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Structural and computational glycobiology: immunity and infection

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889196388 Year: Pages: 102 DOI: 10.3389/978-2-88919-638-8 Language: English
Publisher: Frontiers Media SA
Subject: Allergy and Immunology --- Medicine (General)
Added to DOAB on : 2015-10-30 16:33:44
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Interest in understanding the biological role of carbohydrates has increased significantly over the last 20 years. The use of structural techniques to understand carbohydrate-protein recognition is still a relatively young area, but one that is of emerging importance. The high flexibility of carbohydrates significantly complicates the determination of high quality structures of their complexes with proteins. Specialized techniques are often required to understand the complexity of carbohydrate recognition by proteins. In this Research Topic, we will focus on structural and computational approaches to understanding carbohydrate recognition by proteins involved in immunity and infection. Particular areas of focus include cancer immunotherapeutics, carbohydrate-lectin interactions, glycosylation and glycosyltransferases.

Neuroplasticity and Extracellular Proteolysis

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889198511 Year: Pages: 151 DOI: 10.3389/978-2-88919-851-1 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2016-01-19 14:05:46
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Neuroplasticity refers to the ability of the Central Nervous System (CNS) to alter its structure and function in response to a variety of physiological and pathological processes such as development, cognition, injury or neurological diseases. Since more than four decades, studies on synaptic plasticity in the context of memory and learning attracted a remarkable interest. Soon after first seminal works on synaptic plasticity were published, research in this field was extended by studies on non-synaptic as wells as structural plasticity towards a goal to understand cellular and molecular determinants of cognition. Over the past two decades, yet two additional crucial players in neuroplastic phenomena started to be intensely investigated – glial cells and the extracellular matrix (ECM). Growing awareness that glial cells, especially astrocytes, are important regulators of synaptic functions gave rise to a novel concept of a tri-partite synapse. Also, over the last two decades, a growing body of evidence has accumulated that the extracellular matrix (ECM) in the brain is strongly involved in regulation of neurons, in particular, in synaptic plasticity. Thus, a concept of tetra-partite synapse was put forward by some neuroscientists. The cross-talk between neuron-glia-ECM system involves enzymatic degradation of proteins or peptides and amino acids occurring in each of these brain constituents by means of a variety of proteases. Importantly, it has been realized that proteases such as serine proteases and matrix metalloproteinases, not only accompany “robust” phenomena such as cell division, or development or neurodegnerative conditions but may play a very subtle signaling functions, particularly important in memory acquisition. Indeed, the repertoire of substrates for these enzymes covers a wide variety of proteins known to play important role in the neuroplastic phenomena (e.g. BDNF, TNF-a, ephrin systems, various cell adhesion molecules, etc.). In result, the role of metalloproteinases and such serine proteases as tissue plasminogen activator (tPA), neuropsin or neurotrypsin in synaptic plasticity as well as in learning and memory has been particularly well demonstrated. It needs to be emphasized, however, that in spite of a remarkable progress in this field, several basic questions regarding molecular and cellular mechanisms remain unanswered. Potential involvement of so many important players (various proteases and their substrates in neurons, glia and in ECM) points to an enormous potential for plasticity phenomena but makes also studies into underlying mechanisms particularly difficult. In the proposed Research Topic we provide both review of the current state of the art and present some original reports on specific aspects of the role of proteolysis in neuroplasticity phenomena. The present ebook starts with extensive reviews describing involvement of proteolysis not only in synaptic plasticity but also in regulating endogenous excitability and structural changes at the network, cellular and subcellular levels. Cross-talk between neuroplasticity and proteolysis is also emphasized in the context of development and in relation to various pathologies. Whereas in the first part of the present ebook, the major focus is on metalloproteinases, the successive articles address the role of neuropsin and thrombin. The Research Topic is concluded with a series of articles describing the components of extracellular matrix and adhesion proteins and their elaboration by mechanisms dependent directly or indirectly on proteolysis. We do hope that the present ebook will further stimulate the interest in the fascinating investigations into neuroplasticity-proteolysis cross-talk.

What can neuroscience learn from contemplative practices?

