frequency and functional properties of Th17 cells in healthy donors and in patients with different autoimmune diseases. METHODS: Peripheral blood was obtained from 10 psoriatic arthritis (PsA), 10 ankylosing spondylitis (AS), 10 rheumatoid arthritis (RA), and 5 vitiligo patients, as well as from 25 healthy donors. Synovial tissue samples from a separate group of patients were also evaluated (obtained as paraffin-embedded sections). Peripheral blood cells were analyzed by multiparameter flow cytometry and immunohistochemistry. Cytokine production was examined by enzyme-linked immunosorbent assay and intracellular cytokine staining using specific monoclonal antibodies. Synovial tissue was examined for infiltrating T cells by immunohistochemical analysis. RESULTS: We found increased numbers of circulating Th17 cells in the peripheral blood of patients with seronegative spondylarthritides (PsA and AS), but not in patients with RA or vitiligo. In addition, Th17 cells from the spondylarthritis patients showed advanced differentiation and were polyfunctional in terms of T cell receptor-driven cytokine production. CONCLUSION: These observations suggest a role of Th17 cells in the pathogenesis of certain human autoimmune disorders, in particular the seronegative spondylarthritides.

ERP and cardiovascular correlates of source memory discrimination in older and younger adults /

There is much evidence to support an age-related decline in source memory ability. However, the underlying mechanisms responsible for this decline are not well understood. The current study was carried out to determine the electrophysiological correlates of source memory discrimination in younger and older adults. Event-related potentials (ERPs) and continuous electrocardiographic (ECG) data were collected from younger (M= 21 years) and older (M= 71 years) adults during a source memory task. Older adults were more likely to make source memory errors for recently repeated, non-target words than were younger adults. Moreover, their ERP records for correct trials showed an increased amplitude in the late positive (LP) component (400-800 msec) for the most recently presented, non-target stimuli relative to the LP noted for target items. Younger adults showed an opposite pattern, with a large LP component for target items, and a much smaller LP component for the recently repeated non-target items. Computation of parasympathetic activity in the vagus nerve was performed on the ECG data (Porges, 1985). The resulting measure, vagal tone, was used as an index of physiological responsivity. The vagal tone index of physiological responsivity was negatively related to the LP amplitude for the most recently repeated, non-target words in both groups, after accounting for age effects. The ERP data support the hypothesis that the tendency to make source memory errors on the part of older adults is related to the ability to selectively control attentional processes during task performance. Furthermore, the relationship between vagal tone and ERP reactivity suggests that there is a physiological basis to the heightened reactivity measured in the LP response to recently repeated non-target items such that, under decreased physiological resources, there is an impairment in the ability to selectively inhibit bottom-up, stimulus based properties in favour of task-related goals in older adults. The inconsistency of these results with other explanatory models of source memory deficits is discussed. It is concluded that the data are consistent with a physiological reactivity model requiring inhibition of reactivity to irrelevant, but perceptually-fluent, stimuli.

Contribution from neuropsychology to the study of semantic memory

Semantic memory has been studied from various fields. The first models emerged from cognitive psychology from the hand of the division proposed by Tulving between semantic and episodic memory. Over the past thirty years there have been parallel developments in the fields of psycholinguistics, cognitive psychology and cognitive neuropsychology. The present work is to review the contributions that have emerged within the neuropsychology to the study of semantic memory and to present an updated overview of the points of consensus. First, it is defined the term "semantics" conceptually within the field of neuropsychology. Then, there is a dichotomy that passes through both psychological and neuropsychological models on semantic memory: the existence of modals versus amodal representations. Third, there are  developed the main theoretical models in neuropsychology that emerged in an attempt to explain categoryspecific semantic deficits. Finally, more robust contributions and points that still generate some discussion are reviewed.

Option pricing in market models driven by telegraph processes with jumps

Esta tesis está dividida en dos partes: en la primera parte se presentan y estudian los procesos telegráficos, los procesos de Poisson con compensador telegráfico y los procesos telegráficos con saltos. El estudio presentado en esta primera parte incluye el cálculo de las distribuciones de cada proceso, las medias y varianzas, así como las funciones generadoras de momentos entre otras propiedades. Utilizando estas propiedades en la segunda parte se estudian los modelos de valoración de opciones basados en procesos telegráficos con saltos. En esta parte se da una descripción de cómo calcular las medidas neutrales al riesgo, se encuentra la condición de no arbitraje en este tipo de modelos y por último se calcula el precio de las opciones Europeas de compra y venta.

