Extracting Message Inter-Departure Time Distributions from the Human Electroencephalogram

The complex connectivity of the cerebral cortex is a topic of much study, yet the link between structure and function is still unclear. The processing capacity and throughput of information at individual brain regions remains an open question and one that could potentially bridge these two aspects of neural organization. The rate at which information is emitted from different nodes in the network and how this output process changes under different external conditions are general questions that are not unique to neuroscience, but are of interest in multiple classes of telecommunication networks. In the present study we show how some of these questions may be addressed using tools from telecommunications research. An important system statistic for modeling and performance evaluation of distributed communication systems is the time between successive departures of units of information at each node in the network. We describe a method to extract and fully characterize the distribution of such inter-departure times from the resting-state electroencephalogram (EEG). We show that inter-departure times are well fitted by the two-parameter Gamma distribution. Moreover, they are not spatially or neurophysiologically trivial and instead are regionally specific and sensitive to the presence of sensory input. In both the eyes-closed and eyes-open conditions, inter-departure time distributions were more dispersed over posterior parietal channels, close to regions which are known to have the most dense structural connectivity. The biggest differences between the two conditions were observed at occipital sites, where inter-departure times were significantly more variable in the eyes-open condition. Together, these results suggest that message departure times are indicative of network traffic and capture a novel facet of neural activity

Networks in cognitive science

Networks of interconnected nodes have long played a key role in Cognitive Science, from artificial neural networks to spreading activation models of semantic memory. Recently, however, a new Network Science has been developed, providing insights into the emergence of global, system-scale properties in contexts as diverse as the Internet, metabolic reactions, and collaborations among scientists. Today, the inclusion of network theory into Cognitive Sciences, and the expansion of complex-systems science, promises to significantly change the way in which the organization and dynamics of cognitive and behavioral processes are understood. In this paper, we review recent contributions of network theory at different levels and domains within the Cognitive Sciences.Postprint (author's final draft

Structural-Functional Connectivity Bandwidth of the Human Brain

Background: The human brain is a complex network that seamlessly manifests behaviour and cognition. This network comprises neurons that directly, or indirectly mediate communication between brain regions. Here, we show how multilayer/multiplex network analysis provides a suitable framework to uncover the throughput of structural connectivity (SC) to mediate information transfer-giving rise to functional connectivity (FC). Method: We implemented a novel method to reconcile SC and FC using diffusion and resting-state functional MRI connectivity data from 484 subjects (272 females, 212 males; age = 29.15 ± 3.47) from the Human Connectome Project. First, we counted the number of direct and indirect structural paths that mediate FC. FC nodes with indirect SC paths were then weighted according to their least restrictive SC path. We refer to this as SC-FC Bandwidth. We then mapped paths with the highest SC-FC Bandwidth across 7 canonical resting-state networks. Findings: We found that most pairs of FC nodes were connected by SC paths of length two and three (SC paths of length >5 were virtually non-existent). Direct SC-FC connections accounted for only 10% of all SC-FC connections. The majority of FC nodes without a direct SC path were mediated by a proportion of two (44%) or three SC path lengths (39%). Only a small proportion of FC nodes were mediated by SC path lengths of four (5%). We found high-bandwidth direct SC-FC connections show dense intra- and sparse inter-network connectivity, with a bilateral, anteroposterior distribution. High bandwidth SC-FC triangles have a right superomedial distribution within the somatomotor network. High-bandwidth SC-FC quads have a superoposterior distribution within the default mode network. Conclusion: Our method allows the measurement of indirect SC-FC using undirected, weighted graphs derived from multimodal MRI data in order to map the location and throughput of SC to mediate FC. An extension of this work may be to explore how SC-FC Bandwidth changes over time, relates to cognition/behavior, and if this measure reflects a marker of neurological injury or psychiatric disorders

Network models in neuroimaging: a survey of multimodal applications

Mapping the brain structure and function is one of the hardest problems in science. Different image modalities, in particular the ones based on magnetic resonance imaging (MRI) can shed more light on how it is organised and how its functions unfold, but a theoretical framework is needed. In the last years, using network models and graph theory to represent the brain structure and function has become a major trend in neuroscience. In this review, we outline how network modelling has been used in neuroimaging, clarifying what are the underlying mathematical concepts and the consequent methodological choices. The major findings are then presented for structural, functional and multimodal applications. We conclude outlining what are still the current issues and the perspective for the immediate future