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889199716 Year: Pages: 166 DOI: 10.3389/978-2-88919-971-6 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Psychology
Added to DOAB on : 2016-01-19 14:05:46
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A recent wave of brain research has advanced our understanding of the neural mechanisms of conscious states, contents and functions. A host of questions remain to be explored, as shown by lively debates between models of higher vs. lower-order aspects of consciousness, as well as global vs. local models. (Baars 2007; Block, 2009; Dennett and Cohen, 2011; Lau and Rosenthal, 2011). Over some twenty-five centuries the contemplative traditions have also developed explicit descriptions and taxonomies of the mind, to interpret experiences that are often reported in contemplative practices (Radhakrishnan & Moore, 1967; Rinbochay & Naper, 1981). These traditional descriptions sometimes converge on current scientific debates, such as the question of conceptual vs. non-conceptual consciousness; reflexivity or “self-knowing” associated with consciousness; the sense of self and consciousness; and aspects of consciousness that are said to continue during sleep. These real or claimed aspects of consciousness have not been fully integrated into scientific models so far. This Research Topic in Consciousness Research aims to provide a forum for theoretical proposals, new empirical findings, integrative literature reviews, and methodological improvements inspired by meditation-based models. We include a broad array of topics, including but not limited to: replicable findings from a variety of systematic mental practices; changes in brain functioning and organization that can be attributed to such practices; their effects on adaptation and neural plasticity; measurable effects on perception, cognition, affect and self-referential processes. We include contributions that address the question of causal attribution. Many published studies are correlational in nature, because of the inherent difficulty of conducting longitudinal experiments based on a major lifestyle decision, such as the decision to commit to a mental practice over a period of years. We also feature clinical and case studies, integrative syntheses and significant opinion articles.

Learning a non-native language in a naturalistic environment: Insights from behavioural and neuroimaging research

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889196395 Year: Pages: 150 DOI: 10.3389/978-2-88919-639-5 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Psychology
Added to DOAB on : 2016-08-16 10:34:25
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It is largely accepted in the relevant literature that successful learning of one or more non-native languages is affected by a number of factors that are independent of the target language(s) per se; these factors include the age of acquisition (AoA) of the target language(s), the type and amount of formal instruction the learners have received, as well as the amount of language use that the learners demonstrate. Recent experimental evidence suggests that one crucial factor for efficient native-like performance in the non-native language is the amount of naturalistic exposure, or immersion, that the learners receive to that language. This can be broadly defined as the degree to which language learners use their non-native language outside the classroom and for their day-to-day activities, and usually presupposes that the learners live in an environment where their non-native language is exclusively or mostly used. Existing literature has suggested that linguistic immersion can be beneficial for lexical and semantic acquisition in a non-native language, as well as for non-native morphological and syntactic processing. More recent evidence has also suggested that naturalistic learning of a non-native language can also have an impact on the patterns of brain activity underlying language processing, as well as on the structure of brain regions that are involved, expressed as changes in the grey matter structure. This Research Topic brings together studies on the effects of learning and speaking a non-native language in a naturalistic environment. These include more efficient or “native-like” processing in behavioural tasks tapping on language (lexicon, morphology, syntax), as well as changes in the brain structure and function, as revealed by neuroimaging studies.

Institutional determinants of social inequality

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889197859 Year: Pages: 124 DOI: 10.3389/978-2-88919-785-9 Language: English
Publisher: Frontiers Media SA
Subject: Psychology --- Science (General)
Added to DOAB on : 2017-02-03 17:04:57
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Understanding the factors that create and maintain social inequalities is a core question in social psychology. Research has so far mainly focused on the role of individual stereotyping, prejudice and discrimination. However, there is growing evidence that, beyond the “biased” acts of prejudiced individuals, structural factors related to the very functioning of institutions and organizations can play a role in the reproduction of social inequalities. Indeed, in industrialized countries, society is structured in a way that reflects the perspective of, is organized by, and benefits the dominant groups. In this Research Topic, we propose to bring together researchers who study how institutional ideologies and practices promote norms, rules and opportunities that favor dominant groups and disadvantage dominated groups. This question can be tackled by work investigating how institutional practices (e.g., grading, tracking, recruitment, …) and ideologies (e.g., meritocracy, individualism, protestant work ethic, …) shape the psychological experience of (dis)advantaged people. Moreover, another interesting venue is represented by work investigating how the institutional practices and ideologies are enacted by the agents (e.g., teachers, recruiters, leaders, …). Taking the perspective of agents allows to investigate how institutional functioning constrains the actual opportunities they provide to (dis)advantaged individuals. This could also highlight how institutional ideologies and practices are incorporated by agents, thus revealing mechanisms of change vs. perpetuation of the institutional functioning.