Simplification, approximation and deformation of large models

The high level of realism and interaction in many computer graphic applications requires techniques for processing complex geometric models. First, we present a method that provides an accurate low-resolution approximation from a multi-chart textured model that guarantees geometric fidelity and correct preservation of the appearance attributes. Then, we introduce a mesh structure called Compact Model that approximates dense triangular meshes while preserving sharp features, allowing adaptive reconstructions and supporting textured models. Next, we design a new space deformation technique called *Cages based on a multi-level system of cages that preserves the smoothness of the mesh between neighbouring cages and is extremely versatile, allowing the use of heterogeneous sets of coordinates and different levels of deformation. Finally, we propose a hybrid method that allows to apply any deformation technique on large models obtaining high quality results with a reduced memory footprint and a high performance.

Modeling distributions of immediate memory effects: No strategies needed?

Many models of immediate memory predict the presence or absence of various effects, but none have been tested to see whether they predict an appropriate distribution of effect sizes. The authors show that the feature model (J. S. Nairne, 1990) produces appropriate distributions of effect sizes for both the phonological confusion effect and the word-length effect. The model produces the appropriate number of reversals, when participants are more accurate with similar items or long items, and also correctly predicts that participants performing less well overall demonstrate smaller and less reliable phonological similarity and word-length effects and are more likely to show reversals. These patterns appear within the model without the need to assume a change in encoding or rehearsal strategy or the deployment of a different storage buffer. The implications of these results and the wider applicability of the distributionmodeling approach are discussed.

The relationship between absolute and proportion scores of serial order memory: simulation predictions and empirical data

The capability of a feature model of immediate memory (Nairne, 1990; Neath, 2000) to predict and account for a relationship between absolute and proportion scoring of immediate serial recall when memory load is varied (the list-length effect, LLE) is examined. The model correctly predicts the novel finding of an LLE in immediate serial order memory similar to that observed with free recall and previously assumed to be attributable to the long-term memory component of that procedure (Glanzer, 1972). The usefulness of formal models as predictive tools and the continuity between short-term serial order and longer term item memory are considered.

Short-term memory and the attentional blink: capacity versus content

When people monitor the rapid serial visual presentation (RSVP) of stimuli for two targets (T1 and T2), they often miss T2 if it falls into a time window of about half a second after T1 onset, a phenomenon known as the attentional blink (AB). We found that overall performance in an RSVP task was impaired by a concurrent short-term memory (STM) task and, furthermore, that this effect increased when STM load was higher and when its content was more task relevant. Loading visually defined stimuli and adding articulatory suppression further impaired performance on the RSVP task, but the size of the AB over time (i.e., T1-T2 lag) remained unaffected by load or content. This suggested that at least part of the performance in an RSVP task reflects interference between competing codes within STM, as interference models have held, whereas the AB proper reflects capacity limitations in the transfer to STM, as consolidation models have claimed.

Fault tolerance of Mobius cubes under two forbidden fault set models

An n-dimensional Mobius cube, 0MQ(n) or 1MQ(n), is a variation of n-dimensional cube Q(n) which possesses many attractive properties such as significantly smaller communication delay and stronger graph-embedding capabilities. In some practical situations, the fault tolerance of a distributed memory multiprocessor system can be measured more precisely by the connectivity of the underlying graph under forbidden fault set models. This article addresses the connectivity of 0MQ(n)/1MQ(n), under two typical forbidden fault set models. We first prove that the connectivity of 0MQ(n)/1MQ(n) is 2n - 2 when the fault set does not contain the neighborhood of any vertex as a subset. We then prove that the connectivity of 0MQ(n)/1MQ(n) is 3n - 5 provided that the neighborhood of any vertex as well as that of any edge cannot fail simultaneously These results demonstrate that 0MQ(n)/1MQ(n) has the same connectivity as Q(n) under either of the previous assumptions.