A presença da metáfora em artigos de investigação biomédica

O projecto “O Uso de Metáforas na Pesquisa Biomédica” tem como objectivo geral compreender como a utilização das metáforas pode influenciar a pesquisa biomédica e prevê a inclusão de uma revisão da literatura recentemente publicada sobre o assunto, tanto em formato livro como em artigos de investigação. Nesta comunicação, apresentamos os resultados da revisão dos artigos de investigação com origem em áreas biomédicas e conexas recentemente publicados e acessíveis através da base de dados online da PubMed®. Através do respectivo sítio na Internet, foram compilados 319 artigos com data de publicação entre Janeiro de 2010 e Setembro de 2012, mencionando o termo “metaphor” no título ou resumo. Depois de enquadrados num panorama cronológico mais amplo, estes artigos foram caracterizados segundo a respectiva tipologia e identificadas as áreas disciplinares de maior interesse pelo tema. Seguidamente, foram analisados o modo como a influência da metáfora neles é percebida pelos próprios investigadores e as interpretações mais comuns do termo, revelando quais serão as suas acepções mais correntes entre um público de formação superior, mas presumivelmente alheio aos aspectos técnicos dos debates que se têm desenvolvido acerca da metáfora na área da filosofia. Finalmente, procurámos distinguir nos artigos compilados as linhas de investigação mais relevantes sobre a metáfora na área da biomedicina.The overall objective of the project “The use of metaphors in biomedical research” is to understand some of the ways by which the use of metaphor may influence biomedical research and includes a survey of the most recently published literature on the subject, in books as well as in research papers. This paper presents the results of a survey of research articles in biomedical areas that have been recently published and are accessible through PubMed®, an online database. Through its internet site, 319 research articles have been compiled, with publishing dates ranging from January 2010 to September 2012. All of these articles hold the word “metaphor” in their title and / or their abstract. These articles were then included within a wider chronological frame. They were then divided by different categories according to the disciplinary areas that are more keen on the subject. Subsequently, we were able to identify the way the use of metaphor is acknowledged and understood by researchers themselves and what are the most common interpretations of this notion amidst the scientific community. Finally we were able to identify what are the most relevant areas of research on metaphor within biomedical studies.info:eu-repo/semantics/publishedVersio

Abstract intelligence: Embodying and enabling cognitive systems by mathematical engineering

Basic studies in denotational mathematics and mathematical engineering have led to the theory of abstract intelligence (aI), which is a set of mathematical models of natural and computational intelligence in cognitive informatics (CI) and cognitive computing (CC). Abstract intelligence triggers the recent breakthroughs in cognitive systems such as cognitive computers, cognitive robots, cognitive neural networks, and cognitive learning. This paper reports a set of position statements presented in the plenary panel (Part II) of IEEE ICCI*CC’16 on Cognitive Informatics and Cognitive Computing at Stanford University. The summary is contributed by invited panelists who are part of the world’s renowned scholars in the transdisciplinary field of CI and CC

XIV Colóquio de Outono: Humanidades: novos paradigmas do conhecimento e da investigação

The present volume off ers a selection of the papers presented at the XIV Colóquio de Outono organized by the research unit Centro de Estudos Humanísticos (Universidade do Minho) in November 2012, under the global topic Humanities: New Paradigms of Knowledge and Research (Humanidades: Novos Paradigmas do Conhecimento e da Investigação). It has been the main objective of CEHUM, throughout the various Colóquios de Outono organized in just over a decade, to listen carefully to the “noise of the world” and attempt a global interpretation of the signs of the times issuing from the world around us, as vibrant echoes of many social and cultural pressing issues. This volume gathers the majority of the texts presented in the XIV Colóquio de Outono, which the authors generously off ered us for publication, and which will certainly testify of the important debate around the wide topic proposed for this years analysis and discussion. We hope that this new volume may give evidence of our concern, as a Research Centre within the Humanities which operates in a transdisciplinary structure, of the crucial role played by the Humanities in today’s world and the multidisciplinary dialogue that can be fostered by the diff erent research groups that compose it. Throughout the three days of this XIV Colóquio de Outono we had the privilege to listen to and debate the propositions of a vast number of national and international specialists in the manifold fi elds of inquiry here represented, engaging keynote speakers, project advisors, members of research teams and external researchers attached to the various research projects currently running in CEHUM, in the fi elds of literature, linguistics, philosophy, ethics, visual arts, cultural studies, music and performance. Each specifi c fi eld of studies was however never seen isolated, but always embodied in a geo-cultural context and within the scope of a wide variety of critical debates and current theories of knowledge, as a signal of our understanding of the Humanities as a rich and plural territory which engages us all, scholars, researchers, students. For these lively and thought-provoking three days of the conference we wish to thank each and every one of the colleagues present, our distinguished guests, as well as the research members of CEHUM, who so enthusiastically joined in the debate on the proposed topics of analysis. Special thanks to the Board of Directors and the research team leaders of CEHUM for the precious help provided towards the organization and the setting up of this international event. Last but not least, we wish to thank the Instituto de Letras e Ciências Humanas, as well as the research assistants and staff of CEHUM for all the precious logistic support. Finally, our gratitude to our main sponsor, Fundação para a Ciênca e a Tecnologia (FCT), for encouraging and fi nancially supporting this yearly event and the present publication.Fundação para a Ciência e a Tecnologia (FCT)UECOMPETEQRE