Anatomy and Plasticity in Large-Scale Brain Models

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889450657 Year: Pages: 173 DOI: 10.3389/978-2-88945-065-7 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2017-07-06 13:27:36
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Supercomputing facilities are becoming increasingly available for simulating activity dynamics in large-scale neuronal networks. On today's most advanced supercomputers, networks with up to a billion of neurons can be readily simulated. However, building biologically realistic, full-scale brain models requires more than just a huge number of neurons. In addition to network size, the detailed local and global anatomy of neuronal connections is of crucial importance. Moreover, anatomical connectivity is not fixed, but can rewire throughout life (structural plasticity)—an aspect that is missing in most current network models, in which plasticity is confined to changes in synaptic strength (synaptic plasticity). The papers in this Ebook, which may broadly be divided into three themes, aim to bring together high-performance computing with recent experimental and computational research in neuroanatomy. In the first theme (fiber connectivity), new methods are described for measuring and data-basing microscopic and macroscopic connectivity. In the second theme (structural plasticity), novel models are introduced that incorporate morphological plasticity and rewiring of anatomical connections. In the third theme (large-scale simulations), simulations of large-scale neuronal networks are presented with an emphasis on anatomical detail and plasticity mechanisms. Together, the articles in this Ebook make the reader aware of the methods and models by which large-scale brain networks running on supercomputers can be extended to include anatomical detail and plasticity.Supercomputing facilities are becoming increasingly available for simulating activity dynamics in large-scale neuronal networks. On today's most advanced supercomputers, networks with up to a billion of neurons can be readily simulated. However, building biologically realistic, full-scale brain models requires more than just a huge number of neurons. In addition to network size, the detailed local and global anatomy of neuronal connections is of crucial importance. Moreover, anatomical connectivity is not fixed, but can rewire throughout life (structural plasticity)—an aspect that is missing in most current network models, in which plasticity is confined to changes in synaptic strength (synaptic plasticity). The papers in this Ebook, which may broadly be divided into three themes, aim to bring together high-performance computing with recent experimental and computational research in neuroanatomy. In the first theme (fiber connectivity), new methods are described for measuring and data-basing microscopic and macroscopic connectivity. In the second theme (structural plasticity), novel models are introduced that incorporate morphological plasticity and rewiring of anatomical connections. In the third theme (large-scale simulations), simulations of large-scale neuronal networks are presented with an emphasis on anatomical detail and plasticity mechanisms. Together, the articles in this Ebook make the reader aware of the methods and models by which large-scale brain networks running on supercomputers can be extended to include anatomical detail and plasticity.

Long-Term Structural Changes in Transforming Central & Eastern Europe (The 1990s)

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Book Series: Suedosteuropa-Studien ISBN: 9783631743188 Year: Pages: 195 DOI: 10.3726/b12597 Language: German
Publisher: Peter Lang International Academic Publishing Group
Subject: Social Sciences
Added to DOAB on : 2019-01-15 13:32:46
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Die Südosteuropa-Studien werden von der in München ansässigen Südosteuropa-Gesellschaft, der wichtigsten Wissenschaftsorganisation der Südosteuropa-Forschung im deutschsprachigen Raum, herausgegeben. Sie dienen der vertieften und interdisziplinären wissenschaftlichen Darstellung wichtiger Themen aus der Südosteuropa-Forschung. Auch Fragen zur aktuellen politischen und sozio-ökonomischen Entwicklung in der Region Südosteuropa werden aufgegriffen. Herausgeber der Einzelbände sind renommierte Repräsentanten der deutschen und internationalen Südosteuropa-Forschung.

Information-based methods for neuroimaging: analyzing structure, function and dynamics

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889195022 Year: Pages: 191 DOI: 10.3389/978-2-88919-502-2 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2015-12-03 13:02:24
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The aim of this Research Topic is to discuss the state of the art on the use of Information-based methods in the analysis of neuroimaging data. Information-based methods, typically built as extensions of the Shannon Entropy, are at the basis of model-free approaches which, being based on probability distributions rather than on specific expectations, can account for all possible non-linearities present in the data in a model-independent fashion.Mutual Information-like methods can also be applied on interacting dynamical variables described by time-series, thus addressing the uncertainty reduction (or information) in one variable by conditioning on another set of variables.In the last years, different Information-based methods have been shown to be flexible and powerful tools to analyze neuroimaging data, with a wide range of different methodologies, including formulations-based on bivariate vs multivariate representations, frequency vs time domains, etc. Apart from methodological issues, the information bit as a common unit represents a convenient way to open the road for comparison and integration between different measurements of neuroimaging data in three complementary contexts: Structural Connectivity, Dynamical (Functional and Effective) Connectivity, and Modelling of brain activity. Applications are ubiquitous, starting from resting state in healthy subjects to modulations of consciousness and other aspects of pathophysiology.Mutual Information-based methods have provided new insights about common-principles in brain organization, showing the existence of an active default network when the brain is at rest. It is not clear, however, how this default network is generated, the different modules are intra-interacting, or disappearing in the presence of stimulation. Some of these open-questions at the functional level might find their mechanisms on their structural correlates. A key question is the link between structure and function and the use of structural priors for the understanding of the functional connectivity measures. As effective connectivity is concerned, recently a common framework has been proposed for Transfer Entropy and Granger Causality, a well-established methodology originally based on autoregressive models. This framework can open the way to new theories and applications.This Research Topic brings together contributions from researchers from different backgrounds which are either developing new approaches, or applying existing methodologies to new data, and we hope it will set the basis for discussing the development and validation of new Information-based methodologies for the understanding of brain structure, function, and dynamics.