Autobiographical memory and amnesia: using conceptual knowledge to ground the self

A case of retrograde amnesia, PJM, elucidated the relationship between self, episodic memory and autobiographical knowledge. Results from a variety of measures including the I Am Memory Task (IAM Task), where memories are cued by self-generated self concepts, demonstrate that PJM has a coherent, continuous sense of self, despite having lost episodic memories for an 18-month period. Her use of conceptual autobiographical knowledge, in episodic tasks and to support aspects of identity, shows how autobiographical knowledge can support the self when episodic memories are inaccessible. These results are discussed with relation to current neuropsychological models of self and memory.

Social networks: evolving graphs with memory dependent edges

The plethora, and mass take up, of digital communication tech- nologies has resulted in a wealth of interest in social network data collection and analysis in recent years. Within many such networks the interactions are transient: thus those networks evolve over time. In this paper we introduce a class of models for such networks using evolving graphs with memory dependent edges, which may appear and disappear according to their recent history. We consider time discrete and time continuous variants of the model. We consider the long term asymptotic behaviour as a function of parameters controlling the memory dependence. In particular we show that such networks may continue evolving forever, or else may quench and become static (containing immortal and/or extinct edges). This depends on the ex- istence or otherwise of certain infinite products and series involving age dependent model parameters. To test these ideas we show how model parameters may be calibrated based on limited samples of time dependent data, and we apply these concepts to three real networks: summary data on mobile phone use from a developing region; online social-business network data from China; and disaggregated mobile phone communications data from a reality mining experiment in the US. In each case we show that there is evidence for memory dependent dynamics, such as that embodied within the class of models proposed here.

Epoch-specific functional networks involved in working memory

Working memory (WM) is not a unitary construct. There are distinct processes involved in encoding information, maintaining it on-line, and using it to guide responses. The anatomical configurations of these processes are more accurately analyzed as functionally connected networks than collections of individual regions. In the current study we analyzed event-related functional magnetic resonance imaging (fMRI) data from a Sternberg Item Recognition Paradigm WM task using a multivariate analysis method that allowed the linking of functional networks to temporally-separated WM epochs. The length of the delay epochs was varied to optimize isolation of the hemodynamic response (HDR) for each task epoch. All extracted functional networks displayed statistically significant sensitivity to delay length. Novel information extracted from these networks that was not apparent in the univariate analysis of these data included involvement of the hippocampus in encoding/probe, and decreases in BOLD signal in the superior temporal gyrus (STG), along with default-mode regions, during encoding/delay. The bilateral hippocampal activity during encoding/delay fits with theoretical models of WM in which memoranda held across the short term are activated long-term memory representations. The BOLD signal decreases in the STG were unexpected, and may reflect repetition suppression effects invoked by internal repetition of letter stimuli. Thus, analysis methods focusing on how network dynamics relate to experimental conditions allowed extraction of novel information not apparent in univariate analyses, and are particularly recommended for WM experiments for which task epochs cannot be randomized.

Flexibility of representational states in working memory

The relationship between working memory (WM) and attention is a highly interdependent one, with evidence that attention determines the state in which items in WM are retained. Through focusing of attention, an item might be held in a more prioritized state, commonly termed as the focus of attention (FOA). The remaining items, although still retrievable, are considered to be in a different representational state. One means to bring an item into the FOA is to use retrospective cues (‘retro-cues’) which direct attention to one of the objects retained in WM. Alternatively, an item can enter a privileged state once attention is directed towards it through bottom-up influences (e.g. recency effect) or by performing an action on one of the retained items (‘incidental’ cueing). In all these cases, the item in the FOA is recalled with better accuracy compared to the other items in WM. Far less is known about the nature of the other items in WM and whether they can be flexibly manipulated in and out of the FOA. We present data from three types of experiments as well as transcranial magnetic stimulation to early visual cortex to manipulate the item inside FOA. Taken together, our results suggest that the context in which items are retained in WM matters. When an item remains behaviourally relevant, despite not being inside the FOA, re-focusing attention upon it can increase its recall precision. This suggests that a non-FOA item can be held in a state in which it can be later retrieved. However, if an item is rendered behaviourally unimportant because it is very unlikely to be probed, it cannot be brought back into the FOA, nor recalled with high precision. Under such conditions, some information appears to be irretrievably lost from WM. These findings, obtained from several different methods, demonstrate quite considerable flexibility with which items in WM can be represented depending upon context. They have important consequences for emerging state-dependent models of WM.