RELATING STRUCTURAL CONNECTIVITY TO BRAIN FUNCTION USING DEEP LEARNING, GRAPH THEORY, COMPLEXITY, AND DISEASE

In the field of neuroscience, researchers are tasked with the enormous question of how and why this critical organ containing vast numbers of neurons and synapses is able to produce the complex range of behavioural outputs that make up the human experience. In particular, the relationship between structure and function in the human brain is a core question in network neuroscience, and a topic of paramount importance to our ability to meaningfully describe and predict individual functional and behavioural outcomes. In this thesis, I will review the literature investigating important structure-function relationships in the brain, before describing the variety of novel methods and applications that I have used to address the problem of relating structural connectivity to functional connectivity and activity. First of all, I demonstrate that a graph neural network deep learning model is able to use structural connectivity to predict the functional connectivity and centrality (i.e., how connected and important a region is to the network) accounting for more variance than any other previously applied methods in the literature. Next, I examine the relationship between graph theory structural measures of centrality and the functional complexity of the regional activity, and find that regions in the structural network with high centrality that are able to facilitate the integration of information from many sources produce more complex functional activation as measured using the Hurst exponent. Then, by applying graph theory comparative analyses of structural connectivity and functional analysis of language-related activation to patients with left hemisphere temporal lobe epilepsy (TLE), right hemisphere TLE, and control groups, I show that both structural connectivity and functional activity favour the opposite hemisphere to the locus of TLE, suggesting that both structure and function may adapt in tandem as a response to disordered brain activity. Finally, I examine explicit graph theory models of information transfer in the brain to determine which of the diffusion model and shortest path routing model are better able to account for functional connectivity from the underlying structural connectivity, and show that the diffusion model seems to be the primary driver of this relationship. Taken together, this program of research has led the field of network neuroscience in the direction of both setting a clear benchmark for prediction thanks to the novel deep learning model, while also taking important steps to clearly elucidate the explicit mathematical and theoretical core of how structure informs function in the complex network that is the human brain

Modeling cognition with generative neural networks: The case of orthographic processing

This thesis investigates the potential of generative neural networks to model cognitive processes. In contrast to many popular connectionist models, the computational framework adopted in this research work emphasizes the generative nature of cognition, suggesting that one of the primary goals of cognitive systems is to learn an internal model of the surrounding environment that can be used to infer causes and make predictions about the upcoming sensory information. In particular, we consider a powerful class of recurrent neural networks that learn probabilistic generative models from experience in a completely unsupervised way, by extracting high-order statistical structure from a set of observed variables. Notably, this type of networks can be conveniently formalized within the more general framework of probabilistic graphical models, which provides a unified language to describe both neural networks and structured Bayesian models. Moreover, recent advances allow to extend basic network architectures to build more powerful systems, which exploit multiple processing stages to perform learning and inference over hierarchical models, or which exploit delayed recurrent connections to process sequential information. We argue that these advanced network architectures constitute a promising alternative to the more traditional, feed-forward, supervised neural networks, because they more neatly capture the functional and structural organization of cortical circuits, providing a principled way to combine top-down, high-level contextual information with bottom-up, sensory evidence. We provide empirical support justifying the use of these models by studying how efficient implementations of hierarchical and temporal generative networks can extract information from large datasets containing thousands of patterns. In particular, we perform computational simulations of recognition of handwritten and printed characters belonging to different writing scripts, which are successively combined spatially or temporally in order to build more complex orthographic units such as those constituting English words

A complex systems approach to education in Switzerland

The insights gained from the study of complex systems in biological, social, and engineered systems enables us not only to observe and understand, but also to actively design systems which will be capable of successfully coping with complex and dynamically changing situations. The methods and mindset required for this approach have been applied to educational systems with their diverse levels of scale and complexity. Based on the general case made by Yaneer Bar-Yam, this paper applies the complex systems approach to the educational system in Switzerland. It confirms that the complex systems approach is valid. Indeed, many recommendations made for the general case have already been implemented in the Swiss education system. To address existing problems and difficulties, further steps are recommended. This paper contributes to the further establishment complex systems approach by shedding light on an area which concerns us all, which is a frequent topic of discussion and dispute among politicians and the public, where billions of dollars have been spent without achieving the desired results, and where it is difficult to directly derive consequences from actions taken. The analysis of the education system's different levels, their complexity and scale will clarify how such a dynamic system should be approached, and how it can be guided towards the desired performance