Producing and Analyzing Macro-Connectomes: Current State and Challenges

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889199815 Year: Pages: 139 DOI: 10.3389/978-2-88919-981-5 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Neurology
Added to DOAB on : 2016-01-19 14:05:46
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Construction of comprehensive and detailed brain regions neuroanatomical connections matrices (macro-connectomes) is necessary to understand how the nervous system is organized and to elucidate how its different parts interact. Macro-connectomes also are the structural foundation of any finer granularity approaches at the neuron classes and types (meso-connectomes) or individual neuron (micro-connectomes) levels. The advent of novel neuroanatomical methods, as well as combinations of classic techniques, form the basis of several large scale projects with the ultimate goal of producing publicly available connectomes at different levels. A parallel approach, that of systematic and comprehensive collation of connectivity data from the published literature and from publicly accessible neuroinformatics platforms, has produced macro-connectomes of different parts of the central nervous system (CNS) in several mammalian species. The emergence of these public platforms that allow for the manipulation of rich connectivity data sets and enable the construction of CNS macro-connectomes in different species may have significant and long lasting implications. Moreover, when these efforts are leveraged by novel statistical methods, they may influence our way of thinking about the brain. Hence, the present brain region-centric paradigm may be challenged by a network-centric one. Ultimately, these projects will provide the information and knowledge for understanding how different neuronal parts communicate and function, developing novel approaches to diseases and disorders, and facilitating translational efforts in neurosciences. With this Research Topic we bring together the current state of macro-connectome related projects including the large scale production of thousands of publicly available neuronatomical experiments, databases with tens of thousands of connectivity records collated from the published literature, and the newest methods for displaying and analyzing this information. This topic also includes a wide range of challenges and how they are addressed - from platforms designed to integrate connectivity data across different sources, species and CNS levels of organization, to languages specifically designed to use these data in models at different scales of resolution, to efforts of 3D reconstruction and data integration, and to approaches for extraction and representation of this knowledge. Finally, we address the present state of different efforts of meso-connectomes construction, and of computational modeling in the context of the

Principles Underlying Post-Stroke Recovery of Upper Extremity Sensorimotor Function - A Neuroimaging Perspective

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889197675 Year: Pages: 153 DOI: 10.3389/978-2-88919-767-5 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Medicine (General)
Added to DOAB on : 2016-04-07 11:22:02
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Neuroimaging post-stroke has the potential to uncover underlying principles of disturbed hand function and recovery characterizing defined patient groups, including their long term course as well as individual variations. The methods comprise functional magnetic resonance imaging (MRI) measuring task related activation as well as resting state. Functional MRI may be complemented by arterial spin labeling (ASL) MRI to investigate slowly varying blood flow and associated changes in brain function. For structural MRI robust and accurate computational anatomical methods like voxel-based morphometry and surface based techniques are available. The investigation of the connectivity among brain regions and disruption after stroke is facilitated by diffusion tensor imaging (DTI). Intra- and interhemispheric coherence may be studied by electromagnetic techniques such as electroencephalography and transcranial magnetic stimulation. Consecutive phases of stroke recovery (acute, subacute, early chronic and late chronic stages) are each distinguished by intrinsic processes. The site and size of lesions entail partially different functional implications. New strategies to establish functional specificity of a lesion site include calculating contrast images between patients exhibiting a specific disorder and control subjects without the disorder. Large-size lesions often imply poor cerebral blood flow which impedes recovery significantly and possibly interferes with BOLD response of functional MRI. Thus, depending on the site and size of the infarct lesion the patterns of recovery will vary. These include recovery sensu stricto in the perilesional area, intrinsic compensatory mechanisms using alternative cortical and subcortical pathways, or behavioral compensatory strategies e.g. by using the non-affected limb. In this context, behavioral and neuroimaging measures should be developed and employed to delineate aspects of learning during recovery. Of special interest in recovery of hand paresis is the interplay between sensory and motor areas in the posterior parietal cortex involved during reaching and fine motor skills as well as the interaction with the contralesional hemisphere. The dominant disability should be characterized, from the level of elementary to hierarchically higher processes such as neglect, apraxia and motor planning. In summary, this Research Topic covers new trends in state of the art neuroimaging of stroke during recovery from upper limb paresis. Integration of behavioral and neuroimaging findings in probabilistic brain atlases will further advance knowledge about stroke recovery.

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